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(An electrically excitable cell such as a Neuron, Heart, Muscle, Sensory, or Endocrine cell.)
| Models | Description |
| A Fast Rhythmic Bursting Cell: in vivo cell modeling (Lee 2007) | |
| One of the cellular mechanisms underlying the generation of gamma oscillations is a type of cortical pyramidal neuron named fast rhythmic bursting (FRB) cells. After cells from cats' primary visual cortices were filled with Neurobiotin, the brains were cut, and the cells were photographed. One FRB cell was chosen to be confocaled, reconstructed with Neurolucida software, and generated a detailed multi-compartmental model in the NEURON program. We explore firing properties of FRB cells and the role of enhanced Na+ conductance. | |
| A Model of Multiple Spike Initiation Zones in the Leech C-interneuron (Crisp 2009) | |
| The leech C-interneuron and its electrical synapse with the S-interneuron exhibit unusual properties: an asymmetric delay when impulses travel from one soma to the other, and graded C-interneuron impulse amplitudes under elevated divalent cation concentrations. These properties have been simulated using a SNNAP model in which the C-interneuron has multiple, independent spike initiation zones associated with individual electrical junctions with the C-interneuron. | |
| A cardiac cell simulator (Puglisi and Bers 2001), applied to the QT interval (Busjahn et al 2004) | |
| "LabHEART is an easy to use program that simulates the cardiac action potential, calcium transient and ionic currents. Key parameters such as ionic concentration, stimulus waveform and channel conductance can easily be changed by a click on an icon or dragging a slider. It is a powerfull tool for teaching and researching cardiac electrophysiology." | |
| A dynamic model of the canine ventricular myocyte (Hund, Rudy 2004) | |
| The Hund-Rudy dynamic (HRd) model is based on data from the canine epicardial ventricular myocyte. Rate-dependent phenomena associated with ion channel kinetics, action potential properties and Ca2+ handling are simulated by the model. See paper for more and details. | |
| A finite volume method for stochastic integrate-and-fire models (Marpeau et al. 2009) | |
| "The stochastic integrate and fire neuron is one of the most commonly used stochastic models in neuroscience. Although some cases are analytically tractable, a full analysis typically calls for numerical simulations. We present a fast and accurate finite volume method to approximate the solution of the associated Fokker-Planck equation. ..." | |
| A four compartmental model for ABPD complex in crustacean pyloric network (Maran et al. 2011) | |
| "Central pattern generators (CPGs) frequently include bursting neurons that serve as pacemakers for rhythm generation. Phase resetting curves (PRCs) can provide insight into mechanisms underlying phase locking in such circuits. PRCs were constructed for a pacemaker bursting complex in the pyloric circuit in the stomatogastric ganglion of the lobster and crab. ..." | |
| A model for interaural time difference sensitivity in the medial superior olive (Zhou et al 2005) | |
| This model simulates responses of neurons to interaural time difference (ITD) in the medial superior olive (MSO) of the mammalian brainstem. The model has a bipolar cell structure and incorporates two anatomic observations in the MSO: (1) the axon arises from the dendrite that receives ipsilateral inputs and (2) inhibitory synapses are located primarily on the soma in adult animals. Fine adjustment of the best ITD is achieved by the interplay of somatic sodium currents and synaptic inhibitory currents. The model suggests a mechanism for dynamically "fine-tuning" the ITD sensitivity of MSO cells by the opponency between depolarizing sodium currents and hyperpolarizing inhibitory currents. | |
| A model of the femur-tibia control system in stick insects (Stein et al. 2008) | |
| We studied the femur-tibia joint control system of the insect leg, and its switch between resistance reflex in posture control and "active reaction" in walking. The "active reaction" is basically a reversal of the resistance reflex. Both responses are elicited by the same sensory input and the same neuronal network (the femur-tibia network). The femur-tibia network was modeled by fitting the responses of model neurons to those obtained in animals. Each implemented neuron has a physiological counterpart. The strengths of 16 interneuronal pathways that integrate sensory input were then assigned three different values and varied independently, generating a database of more than 43 million network variants. The uploaded version contains the model that best represented the resistance reflex. Please see the README for more help. We demonstrate that the combinatorial code of interneuronal pathways determines motor output. A switch between different behaviors such as standing to walking can thus be achieved by altering the strengths of selected sensory integration pathways. | |
| A multi-compartment model for interneurons in the dLGN (Halnes et al. 2011) | |
| This model for dLGN interneurons is presented in two parameterizations (P1 & P2), which were fitted to current-clamp data from two different interneurons (IN1 & IN2). The model qualitatively reproduces the responses in IN1 & IN2 under 8 different experimental condition, and quantitatively reproduces the I/O-relations (#spikes elicited as a function of injected current). | |
| A multiphysics neuron model for cellular volume dynamics (Lee et al. 2011) | |
| This paper introduces a novel neuron model, where the cell volume is a time-varying variable and multiple physical principles are combined to build governing equations. Using this model, we analyzed neuronal volume responses during excitation, which elucidated the waveforms of fast intrinsic optical signals observed experimentally across the literature. In addition, we analyzed volume responses on a longer time scale with repetitive stimulation to study the characteristics of slow cell swelling. | |
| A set of reduced models of layer 5 pyramidal neurons (Bahl et al. 2012) | |
| These are the NEURON files for 10 different models of a reduced L5 pyramidal neuron. The parameters were obtained by automatically fitting the models to experimental data using a multi objective evolutionary search strategy. Details on the algorithm can be found at www.g-node.org/emoo and in Bahl et al. (2012). | |
| A simplified cerebellar Purkinje neuron (the PPR model) (Brown et al. 2010) | |
| These models were implemented in NEURON by Sherry-Ann Brown in the laboratory of Leslie M. Loew. The files reproduce Figures 2c-f from Brown et al, 2010 "Virtual NEURON: a Strategy For Merged Biochemical and Electrophysiological Modeling". | |
| A spiking model of cortical broadcast and competition (Shanahan 2008) | |
| "This paper presents a computer model of cortical broadcast and competition based on spiking neurons and inspired by the hypothesis of a global neuronal workspace underlying conscious information processing in the human brain. In the model, the hypothesised workspace is realised by a collection of recurrently interconnected regions capable of sustaining and disseminating a reverberating spatial pattern of activation. ..." | |
| A two-stage model of dendritic integration in CA1 pyramidal neurons (Katz et al. 2009) | |
| "... In a two-stage integration model, inputs contribute directly to dendritic spikes, and outputs from multiple branches sum in the axon. ... We used serial-section electron microscopy to reconstruct individual apical oblique dendritic branches of CA1 pyramidal neurons and observe a synapse distribution consistent with the two-stage integration model. Computational modeling suggests that the observed synapse distribution enhances the contribution of each dendritic branch to neuronal output." | |
| AP back-prop. explains threshold variability and rapid rise (McCormick et al. 2007, Yu et al. 2008) | |
| This simple axon-soma model explained how the rapid rising phase in the somatic spike is derived from the propagated axon initiated spike, and how the somatic spike threshold variance is affected by spike propagation. | |
| AP shape and parameter constraints in optimization of compartment models (Weaver and Wearne 2006) | |
| "... We construct an objective function that includes both time-aligned action potential shape error and errors in firing rate and firing regularity. We then implement a variant of simulated annealing that introduces a recentering algorithm to handle infeasible points outside the boundary constraints. We show how our objective function captures essential features of neuronal firing patterns, and why our boundary management technique is superior to previous approaches." | |
| Accurate and fast simulation of channel noise in conductance-based model neurons (Linaro et al 2011) | |
| We introduce and operatively present a general method to simulate channel noise in conductance-based model neurons, with modest computational overheads. Our approach may be considered as an accurate generalization of previous proposal methods, to the case of voltage-, ion-, and ligand-gated channels with arbitrary complexity. We focus on the discrete Markov process descriptions, routinely employed in experimental identification of voltage-gated channels and synaptic receptors. | |
| Action Potential initiation and backpropagation in Neocortical L5 Pyramidal Neuron (Hu et al. 2009) | |
| "...Previous computational studies have yielded conflicting conclusions about the role of Na+ channel density and biophysical properties in action potential initiation as a result of inconsistent estimates of channel density. Our modeling studies integrated the immunostaining and electrophysiological results and showed that the lowest threshold for action potential initiation at the distal AIS was largely determined by the density of low-threshold Nav1.6 channels ... Distinct from the function of Nav1.6 channel, the Nav1.2 channel may control action potential backpropagation because of its high density at the proximal AIS and high threshold. ... In conclusion, distal AIS accumulation of Nav1.6 channels determines the low threshold for action potential initiation; whereas proximal AIS accumulation of Nav1.2 channels sets the threshold for the generation of somatodendritic potentials and ensures action potential backpropagation to the soma and dendrites. Thus, Nav1.6 and Nav1.2 channels serve distinct functions in action potential initiation and backpropagation." | |
| Action potential of adult rat ventricle (Wang et al. 2008) | |
| "Aconitine (ACO), a highly toxic diterpenoid alkaloid, is recognized to have effects on cardiac voltage-gated Na(+) channels. However, it remains unknown whether it has any effects on K(+) currents. The effects of ACO on ion currents in differentiated clonal cardiac (H9c2) cells and in cultured neonatal rat ventricular myocytes were investigated in this study. ..." The rat action potential in this simulation was played back into the cell for experiments reported in this paper. | |
| Action potential of striated muscel fiber (Adrian et al 1970) | |
| 1. Membrane currents during step depolarizations were determined by a method in which three electrodes were inserted near the end of a fibre in the frog's sartorius muscle. The theoretical basis and limitations of the method are discussed. 2. Measurements of the membrane capacity (CM) and resting resistance (RM) derived from the current during a step change in membrane potential are consistent with values found by other methods. 3. In fibres made mechanically inactive with hypertonic solutions (Ringer solution plus 350 mM sucrose) step depolarizations produced ionic currents which resembled those of nerve in showing (a) an early transient inward current, abolished by tetrodotoxin, which reversed when the depolarization was carried beyond an internal potential of about +20 mV, (b) a delayed outward current, with a linear instantaneous current¡Xvoltage relation, and a mean equilibrium potential with a normal potassium concentration (2¡P5 mM) of -85 mV. 4. The reversal potential for the early current appears to be consistent with the sodium equilibrium potential expected in hypertonic solutions. 5. The variation of the equilibrium potential for the delayed current (V¡¬K) with external potassium concentration suggests that the channel for delayed current has a ratio of potassium to sodium permeability of 30:1; this is less than the resting membrane where the ratio appears to be 100:1. V¡¬K corresponds well with the membrane potential at the beginning of the negative after-potential observed under similar conditions. 6. The variation of V¡¬K with the amount of current which has passed through the delayed channel suggests that potassium ions accumulate in a space of between 1/3 and 1/6 of the fibre volume. If potassium accumulates in the transverse tubular system (T system) much greater variation in V¡¬K would be expected. 7. The delayed current is not maintained but is inactivated like the early current. The inactivation is approximately exponential with a time constant of 0¡P5 to 1 sec at 20¢X C. The steady-state inactivation of the potassium current is similar to that for the sodium current, but its voltage dependence is less steep and the potential for half inactivation is 20 mV rate more positive. 8. Reconstructions of ionic currents were made in terms of the parameters (m, n, h) of the Hodgkin¡XHuxley model for the squid axon, using constants which showed a similar dependence on voltage. 9. Propagated action potentials and conduction velocities were computed for various conditions on the assumption that the T system behaves as if it were a series resistance and capacity in parallel with surface capacity and the channels for sodium, potassium and leak current. There was reasonable agreement with observed values, the main difference being that the calculated velocities and rates of rise were somewhat less than those observed experimentally. | |
| Action potential reconstitution from measured current waveforms (Alle et al. 2009) | |
| This NEURON code reconstitutes action potentials in a model of a hippocampal mossy fiber from experimentally measured sodium, potassium and calcium current waveforms as described in Alle et al. (2009). | |
| Action potential-evoked Na+ influx are similar in axon and soma (Fleidervish et al. 2010) | |
| "In cortical pyramidal neurons, the axon initial segment (AIS) is pivotal in synaptic integration. It has been asserted that this is because there is a high density of Na+ channels in the AIS. However, we found that action potential–associated Na+ flux, as measured by high-speed fluorescence Na+ imaging, was about threefold larger in the rat AIS than in the soma. Spike-evoked Na+ flux in the AIS and the first node of Ranvier was similar and was eightfold lower in basal dendrites. ... In computer simulations, these data were consistent with the known features of action potential generation in these neurons." | |
| Active dendrites and spike propagation in a hippocampal interneuron (Saraga et al 2003) | |
| We create multi-compartment models of an Oriens-Lacunosum/Moleculare (O-LM) hippocampal interneuron using passive properties, channel kinetics, densities and distributions specific to this cell type, and explore its signaling characteristics. We find that spike initiation depends on both location and amount of input, as well as the intrinsic properties of the interneuron. Distal synaptic input always produces strong back-propagating spikes whereas proximal input could produce both forward and back-propagating spikes depending on the input strength. Please see paper for more details. Fernanda.Saraga@utoronto.ca | |
| Active dendritic action potential propagation (Casale & McCormick 2011) | |
| This model explores the dendritic sodium and potassium conductances needed to recapitulate voltage-sensitive dye optical recordings of thalamic interneuron dendrites in the dorsal lateral geniculate nucleus. Model ion channels were selected based on pharmacological data. | |
| Activity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007) | |
| "In this study, we developed a general description of parameter combinations for which specified characteristics of neuronal or network activity are constant. Our approach is based on the implicit function theorem and is applicable to activity characteristics that smoothly depend on parameters. Such smoothness is often intrinsic to neuronal systems when they are in stable functional states. The conclusions about how parameters compensate each other, developed in this study, can thus be used even without regard to the specific mathematical model describing a particular neuron or neuronal network. ..." | |
| Activity dependent changes in motoneurones (Dai Y et al 2002, Gardiner et al 2002) | |
| These two papers review various experimental papers and examine the effects of activity on motoneurons in a similar 5 compartment model with 10 active conductances. Included are slow (S) and fast (F) type and fast fatigue resistant (FR) and fast fatigable (FF) models corresponding to the types of motoneurons. See papers for more and details. | |
| Activity dependent conductances in a neuron model (Liu et al. 1998) | |
| "... We present a model of a stomatogastric ganglion (STG) neuron in which several Ca2+-dependent pathways are used to regulate the maximal conductances of membrane currents in an activity-dependent manner. Unlike previous models of this type, the regulation and modification of maximal conductances by electrical activity is unconstrained. The model has seven voltage-dependent membrane currents and uses three Ca2+ sensors acting on different time scales. ... The model suggests that neurons may regulate their conductances to maintain fixed patterns of electrical activity, rather than fixed maximal conductances, and that the regulation process requires feedback systems capable of reacting to changes of electrical activity on a number of different time scales." | |
| Activity dependent regulation of pacemaker channels by cAMP (Wang et al 2002) | |
| Demonstration of the physiological consequences of the cyclic allosteric gating scheme for Ih mediated by HCN2 in thalamocortical relay cells. | |
| Afferent Integration in the NAcb MSP Cell (Wolf et al. 2005) | |
| "We describe a computational model of the principal cell in the nucleus accumbens (NAcb), the medium spiny projection (MSP) neuron. The model neuron, constructed in NEURON, includes all of the known ionic currents in these cells and receives synaptic input from simulated spike trains via NMDA, AMPA, and GABAA receptors. ... results suggest that afferent information integration by the NAcb MSP cell may be compromised by pathology in which the NMDA current is altered or modulated, as has been proposed in both schizophrenia and addiction." | |
| Alcohol excites Cerebellar Golgi Cells by inhibiting the Na+/K+ ATPase (Botta et al.2010) | |
| Patch-clamp in cerebellar slices and computer modeling show that ethanol excites Golgi cells by inhibiting the Na+/K+ ATPase. In particular, voltage-clamp recordings of Na+/K+ ATPase currents indicated that ethanol partially inhibits this pump and this effect could be mimicked by low concentrations of the Na+/K+ ATPase blocker ouabain. The partial inhibition of Na+/K+ ATPase in a computer model of the Golgi cell reproduced these experimental findings that established a novel mechanism of action of ethanol on neural excitability. | |
| Altered complexity in layer 2/3 pyramidal neurons (Luuk van der Velden et al. 2012) | |
| " ... Our experimental results show that hypercomplexity of the apical dendritic tuft of layer 2/3 pyramidal neurons affects neuronal excitability by reducing the amount of spike frequency adaptation. This difference in firing pattern, related to a higher dendritic complexity, was accompanied by an altered development of the afterhyperpolarization slope with successive action potentials. Our abstract and realistic neuronal models, which allowed manipulation of the dendritic complexity, showed similar effects on neuronal excitability and confirmed the impact of apical dendritic complexity. Alterations of dendritic complexity, as observed in several pathological conditions such as neurodegenerative diseases or neurodevelopmental disorders, may thus not only affect the input to layer 2/3 pyramidal neurons but also shape their firing pattern and consequently alter the information processing in the cortex." | |
| Ambiguous Encoding and Distorted Perception (Carlson and Kawasaki 2006) | |
| "... In the weakly electric fish Eigenmannia, P- and T-type primary afferent fibers are specialized for encoding the amplitude and phase, respectively, of electrosensory stimuli. We used a stimulus estimation technique to quantify the ability of P- and T-units to encode random modulations in amplitude and phase. As expected, P-units exhibited a clear preference for encoding amplitude modulations, whereas T-units exhibited a clear preference for encoding phase modulations. Surprisingly, both types of afferents also encoded their nonpreferred stimulus attribute when it was presented in isolation or when the preferred stimulus attribute was sufficiently weak. Because afferent activity can be affected by modulations in either amplitude or phase, it is not possible to unambiguously distinguish between these two stimulus attributes by observing the activity of a single afferent fiber. Simple model neurons with a preference for encoding either amplitude or phase also encoded their nonpreferred stimulus attribute when it was presented in isolation, suggesting that such ambiguity is unavoidable. ... " See paper for more and details. | |
| Amyloid beta (IA block) effects on a model CA1 pyramidal cell (Morse et al. 2010) | |
| The model simulations provide evidence oblique dendrites in CA1 pyramidal neurons are susceptible to hyper-excitability by amyloid beta block of the transient K+ channel, IA. See paper for details. | |
| Amyloid-beta effects on release probability and integration at CA3-CA1 synapses (Romani et al. 2013) | |
| The role of amyloid beta (Aß) in brain function and in the pathogenesis of Alzheimer’s disease remains elusive. Recent publications reported that an increase in Aß concentration perturbs presynaptic release in hippocampal neurons, in particular by increasing release probability of CA3-CA1 synapses. The model predics how this alteration can affect synaptic plasticity and signal integration. The results suggest that the perturbation of release probability induced by increased Aß can significantly alter the spike probability of CA1 pyramidal neurons and thus contribute to abnormal hippocampal function during Alzheimer’s disease. | |
| Application of Parker-Sochacki method to Hodgkin-Huxley equations (Wilanowski 2013, in review) | |
| Reproduces figures 2-3 from Wilanowski, G. Integrating Hodgkin-Huxley equations (in review) The implementation of the giant squid axon and the Booth model with the Parker-Sochacki method combined with cubic splines interpolation of the Hodgkin-Huxley equations. Contact gwilanowski@ibib.waw.pl if you have any questions about the implementation of the model. Usage: 1. Unzip wilanowski2013.zip into empty directory. 2. Run simulation.m MATLAB script 3. A menu will appear that offers a selection of models (the giant squid axon or the Booth model 4. Choose 1 or 2 to reproduce the simulations shown Fig. 1 or Fig 2 of the original article. Only the Parker-Sochacki traces can be reproduced. Curve Fitting Toolbox is required. The program runs on Windows. It bases upon Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009) (http://senselab.med.yale.edu/modeldb/showmodel.asp?model=117361) | |
| Artificial neuron model (Izhikevich 2003) | |
| A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin–Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC. | |
| Auditory nerve model with linear tuning (Heinz et al 2001) | |
| A method for calculating psychophysical performance limits based on stochastic neural responses is introduced and compared to previous analytical methods for evaluating auditory discrimination of tone frequency and level. The method uses signal detection theory and a computational model for a population of auditory nerve (AN) fiber responses. Please see paper for details. | |
| Availability of low-threshold Ca2+ current in retinal ganglion cells (Lee SC et al. 2003) | |
| "... we measured T-type current of isolated goldfish retinal ganglion cells with perforated-patch voltageclamp methods in solutions containing a normal extracellular Ca2+ concentration. The voltage sensitivities and rates of current activation, inactivation, deactivation, and recovery from inactivation were similar to those of expressed +1G (CaV3.1) Ca2+ channel clones, except that the rate of deactivation was significantly faster. We reproduced the amplitude and kinetics of measured T currents with a numerical simulation based on a kinetic model developed for an +1G Ca2+ channel. Finally, we show that this model predicts the increase of T-type current made available between resting potential and spike threshold by repetitive hyperpolarizations presented at rates that are within the bandwidth of signals processed in situ by these neurons." | |
| Axonal NaV1.6 Sodium Channels in AP Initiation of CA1 Pyramidal Neurons (Royeck et al. 2008) | |
| "... We show that the Na+ channel NaV1.6 displays a striking aggregation at the AIS of cortical neurons. ... In combination with simulations using a realistic computer model of a CA1 pyramidal cell, our results imply that a hyperpolarized voltage-dependence of activation of AIS NaV1.6 channels is important both in determining spike threshold and localizing spike initiation to the AIS. ... These results suggest that NaV1.6 subunits at the AIS contribute significantly to its role as spike trigger zone and shape repetitive discharge properties of CA1 neurons." | |
| Axonal Projection and Interneuron Types (Helmstaedter et al. 2008) | |
| "Interneurons in layer 2/3 (L2/3) of the somatosensory cortex show 4 types of axonal projection patterns with reference to the laminae and borders of columns in rat barrel cortex (Helmstaedter et al. 2008a). Here, we analyzed the dendritic geometry and electrical excitability of these interneurons. ... We conclude that 1) dendritic polarity is correlated to intrinsic electrical excitability, and 2) the axonal projection pattern represents an independent classifier of interneurons. " | |
| Axonal gap junctions produce fast oscillations in cerebellar Purkinje cells (Traub et al. 2008) | |
| Examines how electrical coupling between proximal axons produces fast oscillations in cerebellar Purkinje cells. Traub RD, Middleton SJ, Knopfel T, Whittington MA (2008) Model of very fast (>75 Hz) network oscillations generated by electrical coupling between the proximal axons of cerebellar Purkinje cells. European Journal of Neuroscience in press. | |
| BCM-like synaptic plasticity with conductance-based models (Narayanan Johnston, 2010) | |
| " ... Although the BCM-like plasticity framework has been a useful formulation to understand synaptic plasticity and metaplasticity, a mechanism for the activity-dependent regulation of this modification threshold has remained an open question. In this simulation study based on CA1 pyramidal cells, we use a modification of the calcium-dependent hypothesis proposed elsewhere and show that a change in the hyperpolarization-activated, nonspecific-cation h current is capable of shifting the modification threshold. ..." | |
| Balance of excitation and inhibition (Carvalho and Buonomano 2009) | |
| " ... Here, theoretical analyses reveal that excitatory synaptic strength controls the threshold of the neuronal input-output function, while inhibitory plasticity alters the threshold and gain. Experimentally, changes in the balance of excitation and inhibition in CA1 pyramidal neurons also altered their input-output function as predicted by the model. These results support the existence of two functional modes of plasticity that can be used to optimize information processing: threshold and gain plasticity." | |
