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Models that contain the Model Topic : Bursting

(The model is used to investigate mechanisms of neuronal bursting.)

   Models   Description
3D model of the olfactory bulb (Migliore et al. 2014)
This entry contains a link to a full HD version of movie 1 of the paper: "Distributed organization of a brain microcircuit analysed by three-dimensional modeling: the olfactory bulb" by M Migliore, F Cavarretta, ML Hines, and GM Shepherd.
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 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 network model of tail withdrawal in Aplysia (White et al 1993)
The contributions of monosynaptic and polysynaptic circuitry to the tail-withdrawal reflex in the marine mollusk Aplysia californica were assessed by the use of physiologically based neural network models. Effects of monosynaptic circuitry were examined by the use of a two-layer network model with four sensory neurons in the input layer and one motor neuron in the output layer. Results of these simulations indicated that the monosynaptic circuit could not account fully for long-duration responses of tail motor neurons elicited by tail stimulation. A three-layer network model was constructed by interposing a layer of two excitatory interneurons between the input and output layers of the two-layer network model. The three-layer model could account for long-duration responses in motor neurons. Sensory neurons are a known site of plasticity in Aplysia. Synaptic plasticity at more than one locus modified dramatically the input-output relationship of the three-layer network model. This feature gave the model redundancy in its plastic properties and points to the possibility of distributed memory in the circuitry mediating withdrawal reflexes in Aplysia. Please see paper for more results and details.
A simple integrative electrophysiological model of bursting GnRH neurons (Csercsik et al. 2011)
In this paper a modular model of the GnRH neuron is presented. For the aim of simplicity, the currents corresponding to fast time scales and action potential generation are described by an impulsive system, while the slower currents and calcium dynamics are described by usual ordinary differential equations (ODEs). The model is able to reproduce the depolarizing afterpotentials, afterhyperpolarization, periodic bursting behavior and the corresponding calcium transients observed in the case of GnRH neurons.
A single column thalamocortical network model (Traub et al 2005)
To better understand population phenomena in thalamocortical neuronal ensembles, we have constructed a preliminary network model with 3,560 multicompartment neurons (containing soma, branching dendrites, and a portion of axon). Types of neurons included superficial pyramids (with regular spiking [RS] and fast rhythmic bursting [FRB] firing behaviors); RS spiny stellates; fast spiking (FS) interneurons, with basket-type and axoaxonic types of connectivity, and located in superficial and deep cortical layers; low threshold spiking (LTS) interneurons, that contacted principal cell dendrites; deep pyramids, that could have RS or intrinsic bursting (IB) firing behaviors, and endowed either with non-tufted apical dendrites or with long tufted apical dendrites; thalamocortical relay (TCR) cells; and nucleus reticularis (nRT) cells. To the extent possible, both electrophysiology and synaptic connectivity were based on published data, although many arbitrary choices were necessary.
A spatially extended model for macroscopic spike-wave discharges (Taylor and Baier 2011)
A spatially extended neural field model for generating spike-wave based on the Amari (1977) model implemented in MATLAB.
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."
Basal ganglia network model of subthalamic deep brain stimulation (Hahn and McIntyre 2010)
Basal ganglia network model of parkinsonian activity and subthalamic deep brain stimulation in non-human primates from the article Instructions are provided in the README.txt file. Contact hahnp@ccf.org if you have any questions about the implementation of the model. Please include "ModelDB - BGnet" in the subject heading.
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.
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.
Bursting and resonance in cerebellar granule cells (D
In this study we report theta-frequency (3–12 Hz) bursting and resonance in rat cerebellar granule cells and show that these neurons express a previously unidentified slow repolarizing K1 current (IK-slow ). Our experimental and modeling results indicate that IK-slow was necessary for both bursting and resonance. See paper for more.
Bursting respiratory net: clustered architecture gives large phase diff`s (Fietkiewicz et al 2011)
Using a previous model of respiratory rhythm generation, we modified the network architecture such that cells can be segregated into two clusters. Cells within a given cluster burst with smaller phase differences than do cells from different clusters. This may explain the large phase differences seen experimentally, as reported in the paper.
CA1 oriens alveus interneurons: signaling properties (Minneci et al. 2007)
The model supports the experimental findings showing that the dynamic interaction between cells with various firing patterns could differently affect GABAergic signaling, leading to a wide range of interneuronal communication within the hippocampal network.
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.
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. ..."
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.
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 neuron (Safiulina et al. 2010)
In this review some of the recent work carried out in our laboratory concerning the functional role of GABAergic signalling at immature mossy fibres (MF)-CA3 principal cell synapses has been highlighted. To compare the relative strength of CA3 pyramidal cell output in relation to their MF glutamatergic or GABAergic inputs in postnatal development, a realistic model was constructed taking into account the different biophysical properties of these synapses.