| Basal ganglia-thalamic network model for deep brain stimulation (So et al. 2011) | |
| This is a model of the basal ganglia-thalamic network, modified from the Rubin and Terman model (High frequency stimulation of the Subthalamic Nucleus, Rubin and Terman 2004). We subsequently used this model to investigate the effectiveness of STN and GPi DBS as well as lesion when various proportions of local cells and fibers of passage were activated or silenced. The BG network exhibited characteristics consistent with published experimental data, both on the level of single cells and on the network level. Perhaps most notably, and in contrast to the original RT model, the changes in the thalamic error index with changes in the DBS frequency matched well the changes in clinical symptoms with changes in DBS frequency. | |
| Biophysical and phenomenological models of spike-timing dependent plasticity (Badoual et al. 2006) | |
| "Spike-timing dependent plasticity (STDP) is a form of associative synaptic modification which depends on the respective timing of pre- and post-synaptic spikes. The biophysical mechanisms underlying this form of plasticity are currently not known. We present here a biophysical model which captures the characteristics of STDP, such as its frequency dependency, and the effects of spike pair or spike triplet interactions. ... A simplified phenomenological model is also derived..." | |
| Biophysically detailed model of the mouse sino-atrial node cell (Kharche et al. 2011) | |
| This model is developed to study the role of various electrophysiological mechanisms in generating cardiac pacemaking action potentials (APs).The model incorporates membrane ionic currents and intracellular mechanisms contributing to spontaneous mouse SAN APs. The model was validated by testing the functional roles of individual membrane currents in one and multiple parameter analyses.The roles of intracellular Ca2+-handling mechanisms on cardiac pacemaking were also investigated in the model. | |
| Breakdown of accmmodation in nerve: a possible role for INAp (Hennings et al 2005) | |
| The present modeling study suggests that persistent, low-threshold, rapidly activating sodium currents have a key role in breakdown of accommodation, and that breakdown of accommodation can be used as a tool for studying persistent sodium current under normal and pathological conditions. See paper for more and details. | |
| Brette-Gerstner model (Touboul and Brette 2008) | |
| Brian code to simulate the Brette-Gerstner model and reproduce the figures of Touboul and Brette, Biol Cyber (2008). | |
| Bursting activity of neuron R15 in Aplysia (Canavier et al 1991, Butera et al 1995) | |
| An equivalent circuit model of the R15 bursting neuron in Aplysia has been combined with a fluid compartment model, resulting in a model that incorporates descriptions of most of the membrane ion channels that are known to exist in the somata of R15, as well as providing a Ca2+ balance on the cell. ... (from the second paper) we have implemented proposed mechanisms for the modulation of two ionic currents (IR and ISI) that play key roles in regulating its spontaneous electrical activity. The model was sufficient to simulate a wide range of endogenous activity in the presence of various concentrations of 5-HT or DA. See papers for more and details. | |
| CA1 Pyramidal Neuron: Synaptic Scaling (London, Segev 2001) | |
| London and Segev (2001) discuss location dependent and location independent synaptic scaling in a model CA1 neuron with passive dendrites. The freely available text is followed by a critique by Maggee and Cook who comment that the London and Segev model is accurate and informative and however needs to be augmented by active channels in dendrites. Note: the zip files for this model are stored at the nature neuroscience website - Click above Supplementary Source Code in the readme.html in the model files | |
| CA1 Pyramidal Neuron: slow Na+ inactivation (Migliore 1996) | |
| Model files from the paper: M. Migliore, Modeling the attenuation and failure of action potentials in the dendrites of hippocampal neurons, Biophys. J. 71:2394-403 (1996). Please see the below readme file for installation and use instructions. Contact michele.migliore@pa.ibf.cnr.it if you have any questions about the implementation of the model. | |
| CA1 pyramidal cell: I_NaP and I_M contributions to somatic bursting (Golomb et al 2006) | |
| To study the mechanisms of bursting, we have constructed a conductance-based, one-compartment model of CA1 pyramidal neurons. In this neuron model, reduced [Ca2+]o is simulated by negatively shifting the activation curve of the persistent Na+ current (INaP), as indicated by recent experimental results. The neuron model accounts, with different parameter sets, for the diversity of firing patterns observed experimentally in both zero and normal [Ca2+]o. Increasing INaP in the neuron model induces bursting and increases the number of spikes within a burst, but is neither necessary nor sufficient for bursting. We show, using fast-slow analysis and bifurcation theory, that the M-type K+ current (IM) allows bursting by shifting neuronal behavior between a silent and a tonically-active state, provided the kinetics of the spike generating currents are sufficiently, though not extremely, fast. We suggest that bursting in CA1 pyramidal cells can be explained by a single compartment *square bursting* mechanism with one slow variable, the activation of IM. See paper for more and details. | |
| CA1 pyramidal neuron (Migliore et al 1999) | |
| Hippocampal CA1 pyramidal neuron model from the paper M.Migliore, D.A Hoffman, J.C. Magee and D. Johnston (1999) Role of an A-type K+ conductance in the back-propagation of action potentials in the dendrites of hippocampal pyramidal neurons, J. Comput. Neurosci. 7, 5-15. Instructions are provided in the below README file.Contact michele.migliore@pa.ibf.cnr.it if you have any questions about the implementation of the model. | |
| CA1 pyramidal neuron synaptic integration (Jarsky et al. 2005) | |
| "The perforant-path projection to the hippocampus forms synapses in the apical tuft of CA1 pyramidal neurons. We used computer modeling to examine the function of these distal synaptic inputs, which led to three predictions that we confirmed in experiments using rat hippocampal slices. ... This 'gating' of dendritic spike propagation may be an important activation mode of CA1 pyramidal neurons, and its modulation by neurotransmitters or long-term, activity-dependent plasticity may be an important feature of dendritic integration during mnemonic processing in the hippocampus." | |
| CA1 pyramidal neuron synaptic integration (Li and Ascoli 2006, 2008) | |
| The model shows how different input patterns (irregular & asynchronous, irregular & synchronous, regular & asynchronous, regular & synchronous) affect the neuron's output rate when 1000 synapses are distributed in the proximal apical dendritic tree of a hippocampus CA1 pyramidal neuron. | |
| CA1 pyramidal neuron to study INaP properties and repetitive firing (Uebachs et al. 2010) | |
| A model of a CA1 pyramidal neuron containing a biophysically realistic morphology and 15 distributed voltage and Ca2+-dependent conductances. Repetitive firing is modulated by maximal conductance and the voltage dependence of the persistent Na+ current (INaP). | |
| CA1 pyramidal neuron: as a 2-layer NN and subthreshold synaptic summation (Poirazi et al 2003) | |
| We developed a CA1 pyramidal cell model calibrated with a broad spectrum of in vitro data. Using simultaneous dendritic and somatic recordings, and combining results for two different response measures (peak vs. mean EPSP), two different stimulus formats (single shock vs. 50 Hz trains), and two different spatial integration conditions (within vs. between-branch summation), we found the cell's subthreshold responses to paired inputs are best described as a sum of nonlinear subunit responses, where the subunits correspond to different dendritic branches. In addition to suggesting a new type of experiment and providing testable predictions, our model shows how conclusions regarding synaptic arithmetic can be influenced by an array of seemingly innocuous experimental design choices. | |
| CA1 pyramidal neuron: Synaptic Scaling (Magee, Cook 2000) | |
| Jeffrey Magee and Erik Cook found evidence in experiments and modeling that support the hypothesis that an increase in synaptic conductance for synapses at larger distances from the soma is responsible for reducing the location dependence (relative to the soma) of synapses. | |
| CA1 pyramidal neuron: calculation of MRI signals (Cassara et al. 2008) | |
| NEURON mod files from the paper: Cassarà AM, Hagberg GE, Bianciardi M, Migliore M, Maraviglia B. Realistic simulations of neuronal activity: A contribution to the debate on direct detection of neuronal currents by MRI. Neuroimage. 39:87-106 (2008). In this paper, we use a detailed calculation of the magnetic field produced by the neuronal currents propagating over a hippocampal CA1 pyramidal neuron placed inside a cubic MR voxel of length 1.2 mm to estimate the Magnetic Resonance signal. | |
| CA1 pyramidal neuron: conditional boosting of dendritic APs (Watanabe et al 2002) | |
| Model files from the paper Watanabe S, Hoffman DA, Migliore M, Johnston D (2002). The experimental and modeling results support the hypothesis that dendritic K-A channels and the boosting of back-propagating action potentials contribute to the induction of LTP in CA1 neurons. See the paper for details. Questions about the model may be addressed to Michele Migliore: michele.migliore@pa.ibf.cnr.it | |
| CA1 pyramidal neuron: depolarization block (Bianchi et al. 2012) | |
| NEURON files from the paper: On the mechanisms underlying the depolarization block in the spiking dynamics of CA1 pyramidal neurons by D.Bianchi, A. Marasco, A.Limongiello, C.Marchetti, H.Marie,B.Tirozzi, M.Migliore (2012). J Comput. Neurosci. In press. DOI: 10.1007/s10827-012-0383-y. Experimental findings shown that under sustained input current of increasing strength neurons eventually stop firing, entering a depolarization block. We analyze the spiking dynamics of CA1 pyramidal neuron models using the same set of ionic currents on both an accurate morphological reconstruction and on its reduction to a single-compartment. The results show the specic ion channel properties and kinetics that are needed to reproduce the experimental findings, and how their interplay can drastically modulate the neuronal dynamics and the input current range leading to depolarization block. | |
| CA1 pyramidal neuron: effects of Lamotrigine on dendritic excitability (Poolos et al 2002) | |
| NEURON mod files from N. Poolos, M. Migliore, and D. Johnston, Nature Neuroscience (2002). The experimental and modeling results in this paper demonstrate for the first time that neuronal excitability can be altered by pharmaceuticals acting selectively on dendrites, and suggest an important role for Ih in controlling dendritic excitability and epileptogenesis. | |
| CA1 pyramidal neuron: functional significance of axonal Kv7 channels (Shah et al. 2008) | |
| The model used in this paper confirmed the experimental findings suggesting that axonal Kv7 channels are critically and uniquely required for determining the inherent spontaneous firing of hippocampal CA1 pyramids, independently of alterations in synaptic activity. The model predicts that the axonal Kv7 density could be 3-5 times that at the soma. | |
| CA1 pyramidal neuron: synaptically-induced bAP predicts synapse location (Sterratt et al. 2012) | |
| This is an adaptation of Poirazi et al.'s (2003) CA1 model that is used to measure BAP-induced voltage and calcium signals in spines after simulated Schaffer collateral synapse stimulation. In the model, the peak calcium concentration is highly correlated with soma-synapse distance under a number of physiologically-realistic suprathreshold stimulation regimes and for a range of dendritic morphologies. There are also simulations demonstrating that peak calcium can be used to set up a synaptic democracy in a homeostatic manner, whereby synapses regulate their synaptic strength on the basis of the difference between peak calcium and a uniform target value. | |
| CA1 pyramidal neurons: effects of Kv7 (M-) channels on synaptic integration (Shah et al. 2011) | |
| NEURON mod files from the paper: Shah et al., 2011. In this study, using a combination of electrophysiology and computational modelling, we show that these channels selectively influence peri-somatic but not dendritic post-synaptic excitatory synaptic potential (EPSP) integration in CA1 pyramidal cells. This may be important for their relative contributions to physiological processes such as synaptic plasticity as well as patho-physiological conditions such as epilepsy. | |
| CA1 pyramidal: Stochastic amplification of KCa in Ca2+ microdomains (Stanley et al. 2011) | |
| This minimal model investigates stochastic amplification of calcium-activated potassium (KCa) currents. Amplification results from calcium being released in short high amplitude pulses associated with the stochastic gating of calcium channels in microdomains. This model predicts that such pulsed release of calcium significantly increases subthreshold SK2 currents above what would be produced by standard deterministic models. However, there is little effect on a simple sAHP current kinetic scheme. This suggests that calcium stochasticity and microdomains should be considered when modeling certain KCa currents near subthreshold conditions. | |
| CA1 stratum radiatum interneuron multicompartmental model (Katona et al. 2011) | |
| The model examines dendritic NMDA-spike generation and propagation in the dendrites of CA1 stratum radiatum interneurons. It contains NMDA-channels in a clustered pattern on a dendrite and K-channels. The simulation shows the whole NMDA spike and the rising phase of the traces in separate windows. | |
| CA3 Pyramidal Neuron (Migliore et al 1995) | |
| Model files from the paper: M. Migliore, E. Cook, D.B. Jaffe, D.A. Turner and D. Johnston, Computer simulations of morphologically reconstructed CA3 hippocampal neurons, J. Neurophysiol. 73, 1157-1168 (1995). Demonstrates how the same cell could be bursting or non bursting according to the Ca-independent conductance densities. Includes calculation of intracellular Calcium. Instructions are provided in the below README file. Contact michele.migliore@pa.ibf.cnr.it if you have any questions about the implementation of the model. | |
| CA3 pyramidal cell: rhythmogenesis in a reduced Traub model (Pinsky, Rinzel 1994) | |
| Fig. 2A and 3 are reproduced in this simulation of Pinsky PF, Rinzel J (1994). | |
| CA3 pyramidal neuron (Lazarewicz et al 2002) | |
| The model shows how using a CA1-like distribution of active dendritic conductances in a CA3 morphology results in dendritic initiation of spikes during a burst. | |
| CN bushy, stellate neurons (Rothman, Manis 2003) | |
| Using kinetic data from three different K+ currents in acutely isolated neurons, a single electrical compartment model representing the soma of a ventral cochlear nucleus (VCN) neuron was created. The K+ currents include a fast transient current (IA), a slow-inactivating low-threshold current (ILT), and a noninactivating high-threshold current (IHT). The model also includes a fast-inactivating Na+ current, a hyperpolarization-activated cation current (Ih), and 1-50 auditory nerve synapses. With this model, the role IA, ILT, and IHT play in shaping the discharge patterns of VCN cells is explored. Simulation results indicate these currents have specific roles in shaping the firing patterns of stellate and bushy CN cells. (see readme.txt and the papers, esp 2003c, for details). Any questions regarding these implementations should be directed to: pmanis@med.unc.edu 2 April 2004 Paul B Manis, Ph.D. | |
| CN pyramidal fusiform cell (Kanold, Manis 2001) | |
| Pyramidal cells in the dorsal cochlear nucleus (DCN) show three characteristic discharge patterns in response tones: pauser, buildup, and regular firing. Experimental evidence suggests that a rapidly inactivating K+ current (I(KIF)) plays a critical role in generating these discharge patterns. To explore the role of I(KIF), we used a computational model based on the biophysical data. The model replicated the dependence of the discharge pattern on the magnitude and duration of hyperpolarizing prepulses, and I(KIF) was necessary to convey this dependence. Experimentally, half-inactivation voltage and kinetics of I(KIF) show wide variability. Varying these parameters in the model ... suggests that pyramidal cells can adjust their sensitivity to different temporal patterns of inhibition and excitation by modulating the kinetics of I(KIF). Overall, I(KIF) is a critical conductance controlling the excitability of DCN pyramidal cells. (See readme.txt and paper for details). Any questions regarding these implementations should be directed to: pmanis@med.unc.edu 2 April 2004 Paul B Manis, Ph.D. | |
| Ca2+-activated I_CAN and synaptic depression promotes network-dependent oscil. (Rubin et al. 2009) | |
| "... the preBotzinger complex... we present and analyze a mathematical model demonstrating an unconventional mechanism of rhythm generation in which glutamatergic synapses and the short-term depression of excitatory transmission play key rhythmogenic roles. Recurrent synaptic excitation triggers postsynaptic Ca2+- activated nonspecific cation current (ICAN) to initiate a network-wide burst. Robust depolarization due to ICAN also causes voltage-dependent spike inactivation, which diminishes recurrent excitation and thus attenuates postsynaptic Ca2+ accumulation. ..." | |
| Caffeine-induced electrical oscillations in Aplysia neurons (Komendantov, Kononenko 2000) | |
| It has been found that in cultured Aplysia neurons bath applications of 40 mM cafffeine evokes oscillations of the membrane potential with about a 40 mV amplitude with a frequency of 0.2 to 0.5 Hz. The most probable mechanism of these caffeine-induced oscillations is inhibition of voltage-activated outward potassium current and, as can be seen from our mathematical modeling, slowdown of inactivation of inward sodium current. It seems likely that these oscillations have a purely membrane origin. Please see paper for results and details. | |
| Calcium and potassium currents of olfactory bulb juxtaglomerular cells (Masurkar and Chen 2011) | |
| Inward and outward currents of the olfactory bulb juxtaglomerular cells are characterized in the experiments and modeling in these two Masurkar and Chen 2011 papers. | |
| Calcium spikes in basal dendrites (Kampa and Stuart 2006) | |
| This model was published in Kampa & Stuart (2006) J Neurosci 26(28):7424-32. The simulation creates two plots showing voltage and calcium changes in basal dendrites of layer 5 pyramidal neurons during action potential backpropagation. created by B. Kampa (2006) | |
| Calcium waves in neuroblastoma cells (Fink et al. 2000) | |
| Uses a model of IP3-mediated release of Ca from endoplasmic reticulum (ER) to study how initiation and propagation of Ca waves are affected by cell geometry, spatial distributions of ER and IP3 generation, and diffusion of Ca and mobile buffer. | |
| Cancelling redundant input in ELL pyramidal cells (Bol et al. 2011) | |
| The paper investigates the property of the electrosensory lateral line lobe (ELL) of the brain of weakly electric fish to cancel predictable stimuli. Electroreceptors on the skin encode all signals in their firing activity, but superficial pyramidal (SP) cells in the ELL that receive this feedforward input do not respond to constant sinusoidal signals. This cancellation putatively occurs using a network of feedback delay lines and burst-induced synaptic plasticity between the delay lines and the SP cell that learns to cancel the redundant input. Biologically, the delay lines are parallel fibres from cerebellar-like granule cells in the eminentia granularis posterior. A model of this network (e.g. electroreceptors, SP cells, delay lines and burst-induced plasticity) was constructed to test whether the current knowledge of how the network operates is sufficient to cancel redundant stimuli. | |
| Carbon nanotubes as electrical interfaces to neurons (Giugliano et al. 2008) | |
| In the present NEURON model, we explore simple phenomenological models of the extracellular coupling, occurring at the neuron-metal microelectrode junction and (possibly) at the neuron-carbon nanotube junction. | |
| Cardiac Atrial Cell (Courtemanche et al 1998) (C++) | |
| The mechanisms underlying many important properties of the human atrial action potential (AP) are poorly understood. Using specific formulations of the K+, Na+, and Ca2+ currents based on data recorded from human atrial myocytes, along with representations of pump, exchange, and background currents, we developed a mathematical model of the AP. The model AP resembles APs recorded from human atrial samples and responds to rate changes, L-type Ca2+ current blockade, Na+/Ca2+ exchanger inhibition, and variations in transient outward current amplitude in a fashion similar to experimental recordings. Rate-dependent adaptation of AP duration, an important determinant of susceptibility to atrial fibrillation, was attributable to incomplete L-type Ca2+ current recovery from inactivation and incomplete delayed rectifier current deactivation at rapid rates. Experimental observations of variable AP morphology could be accounted for by changes in transient outward current density, as suggested experimentally. We conclude that this mathematical model of the human atrial AP reproduces a variety of observed AP behaviors and provides insights into the mechanisms of clinically important AP properties. | |
| Cardiac action potentials and pacemaker activity of sinoatrial node (DiFrancesco & Noble 1985) | |
| "Equations have been developed to describe cardiac action potentials and pacemaker activity. The model takes account of extensive developments in experimental work ..." | |
| Cardiac sarcomere dynamics (Negroni and Lascano 1996) | |
| "A muscle model establishing the link between cross-bridge dynamics and intracellular Ca2+ kinetics was assessed by simulation of experiments performed in isolated cardiac muscle. The model is composed by the series arrangement of muscle units formed by inextensible thick and thin filaments in parallel with an elastic element. Attached cross-bridges act as independent force generators whose force is linearly related to the elongation of their elastic structure. Ca2+ kinetics is described by a four-state system of sites on the thin filament associated with troponin C: sites with free troponin C (T), sites with Ca2+ bound to troponin C (TCa); sites with Ca2+ bound to troponin C and attached cross-bridges (TCa*); and sites with troponin C not associated with Ca2+ and attached cross-bridges (T*). The intracellular Ca2+ concentration ([Ca2+]) is controlled solely by the sarcoplasmic reticulum through an inflow function and a saturated outflow pump function. ..." | |
| Cerebellar Golgi cell (Solinas et al. 2007a, 2007b) | |
| "... Our results suggest that a complex complement of ionic mechanisms is needed to fine-tune separate aspects of the neuronal response dynamics. Simulations also suggest that the Golgi cell may exploit these mechanisms to obtain a fine regulation of timing of incoming mossy fiber responses and granular layer circuit oscillation and bursting." | |
| Cerebellar Nucleus Neuron (Steuber, Schultheiss, Silver, De Schutter & Jaeger, 2010) | |
| This is the GENESIS 2.3 implementation of a multi-compartmental deep cerebellar nucleus (DCN) neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than -70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum. | |
| Cerebellar Purkinje Cell: resurgent Na current and high frequency firing (Khaliq et al 2003) | |
| These mod files supplied by Dr Raman are for the below two references. ... we modeled action potential firing by simulating eight currents directly recorded from Purkinje cells in both wild-type and (mutant) med mice. Regular, high-frequency firing was slowed in med Purkinje neurons. In addition to disrupted sodium currents, med neurons had small but significant changes in potassium and leak currents. Simulations indicated that these modified non-sodium currents could not account for the reduced excitability of med cells but instead slightly facilitated spiking. The loss of NaV1.6-specific kinetics, however, slowed simulated spontaneous activity. Together, the data suggest that across a range of conditions, sodium currents with a resurgent component promote and accelerate firing. See papers for more and details. | |
| Cerebellar purkinje cell (De Schutter and Bower 1994) | |
| Tutorial simulation of a cerebellar Purkinje cell. This tutorial is based upon a GENESIS simulation of a cerebellar Purkinje cell, modeled and fine-tuned by Erik de Schutter. The tutorial assumes that you have a basic knowledge of the Purkinje cell and its synaptic inputs. It gives visual insight in how different properties as concentrations and channel conductances vary and interact within a real Purkinje cell. | |
| Cerebellar purkinje cell: K and Ca channels regulate APs (Miyasho et al 2001) | |
| We adopted De Schutter and Bower's model as the starting point, then modified the descriptions of several ion channels, such as the P-type Ca channel and the delayed rectifier K channel, and added class-E Ca channels and D-type K channels to the model. Our new model reproduces most of our experimental results and supports the conclusions of our experimental study that class-E Ca channels and D-type K channels are present and functioning in the dendrites of Purkinje neurons. | |
| Cerebellar purkinje cell: interacting Kv3 and Na currents influence firing (Akemann, Knopfel 2006) | |
| Purkinje neurons spontaneously generate action potentials in the absence of synaptic drive and thereby exert a tonic, yet plastic, input to their target cells in the deep cerebellar nuclei. Purkinje neurons express two ionic currents with biophysical properties that are specialized for high-frequency firing: resurgent sodium currents and potassium currents mediated by Kv3.3. … Numerical simulations indicated that Kv3.3 increases the spontaneous firing rate via cooperation with resurgent sodium currents. We conclude that the rate of spontaneous action potential firing of Purkinje neurons is controlled by the interaction of Kv3.3 potassium currents and resurgent sodium currents. See paper for more and details. | |
| Chirp stimulus responses in a morphologically realistic model (Narayanan and Johnston, 2007) | |
| ...we built a multicompartmental model with a morphologically realistic three-dimensional reconstruction of a CA1 pyramidal neuron. The only active conductance we added to the model was the h conductance. ... We conclude that experimentally observed gradient in density of h channels could theoretically account for experimentally observed gradient in resonance properties (Narayanan and Johnston, 2007). | |
| ClC-2 channels regulate neuronal excitability, not intracellular Cl- levels (Ratte & Prescott 2011) | |
| "The model is for a generic, single compartment neuron with multiple ion currents. The most notable mechanisms include ClC-2 (a rectifying chloride-leak channel) and KCC2 (potassium chloride co-transporter 2). A significant feature of the model is that it tracks intracellular chloride concentration. Moreover, the GABA-A receptor is modeled as passing both chloride and bicarbonate ions, which is important for proper calculation of the GABA reversal potential. Ornstein-Unlenbeck processes to simulate synaptic inhibition and excitation are also included." | |
| Coincidence detection in avian brainstem (Simon et al 1999) | |
| A detailed biophysical model of coincidence detector neurons in the nucleus laminaris (auditory brainstem) which are purported to detect interaural time differences (ITDs) from Simon et al 1999. | |
| Comparison of full and reduced globus pallidus models (Hendrickson 2010) | |
| In this paper, we studied what features of realistic full model activity patterns can and cannot be preserved by morphologically reduced models. To this end, we reduced the morphological complexity of a full globus pallidus neuron model possessing active dendrites and compared its spontaneous and driven responses to those of the reduced models. | |
| Competition for AP initiation sites in a circuit controlling simple learning (Cruz et al. 2007) | |
| "The spatial and temporal patterns of action potential initiations were studied in a behaving leech preparation to determine the basis of increased firing that accompanies sensitization, a form of non-associative learning requiring the S-interneurons. ... The S-interneurons, one in each ganglion and linked by electrical synapses with both neighbors to form a chain, are interposed between sensory and motor neurons. ... the single site with the largest initiation rate, the S-cell in the stimulated segment, suppressed initiations in adjacent ganglia. Experiments showed this was both because (1) it received the earliest, greatest input and (2) the delayed synaptic input to the adjacent S-cells coincided with the action potential refractory period. A compartmental model of the S-cell and its inputs showed that a simple, intrinsic mechanism of inexcitability after each action potential may account for suppression of impulse initiations. Thus, a non-synaptic competition between neurons alters synaptic integration in the chain. In one mode, inputs to different sites sum independently, whereas in another, synaptic input to a single site precisely specifies the overall pattern of activity." | |
| Complex CA1-neuron to study AP initiation (Wimmer et al. 2010) | |
| Complex model of a pyramidal CA1-neuron, adapted from Royeck, M., et al. Role of axonal NaV1.6 sodium channels in action potential initiation of CA1 pyramidal neurons. Journal of neurophysiology 100, 2361-2380 (2008). It contains a biophysically realistic morphology comprising 265 compartments (829 segments) and 15 different distributed Ca2+- and/or voltage-dependent conductances. | |
| Computational neuropharmacology of CA1 pyramidal neuron (Ferrante et al. 2008) | |
| In this paper, the model was used to show how neuroactive drugs targeting different neuronal mechanisms affect the signal integration in CA1 pyramidal neuron. Ferrante M, Blackwell KT, Migliore M, Ascoli GA (2008) | |
| Computer simulations of neuron-glia interactions mediated by ion flux (Somjen et al. 2008) | |
| "... To examine the effect of glial K+ uptake, we used a model neuron equipped with Na+, K+, Ca2+ and Cl− conductances, ion pumps and ion exchangers, surrounded by interstitial space and glia. The glial membrane was either “passive”, incorporating only leak channels and an ion exchange pump, or it had rectifying K+ channels. We computed ion fluxes, concentration changes and osmotic volume changes. ... We conclude that voltage gated K+ currents can boost the effectiveness of the glial “potassium buffer” and that this buffer function is important even at moderate or low levels of excitation, but especially so in pathological states." | |
| Conditions of dominant effectiveness of distal dendrites (Korogod, Kulagina 1998) | |
| The model illustrates and explains bistable spatial patterns of the current transfer effectiveness in the active dendrite with distributed (multiple) tonic excitatory, NMDA type, synaptic input. | |
| Contibutions of input and history to motoneuron output (Powers et al 2005) | |
| "The present study presents results based on recordings of noise-driven discharge in rat hypoglossal motoneurones ... First, we show that the hyperpolarizing trough is larger in Average Current Trajectories (ACTs) calculated from spikes preceded by long interspike intervals, and minimal or absent in those based on short interspike intervals. Second, we show that the trough is present for ACTs calculated from the discharge of a threshold-crossing neurone model with a postspike after- hyperpolarization (AHP), but absent from those calculated from the discharge of a model without an AHP. We show that it is possible to represent noise-driven discharge using a two-component linear model that predicts discharge probability based on the sum of a feedback kernel and a stimulus kernel. The feedback kernel reflects the influence of prior discharge mediated by the AHP, and it increases in amplitude when AHP amplitude is increased by pharmacological manipulations. Finally, we show that the predictions of this model are virtually identical to those based on the first-order Wiener kernel. This suggests that the Wiener kernel derived from standard white-noise analysis of noise-driven discharge in neurones actually reflect the effects of both stimulus and discharge history." See paper for more and details. | |
| Contrast invariance by LGN synaptic depression (Banitt et al. 2007) | |
| "Simple cells in layer 4 of the primary visual cortex of the cat show contrast-invariant orientation tuning, in which the amplitude of the peak response is proportional to the stimulus contrast but the width of the tuning curve hardly changes with contrast. This study uses a detailed model of spiny stellate cells (SSCs) from cat area 17 to explain this property. The model integrates our experimental data, including morphological and intrinsic membrane properties and the number and spatial distribution of four major synaptic input sources of the SSC: the dorsal lateral geniculate nucleus (dLGN) and three cortical sources. ... The model response is in close agreement with experimental results, in terms of both output spikes and membrane voltage (amplitude and fluctuations), with reasonable exceptions given that recurrent connections were not incorporated." | |
| Control of vibrissa motoneuron firing (Harish and Golomb 2010) | |
| We construct and analyze a single-compartment, conductance-based model of vibrissa motoneurons. Low firing rates are supported in extended regimes by adaptation currents and the minimal firing rate decreases with the persistent sodium conductance gNaP and increases with M-potassium and h-cation conductances. Suprathreshold resonance results from the locking properties of vMN firing to stimuli and from reduction of firing rates at low frequencies by slow M and afterhyperpolarization potassium conductances. h conductance only slightly affects the suprathreshold resonance. When a vMN is subjected to a small periodic CPG input, serotonergically induced gNaP elevation may transfer the system from quiescence to a firing state that is highly locked to the CPG input. | |
| Correcting space clamp in dendrites (Schaefer et al. 2003 and 2007) | |
| In voltage-clamp experiments, incomplete space clamp distorts the recorded currents, rendering accurate analysis impossible. Here, we present a simple numerical algorithm that corrects such distortions. The method enabled accurate retrieval of the local densities, kinetics, and density gradients of somatic and dendritic channels. The correction method was applied to two-electrode voltage-clamp recordings of K currents from the apical dendrite of layer 5 neocortical pyramidal neurons. The generality and robustness of the algorithm make it a useful tool for voltage-clamp analysis of voltage-gated currents in structures of any morphology that is amenable to the voltage-clamp technique. | |
| Cortical network model of posttraumatic epileptogenesis (Bush et al 1999) | |
| This simulation from Bush, Prince, and Miller 1999 shows the epileptiform response (Fig. 6C) to a brief single stimulation in a 500 cell network of multicompartment models, some of which have active dendrites. The results which I obtained under Redhat Linux is shown in result.gif. Original 1997 code from Paul Bush modified slightly by Bill Lytton to make it work with current version of NEURON (5.7.139). Thanks to Paul Bush and Ken Miller for making the code available. | |
| Currents contributing to decision making in neurons B31-B32 of Aplysia (Hurwitz et al. 2008) | |
| "Biophysical properties of neurons contributing to the ability of an animal to decide whether or not to respond were examined. B31/B32, two pairs of bilaterally symmetrical Aplysia neurons, are major participants in deciding to initiate a buccal motor program, the neural correlate of a consummatory feeding response. B31/B32 respond to an adequate stimulus after a delay, during which time additional stimuli influence the decision to respond. B31/B32 then respond with a ramp depolarization followed by a sustained soma depolarization and axon spiking that is the expression of a commitment to respond to food. Four currents contributing to decision making in B31/B32 were characterized, and their functional effects were determined, in current- and voltage-clamp experiments and with simulations. ... Hodgkin-Huxley kinetic analyses were performed on the outward currents. Simulations using equations from these analyses showed that IK-V and IK-A slow the ramp depolarization preceding the sustained depolarization. The three outward currents contribute to braking the B31/B32 depolarization and keeping the sustained depolarization at a constant voltage. The currents identified are sufficient to explain the properties of B31/B32 that play a role in generating the decision to feed." | |
| Cytoplasmic electric fields and electroosmosis (Andreev 2013) | |
| The paper presents two mathematical models describing the role of electroosmosis in the transport of the negatively charged messenger proteins to the negatively charged nucleus and in the recovery of the fluorescence after photobleaching. The parameters of the models were derived from the extensive review of the literature data. Computer simulations were performed within the COMSOL 4.2a software environment. The first model demonstrated that the presence of electroosmosis might intensify the flux of messenger proteins to the nucleus and allow the efficient transport of the negatively charged phosphorylated messenger proteins against the electrostatic repulsion of the negatively charged nucleus. The second model revealed that the presence of the electroosmotic flow made the time of fluorescence recovery dependent on the position of the bleaching spot relative to cellular membrane. | |
| D2 dopamine receptor modulation of interneuronal activity (Maurice et al. 2004) | |
| "... Using a combination of electrophysiological, molecular, and computational approaches, the studies reported here show that D2 dopamine receptor modulation of Na+ currents underlying autonomous spiking contributes to a slowing of discharge rate, such as that seen in vivo. Four lines of evidence support this conclusion. ... Fourth, simulation of cholinergic interneuron pacemaking revealed that a modest increase in the entry of Na+ channels into the slow-inactivated state was sufficient to account for the slowing of pacemaker discharge. These studies establish a cellular mechanism linking dopamine and the reduction in striatal cholinergic interneuron activity seen in the initial stages of associative learning." See paper for more and details. | |
| Data-driven, HH-type model of the lateral pyloric (LP) cell in the STG (Nowotny et al. 2008) | |
| This model was developed using voltage clamp data and existing LP models to assemble an initial set of currents which were then adjusted by extensive fitting to a long data set of an isolated LP neuron. The main points of the work are a) automatic fitting is difficult but works when the method is carefully adjusted to the problem (and the initial guess is good enough). b) The resulting model (in this case) made reasonable predictions for manipulations not included in the original data set, e.g., blocking some of the ionic currents. c) The model is reasonably robust against changes in parameters but the different parameters vary a lot in this respect. d) The model is suitable for use in a network and has been used for this purpose (Ivanchenko et al. 2008) | |
| Dendritic Discrimination of Temporal Input Sequences (Branco et al. 2010) | |
| Compartmental model of a layer 2/3 pyramidal cell in the rat somatosensory cortex, exploring NMDA-dependent sensitivity to the temporal sequence of synaptic activation. | |
| Dendritic L-type Ca currents in motoneurons (Carlin et al 2000) | |
| A component of recorded currents demonstrated kinetics consistent with a current originating at a site spatially segregated from the soma. In response to step commands this component was seen as a late-onset, low amplitude persistent current whilst in response to depolarizing-repolarizing ramp commands a low voltage clockwise current hysteresis was recorded. Simulations using a neuromorphic motoneuron model could reproduce these currents only if a noninactivating calcium conductance was placed in the dendritic compartments. | |
| Dendritic Na inactivation drives a decrease in ISI (Fernandez et al 2005) | |
| We use a combination of dynamical analysis and electrophysiological recordings to demonstrate that spike broadening in dendrites is primarily caused by a cumulative inactivation of dendritic Na(+) current. We further show that a reduction in dendritic Na(+) current increases excitability by decreasing the interspike interval (ISI) and promoting burst firing. | |
| Dendritic Na+ spike initiation and backpropagation of APs in active dendrites (Nevian et al. 2007) | |
| NEURON model used to create simulations shown in figure 6 of the paper. The model includes two point processes; one for dendritic spike initiation and the other for somatic action potential generation. The effect of filtering by imperfect recording electrode can be examined in somatic and dendritic locations. | |
| Dendritic processing of excitatory synaptic input in GnRH neurons (Roberts et al. 2006) | |
| "... we used electrophysiological recordings and neuronal reconstructions to generate computer models of (Gonadotopin-Releasing Hormone) GnRH neurons to examine the effects of synaptic inputs at varying distances from the soma along dendrites. ... analysis of reduced morphology models indicated that this population of cells is unlikely to exhibit low-frequency tonic spiking in the absence of synaptic input. ... applying realistic patterns of synaptic input to modeled GnRH neurons indicates that synapses located more than about 30% of the average dendrite length from the soma cannot drive firing at frequencies consistent with neuropeptide release. Thus, processing of synaptic input to dendrites of GnRH neurons is probably more complex than simple summation." | |
| Dendritic signals command firing dynamics in a Cerebellar Purkinje Cell model (Genet et al. 2010) | |
| This model endows the dendrites of a reconstructed Purkinje cells (PC) with the mechanism of Ca-dependent plateau potentials and spikes described in Genet, S., and B. Delord. 2002. A biophysical model of nonlinear dynamics underlying plateau potentials and calcium spikes in Purkinje cell dendrites. J. Neurophysiol. 88:2430–2444). It is a part of a comprehensive mathematical study suggesting that active electric signals in the dendrites of PC command epochs of firing and silencing of the PC soma. | |
| Dendritic tip geometry effects electrical properties (Tsutsui, Oka 2001) | |
| In their teleost thalamic neuron models the authors demonstrate a dramatic increase in the passive propagation of synaptic inputs through the dendritic stalk to the soma in cells with larger tips. | |
| Dentate Basket Cell: spatial summation of inhibitory synaptic inputs (Bartos et al 2001) | |
| Spatial summation of inhibitory synaptic input in a passive model of a basket cell from the dentate gyrus of rat hippocampus. Reproduces Figs. 5Ac and d in Bartos, M., Vida, I., Frotscher, M., Geiger, J.R.P, and Jonas, P.. Rapid signaling at inhibitory synapses in a dentate gyrus interneuron network. Journal of Neuroscience 21:2687-2698, 2001. | |
| Dentate Gyrus Feed-forward inhibition (Ferrante et al. 2009) | |
| In this paper, the model was used to show how that FFI can change a steeply sigmoidal input-output (I/O) curve into a double-sigmoid typical of buffer systems. | |
| Dentate gyrus granule cell: calcium and calcium-dependent conductances (Aradi and Holmes 1999) | |
| We have constructed a detailed model of a hippocampal dentate granule (DG) cell that includes nine different channel types. Channel densities and distributions were chosen to reproduce reported physiological responses observed in normal solution and when blockers were applied. The model was used to explore the contribution of each channel type to spiking behavior with particular emphasis on the mechanisms underlying postspike events. ... The model was used to predict changes in channel densities that could lead to epileptogenic burst discharges and to predict the effect of altered buffering capacity on firing behavior. We conclude that the clustered spatial distributions of calcium related channels, the presence of slow delayed rectifier potassium currents in dendrites, and calcium buffering properties, together, might explain the resistance of DG cells to the development of epileptogenic burst discharges. | |
| Dentate gyrus granule cell: subthreshold signal processing (Schmidt-Hieber et al. 2007) | |
| Detailed compartmental cable models of 8 hippocampal granule cells of adult mice were obtained from dual patch-clamp whole-cell recordings and subsequent 3D reconstructions. This code allows to reproduce figures 6-8 from the paper. | |
| Detailed passive cable model of Dentate Gyrus Basket Cells (Norenberg et al. 2010) | |
| Fast-spiking, parvalbumin-expressing basket cells (BCs) play a key role in feedforward and feedback inhibition in the hippocampus. ... To quantitatively address this question, we developed detailed passive cable models of BCs in the dentate gyrus based on dual somatic or somatodendritic recordings and complete morphologic reconstructions. Both specific membrane capacitance and axial resistivity were comparable to those of pyramidal neurons, but the average somatodendritic specific membrane resistance (R(m)) was substantially lower in BCs. Furthermore, R(m) was markedly nonuniform, being lowest in soma and proximal dendrites, intermediate in distal dendrites, and highest in the axon. ... Further computational analysis revealed that these unique cable properties accelerate the time course of synaptic potentials at the soma in response to fast inputs, while boosting the efficacy of slow distal inputs. These properties will facilitate both rapid phasic and efficient tonic activation of BCs in hippocampal microcircuits. | |
| Deterministic chaos in a mathematical model of a snail neuron (Komendantov and Kononenko 1996) | |
| "Chaotic regimes in a mathematical model of pacemaker activity in the bursting neurons of a snail Helix pomatia, have been investigated. The model includes a slow-wave generating mechanism, a spike-generating mechanism, an inward Ca current, intracellular Ca ions, [Ca2+]in, their fast buffering and uptake by intracellular Ca stores, and a [Ca2+]in-inhibited Ca current. Chemosensitive voltage-activated conductance, gB*, responsible for termination of the spike burst, and chemosensitive sodium conductance, gNa*, responsible for the depolarization phase of the slow-wave, were used as control parameters. ... Time courses of the membrane potential and [Ca2+]in were employed to analyse different regimes in the model. ..." | |
| Development of orientation-selective simple cell receptive fields (Rishikesh and Venkatesh, 2003) | |
| Implementation of a computational model for the development of simple-cell receptive fields spanning the regimes before and after eye-opening. The before eye-opening period is governed by a correlation-based rule from Miller (Miller, J. Neurosci., 1994), and the post eye-opening period is governed by a self-organizing, experience-dependent dynamics derived in the reference below. | |
| Dichotomy of action-potential backpropagation in CA1 pyramidal neuron dendrites (Golding et al 2001) | |
| From reference below and Corrigendum: J Neurophysiol 87:1a, 2002 (better versions of figures 2, 3, 5 and 7 because of poor print quality in the original article; as of 2/2006, these figures are perfectly fine in the PDF of the original article that is currently available from the publisher's WWW site). Examines the anatomical and biophysical factors that account for the fact that retrograde invasion of spikes into the apical dendritic tree past 300 um succeeds in some CA1 pyramidal neurons but fails in others. | |
| Differences between type A and B photoreceptors (Blackwell 2006) | |
| In Hermissenda crassicornis, the memory of light associated with turbulence is stored as changes in intrinsic and synaptic currents in both type A and type B photoreceptors. These photoreceptor types exhibit qualitatively different responses to light and current injection, and these differences shape the spatiotemporal firing patterns that control behavior. Thus the objective of the study was to identify the mechanisms underlying these differences. The approach was to develop a type B model that reproduced characteristics of type B photoreceptors recorded in vitro, and then to create a type A model by modifying a select number of ionic currents. Comparison of type A models with characteristics of type A photoreceptors recorded in vitro revealed that type A and type B photoreceptors have five main differences, three that have been characterized experimentally and two that constitute hypotheses to be tested with experiments in the future. See paper for more and details. | |
| Differential modulation of pattern and rate in a dopamine neuron model (Canavier and Landry 2006) | |
| "A stylized, symmetric, compartmental model of a dopamine neuron in vivo shows how rate and pattern can be modulated either concurrently or differentially. If two or more parameters in the model are varied concurrently, the baseline firing rate and the extent of bursting become decorrelated, which provides an explanation for the lack of a tight correlation in vivo and is consistent with some independence of the mechanisms that generate baseline firing rates versus bursting. ..." See paper for more and details. | |
| Discrete event simulation in the NEURON environment (Hines and Carnevale 2004) | |
| A short introduction to how "integrate and fire" cells are implemented in NEURON. Network simulations that use only artificial spiking cells are extremely efficient, with runtimes proportional to the total number of synaptic inputs received and independent of the number of cells or problem time. | |
| Dopamine-modulated medium spiny neuron, reduced model (Humphries et al. 2009) | |
| We extended Izhikevich's reduced model of the striatal medium spiny neuron (MSN) to account for dopaminergic modulation of its intrinsic ion channels and synaptic inputs. We tuned our D1 and D2 receptor MSN models using data from a recent (Moyer et al, 2007) large-scale compartmental model. Our new models capture the input-output relationships for both current injection and spiking input with remarkable accuracy, despite the order of magnitude decrease in system size. They also capture the paired pulse facilitation shown by MSNs. Our dopamine models predict that synaptic effects dominate intrinsic effects for all levels of D1 and D2 receptor activation. Our analytical work on these models predicts that the MSN is never bistable. Nonetheless, these MSN models can produce a spontaneously bimodal membrane potential similar to that recently observed in vitro following application of NMDA agonists. We demonstrate that this bimodality is created by modelling the agonist effects as slow, irregular and massive jumps in NMDA conductance and, rather than a form of bistability, is due to the voltage-dependent blockade of NMDA receptors | |
| Dopaminergic cell bursting model (Kuznetsov et al 2006) | |
| Dopaminergic neurons of the midbrain fire spontaneously at rates <10/s and ordinarily will not exceed this range even when driven with somatic current injection. During spontaneous bursting of dopaminergic neurons in vivo, bursts related to reward expectation in behaving animals, and bursts generated by dendritic application of N-methyl-D-aspartate (NMDA) agonists, transient firing attains rates well above this range. We suggest a way such highfrequency firing may occur in response to dendritic NMDA receptor activation. We have extended the coupled oscillator model of the dopaminergic neuron, which represents the soma and dendrites as electrically coupled compartments with different natural spiking frequencies, by addition of dendritic AMPA (voltage-independent) or NMDA (voltage-dependent) synaptic conductance. Both soma and dendrites contain a simplified version of the calcium-potassium mechanism known to be the mechanism for slow spontaneous oscillation and background firing in dopaminergic cells. We show that because of its voltage dependence, NMDA receptor activation acts to amplify the effect on the soma of the high-frequency oscillation of the dendrites, which is normally too weak to exert a large influence on the overall oscillation frequency of the neuron. | |
| Dorsal root ganglion (DRG) neuronal model (Kovalsky et al. 2009) | |
| This model, diverged from oscillatory parameters seen in live cells and failed to produce characteristic ectopic discharge patterns. Here we show that use of a more complete set of Na+ conductances--which includes several delayed components--enables simulation of the entire repertoire of oscillation-triggered electrogenic phenomena seen in live dorsal root ganglion (DRG) neurons. This includes a physiological window of induction and natural patterns of spike discharge. An INa+ component at 2-20 ms was particularly important, even though it represented only a tiny fraction of overall INa+ amplitude. With the addition of a delayed rectifier IK+ the singlet firing seen in some DRG neurons can also be simulated. The model reveals the key conductances that underlie afferent ectopia, conductances that are potentially attractive targets in the search for more effective treatments of neuropathic pain. | |
| Drosophila projection neuron electrotonic structure (Gouwens and Wilson 2009) | |
| We address the issue of how electrical signals propagate in Drosophila neurons by modeling the electrotonic structure of the antennal lobe projection neurons innervating glomerulus DM1. The readme file contains instructions for running the model. | |
| Duration-tuned neurons from the inferior colliculus of the big brown bat (Aubie et al. 2009) | |
| dtnet is a generalized neural network simulator written in C++ with an easy to use XML description language to generate arbitrary neural networks and then run simulations covering many different parameter values. For example, you can specify ranges of parameter values for several different connection weights and then automatically run simulations over all possible parameters. Graphing ability is built in as long as the free, open-source, graphing application GLE (http://glx.sourceforge.net/) is installed. Included in the examples folder are simulation descriptions that were used to generate the results in Aubie et al. (2009). Refer to the README file for instructions on compiling and running these examples. The most recent source code can be obtained from GitHub: https://github.com/baubie/dtnet | |
| Duration-tuned neurons from the inferior colliculus of vertebrates (Aubie et al. 2012) | |