CA3 pyramidal neuron: firing properties (Hemond et al. 2008)
In the paper, this model was used to identify how relative differences in K+ conductances, specifically KC, KM, & KD, between cells contribute to the different characteristics of the three types of firing patterns observed experimentally.
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.
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.
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: 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.
Classic model of the Tritonia Swim CPG (Getting, 1989)
Classic model developed by Petter Getting of the 3-cell core CPG (DSI, C2, and VSI-B) mediating escape swimming in Tritonia diomedea. Cells use a hybrid integrate-and-fire scheme pioneered by Peter Getting. Each model cell is reconstructed from extensive physiological measurements to precisely mimic I-F curves, synaptic waveforms, and functional connectivity. **However, continued physiological measurements show that Getting may have inadvertently incorporated modulatory and or polysynaptic effects -- the properties of this model do *not* match physiological measurements in rested preparations.** This simulation reconstructs the Getting model as reported in: Getting (1989) 'Reconstruction of small neural networks' In Methods in Neural Modeling, 1st ed, p. 171-196. See also, an earlier version of this model reported in Getting (1983). Every attempt has been made to replicate the 1989 model as precisely as possible.
Computer model of clonazepam`s effect in thalamic slice (Lytton 1997)
Demonstration of the effect of a minor pharmacological synaptic change at the network level. Clonazepam, a benzodiazepine, enhances inhibition but is paradoxically useful for certain types of seizures. This simulation shows how inhibition of inhibitory cells (the RE cells) produces this counter-intuitive effect.
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 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.
Dendritica (Vetter et al 2001)
Dendritica is a collection of programs for relating dendritic geometry and signal propagation. The programs are based on those used for the simulations described in: Vetter, P., Roth, A. & Hausser, M. (2001) For reprint requests and additional information please contact Dr. M. Hausser, email address: m.hausser@ucl.ac.uk
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.
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. ..."
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.
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.
Dynamic cortical interlaminar interactions (Carracedo et al. 2013)
"... Here we demonstrate the mechanism underlying a purely neocortical delta rhythm generator and show a remarkable laminar, cell subtype and local subcircuit delineation between delta and nested theta rhythms. We show that spike timing during delta-nested theta rhythms controls an iterative, reciprocal interaction between deep and superficial cortical layers resembling the unsupervised learning processes proposed for laminar neural networks by Hinton and colleagues ... and mimicking the alternating cortical dynamics of sensory and memory processing during wakefulness."
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.
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.
Febrile seizure-induced modifications to Ih (Chen et al 2001)
Modeling and experiments in the paper Chen K,Aradi I, Thom N,Eghbal-Ahmadi M, Baram TZ, and Soltesz I (2001) support the hypothesis that modified Ih currents strongly influence inhibitory inputs in CA1 cells and that the depolarizing shift in Ih activation plays a primary role in this process. Please see the paper for details. Some modeling details are available at http://www.ucihs.uci.edu/anatomy/soltesz/supp.htm Correspondance should be addressed to isoltesz@uci.edu (modeling was done by Ildiko Aradi, iaradi@uci.edu)
Gating of steering signals through phasic modulation of reticulospinal neurons (Kozlov et al. 2014)
" ... We use the lamprey as a model for investigating the role of this phasic modulation of the reticulospinal activity, because the brainstem–spinal cord networks are known down to the cellular level in this phylogenetically oldest extant vertebrate. We describe how the phasic modulation of reticulospinal activity from the spinal CPG ensures reliable steering/turning commands without the need for a very precise timing of on- or offset, by using a biophysically detailed large-scale (19,600 model neurons and 646,800 synapses) computational model of the lamprey brainstem–spinal cord network. To verify that the simulated neural network can control body movements, including turning, the spinal activity is fed to a mechanical model of lamprey swimming. ..."
Generating oscillatory bursts from a network of regular spiking neurons (Shao et al. 2009)
Avian nucleus isthmi pars parvocellularis (Ipc) neurons are reciprocally connected with the tectal layer 10 (L10) neurons and respond with oscillatory bursts to visual stimulation. To elucidate mechanisms of oscillatory bursting in this network of regularly spiking neurons, we investigated an experimentally constrained model of coupled leaky integrate-and-fire neurons with spike-rate adaptation. The model reproduces the observed Ipc oscillatory bursting in response to simulated visual stimulation.
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. ..."