| These models reproduce the responses of duration-tuned neurons in the auditory midbrain of the big brown bat, the rat, the mouse and the frog (Aubie et al. 2012). They are written in the Python interface to NEURON and a subset of the figures from Aubie et al. (2012) are pre-set in run.py (raw data is generated and a separate graphing program must be used to visualize the results). | |
| Dynamical model of olfactory bulb mitral cell (Rubin, Cleland 2006) | |
| This four-compartment mitral cell exhibits endogenous subthreshold oscillations, phase resetting, and evoked spike phasing properties as described in electrophysiological studies of mitral cells. It is derived from the prior work of Davison et al (2000) and Bhalla and Bower (1993). See readme.txt for details. | |
| Dynamics of Spike Initiation (Prescott et al. 2008) | |
| "Transduction of graded synaptic input into trains of all-or-none action potentials (spikes) is a crucial step in neural coding. Hodgkin identified three classes of neurons with qualitatively different analog-to-digital transduction properties. Despite widespread use of this classification scheme, a generalizable explanation of its biophysical basis has not been described. We recorded from spinal sensory neurons representing each class and reproduced their transduction properties in a minimal model. With phase plane and bifurcation analysis, each class of excitability was shown to derive from distinct spike initiating dynamics. Excitability could be converted between all three classes by varying single parameters; moreover, several parameters, when varied one at a time, had functionally equivalent effects on excitability. From this, we conclude that the spike-initiating dynamics associated with each of Hodgkin’s classes represent different outcomes in a nonlinear competition between oppositely directed, kinetically mismatched currents. ..." | |
| Effect of riluzole on action potential in cultured human skeletal muscle cells (Wang YJ et al. 2008) | |
| Simulation studies also unraveled that both decreased conductance of I(Na) and increased conductance of I(K(Ca)) utilized to mimic riluzole actions in skeletal muscle cells could combine to decrease the amplitude of action potentials and increase the repolarization of action potentials. | |
| Effect of slowly inactivating IKdr to delayed firing of action potentials (Wu et al. 2008) | |
| "The properties of slowly inactivating delayed-rectifier K+ current (IKdr) were investigated in NG108-15 neuronal cells differentiated with long-term exposure to dibutyryl cyclic AMP. ... The computer model, in which state-dependent inactivation of IKdr was incorporated, was also implemented to predict the firing behavior present in NG108-15 cells. ... Our theoretical work and the experimental results led us to propose a pivotal role of slowly inactivating IKdr in delayed firing of APs in NG108-15 cells. The results also suggest that aconitine modulation of IKdr gating is an important molecular mechanism through which it can contribute to neuronal firing." | |
| Effect of voltage sensitive fluorescent proteins on neuronal excitability (Akemann et al. 2009) | |
| "Fluorescent protein voltage sensors are recombinant proteins that are designed as genetically encoded cellular probes of membrane potential using mechanisms of voltage-dependent modulation of fluorescence. Several such proteins, including VSFP2.3 and VSFP3.1, were recently reported with reliable function in mammalian cells. ... Expression of these proteins in cell membranes is accompanied by additional dynamic membrane capacitance, ... We used recordings of sensing currents and fluorescence responses of VSFP2.3 and of VSFP3.1 to derive kinetic models of the voltage-dependent signaling of these proteins. Using computational neuron simulations, we quantitatively investigated the perturbing effects of sensing capacitance on the input/output relationship in two central neuron models, a cerebellar Purkinje and a layer 5 pyramidal neuron. ... ". The Purkinje cell model is included in ModelDB. | |
| Effects of Acetyl-L-carnitine on neural transmission (Lombardo et al 2004) | |
| Acetyl-L-carnitine is known to improve many aspects of the neural activity even if its exact role in neurotransmission is still unknown. This study investigates the effects of acetyl-L-carnitine in T segmental sensory neurons of the leech Hirudo medicinalis. These neurons are involved in some forms of neural plasticity associated with learning processes. Their physiological firing is accompanied by a large afterhyperpolarization that is mainly due to the Na+/K+ ATPase activity and partially to a Ca2+-dependent K+ current. A clear-cut hyperpolarization and a significant increase of the afterhyperpolarization have been recorded in T neurons of leeches injected with 2 mM acetyl-L-carnitine some days before. Acute treatments of 50 mM acetyl-L-carnitine induced similar effects in T cells of naive animals. Moreover, in these cells, widely arborized, the afterhyperpolarization seems to play an important role in determining the action potential transmission at neuritic bifurcations. A computational model of a T cell has been previously developed considering detailed data for geometry and the modulation of the pump current. Herein, we showed that to a larger afterhyperpolarization, due to the acetyl-L-carnitine-induced effects, corresponds a decrement in the number of action potentials reaching synaptic terminals. | |
| Effects of Chloride accumulation and diffusion on GABAergic transmission (Jedlicka et al 2011) | |
| "In the CNS, prolonged activation of GABA(A) receptors (GABA(A)Rs) has been shown to evoke biphasic postsynaptic responses, consisting of an initial hyperpolarization followed by a depolarization. A potential mechanism underlying the depolarization is an acute chloride (Cl(-)) accumulation resulting in a shift of the GABA(A) reversal potential (E(GABA)). The amount of GABA-evoked Cl(-) accumulation and accompanying depolarization depends on presynaptic and postsynaptic properties of GABAergic transmission, as well as on cellular morphology and regulation of Cl(-) intracellular concentration ([Cl(-)](i)). To analyze the influence of these factors on the Cl(-) and voltage behavior, we studied spatiotemporal dynamics of activity-dependent [Cl(-)](i) changes in multicompartmental models of hippocampal cells based on realistic morphological data. ..." | |
| Effects of KIR current inactivation in NAc Medium Spiny Neurons (Steephen and Manchanda 2009) | |
| "Inward rectifying potassium (KIR) currents in medium spiny (MS) neurons of nucleus accumbens inactivate significantly in ~40% of the neurons but not in the rest, which may lead to differences in input processing by these two groups. Using a 189-compartment computational model of the MS neuron, we investigate the influence of this property using injected current as well as spatiotemporally distributed synaptic inputs. Our study demonstrates that KIR current inactivation facilitates depolarization, firing frequency and firing onset in these neurons. ..." | |
| Efficient estimation of detailed single-neuron models (Huys et al. 2006) | |
| "Biophysically accurate multicompartmental models of individual neurons ... depend on a large number of parameters that are difficult to estimate. ... We propose a statistical approach to the automatic estimation of various biologically relevant parameters, including 1) the distribution of channel densities, 2) the spatiotemporal pattern of synaptic input, and 3) axial resistances across extended dendrites. ... We demonstrate that the method leads to accurate estimations on a wide variety of challenging model data sets that include up to about 10,000 parameters (roughly two orders of magnitude more than previously feasible) and describe how the method gives insights into the functional interaction of groups of channels." | |
| Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011) | |
| "We have developed a spiking neural network simulator, which is both easy to use and computationally efficient, for the generation of large-scale computational neuroscience models. The simulator implements current or conductance based Izhikevich neuron networks, having spike-timing dependent plasticity and short-term plasticity. ..." | |
| Electrically-coupled Retzius neurons (Vazquez et al. 2009) | |
| "Dendritic electrical coupling increases the number of effective synaptic inputs onto neurons by allowing the direct spread of synaptic potentials from one neuron to another. Here we studied the summation of excitatory postsynaptic potentials (EPSPs) produced locally and arriving from the coupled neuron (transjunctional) in pairs of electrically-coupled Retzius neurons of the leech. We combined paired recordings of EPSPs, the production of artificial EPSPs (APSPs) in neuron pairs with different coupling coefficients and simulations of EPSPs produced in the coupled dendrites. ..." | |
| Emergent properties of networks of biological signaling pathways (Bhalla, Iyengar 1999) | |
| Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways. | |
| Endothelin action on pituitary latotrophs (Bertram et al. 2006) | |
| Endothelin (ET-1, -2, and -3 designate three genes which produce different endothelin isopeptides) is a prolactin inhibiting substance of hypothalmic origin. ET-1 binding is part of at least four G protein signaling pathways in lactotrophs. The sequence of events in these pathways following the presentation of nano- and pico-molar concentrations of ET-1 is modeled in the paper. | |
| Enhanced Excitability in Hermissenda: modulation by 5-HT (Cai et al 2003) | |
| Serotonin (5-HT) applied to the exposed but otherwise intact nervous system results in enhanced excitability of Hermissenda type-B photoreceptors. Several ion currents in the type-B photoreceptors are modulated by 5-HT, including the A-type K+ current (IK,A), sustained Ca2+ current (ICa,S), Ca-dependent K+ current (IK,Ca), and a hyperpolarization-activated inward rectifier current (Ih). In this study,we developed a computational model that reproduces physiological characteristics of type B photoreceptors, e.g. resting membrane potential, dark-adapted spike activity, spike width, and the amplitude difference between somatic and axonal spikes. We then used the model to investigate the contribution of different ion currents modulated by 5-HT to the magnitudes of enhanced excitability produced by 5-HT. See paper for results and more details. | |
| Excitability of PFC Basal Dendrites (Acker and Antic 2008) | |
| ".. We carried out multi-site voltage-sensitive dye imaging of membrane potential transients from thin basal branches of prefrontal cortical pyramidal neurons before and after application of channel blockers. We found that backpropagating action potentials (bAPs) are predominantly controlled by voltage-gated sodium and A-type potassium channels. In contrast, pharmacologically blocking the delayed rectifier potassium, voltage-gated calcium or Ih, conductance had little effect on dendritic action potential propagation. Optically recorded bAP waveforms were quantified and multicompartmental modeling (NEURON) was used to link the observed behavior with the underlying biophysical properties. The best-fit model included a non-uniform sodium channel distribution with decreasing conductance with distance from the soma, together with a non-uniform (increasing) A-type potassium conductance. AP amplitudes decline with distance in this model, but to a lesser extent than previously thought. We used this model to explore the mechanisms underlying two sets of published data involving high frequency trains of action potentials, and the local generation of sodium spikelets. ..." | |
| Excitability of the soma in central nervous system neurons (Safronov et al 2000) | |
| The ability of the soma of a spinal dorsal horn neuron, a spinal ventral horn neuron, and a hippocampal pyramidal neuron to generate action potentials was studied using experiments and computer simulations. By comparing recordings ... of a dorsal horn neuron with simulated responses, it was shown that computer models can be adequate for the study of somatic excitability. The modeled somata of both spinal neurons were unable to generate action potentials, showing only passive and local responses to current injections. ... In contrast to spinal neurons, the modeled soma of the hippocampal pyramidal neuron generated spikes with an overshoot of +9 mV. It is concluded that the somata of spinal neurons cannot generate action potentials and seem to resist their propagation from the axon to dendrites. ... See paper for more and details. | |
| Excitation-contraction coupling/mitochondrial energetics (ECME) model (Cortassa et al. 2006) | |
| "An intricate network of reactions is involved in matching energy supply with demand in the heart. This complexity arises because energy production both modulates and is modulated by the electrophysiological and contractile activity of the cardiac myocyte. Here, we present an integrated mathematical model of the cardiac cell that links excitation-contraction coupling with mitochondrial energy generation. The dynamics of the model are described by a system of 50 ordinary differential equations. The formulation explicitly incorporates cytoplasmic ATP-consuming processes associated with force generation and ion transport, as well as the creatine kinase reaction. Changes in the electrical and contractile activity of the myocyte are coupled to mitochondrial energetics through the ATP, Ca21, and Na1 concentrations in the myoplasmic and mitochondrial matrix compartments. ..." | |
| Extraction and classification of three cortical neuron types (Mensi et al. 2011) | |
| This script proposes a new convex fitting procedure that allows the parameters estimation of a large class of stochastic Integrate-and-Fire model upgraded with spike-triggered current and moving threshold from patch-clamp experiments (i.e. given the injected current and the recorded membrane potential). This script applies the method described in the paper to estimate the parameters of a reference model from a single voltage trace and the corresponding input current and evaluate the performance of the fitted model on a separated test set. | |
| FS Striatal interneuron: K currents solve signal-to-noise problems (Kotaleski et al 2006) | |
| ... We show that a transient potassium (KA) current allows the Fast Spiking (FS) interneuron to strike a balance between sensitivity to correlated input and robustness to noise, thereby increasing its signal-to-noise ratio (SNR). First, a compartmental FS neuron model was created to match experimental data from striatal FS interneurons in cortex–striatum–substantia nigra organotypic cultures. Densities of sodium, delayed rectifier, and KA channels were optimized to replicate responses to somatic current injection. Spontaneous AMPA and GABA synaptic currents were adjusted to the experimentally measured amplitude, rise time, and interevent interval histograms. Second, two additional adjustments were required to emulate the remaining experimental observations. GABA channels were localized closer to the soma than AMPA channels to match the synaptic population reversal potential. Correlation among inputs was required to produce the observed firing rate during up-states. In this final model, KA channels were essential for suppressing down-state spikes while allowing reliable spike generation during up-states. ... Our results suggest that KA channels allow FS interneurons to operate without a decrease in SNR during conditions of increased dopamine, as occurs in response to reward or anticipated reward. See paper for more and details. | |
| Fast sodium channel gating in mossy fiber axons (Schmidt-Heiber et al. 2010) | |
| "... To study the mechanisms underlying AP initiation in unmyelinated hippocampal mossy fibers of adult mice, we recorded sodium currents in axonal and somatic membrane patches. We demonstrate that sodium channel density in the proximal axon is ~5 times higher than in the soma. Furthermore, sodium channel activation and inactivation are ~2 times faster. Modeling revealed that the fast activation localized the initiation site to the proximal axon even upon strong synaptic stimulation, while fast inactivation contributed to energy-efficient membrane charging during APs. ..." | |
| Fast-spiking cortical interneuron (Golomb et al. 2007) | |
| Cortical fast-spiking (FS) interneurons display highly variable electrophysiological properties. We hypothesize that this variability emerges naturally if one assumes a continuous distribution of properties in a small set of active channels. We construct a minimal, single-compartment conductance-based model of FS cells that includes transient Na+, delayed-rectifier K+, and slowly inactivating d-type K+ conductances. The model may display delay to firing. Stuttering (elliptic bursting) and subthreshold oscillations may be observed for small Na+ window current. | |
| Firing patterns in stuttering fast-spiking interneurons (Klaus et al. 2011) | |
| This is a morphologically extended version of the fast-spiking interneuron by Golomb et al. (2007). The model captures the stuttering firing pattern and subthreshold oscillations in response to step current input as observed in many cortical and striatal fast-spiking cells. | |
| Fly lobular plate VS cell (Borst and Haag 1996, et al. 1997, et al. 1999) | |
| In a series of papers the authors conducted experiments to develop understanding and models of fly visual system HS, CS, and VS neurons. This model recreates the VS neurons from those papers with enough success to merit approval by Borst although some discrepancies remain (see readme). | |
| Frog second-order vestibular neuron models (Rössert et al. 2011) | |
| This implements spiking Hodgkin-Huxley type models of tonic and phasic second-order vestibular neurons. Models fitted to intracellular spike and membrane potential recordings from frog (Rana temporaria). The models can be stimulated by intracellular step current, frequency current (ZAP) or synaptic stimulation. | |
| Functional structure of mitral cell dendritic tuft (Djurisic et al. 2008) | |
| The computational modeling component of Djurisic et al. 2008 addressed two primary questions: whether amplification by active currents is necessary to explain the relatively mild attenuation suffered by tuft EPSPs spreading along the primary dendrite to the soma; what accounts for the relatively uniform peak EPSP amplitude throughout the tuft. These simulations show that passive spread from tuft to soma is sufficient to yield the low attenuation of tuft EPSPs, and that random distribution of a biologically plausible number of excitatory synapses throughout the tuft can produce the experimentally observed uniformity of depolarization. | |
| GP Neuron, somatic and dendritic phase response curves (Schultheiss et al. 2011) | |
| Phase response analysis of a GP neuron model showing type I PRCs for somatic inputs and type II PRCs for dendritic excitation. Analysis of intrinsic currents underlying type II dendritic PRCs. | |
| GPi/GPe neuron models (Johnson and McIntyre 2008) | |
| Model files for two types of non-human primate neurons used in the paper: simplified versions of 1) a GPi neuron and 2) a GPe axon collateralizing in GPi en route to STN. | |
| Gamma and theta rythms in biophysical models of hippocampus circuits (Kopell et al. 2011) | |
| " ... the main rhythms displayed by the hippocampus, the gamma (30–90 Hz) and theta (4–12 Hz) rhythms. We concentrate on modeling in vitro experiments, but with an eye toward possible in vivo implications. ... We use simpler biophysical models; all cells have a single compartment only, and the interneurons are restricted to two types: fast-spiking (FS) basket cells and oriens lacunosum-moleculare (O-LM) cells. ... , we aim not so much at reproducing dynamics in great detail, but at clarifying the essential mechanisms underlying the production of the rhythms and their interactions (Kopell, 2005). ..." | |
| Gap junction coupled network of striatal fast spiking interneurons (Hjorth et al. 2009) | |
| Gap junctions between striatal FS neurons has very weak ability to synchronise spiking. Input uncorrelated between neighbouring neurons is shunted, while correlated input is not. | |
| Gap-junction coupled network activity depends on coupled dendrites diameter (Gansert et al. 2007) | |
| "... We have previously shown that the amplitude of electrical signals propagating across gap-junctionally coupled passive cables is maximized at a unique diameter. This suggests that threshold-dependent signals may propagate through gap junctions for a finite range of diameters around this optimal value. Here we examine the diameter dependence of action potential propagation across model networks of dendro-dendritically coupled neurons. The neurons in these models have passive soma and dendrites and an action potential-generating axon. We show that propagation of action potentials across gap junctions occurs only over a finite range of dendritic diameters and that propagation delay depends on this diameter. ...". See paper for more and details. | |
| Global structure, robustness, and modulation of neuronal models (Goldman et al. 2001) | |
| "The electrical characteristics of many neurons are remarkably robust in the face of changing internal and external conditions. At the same time, neurons can be highly sensitive to neuromodulators. We find correlates of this dual robustness and sensitivity in a global analysis of the structure of a conductance-based model neuron. ..." | |
| Globus pallidus multi-compartmental model neuron with realistic morphology (Gunay et al. 2008) | |
| "Globus pallidus (GP) neurons recorded in brain slices show significant variability in intrinsic electrophysiological properties. To investigate how this variability arises, we manipulated the biophysical properties of GP neurons using computer simulations. ... Our results indicated that most of the experimental variability could be matched by varying conductance densities, which we confirmed with additional partial block experiments. Further analysis resulted in two key observations: (1) each voltage-gated conductance had effects on multiple measures such as action potential waveform and spontaneous or stimulated spike rates; and (2) the effect of each conductance was highly dependent on the background context of other conductances present. In some cases, such interactions could reverse the effect of the density of one conductance on important excitability measures. ..." | |
| Globus pallidus neuron models with differing dendritic Na channel expression (Edgerton et al., 2010) | |
| A set of 9 multi-compartmental rat GP neuron models (585 compartments) differing only in their expression of dendritic fast sodium channels were compared in their synaptic integration properties. Dendritic fast sodium channels were found to increase the importance of distal synapses (both excitatory AND inhibitory), increase spike timing variability with in vivo-like synaptic input, and make the model neurons highly sensitive to clustered synchronous excitation. | |
| Grid cell oscillatory interference with noisy network oscillators (Zilli and Hasselmo 2010) | |
| To examine whether an oscillatory interference model of grid cell activity could work if the oscillators were noisy neurons, we implemented these simulations. Here the oscillators are networks (either synaptically- or gap-junction--coupled) of one or more noisy neurons (either Izhikevich's simple model or a Hodgkin-Huxley--type biophysical model) which drive a postsynaptic cell (which may be integrate-and-fire, resonate-and-fire, or the simple model) which should fire spatially as a grid cell if the simulation is successful. | |
| HERG K+ channels spike-frequency adaptation (Chiesa et al 1997) | |
| Spike frequency adaptation has contributions from the IHERG current (encoded by the human eag-related gene (HERG); Warmke & Ganetzky, 1994), which develops with slow kinetics during depolarization and contributes to the repolarization of the long action potentials typically present in the heart. IHERG is one of the delayed rectifier currents (IK(r)) of the heart, and HERG mutations are associated with one of the cardiac arrhythmia LQT syndromes (LQT2). See paper for more and details. | |
| High frequency stimulation of the Subthalamic Nucleus (Rubin and Terman 2004) | |
| " ... Using a computational model, this paper considers the hypothesis that DBS works by replacing pathologically rhythmic basal ganglia output with tonic, high frequency firing. In our simulations of parkinsonian conditions, rhythmic inhibition from GPi to the thalamus compromises the ability of thalamocortical relay (TC) cells to respond to depolarizing inputs, such as sensorimotor signals. High frequency stimulation of STN regularizes GPi firing, and this restores TC responsiveness, despite the increased frequency and amplitude of GPi inhibition to thalamus that result. We provide a mathematical phase plane analysis of the mechanisms that determine TC relay capabilities in normal, parkinsonian, and DBS states in a reduced model. This analysis highlights the differences in deinactivation of the low-threshold calcium T -current that we observe in TC cells in these different conditions. ..." | |
| Hodgkin-Huxley model of persistent activity in PFC neurons (Winograd et al. 2008) (NEURON python) | |
| The paper demonstrate a form of graded persistent activity activated by hyperpolarization. This phenomenon is modeled based on a slow calcium regulation of Ih, similar to that introduced earlier for thalamic neurons (see Destexhe et al., J Neurophysiol. 1996). The only difference is that the calcium signal is here provided by the high-threshold calcium current (instead of the low-threshold calcium current in thalamic neurons). | |
| Hodgkin-Huxley model of persistent activity in prefrontal cortex neurons (Winograd et al. 2008) | |
| The paper demonstrate a form of graded persistent activity activated by hyperpolarization. This phenomenon is modeled based on a slow calcium regulation of Ih, similar to that introduced earlier for thalamic neurons (see Destexhe et al., J Neurophysiol. 1996). The only difference is that the calcium signal is here provided by the high-threshold calcium current (instead of the low-threshold calcium current in thalamic neurons). | |
| Hodgkin-Huxley models of different classes of cortical neurons (Pospischil et al. 2008) | |
| "We review here the development of Hodgkin– Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are “fast spiking”, “regular spiking”, “intrinsically bursting” and “low-threshold spike” cells. For each class, we fit “minimal” HH type models to experimental data. ..." | |
| Hodgkin-Huxley simplifed 2D and 3D models (Lundstrom et al. 2009) | |
| "Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f–I curve. We introduce a novel classification of neurons into Types A, B−, and B+ according to how f–I curves are modulated by input fluctuations. ..." | |
| Homeostatic synaptic plasticity (Rabinowitch and Segev 2006a,b) | |
| (2006a): "We investigated analytically and numerically the interplay between two opposing forms of synaptic plasticity: positive-feedback, long-term potentiation/depression (LTP/LTD), and negative-feedback, homeostatic synaptic plasticity (HSP). A detailed model of a CA1 pyramidal neuron, with numerous HSP-modifiable dendritic synapses, demonstrates that HSP may have an important role in selecting which spatial patterns of LTP/LTD are to last. ... Despite the negative-feedback nature of HSP, under both local and global HSP, numerous synaptic potentiations/depressions can persist. These experimentally testable results imply that HSP could be significantly involved in shaping the spatial distribution of synaptic weights in the dendrites and not just normalizing it, as is currently believed." (2006b): "Homeostatic synaptic plasticity (HSP) is an important mechanism attributed with the slow regulation of the neuron's activity. Whenever activity is chronically enhanced, HSP weakens the weights of the synapses in the dendrites and vice versa. Because dendritic morphology and its electrical properties partition the dendritic tree into functional compartments, we set out to explore the interplay between HSP and dendritic compartmentalization. ... The spatial distribution of synaptic weights throughout the dendrites will markedly differ under the local versus global HSP mechanisms. We suggest an experimental paradigm to unravel which type of HSP mechanism operates in the dendritic tree. The answer to this question will have important implications to our understanding of the functional organization of the neuron." | |
| I A in Kenyon cells resemble Shaker currents (Pelz et al 1999) | |
| Cultured Kenyon cells from the mushroom body of the honeybee, Apis mellifera, show a voltage-gated, fast transient K1 current that is sensitive to 4-aminopyridine, an A current. The kinetic properties of this A current and its modulation by extracellular K1 ions were investigated in vitro with the whole cell patch-clamp technique. The A current was isolated from other voltage-gated currents either pharmacologically or with suitable voltage-clamp protocols. Hodgkin- and Huxley-style mathematical equations were used for the description of this current and for the simulation of action potentials in a Kenyon cell model. The data of the A current were incorporated into a reduced computational model of the voltage-gated currents of Kenyon cells. In addition, the model contained a delayed rectifier K current, a Na current, and a leakage current. The model reproduces several experimental features and makes predictions. See paper for details and results. | |
| IA and IT interact to set first spike latency (Molineux et al 2005) | |
| Using patch clamp and modeling, we illustrate that spike latency characteristics are the product of an interplay between I(A) and low-threshold calcium current (I(T)) that requires a steady-state difference in the inactivation parameters of the currents. Furthermore, we show that the unique first-spike latency characteristics of stellate cells have important implications for the integration of coincident IPSPs and EPSPs, such that inhibition can shift first-spike latency to differentially modulate the probability of firing. | |
| INa and IKv4.3 heterogeneity in canine LV myocytes (Flaim et al 2006) | |
| "The roles of sustained components of INa and IKv43 in shaping the action potentials (AP) of myocytes isolated from the canine left ventricle (LV) have not been studied in detail. Here we investigate the hypothesis that these two currents can contribute substantially to heterogeneity of early repolarization and arrhythmic risk.... The resulting simulations illustrate ways in which KChIP2- and Ca2+- dependent control of IKv43 can result in a sustained outward current that can neutralize INaL in a rate- and myocyte subtype-dependent manner. Both these currents appear to play significant roles in modulating AP duration and rate dependence in midmyocardial myocytes. ... By design, these models allow upward integration into organ models or may be used as a basis for further investigations into cellular heterogeneities." See paper for more and details. | |
| Ih levels roles in bursting and regular-spiking subiculum pyramidal neurons (van Welie et al 2006) | |
| Pyramidal neurons in the subiculum typically display either bursting or regular-spiking behavior. ... Here we report that bursting neurons posses a hyperpolarization-activated cation current (Ih) that is two-fold larger (conductance: 5.3 ± 0.5 nS) than in regularspiking neurons (2.2 ± 0.6 nS), while Ih exhibits similar voltage-dependent and kinetic properties in both classes of neurons. Bursting and regular-spiking neurons display similar morphology. The difference in Ih between the two classes is not responsible for the distinct firing patterns, since neither pharmacological blockade of Ih nor enhancement of Ih using a dynamic clamp affects the qualitative firing patterns. Instead, the difference in Ih between bursting and regular-spiking neurons determines the temporal integration of evoked synaptic input from the CA1 area. In response to 50 Hz stimulation, bursting neurons, with a large Ih, show ~50% less temporal summation than regular-spiking neurons. ... A computer simulation model of a subicular neuron with the properties of either a bursting or a regular-spiking neuron confirmed the pivotal role of Ih in temporal integration of synaptic input. These data suggest that in the subicular network, bursting neurons are better suited to discriminate the content of high frequency input, such as that occurring during gamma oscillations, compared to regular-spiking neurons. See paper for more and details. | |
| Impact of dendritic atrophy on intrinsic and synaptic excitability (Narayanan & Chattarji, 2010) | |
| These simulations examined the atrophy induced changes in electrophysiological properties of CA3 pyramidal neurons. We found these neurons change from bursting to regular spiking as atrophy increases. Region-specific atrophy induced region-specific increases in synaptic excitability in a passive dendritic tree. All dendritic compartments of an atrophied neuron had greater synaptic excitability and a larger voltage transfer to the soma than the control neuron. | |
| Impact of dendritic size and topology on pyramidal cell burst firing (van Elburg and van Ooyen 2010) | |
| The code provided here was written to systematically investigate which of the
physical parameters controlled by dendritic morphology underlies the differences
in spiking behaviour observed in different realizations of the
'ping-pong'-model. Structurally varying dendritic topology and length in a
simplified model allows us to separate out the physical parameters derived from
morphology underlying burst firing. To perform the parameter scans we created a new NEURON tool the MultipleRunControl which can be used to easily set up a parameter scan and write the simulation results to file. Using this code we found that not input conductance but the arrival time of the return current, as measured provisionally by the average electrotonic path length, determines whether the pyramidal cell (with ping-pong model dynamics) will burst or fire single spikes. | |
| Increased computational accuracy in multi-compartmental cable models (Lindsay et al. 2005) | |
| Compartmental models of dendrites are the most widely used tool for investigating their electrical behaviour. Traditional models assign a single potential to a compartment. This potential is associated with the membrane potential at the centre of the segment represented by the compartment. All input to that segment, independent of its location on the segment, is assumed to act at the centre of the segment with the potential of the compartment. By contrast, the compartmental model introduced in this article assigns a potential to each end of a segment, and takes into account the location of input to a segment on the model solution by partitioning the effect of this input between the axial currents at the proximal and distal boundaries of segments. For a given neuron, the new and traditional approaches to compartmental modelling use the same number of locations at which the membrane potential is to be determined, and lead to ordinary differential equations that are structurally identical. However, the solution achieved by the new approach gives an order of magnitude better accuracy and precision than that achieved by the latter in the presence of point process input. | |
| Inferring connection proximity in electrically coupled networks (Cali et al. 2007) | |
| In order to explore electrical coupling in the nervous system and its network-level organization, it is imperative to map the electrical synaptic microcircuits, in analogy with in vitro studies on monosynaptic and disynaptic chemical coupling. However, “walking” from cell to cell over large distances with a glass pipette is challenging, and microinjection of (fluorescent) dyes diffusing through gap-junctions remains so far the only method available to decipher such microcircuits even though technical limitations exist. Based on circuit theory, we derived analytical descriptions of the AC electrical coupling in networks of isopotential cells. We then proposed an operative electrophysiological protocol to distinguish between direct electrical connections and connections involving one or more intermediate cells. This method allows inferring the number of intermediate cells, generalizing the conventional coupling coefficient, which provides limited information. We provide here some analysis and simulation scripts that used to test our method through computer simulations, in vitro recordings, theoretical and numerical methods. Key words: Gap-Junctions; Electrical Coupling; Networks; ZAP current; Impedance. | |
| Inhibitory plasticity balances excitation and inhibition (Vogels et al. 2011) | |
| "Cortical neurons receive balanced excitatory and inhibitory synaptic currents. Such a balance could be established and maintained in an experience-dependent manner by synaptic plasticity at inhibitory synapses. We show that this mechanism provides an explanation for the sparse firing patterns observed in response to natural stimuli and fits well with a recently observed interaction of excitatory and inhibitory receptive field plasticity. ... Our results suggest an essential role of inhibitory plasticity in the formation and maintenance of functional cortical circuitry." | |
| Input Fluctuations effects on f-I curves (Arsiero et al. 2007) | |
| "... We examined in vitro frequency versus current (f-I) relationships of layer 5 (L5) pyramidal cells of the rat medial prefrontal cortex (mPFC) using fluctuating stimuli. ...our results show that mPFC L5 pyramidal neurons retain an increased sensitivity to input fluctuations, whereas their sensitivity to the input mean diminishes to near zero. ..." | |
| Integrate and fire model code for spike-based coincidence-detection (Heinz et al. 2001, others) | |
| Model code relevant to three papers; two on level discrimination and one on masked detection at low frequencies. | |
| Interacting synaptic conductances during, distorting, voltage clamp (Poleg-Polsky and Diamond 2011) | |
| This simulation examines the accuracy of the voltage clamp technique in detecting the excitatory and the inhibitory components of the synaptic drive. | |
| Intracortical synaptic potential modulation by presynaptic somatic potential (Shu et al. 2006, 2007) | |
| " ... Here we show that the voltage fluctuations associated with dendrosomatic synaptic activity propagate significant distances along the axon, and that modest changes in the somatic membrane potential of the presynaptic neuron modulate the amplitude and duration of axonal action potentials and, through a Ca21- dependent mechanism, the average amplitude of the postsynaptic potential evoked by these spikes. These results indicate that synaptic activity in the dendrite and soma controls not only the pattern of action potentials generated, but also the amplitude of the synaptic potentials that these action potentials initiate in local cortical circuits, resulting in synaptic transmission that is a mixture of triggered and graded (analogue) signals." | |
| Investigation of different targets in deep brain stimulation for Parkinson`s (Pirini et al. 2009) | |
| "We investigated by a computational model of the basal ganglia the different network effects of deep brain stimulation (DBS) for Parkinson’s disease (PD) in different target sites in the subthalamic nucleus (STN), the globus pallidus pars interna (GPi), and the globus pallidus pars externa (GPe). A cellular-based model of the basal ganglia system (BGS), based on the model proposed by Rubin and Terman (J Comput Neurosci 16:211–235, 2004), was developed. ... Our results suggest that DBS in the STN could functionally restore the TC relay activity, while DBS in the GPe and in the GPi could functionally over-activate and inhibit it, respectively. Our results are consistent with the experimental and the clinical evidences on the network effects of DBS." | |
| Ion concentration dynamics as a mechanism for neuronal bursting (Barreto & Cressman 2011) | |
| "We describe a simple conductance-based model neuron that includes intra and extracellular ion concentration dynamics and show that this model exhibits periodic bursting. The bursting arises as the fast-spiking behavior of the neuron is modulated by the slow oscillatory behavior in the ion concentration variables and vice versa. By separating these time scales and studying the bifurcation structure of the neuron, we catalog several qualitatively different bursting profiles that are strikingly similar to those seen in experimental preparations. Our work suggests that ion concentration dynamics may play an important role in modulating neuronal excitability in real biological systems." | |
| Ionic basis of alternans and Timothy Syndrome (Fox et al. 2002), (Zhu and Clancy 2007) | |
| From Zhu and Clancy: "... Here we employ theoretical simulations to examine the effects of a Timothy Syndrome (TS) mutation in the L-type Ca2+ channel on cardiac dynamics over multiple scales, from a gene mutation to protein, cell, tissue, and finally the ECG, to connect a defective Ca2+ channel to arrhythmia susceptibility. ..." | |
| Ionic mechanisms of bursting in CA3 pyramidal neurons (Xu and Clancy 2008) | |
| "... We present a single-compartment model of a CA3 hippocampal pyramidal neuron based on recent experimental data. We then use the model to determine the roles of primary depolarizing currents in burst generation. The single compartment model incorporates accurate representations of sodium (Na+) channels (NaV1.1) and T-type calcium (Ca2+) channel subtypes (CaV3.1, CaV3.2, and CaV3.3). Our simulations predict the importance of Na+ and T-type Ca2+ channels in hippocampal pyramidal cell bursting and reveal the distinct contribution of each subtype to burst morphology. We also performed fastslow analysis in a reduced comparable model, which shows that our model burst is generated as a result of the interaction of two slow variables, the T-type Ca2+ channel activation gate and the Ca2+-dependent potassium (K+) channel activation gate. The model reproduces a range of experimentally observed phenomena including afterdepolarizing potentials, spike widening at the end of the burst, and rebound. Finally, we use the model to simulate the effects of two epilepsy-linked mutations: R1648H in NaV1.1 and C456S in CaV3.2, both of which result in increased cellular excitability." | |
| KV1 channel governs cerebellar output to thalamus (Ovsepian et al. 2013) | |
| The output of the cerebellum to the motor axis of the central nervous system is orchestrated mainly by synaptic inputs and intrinsic pacemaker activity of deep cerebellar nuclear (DCN) projection neurons. Herein, we demonstrate that the soma of these cells is enriched with KV1 channels produced by mandatory multi-merization of KV1.1, 1.2 alpha andKV beta2 subunits. Being constitutively active, the K+ current (IKV1) mediated by these channels stabilizes the rate and regulates the temporal precision of self-sustained firing of these neurons. ... Through the use of multi-compartmental modelling and ... the physiological significance of the described functions for processing and communication of information from the lateral DCN to thalamic relay nuclei is established. | |
| Kenyon cells in the honeybee (Wustenberg et al 2004) | |
| The mushroom body of the insect brain is an important locus for olfactory information processing and associative learning. ... Current- and voltage-clamp analyses were performed on cultured Kenyon cells from honeybees. ... Voltage-clamp analyses characterized a fast transient Na+ current (INa), a delayed rectifier K+ current (IK,V) and a fast transient K+ current (IK,A). Using the neurosimulator SNNAP, a Hodgkin-Huxley type model was developed and used to investigate the roles of the different currents during spiking. The model led to the prediction of a slow transient outward current (IK,ST) that was subsequently identified by reevaluating the voltage-clamp data. Simulations indicated that the primary currents that underlie spiking are INa and IK,V, whereas IK,A and IK,ST primarily determined the responsiveness of the model to stimuli such constant or oscillatory injections of current. See paper for more details. | |
| Kv4.3, Kv1.4 encoded K channel in heart cells & tachy. (Winslow et al 1999, Greenstein et al 2000) | |
| (1999) We present a model of the canine midmyocardial ventricular action potential and Ca2+ transient. The model is used to estimate the degree of functional upregulation and downregulation of Na/Ca exchanger protein and sarcoplasmic reticulum Ca ATPase in heart failure using data obtained from 2 different experimental protocols. (2000): A model of canine I:(to1) (the Ca(2+)-independent transient outward current) is formulated as the combination of Kv4.3 and Kv1.4 currents and is incorporated into an existing canine ventricular myocyte model. Simulations demonstrate strong coupling between L-type Ca(2+) current and I:(Kv4.3) and predict a bimodal relationship between I:(Kv4.3) density and APD whereby perturbations in I:(Kv4.3) density may produce either prolongation or shortening of APD, depending on baseline I:(to1) current level. See each paper for more and details. | |
| L5b PC model constrained for BAC firing and perisomatic current step firing (Hay et al., 2011) | |
| "... L5b pyramidal cells have been the subject of extensive experimental and modeling studies, yet conductance-based models of these cells that faithfully reproduce both their perisomatic Na+-spiking behavior as well as key dendritic active properties, including Ca2+ spikes and back-propagating action potentials, are still lacking. Based on a large body of experimental recordings from both the soma and dendrites of L5b pyramidal cells in adult rats, we characterized key features of the somatic and dendritic firing and quantified their statistics. We used these features to constrain the density of a set of ion channels over the soma and dendritic surface via multi-objective optimization with an evolutionary algorithm, thus generating a set of detailed conductance-based models that faithfully replicate the back-propagating action potential activated Ca2+ spike firing and the perisomatic firing response to current steps, as well as the experimental variability of the properties. ... The models we present provide several experimentally-testable predictions and can serve as a powerful tool for theoretical investigations of the contribution of single-cell dynamics to network activity and its computational capabilities. " | |
| LGMD Variability and logarithmic compression in dendrites (Jones and Gabbiani, 2012, 2012B) | |
| A compartmental model of the LGMD with a simplified, rake shaped, excitatory dendrite. It receives spontaneous input and excitatory and inhibitory synaptic inputs triggered by visual stimuli. It generates realistic responses to looming through the velocity dependent scaling and delay of individual excitatory synaptic inputs, with variability. We use the model to show that the key determinants of output variability are spontaneous input and temporal jitter of the excitatory inputs, rather than variability in magnitude of individual inputs (2012B, J Neurophysiol). We also use the model to analyze the transformation of the excitatory signals through the visual pathway; concluding that the representation of stimulus velocity is transformed from an expansive relationship at the level of the LGMD inputs to a logarithmic one at the level of its membrane potential (2012, J Neurosci). | |
| Lamprey spinal CPG neuron (Huss et al. 2007) | |
| This is a model of a generic locomotor network neuron in the lamprey spinal cord. The given version is assumed to correspond to an interneuron; motoneurons can also be modelled by changing the dendritic tree morphology. | |
| Lateral dendrodenditic inhibition in the Olfactory Bulb (David et al. 2008) | |
| Mitral cells, the principal output neurons of the olfactory bulb, receive direct synaptic activation from primary sensory neurons. Shunting inhibitory inputs delivered by granule cell interneurons onto mitral cell lateral dendrites are believed to influence spike timing and underlie coordinated field potential oscillations. Lateral dendritic shunt conductances delayed spiking to a degree dependent on both their electrotonic distance and phase of onset. Recurrent inhibition significantly narrowed the distribution of mitral cell spike times, illustrating a tendency towards coordinated synchronous activity. This result suggests an essential role for early mechanisms of temporal coordination in olfaction. The model was adapted from Davison et al, 2003, but include additional noise mechanisms, long lateral dendrite, and specific synaptic point processes. | |
| Layer V PFC pyramidal neuron used to study persistent activity (Sidiropoulou & Poirazi 2012) | |
| "... Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. ... Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression. " | |
| Leaky integrate-and-fire model of spike frequency adaptation in the LGMD (Gabbiani and Krapp 2006) | |
| This will reproduce Figure 9 of Gabbiani and Krapp (2006) J Neurophysiol 96:2951-2962. The figure simply shows that a leaky-integrate-and-fire model cannot reproduce spike frequency adaptation as it is seen experimentally in the LGMD neuron. | |
| Leech Mechanosensory Neurons: Synaptic Facilitation by Reflected APs (Baccus 1998) | |
| This model by Stephen Baccus explores the phenomena of action potential (AP) propagation at branch boints in axons. APs are sometimes transmitted down the efferent processes and sometimes are reflected back to the axon of AP origin or neither. See the paper for details. The model zip file contains a readme.txt which list introductory steps to follow to run the simulation. Stephen Baccus's email address: baccus@fas.harvard.edu | |
| Linear vs non-linear integration in CA1 oblique dendrites (Gómez González et al. 2011) | |
| The hippocampus in well known for its role in learning and memory processes. The CA1 region is the output of the hippocampal formation and pyramidal neurons in this region are the elementary units responsible for the processing and transfer of information to the cortex. Using this detailed single neuron model, it is investigated the conditions under which individual CA1 pyramidal neurons process incoming information in a complex (non-linear) as opposed to a passive (linear) manner. This detailed compartmental model of a CA1 pyramidal neuron is based on one described previously (Poirazi, 2003). The model was adapted to five different reconstructed morphologies for this study, and slightly modified to fit the experimental data of (Losonczy, 2006), and to incorporate evidence in pyramidal neurons for the non-saturation of NMDA receptor-mediated conductances by single glutamate pulses. We first replicate the main findings of (Losonczy, 2006), including the very brief window for nonlinear integration using single-pulse stimuli. We then show that double-pulse stimuli increase a CA1 pyramidal neuron’s tolerance for input asynchrony by at last an order of magnitude. Therefore, it is shown using this model, that the time window for nonlinear integration is extended by more than an order of magnitude when inputs are short bursts as opposed to single spikes. | |
| Low Threshold Calcium Currents in TC cells (Destexhe et al 1998) | |
| In Destexhe, Neubig, Ulrich, and Huguenard (1998) experiments and models examine low threshold calcium current's (IT, or T-current) distribution in thalamocortical (TC) cells. Multicompartmental modeling supports the hypothesis that IT currents have a density at least several fold higher in the dendrites than the soma. The IT current contributes significantly to rebound bursts and is thought to have important network behavior consequences. See the paper for details. See also http://cns.iaf.cnrs-gif.fr Correspondance may be addressed to Alain Destexhe: Destexhe@iaf.cnrs-gif.fr | |
| Low dose of dopamine may stimulate prolactin secretion by increasing K currents (Tabak et al. 2006) | |
| ".. We considered the fast K+ currents flowing through large-conductance BK channels and through A-type channels. We developed a minimal lactotroph model to investigate the effects of these two currents. Both IBK and IA could transform the electrical pattern of activity from spiking to bursting, but through distinct mechanisms. IBK always increased the intracellular Ca2+ concentration, while IA could either increase or decrease it. Thus, the stimulatory effects of DA could be mediated by a fast K+ conductance which converts tonically spiking cells to bursters. In addition, the study illustrates that a heterogeneous distribution of fast K+ conductances could cause heterogeneous lactotroph firing patterns." | |
| MNTB Neuron: Kv3.1 currents (Wang et al 1998) | |
| Model of Medial Nucleus of the Trapezoid Body (MNTB) neurons described in Lu-Yang Wang, Li Gan, Ian D. Forsythe and Leonard K. Kaczmarek. Contribution of the Kv3.1 potassium channel to high-frequency firing in mouse auditory neurones. J. Physiol (1998) 509.1 183-194. Created by David Kornfeld, Byram Hills High School, Armonk NY. Please email dbk1@mindspring.com for questions about the model. See Readme.txt below for more info. | |
| Mammalian Ventricular Cell (Beeler and Reuter 1977) | |
| This classic model of ventricular myocardial fibres was implemented by Francois Gannier. "... Four individual components of ionic current were formulated mathematically in terms of Hodgkin-Huxley type equations. The model incorporates two voltage- and time-dependent inward currents, the excitatory inward sodium current, illa, and a secondary or slow inward current, is, primarily carried by calcium ions. A time-independent outward potassium current, iK1, exhibiting inward-going rectification, and a voltage- and time-dependent outward current, i.1, primarily carried by potassium ions, are further elements of the model...." | |
| Mapping function onto neuronal morphology (Stiefel and Sejnowski 2007) | |
| "... We used an optimization procedure to find neuronal morphological structures for two computational tasks: First, neuronal morphologies were selected for linearly summing excitatory synaptic potentials (EPSPs); second, structures were selected that distinguished the temporal order of EPSPs. The solutions resembled the morphology of real neurons. In particular the neurons optimized for linear summation electrotonically separated their synapses, as found in avian nucleus laminaris neurons, and neurons optimized for spike-order detection had primary dendrites of significantly different diameter, as found in the basal and apical dendrites of cortical pyramidal neurons. ..." | |
| Markov Chain-based Stochastic Shielding Hodgkin Huxley Model (Schmandt, Galan 2012) | |
| Mathematical model for windup (Aguiar et al. 2010) | |
| "Windup is characterized as a frequency-dependent increase in the number of evoked action potentials in dorsal horn neurons in response to electrical stimulation of afferent C-fibers. ... The approach presented here relies on mathematical and computational analysis to study the mechanism(s) underlying windup. From experimentally obtained windup profiles, we extract the time scale of the facilitation mechanisms that may support the characteristics of windup. Guided by these values and using simulations of a biologically realistic compartmental model of a wide dynamic range (WDR) neuron, we are able to assess the contribution of each mechanism for the generation of action potentials windup. ..." | |
| Mechanisms of fast rhythmic bursting in a layer 2/3 cortical neuron (Traub et al 2003) | |
| This simulation is based on the reference paper listed below.