Half-center oscillator database of leech heart interneuron model (Doloc-Mihu & Calabrese 2011)
We have created a database (HCO-db) of instances of a half-center oscillator computational model [Hill et al., 2001] for analyzing how neuronal parameters influence network activity. We systematically explored the parameter space of about 10.4 million simulated HCO instances and corresponding isolated neuron model simulations obtained by varying a set of selected parameters (maximal conductance of intrinsic and synaptic currents) in all combinations using a brute-force approach. We classified these HCO instances by their activity characteristics into identifiable groups. We built an efficient relational database table (HCO-db) with the resulting instances characteristics.
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.
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 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."
Irregular oscillations produced by cyclic recurrent inhibition (Friesen, Friesen 1994)
Model of recurrent cyclic inhibition as described on p.119 of Friesen and Friesen (1994), which was slightly modified from Szekely's model (1965) of a network for producing alternating limb movements.
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.
Large scale model of the olfactory bulb (Yu et al., 2013)
The readme file currently contains links to the results for all the 72 odors investigated in the paper, and the movie showing the network activity during learning of odor k3-3 (an aliphatic ketone).
Leech Heart (HE) Motor Neuron conductances contributions to NN activity (Lamb & Calabrese 2013)
"... To explore the relationship between conductances, and in particular how they influence the activity of motor neurons in the well characterized leech heartbeat system, we developed a new multi-compartmental Hodgkin-Huxley style leech heart motor neuron model. To do so, we evolved a population of model instances, which differed in the density of specific conductances, capable of achieving specific output activity targets given an associated input pattern. ... We found that the strengths of many conductances, including those with differing dynamics, had strong partial correlations and that these relationships appeared to be linked by their influence on heart motor neuron activity. Conductances that had positive correlations opposed one another and had the opposite effects on activity metrics when perturbed whereas conductances that had negative correlations could compensate for one another and had similar effects on activity metrics. "
Leech heart interneuron network model (Hill et al 2001, 2002)
We have created a computational model of the timing network that paces the heartbeat of the medicinal leech, Hirudo medicinalis. In the intact nerve cord, segmental oscillators are mutually entrained to the same cycle period. Although experiments have shown that the segmental oscillators are coupled by inhibitory coordinating interneurons, the underlying mechanisms of intersegmental coordination have not yet been elucidated. To help understand this coordination, we have created a simple computational model with two variants: symmetric and asymmetric. See references for more details. Biologically realistic network models with two, six, and eight cells and a tutorial are available at the links to Calabrese's web site below.
Lobster STG pyloric network model with calcium sensor (Gunay & Prinz 2010) (Prinz et al. 2004)
This pyloric network model simulator is a C/C++ program that saves 384 different calcium sensor values that are candidates for activity sensors (Gunay and Prinz, 2010). The simulator was used to scan all of the 20 million pyloric network models that were previously collected in a database (Prinz et al, 2004).
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."
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
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.

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.
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.
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.
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
Neocortical Layer I: I-A and I-K (Zhou, Hablitz 1996)
NEURON mod files for the I-A and I-K currents from the paper: Zhou FM, Hablitz JJ. Layer I neurons of the rat neocortex. II. Voltage-dependent outward currents. J Neurophysiol 1996 76:668-82.
Network bursts in cultured NN result from different adaptive mechanisms (Masquelier & Deco 2013)
It is now well established that cultured neuron networks are spontaneously active, and tend to synchronize. Synchronous events typically involve the whole network, and have thus been termed “network spikes” (NS). Using experimental recordings and numerical simulations, we show here that the inter-NS interval statistics are complex, and allow inferring the neural mechanisms at work, in particular the adaptive ones, and estimating a number of parameters to which we cannot access experimentally.
Network model with neocortical architecture (Anderson et al. 2011 plus under review paper)
Architecturally realistic neocortical model using seven classes of excitatory and inhibitory single compartment Hodgkin-Huxley cells. This is an addendum to ModelDB Accession # 98902, Studies of stimulus parameters for seizure disruption (Anderson et al. 2007). Wiring is adapted from the minicolumn hypothesis and incorporates visual and neocortical wiring data. Simulation demonstrates spontaneous bursting onset and cessation. This activity can be induced by random fluctuations in the surrounding background input (Manuscript in preparation).
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.
Olfactory bulb mitral cell gap junction NN model: burst firing and synchrony (O`Connor et al. 2012)
In a network of 6 mitral cells connected by gap junction in the apical dendrite tuft, continuous current injections of 0.06 nA are injected into 20 locations in the apical tufts of two of the mitral cells. The current injections into one of the cells starts 10 ms after the other to generate asynchronous firing in the cells (Migliore et al. 2005 protocol). Firing of the cells is asynchronous for the first 120 ms. However after the burst firing phase is completed the firing in all cells becomes synchronous.
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. ..."
Persistent synchronized bursting activity in cortical tissues (Golomb et al 2005)
The program simulates a one-dimensional model of a cortical tissue with excitatory and inhibitory populations.