This port was made by Roger D Traub and Maciej T Lazarewicz (mlazarew@seas.upenn.edu) Thanks to Ashlen P Reid for help with porting a morphology of the cell. | |
| Mechanisms of magnetic stimulation of central nervous system neurons (Pashut et al. 2011) | |
| Transcranial magnetic stimulation (TMS) is a widely applied tool for probing cognitive function in humans and is one of the best tools for clinical treatments and interfering with cognitive tasks. Surprisingly, while TMS has been commercially available for decades, the cellular mechanisms underlying magnetic stimulation remain unclear. Here we investigate these mechanisms using compartmental modeling. We generated a numerical scheme allowing simulation of the physiological response to magnetic stimulation of neurons with arbitrary morphologies and active properties. Computational experiments using this scheme suggested that TMS affects neurons in the central nervous system (CNS) primarily by somatic stimulation. | |
| Mechanisms of very fast oscillations in axon networks coupled by gap junctions (Munro, Borgers 2010) | |
| Axons connected by gap junctions can produce very fast oscillations (VFOs, > 80 Hz) when stimulated randomly at a low rate. The models here explore the mechanisms of VFOs that can be seen in an axonal plexus, (Munro & Borgers, 2009): a large network model of an axonal plexus, small network models of axons connected by gap junctions, and an implementation of the model underlying figure 12 in Traub et al. (1999) . The large network model consists of 3,072 5-compartment axons connected in a random network. The 5-compartment axons are the 5 axonal compartments from the CA3 pyramidal cell model in Traub et al. (1994) with a fixed somatic voltage. The random network has the same parameters as the random network in Traub et al. (1999), and axons are stimulated randomly via a Poisson process with a rate of 2/s/axon. The small network models simulate waves propagating through small networks of axons connected by gap junctions to study how local connectivity affects the refractory period. | |
| Medial vestibular neuron models (Quadroni and Knopfel 1994) | |
| The structure and the parameters of the model cells were chosen to reproduce the responses of type A and type B MVNns as described in electrophysiological recordings. The emergence of oscillatory firing under these two specific experimental conditions is consistent with electrophysiological recordings not used during construction of the model. We, therefore, suggest that these models have a high predictive value. | |
| Membrane potential changes in dendritic spines during APs and synaptic input (Palmer & Stuart 2009) | |
| " ... Finally, we used simulations of our experimental observations in morphologically realistic models to estimate spine neck resistance. These simulations indicated that spine neck resistance ranges up to ~500 M Ohm. Spine neck resistances of this magnitude reduce somatic EPSPs by ~15%, indicating that the spine neck is unlikely to act as a physical device to significantly modify synaptic strength." | |
| Midbrain dopamine neuron: firing patterns (Canavier 1999) | |
| Sodium dynamics drives the generation of slow oscillations postulated to underly NMDA-evoked bursting activity. | |
| Model of SK current`s influence on precision in Globus Pallidus Neurons (Deister et al. 2009) | |
| " ... In numerical simulations, the availability of both Na+ and A-type K+ channels during autonomous firing were reduced when SK channels were removed, and a nearly equal reduction in Na+ and K+ subthreshold-activated ion channel availability produced a large decrease in the neuron's slope conductance near threshold. This change made the neuron more sensitive to intrinsically generated noise. In vivo, this change would also enhance the sensitivity of GP (Globus Pallidus) neurons to small synaptic inputs." | |
| Modeling conductivity profiles in the deep neocortical pyramidal neuron (Wang K et al. 2013) | |
| "With the rapid increase in the number of technologies aimed at observing electric activity inside the brain, scientists have felt the urge to create proper links between intracellular- and extracellular-based experimental approaches. Biophysical models at both physical scales have been formalized under assumptions that impede the creation of such links. In this work, we address this issue by proposing amulticompartment model that allows the introduction of complex extracellular and intracellular resistivity profiles. This model accounts for the geometrical and electrotonic properties of any type of neuron through the combination of four devices: the integrator, the propagator, the 3D connector, and the collector. ..." | |
| Modeling interactions in Aplysia neuron R15 (Yu et al 2004) | |
| "The biophysical properties of neuron R15 in Aplysia endow it with the ability to express multiple modes of oscillatory electrical activity, such as beating and bursting. Previous modeling studies examined the ways in which membrane conductances contribute to the electrical activity of R15 and the ways in which extrinsic modulatory inputs alter the membrane conductances by biochemical cascades and influence the electrical activity. The goals of the present study were to examine the ways in which electrical activity influences the biochemical cascades and what dynamical properties emerge from the ongoing interactions between electrical activity and these cascades." See paper for more and details. | |
| Modeling temperature changes in AMPAR kinetics (Postlethwaite et al 2007) | |
| This model was used to simulate glutamatergic, AMPA receptor mediated mEPSCs (miniature EPSCs, resulting from spontaneous vesicular transmitter release) at the calyx of Held synapse. It was used to assess the influence of temperature (physiological vs. subphysiological) on the amplitude and time course of mEPSCs. In the related paper, simulation results were directly compared to the experimental data, and it was concluded that an increase of temperature accelerates AMPA receptor kinetics. | |
| Modelling reduced excitability in aged CA1 neurons as a Ca-dependent process (Markaki et al. 2005) | |
| "We use a multi-compartmental model of a CA1 pyramidal cell to study changes in hippocampal excitability that result from aging-induced alterations in calcium-dependent membrane mechanisms. The model incorporates N- and L-type calcium channels which are respectively coupled to fast and slow afterhyperpolarization potassium channels. Model parameters are calibrated using physiological data. Computer simulations reproduce the decreased excitability of aged CA1 cells, which results from increased internal calcium accumulation, subsequently larger postburst slow afterhyperpolarization, and enhanced spike frequency adaptation. We find that aging-induced alterations in CA1 excitability can be modelled with simple coupling mechanisms that selectively link specific types of calcium channels to specific calcium-dependent potassium channels." | |
| Models of Na channels from a paper on the PKC control of I Na,P (Baker 2005) | |
| "The tetrodotoxin-resistant (TTX-r) persistent Na(+) current, attributed to Na(V)1.9, was recorded in small (< 25 mum apparent diameter) dorsal root ganglion (DRG) neurones cultured from P21 rats and from adult wild-type and Na(V)1.8 null mice. ... Numerical simulation of the up-regulation qualitatively reproduced changes in sensory neurone firing properties. ..." Note: models of NaV1.8 and NaV1.9 and also persistent and transient Na channels that collectively model Nav 1.1, 1.6, and 1.7 are present in this model. | |
| Modulation of neuronal synchronization by D4 dopamine receptor-mediated phospholipid methylation | |
| "We describe a new molecular mechanism of dopamine-induced membrane protein modulation that can tune neuronal oscillation frequency to attention related gamma rhythm. This mechanism is based on the unique ability of D4 dopamine receptors (D4R) to carry out phospholipid methylation (PLM) that may affect the kinetics of ion channels. We show that by deceasing the inertia of the delayed rectifier potassium channel, a transition to 40 Hz oscillations can be achieved. ..." | |
| Modulation of septo-hippocampal theta activity by GABAA receptors (Hajos et al. 2004) | |
| θ Frequency oscillation of the septo-hippocampal system has been considered as a prominent activity associated with cognitive function and affective processes. ... In the present experiments we applied a combination of computational and physiological techniques to explore the functional role of GABAA receptors in θ oscillation. ... In parallel to these experimental observations, a computational model has been constructed by implementing a septal GABA neuron model with a CA1 hippocampal model containing three types of neurons (including oriens and basket interneurons and pyramidal cells; latter modeled by multicompartmental techniques; for detailed model description with network parameters see online addendum: http://geza.kzoo.edu/theta). This connectivity made the network capable of simulating the responses of the septo-hippocampal circuitry to the modulation of GABAA transmission, and the presently described computational model proved suitable to reveal several aspects of pharmacological modulation of GABAA receptors. In addition, computational findings indicated different roles of distinctively located GABAA receptors in θ generation. | |
| Modulation of temporal integration window (Migliore, Shepherd 2002) | |
| Model simulation file from the paper M.Migliore and Gordon M. Shepherd Emerging rules for distributions of active dendritic properties underlying specific neuronal functions. Nature Rev. Neurosci. 3, 362-370 (2002). | |
| Morris-Lecar model of the barnacle giant muscle fiber (Morris, Lecar 1981) | |
| ... This paper presents an analysis of the possible modes of behavior available to a system of two noninactivating conductance mechanisms, and indicates a good correspondence to the types of behavior exhibited by barnacle fiber. The differential equations of a simple equivalent circuit for the fiber are dealt with by means of some of the mathematical techniques of nonlinear mechanics. General features of the system are (a) a propensity to produce damped or sustained oscillations over a rather broad parameter range, and (b) considerable latitude in the shape of the oscillatory potentials. It is concluded that for cells subject to changeable parameters (either from cell to cell or with time during cellular activity), a system dominated by two noninactivating conductances can exhibit varied oscillatory and bistable behavior. See paper for details. | |
| Motoneuron model of self-sustained firing after spinal cord injury (Kurian et al. 2011) | |
| " ... During the acute-stage of spinal cord injury (SCI), the endogenous ability to generate plateaus is lost; however, during the chronic-stage of SCI, plateau potentials reappear with prolonged self-sustained firing that has been implicated in the development of spasticity. In this work, we extend previous modeling studies to systematically investigate the mechanisms underlying the generation of plateau potentials in motoneurons, including the influences of specific ionic currents, the morphological characteristics of the soma and dendrite, and the interactions between persistent inward currents and synaptic input. ..." | |
| Multicompartmental cerebellar granule cell model (Diwakar et al. 2009) | |
| A detailed multicompartmental model was used to study neuronal electroresponsiveness of cerebellar granule cells in rats. Here we show that, in cerebellar granule cells, Na+ channels are enriched in the axon, especially in the hillock, but almost absent from soma and dendrites. Numerical simulations indicated that granule cells have a compact electrotonic structure allowing EPSPs to diffuse with little attenuation from dendrites to axon. The spike arose almost simultaneously along the whole axonal ascending branch and invaded the hillock, whose activation promoted spike back-propagation with marginal delay (<200 micros) and attenuation (<20 mV) into the somato-dendritic compartment. For details check the cited article. | |
| Multiple modes of a conditional neural oscillator (Epstein, Marder 1990) | |
| We present a model for a conditional bursting neuron consisting of five conductances: Hodgkin-Huxley type time- and voltage-dependent Na+ and K+ conductances, a calcium activated voltage-dependent K+ conductance, a calcium-inhibited time- and voltage-dependent Ca++ conductance, and a leakage Cl- conductance. Different bursting and silent modes and transitions between them are analyzed in the model and compared to bursting modes in experiment. See the paper for details. | |
| Multiple modes of inner hair cell stimulation (Mountain, Cody 1999) | |
| This model simulates the membrane potential of an inner hair cell for a sinusoidal stimulus to the hair bundle. It uses a 2-state Boltzmann model for the tension-gated conductance in the stereocilia and a linear model for the basolateral membrane. This model is based on the IHC model used in Mountain and Cody (1999). | |
| Multiscale interactions between chemical and electric signaling in LTP (Bhalla 2011) | |
| "Synaptic plasticity leads to long-term changes in excitability, whereas cellular homeostasis maintains excitability. Both these processes involve interactions between molecular events, electrical events, and network activity. Here I explore these intersections with a multilevel model that embeds molecular events following synaptic calcium influx into a multicompartmental electrical model of a CA1 hippocampal neuron. ..." | |
| Multiscale model of olfactory receptor neuron in mouse (Dougherty 2009) | |
| Collection of XPP (.ode) files simulating the signal transduction (slow) and action potential (fast) currents in the olfactory receptor neuron of mouse. Collection contains model configured for dual odorant pulse delivery and model configured for prolonged odorant delivery. For those interested more in transduction processes, each whole cell recording model comes with a counter part file configured to show just the slow transduction current for ease of use and convenience. These transduction-only models typically run faster than the full multi-scale models but do not demonstrate action potentials. | |
| MyFirstNEURON (Houweling, Sejnowski 1997) | |
| MyFirstNEURON is a NEURON demo by Arthur Houweling and Terry Sejnowski. Perform experiments from the book 'Electrophysiology of the Neuron, A Companion to Shepherd's Neurobiology, An Interactive Tutorial' by John Huguenard & David McCormick, Oxford University Press 1997, or design your own one or two cell simulation. For more information see http://www.cnl.salk.edu/Simulations. Salk Institute, Computational Neurobiology Lab, 10010 North Torrey Pines Rd., La Jolla CA 092037. Email: arthur@salk.edu | |
| NMDA subunit effects on Calcium and STDP (Evans et al. 2012) | |
| Effect of NMDA subunit on spike timing dependent plasticity. | |
| Na+ channel dependence of AP initiation in cortical pyramidal neuron (Kole et al. 2008) | |
| In this simulation action potential initiation, action potential properties and the role of axon initial segment Na+ channels are investigated in a realistic model of a layer 5 pyramidal neuron axon initial segment. The main Na+ channel properties were constrained by experimental data and the axon initial segment was reconstructed. Model parameters were constrained by direct recordings at the axon initial segment. | |
| Nav1.6 sodium channel model in globus pallidus neurons (Mercer et al. 2007) | |
| Model files for the paper Mercer JN, Chan CS, Tkatch T, Held J, Surmeier DJ. Nav1.6 sodium channels are critical to pacemaking and fast spiking in globus pallidus neurons.,J Neurosci. 2007 Dec 5;27(49):13552-66. | |
| Neocort. pyramidal cells subthreshold somatic voltage controls spike propagation (Munro Kopell 2012) | |
| There is suggestive evidence that pyramidal cell axons in neocortex may be coupled by gap junctions into an ``axonal plexus" capable of generating Very Fast Oscillations (VFOs) with frequencies exceeding 80 Hz. It is not obvious, however, how a pyramidal cell in such a network could control its output when action potentials are free to propagate from the axons of other pyramidal cells into its own axon. We address this problem by means of simulations based on 3D reconstructions of pyramidal cells from rat somatosensory cortex. We show that somatic depolarization enables propagation via gap junctions into the initial segment and main axon, while somatic hyperpolarization disables it. We show further that somatic voltage cannot effectively control action potential propagation through gap junctions on minor collaterals; action potentials may therefore propagate freely from such collaterals regardless of somatic voltage. In previous work, VFOs are all but abolished during the hyperpolarization phase of slow-oscillations induced by anesthesia in vivo. This finding constrains the density of gap junctions on collaterals in our model and suggests that axonal sprouting due to cortical lesions may result in abnormally high gap junction density on collaterals, leading in turn to excessive VFO activity and hence to epilepsy via kindling. | |
| Neocortical pyramidal neuron: deep; effects of dopamine (Durstewitz et al 2000) | |
| "... Simulated dopamine strongly enhanced high, delay-type activity but not low, spontaneous activity in the model network. Furthermore the strength of an afferent stimulation needed to disrupt delay-type activity increased with the magnitude of the dopamine-induced shifts in network parameters, making the currently active representation much more stable. Stability could be increased by dopamine-induced enhancements of the persistent Na(+) and N-methyl-D-aspartate (NMDA) conductances. Stability also was enhanced by a reduction in AMPA conductances. The increase in GABA(A) conductances that occurs after stimulation of dopaminergic D1 receptors was necessary in this context to prevent uncontrolled, spontaneous switches into high-activity states (i.e., spontaneous activation of task-irrelevant representations). In conclusion, the dopamine-induced changes in the biophysical properties of intrinsic ionic and synaptic conductances conjointly acted to highly increase stability of activated representations in PFC networks and at the same time retain control over network behavior and thus preserve its ability to adequately respond to task-related stimuli. ..." See paper and references for more and details. | |
| Neural Query System NQS Data-Mining From Within the NEURON Simulator (Lytton 2006) | |
| NQS is a databasing program with a query command modeled loosely on the SQL select command. Please see the manual NQS.pdf for details of use. An NQS database must be populated with data to be used. This package includes MFP (model fingerprint) which provides an example of NQS use with the model provided in the modeldb folder (see readme for usage). | |
| Neuronal morphology goes digital ... (Parekh & Ascoli 2013) | |
| An illustration of a NEURON model and why reconstructing morphologies is useful in this regard (i.e. investigating spatial/temporal aspect of how different currents and voltage propagate in dendrites). | |
| Neurophysiological impact of inactivation pathways in A-type K+ channels (Fineberg et al 2012) | |
| These models predict the differential effects of varying pathways of inactivation (closed state inactivation, CSI, or open state inactivation, OSI). Specifically, Markov models of Kv4 potassium channels with CSI or CSI+OSI were inserted into the CA1 pyramidal neuron model from Migliore et al (1999; ModelDB accession #2796) to determine the neurophysiological impact of inactivation pathways. Furthermore, Markov models of Kv4.2 and Kv3.4 channels are used to illustrate a method by which to test what pathway of inactivation a channel uses. | |
| Nigral dopaminergic neurons: effects of ethanol on Ih (Migliore et al. 2008) | |
| We use a realistic computational model of dopaminergic neurons in vivo to suggest that ethanol, through its effects on Ih, modifies the temporal structure of the spiking activity. The model predicts that the dopamine level may increase much more during bursting than pacemaking activity, especially in those brain regions with a slow dopamine clearance rate. The results suggest that a selective pharmacological remedy could thus be devised against the rewarding effects of ethanol that are postulated to mediate alcohol abuse and addiction, targeting the specific HCN genes expressed in dopaminergic neurons. | |
| Nodose sensory neuron (Schild et al. 1994, Schild and Kunze 1997) | |
| This is a simulink implementation of the model described in Schild et al. 1994, and Schild and Kunze 1997 papers on Nodose sensory neurons. These papers describe the sensitivity these models have to their parameters and the match of the models to experimental data. | |
| Nonlinear dendritic processing in barrel cortex spiny stellate neurons (Lavzin et al. 2012) | |
| This is a multi-compartmental simulation of a spiny stellate neuron which is stimulated by a thalamocortical (TC) and cortico-cortical (CC) inputs. No other cells are explicitly modeled; the presynaptic network activation is represented by the number of active synapses. Preferred and non –preferred thalamic directions thus correspond to larder/smaller number of TC synapses. This simulation revealed that randomly activated synapses can cooperatively trigger global NMDA spikes, which involve participation of most of the dendritic tree. Surprisingly, we found that although the voltage profile of the cell was uniform, the calcium influx was restricted to ‘hot spots’ which correspond to synaptic clusters or large conductance synapses | |
| O-LM interneuron model (Lawrence et al. 2006) | |
| Exploring the kinetics and distribution of the muscarinic potassium channel, IM, in 2 O-LM interneuron morphologies. Modulation of the ion channel by drugs such as XE991 (antagonist) and retigabine (agonist) are simulated in the models to examine the role of IM in spiking properties. | |
| Olfactory Mitral Cell (Bhalla, Bower 1993) | |
| This is a conversion to NEURON of the mitral cell model described in Bhalla and Bower (1993). The original model was written in GENESIS and is available by joining BABEL, the GENESIS users' group. | |
| Olfactory Mitral Cell (Davison et al 2000) | |
| A four-compartment model of a mammalian olfactory bulb mitral cell, reduced from the complex 286-compartment model described by Bhalla and Bower (1993). The compartments are soma/axon, secondary dendrites, primary dendrite shaft and primary dendrite tuft. The reduced model runs 75 or more times faster than the full model, making its use in large, realistic network models of the olfactory bulb practical. | |
| Olfactory Mitral Cell (Shen et al 1999) | |
| Mitral cell model with standard parameters for the paper: Shen, G.Y., Chen, W. R., Midtgaard, J., Shepherd, G.M., and Hines, M.L. (1999) Computational Analysis of Action Potential Initiation in Mitral Cell Soma and Dendrites Based on Dual Patch Recordings. Journal of Neurophysiology 82:3006. Contact Michael.Hines@yale.edu if you have any questions about the implementation of the model. | |
| Olfactory Mitral cell: AP initiation modes (Chen et al 2002) | |
| The mitral cell primary dendrite plays an important role in transmitting distal olfactory nerve input from olfactory glomerulus to the soma-axon initial segment. To understand how dendritic active properties are involved in this transmission, we have combined dual soma and dendritic patch recordings with computational modeling to analyze action-potential initiation and propagation in the primary dendrite. | |
| On stochastic diff. eq. models for ion channel noise in Hodgkin-Huxley neurons (Goldwyn et al. 2010) | |
| " ... We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effect on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. ..." | |
| Oversampling method to extract excitatory and inhibitory conductances (Bedard et al. 2012) | |
| " ... We present here a new method that allows extracting estimates of the full time course of excitatory and inhibitory conductances from single-trial Vm recordings. This method is based on oversampling of the Vm . We test the method numerically using models of increasing complexity. Finally, the method is evaluated using controlled conductance injection in cortical neurons in vitro using the dynamic-clamp technique. ..." | |
| Paired turbulence and light effect on calcium increase in Hermissenda (Blackwell 2004) | |
| The sea slug Hermissenda learns to associate light and hair cell stimulation, but not when the stimuli are temporally uncorrelated...These issues were addressed using a multi-compartmental computer model of phototransduction, calcium dynamics, and ionic currents of the Hermissenda photoreceptor...simulations show that a potassium leak channel, which closes with an increase in calcium, is required to produce both the untrained LLD and the enhanced LLD due to the decrease in voltage dependent potassium currents. | |
| Paradoxical GABA-mediated excitation (Lewin et al. 2012) | |
| "GABA is the key inhibitory neurotransmitter in the adult central nervous system, but in some circumstances can lead to a paradoxical excitation that has been causally implicated in diverse pathologies from endocrine stress responses to diseases of excitability including neuropathic pain and temporal lobe epilepsy. We undertook a computational modeling approach to determine plausible ionic mechanisms of GABAA-dependent excitation in isolated post-synaptic CA1 hippocampal neurons because it may constitute a trigger for pathological synchronous epileptiform discharge. In particular, the interplay intracellular chloride accumulation via the GABAA receptor and extracellular potassium accumulation via the K/Cl co-transporter KCC2 in promoting GABAA-mediated excitation is complex. ..." | |
| Parameter estimation for Hodgkin-Huxley based models of cortical neurons (Lepora et al. 2011) | |
| Simulation and fitting of two-compartment (active soma, passive dendrite) for different classes of cortical neurons. The fitting technique indirectly matches neuronal currents derived from somatic membrane potential data rather than fitting the voltage traces directly. The method uses an analytic solution for the somatic ion channel maximal conductances given approximate models of the channel kinetics, membrane dynamics and dendrite. This approach is tested on model-derived data for various cortical neurons. | |
| Periodicity in Na channel properties alters model neuron excitability (Majumdar and Sikdar 2007) | |
| "... We have shown earlier that the duration and amplitude of a prolonged depolarization alter all the steady state and kinetic parameters of rNav1.2a voltage gated Na channel in a pseudo-oscillatory fashion. In the present study, we show that the Hodgkin–Huxley voltage and time dependent rate constants of activation (am and bm) and fast inactivation (ah and bh), obtained from the analyses of Na currents and steady state activation and inactivation plots, following application of prepulses in both slow (1–100 s) and fast (100–1000 ms) ranges, vary with the duration of a prepulse in a pseudo-oscillatory manner. ..." | |
| Phase response curve of a globus pallidal neuron (Fujita et al. 2011) | |
| We investigated how changes in ionic conductances alter the phase response curve (PRC) of a globus pallidal (GP) neuron and stability of a synchronous activity of a GP network, using a single-compartmental conductance-based neuron model. The results showed the PRC and the stability were influenced by changes in the persistent sodium current, the Kv3 potassium, the M-type potassium and the calcium-dependent potassium current. | |
| Point process framework for modeling electrical stimulation of auditory nerve (Goldwyn et al. 2012) | |
| A point process model of the auditory nerve that provides a compact and accurate description of neural responses to electric stimulation. Inspired by the framework of generalized linear models, the model consists of a cascade of linear and nonlinear stages. A semi-analytical procedure uniquely determines each parameter in the model on the basis of fundamental statistics from recordings of single fiber responses to electric stimulation, including threshold, relative spread, jitter, and chronaxie. The model also accounts for refractory and summation effects that influence the responses of auditory nerve fibers to high pulse rate stimulation. | |
| Principles of Computational Modelling in Neuroscience (Book) (Sterratt et al. 2011) | |
| "... This book provides a step-by-step account of how to model the neuron and neural circuitry to understand the nervous system at all levels, from ion channels to networks. Starting with a simple model of the neuron as an electrical circuit, gradually more details are added to include the effects of neuronal morphology, synapses, ion channels and intracellular signaling. The principle of abstraction is explained through chapters on simplifying models, and how simplified models can be used in networks. This theme is continued in a final chapter on modeling the development of the nervous system. Requiring an elementary background in neuroscience and some high school mathematics, this textbook is an ideal basis for a course on computational neuroscience." | |