PreBotzinger Complex inspiratory neuron with NaP and CAN currents (Park and Rubin 2013)
We have built on earlier models to develop a single-compartment Hodgkin-Huxley type model incorporating NaP and CAN currents, both of which can play important roles in bursting of inspiratory neurons in the PreBotzinger Complex of the mammalian respiratory brain stem. The model tracks the evolution of membrane potential, related (in)activation variables, calcium concentration, and available fraction of IP3 channels. The model can produce several types of bursting, presented and analyzed from a dynamical systems perspective in our paper.
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."
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, 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
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.
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.
Reliability of Morris-Lecar neurons with added T, h, and AHP currents (Zeldenrust et al. 2013)
We investigated the reliability of the timing of spikes in a spike train in a Morris-Lecar model with several extensions. A frozen Gaussian noise current, superimposed on a DC current, was injected. The neuron responded with spike trains that showed trial-to-trial variability. The reliability depends on the shape (steepness) of the current input versus spike frequency output curve. The model also allowed to study the contribution of three relevant ionic membrane currents to reliability: a T-type calcium current, a cation selective h-current and a calcium dependent potassium current in order to allow bursting, investigate the consequences of a more complex current-frequency relation and produce realistic firing rates.
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. "
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.
Simulating ion channel noise in an auditory brainstem neuron model (Schmerl & McDonnell 2013)
" ... Here we demonstrate that biophysical models of channel noise can give rise to two kinds of recently discovered stochastic facilitation effects in a Hodgkin-Huxley-like model of auditory brainstem neurons. The first, known as slope-based stochastic resonance (SBSR), enables phasic neurons to emit action potentials that can encode the slope of inputs that vary slowly relative to key time constants in the model. The second, known as inverse stochastic resonance (ISR), occurs in tonically firing neurons when small levels of noise inhibit tonic firing and replace it with burstlike dynamics. ..." Preprint available at http://arxiv.org/abs/1311.2643
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.
Spike trains in Hodgkin–Huxley model and ISIs of acupuncture manipulations (Wang et al. 2008)
The Hodgkin-Huxley equations (HH) are parameterized by a number of parameters and shows a variety of qualitatively different behaviors depending on the parameter values. Under stimulation of an external periodic voltage, the ISIs (interspike intervals) of a HH model are investigated in this work, while the frequency of the voltage is taken as the controlling parameter. As well-known, the science of acupuncture and moxibustion is an important component of Traditional Chinese Medicine with a long history. Although there are a number of different acupuncture manipulations, the method for distinguishing them is rarely investigated. With the idea of ISI, we study the electrical signal time series at the spinal dorsal horn produced by three different acupuncture manipulations in Zusanli point and present an effective way to distinguish them.
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).
Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)
This entry includes tools for generating and analyzing network structure, and for running the neuronal network simulations on them.
Studies of stimulus parameters for seizure disruption using NN simulations (Anderson et al. 2007)
Architecturally realistic neocortical model using seven classes of excitatory and inhibitory single compartment Hodgkin-Huxley cells. Wiring is adapted to minicolumn hypothesis and incorporates visual and neocortical data. Simulation demonstrates spontaneous bursting onset and cessation, and activity can be altered with external electric field.
Temperature-Dependent Pyloric Pacemaker Kernel (Caplan JS et al., 2014)
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: 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.
The activity phase of postsynaptic neurons (Bose et al 2004)
We show, in a simplified network consisting of an oscillator inhibiting a follower neuron, how the interaction between synaptic depression and a transient potassium current in the follower neuron determines the activity phase of this neuron. We derive a mathematical expression to determine at what phase of the oscillation the follower neuron becomes active. This expression can be used to understand which parameters determine the phase of activity of the follower as the frequency of the oscillator is changed. See paper for more.
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. ..."
Two-cell inhibitory network bursting dynamics captured in a one-dimensional map (Matveev et al 2007)
" ... Here we describe a simple method that allows us to investigate the existence and stability of anti-phase bursting solutions in a network of two spiking neurons, each possessing a T-type calcium current and coupled by reciprocal inhibition. We derive a one-dimensional map which fully characterizes the genesis and regulation of anti-phase bursting arising from the interaction of the T-current properties with the properties of synaptic inhibition. ..."
Updated Tritonia Swim CPG (Calin-Jagemann et al. 2007)
Model of the 3-cell core CPG (DSI, C2, and VSI-B) mediating escape swimming in Tritonia diomedea. Cells use a hybrid integrate-and-fire scheme pioneered by Peter Getting. Each model cell is reconstructed from extensive physiological measurements to precisely mimic I-F curves, synaptic waveforms, and functional connectivity.


Re-display model names without descriptions

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