| Properties of aconitine-induced block of KDR current in NG108-15 neurons (Lin et al. 2008) | |
| "The effects of aconitine (ACO), a highly toxic alkaloid, on ion currents in differentiated NG108-15 neuronal cells were investigated in this study. ACO (0.3-30 microM) suppressed the amplitude of delayed rectifier K+ current (IK(DR)) in a concentration-dependent manner with an IC50 value of 3.1 microM. The presence of ACO enhanced the rate and extent of IK(DR) inactivation, although it had no effect on the initial activation phase of IK(DR). ... A modeled cell was designed to duplicate its inhibitory effect on spontaneous pacemaking. ... Taken together, the experimental data and simulations show that ACO can block delayed rectifier K+ channels of neurons in a concentration- and state-dependent manner. Changes in action potentials induced by ACO in neurons in vivo can be explained mainly by its blocking actions on IK(DR) and INa." | |
| Proximal inhibition of Renshaw cells (Bui et al 2005) | |
| Inhibitory synaptic inputs to Renshaw cells are concentrated on the soma and the juxtasomatic dendrites. In the present study, we investigated whether this proximal bias leads to more effective inhibition under different neuronal operating conditions. Using compartmental models based on detailed anatomical measurements of intracellularly stained Renshaw cells, we compared the inhibition produced by GABAA synapses when distributed with a proximal bias to the inhibition produced when the same synapses were distributed uniformly. See paper for more and details. | |
| Pyramidal Neuron Deep, Superficial; Aspiny, Stellate (Mainen and Sejnowski 1996) | |
| This package contains compartmental models of four reconstructed neocortical neurons (layer 3 Aspiny, layer 4 Stellate, layer 3 and layer 5 Pyramidal neurons) with active dendritic currents using NEURON. Running this simulation demonstrates that an entire spectrum of firing patterns can be reproduced in this set of model neurons which share a common distribution of ion channels and differ only in their dendritic geometry. The reference paper is: Z. F. Mainen and T. J. Sejnowski (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382: 363-366. See also http://www.cnl.salk.edu/~zach/methods.html and http://www.cnl.salk.edu/~zach/ More info in readme.txt file below made visible by clicking on the patdemo folder and then on the readme.txt file. | |
| Pyramidal Neuron Deep: Constrained by experiment (Dyhrfjeld-Johnsen et al. 2005) | |
| "... As a practical demonstration of the use of CoCoDat we constructed a detailed computer model of an intrinsically bursting (IB) layer V pyramidal neuron from the rat barrel cortex supplementing experimental data (Schubert et al., 2001) with information extracted from the database. The pyramidal neuron morphology (Fig. 10B) was reconstructed from histological sections of a biocytin-stained IB neuron using the NeuroLucida software package..." | |
| Pyramidal Neuron Deep: attenuation in dendrites (Stuart, Spruston 1998) | |
| Stuart, G. and Spruston, N. Determinants of voltage attenuation in neocortical pyramidal neuron dendrites. Journal of Neuroscience 18:3501-3510, 1998. | |
| Pyramidal Neuron: Deep, Thalamic Relay and Reticular, Interneuron (Destexhe et al 1998, 2001) | |
| This package shows single-compartment models of different classes of cortical neurons, such as the "regular-spiking", "fast-spiking" and "bursting" (LTS) neurons. The mechanisms included are the Na+ and K+ currents for generating action potentials (INa, IKd), the T-type calcium current (ICaT), and a slow voltage-dependent K+ current (IM). See http://cns.fmed.ulaval.ca/alain_demos.html | |
| Pyramidal neuron coincidence detection tuned by dendritic branching pattern (Schaefer et al 2006) | |
| "... We examined the relationship between dendritic arborization and the coupling between somatic and dendritic action potential (AP) initiation sites in layer 5 (L5) neocortical pyramidal neurons. Coupling was defined as the relative reduction in threshold for initiation of a dendritic calcium AP due to a coincident back-propagating AP. Simulations based on reconstructions of biocytin-filled cells showed that addition of oblique branches of the main apical dendrite in close proximity to the soma (d < 140 um) increases the coupling between the apical and axosomatic AP initiation zones, whereas incorporation of distal branches decreases coupling. ... We conclude that variation in dendritic arborization may be a key determinant of variability in coupling (49+-17%; range 19-83%; n = 37) and is likely to outweigh the contribution made by variations in active membrane properties. Thus coincidence detection of inputs arriving from different cortical layers is strongly regulated by differences in dendritic arborization." | |
| Pyramidal neuron conductances state and STDP (Delgado et al. 2010) | |
| Neocortical neurons in vivo process each of their individual inputs in the context of ongoing synaptic background activity, produced by the thousands of presynaptic partners a typical neuron has. That background activity affects multiple aspects of neuronal and network function. However, its effect on the induction of spike-timing dependent plasticity (STDP) is not clear. Using the present biophysically-detailed computational model, it is not only able to replicate the conductance-dependent shunting of dendritic potentials (Delgado et al,2010), but show that synaptic background can truncate calcium dynamics within dendritic spines, in a way that affects potentiation more strongly than depression. This program uses a simplified layer 2/3 pyramidal neuron constructed in NEURON. It was similar to the model of Traub et al., J Neurophysiol. (2003), and consisted of a soma, an apical shaft, distal dendrites, five basal dendrites, an axon, and a single spine. The spine’s location was variable along the apical shaft (initial 50 μm) and apical. The axon contained an axon hillock region, an initial segment, segments with myelin, and nodes of Ranvier, in order to have realistic action potential generation. For more information about the model see supplemental material, Delgado et al 2010. | |
| Pyramidal neurons switch from integrators to resonators (Prescott et al. 2008) | |
| During wakefulness, pyramidal neurons in the intact brain are bombarded by synaptic input that causes tonic depolarization, increased membrane conductance (i.e. shunting), and noisy fluctuations in membrane potential; by comparison, pyramidal neurons in acute slices typically experience little background input. Such differences in operating conditions can compromise extrapolation of in vitro data to explain neuronal operation in vivo. ... in slice experiments, we show that CA1 hippocampal pyramidal cells switch from integrators to resonators, i.e. from class 1 to class 2 excitability. The switch is explained by increased outward current contributed by the M-type potassium current IM ... Thus, even so-called “intrinsic” properties may differ qualitatively between in vitro and in vivo conditions. | |
| Rat phrenic motor neuron (Amini et al 2004) | |
| We have developed a model for the rat phrenic motor neuron (PMN) that robustly replicates many experimentally observed behaviors of PMNs in response to pharmacological, ionic, and electrical perturbations using a single set of parameters. | |
| Rat subthalamic projection neuron (Gillies and Willshaw 2006) | |
| A computational model of the rat subthalamic nucleus projection neuron is constructed using electrophysiological and morphological data and a restricted set of channel specifications. The model cell exhibits a wide range of electrophysiological behaviors characteristic of rat subthalamic neurons. It reveals that a key set of three channels play a primary role in distinguishing behaviors: a high-voltage-activated calcium channel (Cav 1.2.-1.3), a low-voltage-activated calcium channel (Cav 3.-), and a small current calcium-activated potassium channel (KCa 2.1-2.3). See paper for more and details. | |
| Reciprocal regulation of rod and cone synapse by NO (Kourennyi et al 2004) | |
| We constructed models of rod and cone photoreceptors using NEURON software to predict how changes in Ca channels would affect the light response in these cells and in postsynaptic horizontal cells. | |
| Reconstructing cerebellar granule layer evoked LFP using convolution (ReConv) (Diwakar et al. 2011) | |
| The model allows reconstruction of evoked local field potentials as seen in the cerebellar granular layer. The approach uses a detailed model of cerebellar granule neuron to generate data traces and then uses a "ReConv" or jittered repetitive convolution technique to reproduce post-synaptic local field potentials in the granular layer. The algorithm was used to generate both in vitro and in vivo evoked LFP and reflected the changes seen during LTP and LTD, when such changes were induced in the underlying neurons by modulating release probability of synapses and sodium channel regulated intrinsic excitability of the cells. | |
| Reduced leech heart interneuron (Channell et al. 2009) | |
| "Spiking and bursting patterns of neurons are characterized by a high degree of variability. A single neuron can demonstrate endogenously various bursting patterns, changing in response to external disturbances due to synapses, or to intrinsic factors such as channel noise. We argue that in a model of the leech heart interneuron existing variations of bursting patterns are significantly enhanced by a small noise. In the absence of noise this model shows periodic bursting with fixed numbers of interspikes for most parameter values. ..." | |
| Reflected SDE Hodgkin-Huxley Model (Dangerfield et al. 2012) | |
| Matlab code for simulating channel noise using the original Hodgkin-Huxley equations and a variant of the Hodkgin-Huxley model from (Bruce, Annals Bio Eng, Vol 36, pp 824-838, 2009). Methods used in simulation are SSA, SDE method and RSDE method. | |
| Region-specific atrophy in dendrites (Narayanan, Narayan, Chattarji, 2005) | |
| ...in this study, we develop an algorithm that uses statistics from precise morphometric analyses to systematically remodel neuronal reconstructions. We use the distribution function of the ratio of two normal distributed random variables to specify the probabilities of remodeling along various regions of the dendritic arborization. We then use these probabilities to drive an iterative algorithm for manipulating the dendritic tree in a region-specific manner. As a test, we apply this framework to a well characterized example of dendritic remodeling: stress-induced dendritic atrophy in hippocampal CA3 pyramidal cells. We show that our pruning algorithm is capable of eliciting atrophy that matches biological data from rodent models of chronic stress.
| |
| Regulation of KCNQ2/KCNQ3 current by G protein cycling (Suh et al 2004) | |
| Receptor-mediated modulation of KCNQ channels regulates neuronal excitability. This study concerns the kinetics and mechanism of M1 muscarinic receptor-mediated regulation of the cloned neuronal M channel, KCNQ2/KCNQ3 (Kv7.2/Kv7.3). ... observations were successfully described by a kinetic model representing biochemical steps of the signaling cascade using published rate constants where available. The model supports the following sequence of events for this Gq-coupled signaling: A classical G-protein cycle, including competition for nucleotide-free G-protein by all nucleotide forms and an activation step requiring Mg2, followed by G-protein-stimulated phospholipase C and hydrolysis of PIP2, and finally PIP2 dissociation from binding sites for inositol lipid on the channels so that KCNQ current was suppressed. See paper for details and more. | |
| Regulation of firing frequency in a midbrain dopaminergic neuron model (Kuznetsova et al. 2010) | |
| A dopaminergic (DA) neuron model with a morphologicaly realistic dendritic architecture. The model captures several salient features of DA neurons under different pharmacological manipulations and exhibits depolarization block for sufficiently high current pulses applied to the soma. | |
| Regulation of the firing pattern in dopamine neurons (Komendantov et al 2004) | |
| Midbrain dopaminergic (DA) neurons in vivo exhibit two major firing patterns: single-spike firing and burst firing. The firing pattern expressed is dependent on both the intrinsic properties of the neurons and their excitatory and inhibitory synaptic inputs. Experimental data suggest that the activation of NMDA and GABAA receptors is crucial contributor to the initiation and suppression of burst firing, respectively, and that blocking calcium-activated potassium channels can facilitate burst firing. This multi-compartmental model of a DA neuron with a branching structure was developed and calibrated based on in vitro experimental data to explore the effects of different levels of activation of NMDA and GABAA receptors as well as the modulation of the SK current on the firing activity. | |
| Rejuvenation model of dopamine neuron (Chan et al. 2007) | |
| Model files for the paper C. Savio Chan, et al. 'Rejuvenation' protects neurons in mouse models of Parkinson's disease, Nature 447, 1081-1086(28 June 2007). | |
| Resonance properties through Chirp stimulus responses (Narayanan Johnston 2007, 2008) | |
| ...we constructed a simple, single-compartment
model with Ih as the only active current... we found that both resonance frequency and resonance strength increased monotonically with the increase in the h conductance, supporting the notion of a direct, graded relationship between h conductance and resonance properties... (Narayanan and Johnston, 2007). ...we show that the h channels introduce an apparent negative delay in the local voltage response of these neurons with respect to the injected current within the theta frequency range... we found that the total inductive phase increased monotonically with the h conductance, whereas it had a bell-shaped dependence on both the membrane voltage and the half-maximal activation voltage for the h conductance. (Narayanan and Johnston, 2008). | |
| Response properties of an integrate and fire model (Zhang and Carney 2005) | |
| "A computational technique is described for calculation of the interspike interval and poststimulus time histograms for the responses of an integrate-and-fire model to arbitrary inputs. ... For stationary inputs, the regularity of the output was studied in detail for various model parameters. For nonstationary inputs, the effects of the model parameters on the output synchronization index were explored. ... these response properties have been reported for some cells in the ventral cochlear nucleus in the auditory brainstem. " | |
| Rhesus Monkey Layer 3 Pyramidal Neurons: V1 vs PFC (Amatrudo, Weaver et al. 2012) | |
| Whole-cell patch-clamp recordings and high-resolution 3D morphometric analyses of layer 3 pyramidal neurons in in vitro slices of monkey primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) revealed that neurons in these two brain areas possess highly distinctive structural and functional properties. ... Three-dimensional reconstructions of V1 and dlPFC neurons were incorporated into computational models containing Hodgkin-Huxley and AMPA- and GABAA-receptor gated channels. Morphology alone largely accounted for observed passive physiological properties, but led to AP firing rates that differed more than observed empirically, and to synaptic responses that opposed empirical results. Accordingly, modeling predicts that active channel conductances differ between V1 and dlPFC neurons. The unique features of V1 and dlPFC neurons are likely fundamental determinants of area-specific network behavior. The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information. The greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning. | |
| Role of Ih in firing patterns of cold thermoreceptors (Orio et al., 2012) | |
| " ... Here we investigated the role of Ih in cold-sensitive (CS) nerve endings, where cold sensory transduction actually takes place. Corneal CS nerve endings in mice show a rhythmic spiking activity at neutral skin temperature that switches to bursting mode when the temperature is lowered. ... Mathematical modeling shows that the firing phenotype of CS nerve endings from HCN1−/− mice can be reproduced by replacing HCN1 channels with the slower HCN2 channels rather than by abolishing Ih. We propose that Ih carried by HCN1 channels helps tune the frequency of the oscillation and the length of bursts underlying regular spiking in cold thermoreceptors, having important implications for neural coding of cold sensation. " | |
| Role of active dendrites in rhythmically-firing neurons (Goldberg et al 2006) | |
| "The responsiveness of rhythmically-firing neurons to synaptic inputs is characterized by their phase response curve (PRC), which relates how weak somatic perturbations affect the timing of the next action potential. The shape of the somatic PRC is an important determinant of collective network dynamics. Here we study theoretically and experimentally the impact of distally-located synapses and dendritic nonlinearities on the synchronization properties of rhythmically firing neurons. Combining the theories of quasi-active cables and phase-coupled oscillators we derive an approximation for the dendritic responsiveness, captured by the neuron's dendritic PRC (dPRC). This closed-form expression indicates that the dPRCs are linearly-filtered versions of the somatic PRC, and that the filter characteristics are determined by the passive and active properties of the dendrite. ... collective dynamics can be qualitatively different depending on the location of the synapse, the neuronal firing rates and the dendritic nonlinearities." See paper for more and details. | |
| Roles of I(A) and morphology in AP prop. in CA1 pyramidal cell dendrites (Acker and White 2007) | |
| " ...Using conductance-based models of CA1 pyramidal cells, we show that underlying “traveling wave attractors” control action potential propagation in the apical dendrites. By computing these attractors, we dissect and quantify the effects of IA channels and dendritic morphology on bAP amplitudes. We find that non-uniform activation properties of IA can lead to backpropagation failure similar to that observed experimentally in these cells. ... " | |
| STD-dependent and independent encoding of Input irregularity as spike rate (Luthman et al. 2011) | |
| "... We use a conductance-based model of a CN neuron to study the effect of the regularity of Purkinje cell spiking on CN neuron activity. We find that increasing the irregularity of Purkinje cell activity accelerates the CN neuron spike rate and that the mechanism of this recoding of input irregularity as output spike rate depends on the number of Purkinje cells converging onto a CN neuron. ..." | |
| STDP depends on dendritic synapse location (Letzkus et al. 2006) | |
| This model was published in Letzkus, Kampa & Stuart (2006) J Neurosci 26(41):10420-9. The simulation creates several plots showing voltage and NMDA current and conductance changes at different apical dendritic locations in layer 5 pyramidal neurons during STDP induction protocols. Created by B. Kampa (2006). | |
| Salamander retinal ganglian cells: morphology influences firing (Sheasby, Fohlmeister 1999) | |
| Nerve impulse entrainment and other excitation and passive phenomena are analyzed for a morphologically diverse and exhaustive data set (n=57) of realistic (3-dimensional computer traced) soma-dendritic tree structures of ganglion cells in the tiger salamander (Ambystoma tigrinum) retina. | |
| Salamander retinal ganglion cell: ion channels (Fohlmeister, Miller 1997) | |
| A realistic five (5) channel spiking model reproduces the bursting behavior of tiger salamander ganglion cells in the retina. Please see the readme for more information. | |
| Selective control of cortical axonal spikes by a slowly inactivating K+ current (Shu et al. 2007) | |
| We discovered a low-threshold, slowly inactivating K+ current, containing Kv1.2 alpha subunits, in axon initial segment, playing a key role in the modulation of spike threshold and spike duration as well as the spike timing in prefrontal cortex layer V pyramidal cell of ferrets and rats. A kd.mod file implements this D current and put it in the axonal model: Neuron_Dcurrent.hoc. Run the model to see the gradual modulation effect over seconds on spike shape. | |
| Self-influencing synaptic plasticity (Tamosiunaite et al. 2007) | |
| "... Similar to a previous study (Saudargiene et al., 2004) we employ a differential Hebbian learning rule to emulate spike-timing dependent plasticity and investigate how the interaction of dendritic and back-propagating spikes, as the post-synaptic signals, could influence plasticity. ..." | |
| Serotonergic modulation of Aplysia sensory neurons (Baxter et al 1999) | |
| The present study investigated how the modulation of these currents altered the spike duration and excitability of sensory neurons and examined the relative contributions of PKA- and PKC-mediated effects to the actions of 5-HT. A Hodgkin-Huxley type model was developed that described the ionic conductances in the somata of sensory neurons. The descriptions of these currents and their modulation were based largely on voltageclamp data from sensory neurons. Simulations were preformed with the program SNNAP (Simulator for Neural Networks and Action Potentials). The model was sufficient to replicate empirical data that describes the membrane currents, action potential waveform and excitability as well as their modulation by application of 5-HT, increased levels of adenosine cyclic monophosphate or application of active phorbol esters. The results provide several predictions that warrant additional experimental investigation and illustrate the importance of considering indirect as well as direct effects of modulatory agents on the modulation of membrane currents. See paper for more details. | |
| Shaping of action potentials by different types of BK channels (Jaffe et al., 2011) | |
| Dentate gyrus granule cells highly express the beta4 accessory subunit which confer BK channels with type II properties. The properties of heterologously-expressed BK channels (with and without the beta4 subunit) were used to construct channel models. These were then used to study how they affect single action potentials and trains of spikes in a model dentate gyrus granule cells (based on Aradi and Holmes, 1999). | |
| Signal integration in LGN cells (Briska et al 2003) | |
| Computer models were used to investigate passive properties of lateral geniculate nucleus thalamocortical cells and thalamic interneurons based on in vitro whole-cell study. Two neurons of each type were characterized physiologically and morphologically. Differences in the attenuation of propagated signals depend on both cell morphology and signal frequency. See the paper for details. | |
| Signal integration in a CA1 pyramidal cell (Graham 2001) | |
| This model investigates signal integration in the dendritic tree of a hippocampal CA1 pyramidal cell when different combinations of active channels are present in the tree (Graham, 2001) | |
| Simple and accurate Diffusion Approximation algorithm for stochastic ion channels | |
| " ... We derived the (Stochastic Differential Equations) SDE explicitly for any given ion channel kinetic scheme. The resulting generic equations were surprisingly simple and interpretable – allowing an easy, transparent and efficient (Diffusion Approximation) DA implementation, avoiding unnecessary approximations. The algorithm was tested in a voltage clamp simulation and in two different current clamp simulations, yielding the same results as (Markov Chains) MC modeling. Also, the simulation efficiency of this DA method demonstrated considerable superiority over MC methods, except when short time steps or low channel numbers were used." | |
| Simple model of barrel-specific segregation in cortex (Lu et al 2006) | |
| Mice with a loss-of-function mutation of calcium/calmodulin-activated adenylyl cyclase I (AC1) - barrelless mice - have strikingly abherrent cortical development: the thalamic afferents into the barrel cortex do not segregate into whisker-specific barrels. Our paper investigates the link between this mutation and the "barrelless" phenotype, and demonstrates that the loss-of-function mutation leads to deficits in presynaptic mechanisms at the thalamocortical synapse. How might presynaptic deficits disrupt whisker-specific segregation in the barrel cortex? We used a model to demonstrate one possibility: decrease in the release probability at the thalamocortical synapse (which is observed in the barrelless mutant) can influence the balance between LTP and LTD (in favor of LTD), which can disrupt whisker segregaton. Though how this occurs is easily explained with a conceptual model (described succinctly in the associated paper), we also produced a computational simulation of this phenomenon. | |
| Simulated light response in rod photoreceptors (Liu and Kourennyi 2004) | |
| We developed a complete computer model of the rod, which accurately reproduced the main features of the light response and allowed us to demonstrate that it was suppression of Kx channels that was essential for slowing SLR and increasing excitability of rods. The results reported in this work further establish the importance of Kx channels in rod photoreceptor function. | |
| Simulation studies on mechanisms of levetiracetam-mediated inhibition of IK(DR) (Huang et al. 2009) | |
| Levetiracetam (LEV) is an S-enantiomer pyrrolidone derivative with established antiepileptic efficacy in generalized epilepsy and partial epilepsy. However, its effects on ion currents and membrane potential remain largely unclear. In this study, we investigated the effect of LEV on differentiated NG108-15 neurons. ... Simulation studies in a modified Hodgkin-Huxley neuron and network unraveled that the reduction of slowly inactivating IK(DR) resulted in membrane depolarization accompanied by termination of the firing of action potentials in a stochastic manner. Therefore, the inhibitory effects on slowly inactivating IK(DR) (Kv3.1-encoded current) may constitute one of the underlying mechanisms through which LEV affects neuronal activity in vivo. | |
| Simulation study of Andersen-Tawil syndrome (Sung et al 2006) | |
| Patients with Andersen-Tawil syndrome (ATS) mostly have mutations on the KCNJ2 gene producing loss of function or dominant-negative suppression of the inward rectifier K(+) channel Kir2.1. However, clinical manifestations of ATS including dysmorphic features, periodic paralysis (hypo-, hyper-, or normokalemic), long QT, and ventricular arrhythmias (VA) are considerably variable. Using a modified dynamic Luo-Rudy simulation model of cardiac ventricular myocyte, we elucidate the mechanisms of VA in ATS. We adopted a kinetic model of KCNJ2 in which channel block by Mg(+2) and spermine was incorporated. In this study, we attempt to examine the effects of KCNJ2 mutations on the ventricular action potential (AP), single-channel Markovian models were reformulated and incorporated into the dynamic Luo-Rudy model for rapidly and slowly delayed rectifying K(+) currents and KCNJ2 channel. During pacing at 1.0 Hz with [K(+)]o at 5.4 mM, a stepwise 10% reduction of Kir2.1 channel conductance progressively prolonged the terminal repolarization phase of AP along with gradual depolarization of the resting membrane potential (RMP). At 90% reduction, early after- depolarizations (EADs) became inducible and RMP was depolarized to -55.0 mV (control: -90.1 mV) followed by emergence of spontaneous action potentials (SAP). Both EADs and SAP were facilitated by a decrease in [K(+)]o and suppressed by increase in [K(+)]o. beta-adrenergic stimulation enhanced delayed after-depolarizations (DADs) and could also facilitate EADs as well as SAP in the setting of low [K(+)]o and reduced Kir2.1 channel conductance. In conclusion, the spectrum of VA in ATS includes (1) triggered activity mediated by EADs and/or DADs, and (2) abnormal automaticity manifested as SAP. These VA can be aggravated by a decrease in [K(+)]o and beta-adrenergic stimulation, and may potentially induce torsades de pointes and cause sudden death. In patients with ATS, the hypokalemic form of periodic paralysis should have the highest propensity to VA especially during physical activities. | |
| Simulations of motor unit discharge patterns (Powers et al. 2011) | |
| " ... To estimate the potential contributions of PIC (Persistent Inward Current) activation and synaptic input patterns to motor unit discharge patterns, we examined the responses of a set of cable motoneuron models to different patterns of excitatory and inhibitory inputs. The models were first tuned to approximate the current- and voltage-clamp responses of low- and medium-threshold spinal motoneurons studied in decerebrate cats and then driven with different patterns of excitatory and inhibitory inputs. The responses of the models to excitatory inputs reproduced a number of features of human motor unit discharge. However, the pattern of rate modulation was strongly influenced by the temporal and spatial pattern of concurrent inhibitory inputs. Thus, even though PIC activation is likely to exert a strong influence on firing rate modulation, PIC activation in combination with different patterns of excitatory and inhibitory synaptic inputs can produce a wide variety of motor unit discharge patterns." | |
| Single neuron with dynamic ion concentrations (Cressman et al. 2009) | |
| These are the full and reduced models of a generic single neuron with dynamic ion concentrations as described in Cressman et al., Journal of Computational Neuroscience (2009) 26:159–170. | |
| Single neuron with ion concentrations to model anoxic depolarization (Zandt et al. 2011) | |
| A minimal single neuron model, including changing ion concentrations and homeostasis mechanisms. It shows the sudden depolarization that occurs after prolonged anoxia/ischemia. | |
| Site of impulse initiation in a neuron (Moore et al 1983) | |
| Examines the effect of temperature, the taper of the axon hillock, and HH channel density on antidromic spike invasion into the soma and spike initiation under dendritic stimulation. | |
| Small world networks of Type I and Type II Excitable Neurons (Bogaard et al. 2009) | |
| Implemented with NEURON 5.9, four model neurons with varying excitability properties affect the spatiotemporal patterning of small world networks of homogeneous and heterogeneous cell population. | |
| Sodium channel mutations causing generalized epilepsy with febrile seizures + (Barela et al. 2006) | |
| A novel mutation, R859C, in the Nav1.1 sodium channel was identified in a 4-generation, 33-member Caucasian family with a clinical presentation consistent with GEFS+. The mutation neutralizes a positively charged arginine in the domain 2 S4 voltage sensor of the Nav1.1 channel Ą subunit. When the mutation was placed in the rat Nav1.1 channel and expressed in Xenopus oocytes, the mutant channel displayed a positive shift in the voltage-dependence of sodium channel activation, slower recovery from slow inactivation, and lower levels of current compared to the wild-type channel. Computational analysis suggests that neurons expressing the mutant channel have higher thresholds for firing a single action potential and for firing multiple action potentials, along with decreased repetitive firing. Therefore, this mutation should lead to decreased neuronal excitability, in contrast to most previous GEFS+ sodium channel mutations that have changes predicted to increase neuronal firing. | |
| Space clamp problems in neurons with voltage-gated conductances (Bar-Yehuda and Korngreen 2008) | |
| " ... using numerical simulations, we show that the distortions of voltage-gated K+ and Ca2+ currents are substantial even in neurons with short dendrites. The simulations also demonstrate that passive cable theory cannot be used to justify voltage-clamping of neurons, due to significant shunting to the reversal potential of the voltage-gated conductance during channel activation. ... " | |
| Spatial gridding and temporal accuracy in NEURON (Hines and Carnevale 2001) | |
| A heuristic for compartmentalization based on the space constant at 100 Hz is proposed. The paper also discusses spatio/temporal accuracy and the use of CVODE. | |
| Spatial summation of excitatory and inhibitory inputs in pyramidal neurons (Hao et al. 2010) | |
| "... Based on realistic modeling and experiments in rat hippocampal slices, we derived a simple arithmetic rule for spatial summation of concurrent excitatory glutamatergic inputs (E) and inhibitory GABAergic inputs (I). The somatic response can be well approximated as the sum of the excitatory postsynaptic potential (EPSP), the inhibitory postsynaptic potential (IPSP), and a nonlinear term proportional to their product (k*EPSP*IPSP), where the coefficient k reflects the strength of shunting effect. ..." | |
| Spectral method and high-order finite differences for nonlinear cable (Omurtag and Lytton 2010) | |
| We use high-order approximation schemes for the space derivatives in the nonlinear cable equation and investigate the behavior of numerical solution errors by using exact solutions, where available, and grid convergence. The space derivatives are numerically approximated by means of differentiation matrices. A flexible form for the injected current is used that can be adjusted smoothly from a very broad to a narrow peak, which leads, for the passive cable, to a simple, exact solution. We provide comparisons with exact solutions in an unbranched passive cable, the convergence of solutions with progressive refinement of the grid in an active cable, and the simulation of spike initiation in a biophysically realistic single-neuron model. | |
| Spike Initiation in Neocortical Pyramidal Neurons (Mainen et al 1995) | |
| This model reproduces figure 3A from the paper Mainen ZF, Joerges J, Huguenard JR, Sejnowski TJ (1995). Please see the paper for detail whose full text is available at http://www.cnl.salk.edu/~zach/methods.html Email Zach Mainen for questions: mainen@cshl.org | |
| Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008) | |
| The Spike Response Model (SRM) optimized on the experimental data in the Single-Neuron modelling Competition ( www.incf.org/community/competitions ) for edition 2007 and edition 2008. The Spike Response Model is a simplified model of neuronal excitability where current linearly integrates to an artificial threshold. After the spike, the threshold is augmented and the voltage follows a voltage kernel that is the average voltage trace during and after a spike. The parameters were chosen to best fit the observed spike times with a method outlined in Jolivet et al. (2006). | |
| Spike frequency adaptation in the LGMD (Peron and Gabbiani 2009) | |
| This model is used in the referenced paper to demonstrate that a model of an SK-like calcium-sensitive potassium (KCa) conductance can replicate the spike frequency adaptation (SFA) of the locust lobula giant movement detector (LGMD) neuron. The model simulates current injection experiments with and without KCa block in the LGMD, as well as visual stimulation experiments with and without KCa block. | |
| Spike repolarization in axon collaterals (Foust et al. 2011) | |
| Voltage sensing dye experiments and simulations characterize the location and re-polarizing function of Kv1 channels in cortical neurons. "... (the papers) results indicate that action potential-induced synaptic transmission may operate through a mix of analog–digital transmission owing to the properties of Kv1 channels in axon collaterals and presynaptic boutons." | |
| Spiking GridPlaceMap model (Pilly & Grossberg, PLoS One, 2013) | |
| Development of spiking grid cells and place cells in the entorhinal-hippocampal system to represent positions in large spaces | |
| Spinal Motor Neuron (Dodge, Cooley 1973) | |
| Dodge & Cooley (1973) "Action Potential of the Motorneuron" IBM J. Res. Develop. May 219--229 | |
| Spiny neuron model with dopamine-induced bistability (Gruber et al 2003) | |
| These files implement a model of dopaminergic modulation of voltage-gated currents (called kir2 and caL in the original paper). See spinycell.html for details of usage and implementation. For questions about this implementation, contact Ted Carnevale (ted.carnevale@yale.edu) | |
| State and location dependence of action potential metabolic cost (Hallermann et al., 2012) | |
| With this model of a layer 5 pyramidal neuron the state and location dependence of the ATP usage and the metabolic efficiency of action potentials can be analyzed. Model parameters were constrained by direct subcellular recordings at dendritic, somatic and axonal compartments. | |
| State dependent drug binding to sodium channels in the dentate gyrus (Thomas & Petrou 2013) | |
| A Markov model of sodium channels was developed that includes drug binding to fast inactivated states. This was incorporated into a model of the dentate gyrus to investigate the effects of anti-epileptic drugs on neuron and network properties. | |
| Stochastic 3D model of neonatal rat spinal motoneuron (Ostroumov 2007) | |
| " ... Although existing models of motoneurons have indicated the distributed role of certain conductances in regulating firing, it is unclear how the spatial distribution of certain currents is ultimately shaping motoneuron output. Thus, it would be helpful to build a bridge between histological and electrophysiological data. The present report is based on the construction of a 3D motoneuron model based on available parameters applicable to the neonatal spinal cord. ..." | |
| Stochastic Ih and Na-channels in pyramidal neuron dendrites (Kole et al 2006) | |
| The hyperpolarization-activated cation current (Ih) plays an important role in regulating neuronal excitability, yet its native single-channel properties in the brain are essentially unknown. Here we use variance-mean analysis to study the properties of single Ih channels in the apical dendrites of cortical layer 5 pyramidal neurons in vitro. ... In contrast to the uniformly distributed single-channel conductance, Ih channel number increases exponentially with distance, reaching densities as high as approximately 550 channels/microm2 at distal dendritic sites. These high channel densities generate significant membrane voltage noise. By incorporating a stochastic model of Ih single-channel gating into a morphologically realistic model of a layer 5 neuron, we show that this channel noise is higher in distal dendritic compartments and increased threefold with a 10-fold increased single-channel conductance (6.8 pS) but constant Ih current density. ... These data suggest that, in the face of high current densities, the small single-channel conductance of Ih is critical for maintaining the fidelity of action potential output. See paper for more and details. | |
| Stochastic ion channels and neuronal morphology (Cannon et al. 2010) | |
| "... We introduce and validate new computational tools that enable efficient generation and simulation of models containing stochastic ion channels distributed across dendritic and axonal membranes. Comparison of five morphologically distinct neuronal cell types reveals that when all simulated neurons contain identical densities of stochastic ion channels, the amplitude of stochastic membrane potential fluctuations differs between cell types and depends on sub-cellular location. ..." The code is downloadable and more information is available at http://www.psics.org/ | |
| Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011) | |
| A Matlab gui for simulating different channel noise models using the Hodgkin-Huxley equations. Methods provided and reviewed in Goldwyn and Shea-Brown (2011) are: current noise, subunit noise, conductance noise, and Markov chain, as well as the standard deterministic Hodgkin-Huxley model. | |
| Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011) (pylab) | |
| A pylab version from Alan Leggitt for simulating different channel noise models using the Hodgkin-Huxley equations. Methods provided and reviewed in Goldwyn and Shea-Brown (2011) are: current noise, subunit noise, conductance noise, and Markov chain, as well as the standard deterministic Hodgkin-Huxley model. | |
| Striatal GABAergic microcircuit, dopamine-modulated cell assemblies (Humphries et al. 2009) | |
| To begin identifying potential dynamically-defined computational elements within the striatum, we constructed a new three-dimensional model of the striatal microcircuit's connectivity, and instantiated this with our dopamine-modulated neuron models of the MSNs and FSIs. A new model of gap junctions between the FSIs was introduced and tuned to experimental data. We introduced a novel multiple spike-train analysis method, and apply this to the outputs of the model to find groups of synchronised neurons at multiple time-scales. We found that, with realistic in vivo background input, small assemblies of synchronised MSNs spontaneously appeared, consistent with experimental observations, and that the number of assemblies and the time-scale of synchronisation was strongly dependent on the simulated concentration of dopamine. We also showed that feed-forward inhibition from the FSIs counter-intuitively increases the firing rate of the MSNs. | |
| Striatal GABAergic microcircuit, spatial scales of dynamics (Humphries et al, 2010) | |
| The main thrust of this paper was the development of the 3D anatomical network of the striatum's GABAergic microcircuit. We grew dendrite and axon models for the MSNs and FSIs and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. These networks were examined for their predictions for the distributions of the numbers and distances of connections for all the connections in the microcircuit. We then combined the neuron models from a previous model (Humphries et al, 2009; ModelDB ID: 128874) with the new anatomical model. We used this new complete striatal model to examine the impact of the anatomical network on the firing properties of the MSN and FSI populations, and to study the influence of all the inputs to one MSN within the network. | |
| Superior paraolivary nucleus neuron (Kopp-Scheinpflug et al. 2011) | |
| This is a model of neurons in the brainstem superior paraolivary nucleus (SPN), which produce very salient offset firing during sound stimulation. Rebound offset firing is triggered by IPSPs coming from the medial nucleus of the trapezoid body (MNTB). This model shows that AP firing can emerge from inhibition through integration of large IPSPs, driven by an extremely negative chloride reversal potential, combined with a large hyperpolarization- activated non-specific cationic current (IH), with a secondary contribution from a T-type calcium conductance (ITCa). As a result, tiny gaps in sound stimuli of just 3-4ms can elicit reliable APs that signal such brief offsets. | |
| Sympathetic neuron (Wheeler et al 2004) | |
| This study shows how synaptic convergence and plasticity can interact to generate synaptic gain in autonomic ganglia and thereby enhance homeostatic control. Using a conductance-based computational model of an idealized sympathetic neuron, we simulated the postganglionic response to noisy patterns of presynaptic activity and found that a threefold amplification in postsynaptic spike output can arise in ganglia, depending on the number and strength of nicotinic synapses, the presynaptic firing rate, the extent of presynaptic facilitation, and the expression of muscarinic and peptidergic excitation. See references for details. | |
| Synaptic integration in a model of granule cells (Gabbiani et al 1994) | |
| We have developed a compartmental model of a turtle cerebellar granule cell consisting of 13 compartments that represent the soma and 4 dendrites. We used this model to investigate the synaptic integration of mossy fiber inputs in granule cells. See reference or abstract at PubMed link below for more information. | |
| Synaptic integration in tuft dendrites of layer 5 pyramidal neurons (Larkum et al. 2009) | |
| Simulations used in the paper. Voltage responses to current injections in different tuft locations; NMDA and calcium spike generation. Summation of multiple input distribution. | |
| Synchrony by synapse location (McTavish et al. 2012) | |
| This model considers synchrony between mitral cells induced via shared granule cell interneurons while taking into account the spatial constraints of the system. In particular, since inhibitory inputs decay passively along the lateral dendrites, this model demonstrates that an optimal arrangement of the inhibitory synapses will be near the cell bodies of the relevant mitral cells. | |
| Synergistic inhibitory action of oxcarbazepine on INa and IK (Huang et al. 2008) | |
| "Oxcarbazepine (OXC), one of the newer anti-epileptic drugs, has been demonstrating its efficacy on wide-spectrum neuropsychiatric disorders. ... With the aid of patch-clamp technology, we first investigated the effects of OXC on ion currents in NG108-15 neuronal cells differentiated with cyclic AMP. We found OXC ... caused a reversible reduction in the amplitude of voltage-gated Na+ current (INa) ... and produce(d) a significant prolongation in the recovery of INa inactivation. ... Moreover, OXC could suppress the amplitude of delayed rectifier K+ current (IK(DR)), with no effect on M-type K+ current (IK(M)). ... Furthermore, the simulations, based on hippocampal pyramidal neurons (Pinsky-Rinzel model) and a network of the Hodgkin-Huxley model, were analysed to investigate the effect of OXC on action potentials. Taken together, our results suggest that the synergistic blocking effects on INa and IK(DR) may contribute to the underlying mechanisms through which OXC affects neuronal function in vivo." | |
| Synthesis of spatial tuning functions from theta cell spike trains (Welday et al., 2011) | |
| A single compartment model reproduces the firing rate maps of place, grid, and boundary cells by receiving inhibitory inputs from theta cells. The theta cell spike trains are modulated by the rat's movement velocity in such a way that phase interference among their burst pattern creates spatial envelope function which simulate the firing rate maps. | |
| T-type Ca current in thalamic neurons (Wang et al 1991) | |
| A model of the transient, low-threshold voltage-dependent (T-type) Ca2+ current is constructed using whole-cell voltage-clamp data from enzymatically isolated rat thalamocortical relay neurons. The T-type Ca2+ current is described according to the Hodgkin-Huxley scheme, using the m3h format, with rate constants determined from the experimental data. | |
| TTX-R Na+ current effect on cell response (Herzog et al 2001) | |
| "Small dorsal root ganglion (DRG) neurons, which include nociceptors, express multiple voltage-gated sodium currents. In addition to a classical fast inactivating tetrodotoxin-sensitive (TTX-S) sodium current, many of these cells express a TTX-resistant (TTX-R) sodium current that activates near -70 mV and is persistent at negative potentials. To investigate the possible contributions of this TTX-R persistent (TTX-RP) current to neuronal excitability, we carried out computer simulations using the Neuron program with TTX-S and -RP currents, fit by the Hodgkin-Huxley model, that closely matched the currents recorded from small DRG neurons. ..." See paper for more and details. | |
| TTX-R Na+ current effect on cell response (Herzog et al 2001) (MATLAB) | |
| "Small dorsal root ganglion (DRG) neurons, which include nociceptors, express multiple voltage-gated sodium currents. In addition to a classical fast inactivating tetrodotoxin-sensitive (TTX-S) sodium current, many of these cells express a TTX-resistant (TTX-R) sodium current that activates near -70 mV and is persistent at negative potentials. To investigate the possible contributions of this TTX-R persistent (TTX-RP) current to neuronal excitability, we carried out computer simulations using the Neuron program with TTX-S and -RP currents, fit by the Hodgkin-Huxley model, that closely matched the currents recorded from small DRG neurons. ..." See paper for more and details. | |
| Tag Trigger Consolidation (Clopath and Ziegler et al. 2008) | |
| This model simulates different phases of LTP/D, i.e. the induction or early phase, the setting of synaptic tags, a trigger process for protein synthesis, and a slow transition leading to synaptic consolidation namely the late phase of synaptic plasticity. The model explains a large body of experimental data on synaptic tagging and capture, cross-tagging, and the late phases of LTP and LTD. Moreover, the model accounts for the dependence of LTP and LTD induction on voltage and presynaptic stimulation frequency. | |
| Thalamic interneuron multicompartment model (Zhu et al. 1999) | |
| this is an attempt to recreate a set of simulations originally performed in 1994 under NEURON version 3 and last tested in 1999. When I ran it now it did not behave exactly the same as previously which I suspect is due to some minor mod file changes on my side rather than due to any differences among versions. After playing around with the parameters a little bit I was able to get something that looks generally like a physiological trace in J Neurophysiol, 81:702--711, 1999, fig. 8b top trace. This sad preface is simply offered in order to encourage anyone who is interested in this model to make and post fixes. I'm happy to help out. Simulation by JJ Zhu To run nrnivmodl nrngui.hoc | |
| Thalamic neuron, zebra finch DLM: Integration of pallidal and cortical inputs (Goldberg et al. 2012) | |
| This is a single-compartment model of a zebra finch thalamic relay neuron from nucleus DLM. It is used to explore the interaction between cortex-like glutamatergic input and pallidum-like GABAergic input as they control the spiking output of these neurons. | |
| Thalamic neuron: Modeling rhythmic neuronal activity (Meuth et al. 2005) | |
| The authors use an in vitro cell model of a single acutely isolated thalamic neuron in the NEURON simulation environment to address and discuss questions in an undergraduate course. Topics covered include passive electrical properties, composition of action potentials, trains of action potentials, multicompartment modeling, and research topics. The paper includes detailed instructions on how to run the simulations in the appendix. | |
| Thalamic reticular neurons: the role of Ca currents (Destexhe et al 1996) | |
| The experiments and modeling reported in this paper show how intrinsic bursting properties of RE cells may be explained by dendritic calcium currents. | |
| Thalamic transformation of pallidal input (Hadipour-Niktarash 2006) | |
| "In Parkinson’s disease, neurons of the internal segment of the globus pallidus (GPi) display the low-frequency tremor-related oscillations. These oscillatory activities are transmitted to the thalamic relay nuclei. Computer models of the interacting thalamocortical (TC) and thalamic reticular (RE) neurons were used to explore how the TC-RE network processes the low-frequency oscillations of the GPi neurons. ..." | |
| The role of ATP-sensitive potassium channels in a hippocampal neuron (Huang et al. 2007) | |
| "Hyperglycemia-related neuronal excitability and epileptic seizures are not uncommon in clinical practice. However, their underlying mechanism remains elusive. ATP-sensitive K(+) (K(ATP)) channels are found in many excitable cells, including cardiac myocytes, pancreatic beta cells, and neurons. These channels provide a link between the electrical activity of cell membranes and cellular metabolism. We investigated the effects of higher extracellular glucose on hippocampal K(ATP) channel activities and neuronal excitability. The cell-attached patch-clamp configuration on cultured hippocampal cells and a novel multielectrode recording system on hippocampal slices were employed. In addition, a simulation modeling hippocampal CA3 pyramidal neurons (Pinsky-Rinzel model) was analyzed to investigate the role of K(ATP) channels in the firing of simulated action potentials. ..." | |
| Theta phase precession in a model CA3 place cell (Baker and Olds 2007) | |
| "... The present study concerns a neurobiologically based computational model of the emergence of theta phase precession in which the responses of a single model CA3 pyramidal cell are examined in the context of stimulation by realistic afferent spike trains including those of place cells in entorhinal cortex, dentate gyrus, and other CA3 pyramidal cells. Spike-timing dependent plasticity in the model CA3 pyramidal cell leads to a spatially correlated associational synaptic drive that subsequently creates a spatially asymmetric expansion of the model cell’s place field. ... Through selective manipulations of the model it is possible to decompose theta phase precession in CA3 into the separate contributing factors of inheritance from upstream afferents in the dentate gyrus and entorhinal cortex, the interaction of synaptically controlled increasing afferent drive with phasic inhibition, and the theta phase difference between dentate gyrus granule cell and CA3 pyramidal cell activity." | |
| Tonic firing in substantia gelatinosa neurons (Melnick et al 2004) | |
| Ionic conductances underlying excitability in tonically firing neurons (TFNs) from substantia gelatinosa (SG) were studied by the patch-clamp method in rat spinal cord slices. ... Suppression of Ca2+ and KCA currents ... did not abolish the basic pattern of tonic firing, indicating that it was generated by voltage-gated Na+ and K+ currents. ... on the basis of present data, we created a model of TFN and showed that Na+ and KDR currents are sufficient to generate a basic pattern of tonic firing. It is concluded that the balanced contribution of all ionic conductances described here is important for generation and modulation of tonic firing in SG neurons. See paper for more and details. | |
| Tonic neuron in spinal lamina I: prolongation of subthreshold depol. (Prescott and De Koninck 2005) | |
| Model demonstrates mechanism whereby two kinetically distinct inward currents act synergistically to prolong subthreshold depolarization. The important currents are a persistent Na current (with fast kinetics) and a persistent Ca current (with slower kinetics). Model also includes a slow K current and transient Ca current, in addition to standard HH currents. Model parameters are set to values used in Fig. 8A. Simulation shows prolonged depolarizations in response to two brief stimuli. | |
| Touch Sensory Cells (T Cells) of the Leech (Cataldo et al. 2004) (Scuri et al. 2007) | |
| Bursts of spikes in leech T cells produce an AHP, which results from activation of a Na+/K+ pump and a Ca2+-dependent K+ current. Activity-dependent increases in the AHP are believed to induce conduction block of spikes in several regions of the neuron, which in turn, may decrease presynaptic invasion of spikes and thereby decrease transmitter release. To explore this possibility, we used the neurosimulator SNNAP to develop a multi-compartmental model of the T cell. Each compartment was modeled as an equivalent electrical circuit, in which some currents were regulated by intracellular Ca2+ and Na+. The membrane model consisted of a membrane capacitance (Cm), for which we used the value 1 uF/cm2, in parallel with two inward currents (Na+ and Ca2+), two K+ currents, a leak current and pump current. The model incorporated empirical data that describe the geometry of the cell and activity-dependent changes of the AHP (see paper for details). Simulations indicated that at some branching points, activity-dependent increases of the AHP reduced the number of spikes transmitted from the minor receptive field to the soma and beyond. These results suggest that the AHP can regulate spike conduction within the presynaptic arborizations of the cell and could in principle contribute to the synaptic depression that is correlated with increases in the AHP. | |
| Transfer properties of Neuronal Dendrites (Korogod et al 1998) | |
| The somatopetal current transfer was studied in mathematical models of a reconstructed brainstem motoneuron with tonically activated excitatory synaptic inputs uniformly distributed over the dendritic arborization. See paper and below readme.txt for more information. | |
| Visual Cortex Neurons: Dendritic computations (Archie, Mel 2000) | |
| Neuron and C program files from Archie, K.A. and Mel, B.W. A model of intradendritic computation of binocular disparity. Nature Neuroscience 3:54-63, 2000 The original files for this model are located at the web site | |
| Visual Cortex Neurons: Dendritic study (Anderson et al 1999) | |
| Neuron mod and hoc files for the paper: Anderson, J.C. Binzegger, T., Kahana, O., Segev, I., and Martin, K.A.C Dendritic asymmetry cannot account for directional responses in visual cortex. Nature Neuroscience 2:820:824, 1999 | |
| Voltage attenuation in CA1 pyramidal neuron dendrites (Golding et al 2005) | |
| Voltage attenuation in the apical dendritic field of CA1 pyramidal neurons is particularly strong for epsps spreading toward the soma. High cytoplasmic resistivity and high membrane (leak) conductance appear to be the major determinants of voltage attenuation over most of the apical field, but H current may be responsible for as much as half of the attenuation of distal apical epsps. | |
| Vomeronasal sensory neuron (Shimazaki et al 2006) | |
| NEURON model files from the papers: Shimazaki et al, Chem. Senses, epub ahead of print (2006) Electrophysiological properties and modeling of murine vomeronasal sensory neurons in acute slice preparations. The model reproduces quantitatively the experimentally observed firing rates of these neurons under a wide range of input currents. | |
| Wang-Buzsaki Interneuron (Talathi et al., 2010) | |
| The submitted code provides the relevant C++ files, matlabfiles and the data files essential to reproduce the figures in the JCNS paper titled Control of neural synchrony using channelrhodopsin-2: A computational study. | |
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