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Models that contain the Model Topic : Synaptic Integration

(A neuron's presynaptic partners are adding neurotransmitters to the synaptic clefts either in pulses which correlate with presynaptic action potentials or continuously in a graded response to presynaptic activity.)

   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 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 simplified cerebellar Purkinje neuron (the PPR model) (Brown et al. 2011)
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, 2011 "Virtual NEURON: a Strategy For Merged Biochemical and Electrophysiological Modeling".
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."
Activity dependent changes in dendritic spine density and spine structure (Crook et al. 2007)
"... In this work, we extend previous modeling studies [27] by combining a model for activity-dependent spine density with one for calcium-mediated spine stem restructuring. ... Additional equations characterize the change in spine density along the dendrite, the current balance equation for an individual spine head, the change in calcium concentration in the spine head, and the dynamics of spine stem resistance. We use computational studies to investigate the changes in spine density and structure for differing synaptic inputs and demonstrate the effects of these changes on the input-output properties of the dendritic branch. ... "
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.
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."
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: Ih current (Migliore et al. 2012)
NEURON files from the paper: Migliore M, Migliore R (2012) Know Your Current Ih: Interaction with a Shunting Current Explains the Puzzling Effects of Its Pharmacological or Pathological Modulations. PLoS ONE 7(5): e36867. doi:10.1371/journal.pone.0036867. Experimental findings on the effects of Ih current modulation, which is particularly involved in epilepsy, appear to be inconsistent. In the paper, using a realistic model we show how and why a shunting current, such as that carried by TASK-like channels, dependent on the Ih peak conductance is able to explain virtually all experimental findings on Ih up- or down-regulation by modulators or pathological conditions.
CA1 pyramidal neuron: rebound spiking (Ascoli et al.2010)
The model demonstrates that CA1 pyramidal neurons support rebound spikes mediated by hyperpolarization-activated inward current (Ih), and normally masked by A-type potassium channels (KA). Partial KA reduction confined to one or few branches of the apical tuft may be sufficient to elicit a local spike following a train of synaptic inhibition. These data suggest that the plastic regulation of KA can provide a dynamic switch to unmask post-inhibitory spiking in CA1 pyramidal neurons, further increasing the signal processing power of the CA1 synaptic microcircuitry.
CA1 pyramidal neuron: schizophrenic behavior (Migliore et al. 2011)
NEURON files from the paper: A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior. by M. Migliore, I. De Blasi, D. Tegolo, R. Migliore, Neural Networks,(2011), doi:10.1016/j.neunet.2011.01.001. Starting from the experimentally supported assumption on hippocampal neurons we explore an experimentally testable prediction at the single neuron level. The model shows how and to what extent a pathological hypofunction of a contextdependent distal input on a CA1 neuron can generate hallucinations by altering the normal recall of objects on which the neuron has been previously tuned. The results suggest that a change in the context during the recall phase may cause an occasional but very significant change in the set of active dendrites used for features recognition, leading to a distorted perception of objects.
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 if you have any questions about the implementation of the model.
CA1 pyramidal neurons: binding properties and the magical number 7 (Migliore et al. 2008)
NEURON files from the paper: Single neuron binding properties and the magical number 7, by M. Migliore, G. Novara, D. Tegolo, Hippocampus, in press (2008). In an extensive series of simulations with realistic morphologies and active properties, we demonstrate how n radial (oblique) dendrites of these neurons may be used to bind n inputs to generate an output signal. The results suggest a possible neural code as the most effective n-ple of dendrites that can be used for short-term memory recollection of persons, objects, or places. Our analysis predicts a straightforward physiological explanation for the observed puzzling limit of about 7 short-term memory items that can be stored by humans.
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.
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 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: membrane response near rest (Hemond et al. 2009)
In this paper, the model was used to show how the temporal summation of excitatory inputs in CA3 pyramidal neurons was affected by the presence of Ih in the dendrites in a frequency- and distance-dependent fashion.
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)
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 (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.
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: 2 April 2004 Paul B Manis, Ph.D.
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.
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)
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."
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.
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 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."
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.
Dentate gyrus network model (Santhakumar et al 2005)
Mossy cell loss and mossy fiber sprouting are two characteristic consequences of repeated seizures and head trauma. However, their precise contributions to the hyperexcitable state are not well understood. Because it is difficult, and frequently impossible, to independently examine using experimental techniques whether it is the loss of mossy cells or the sprouting of mossy fibers that leads to dentate hyperexcitability, we built a biophysically realistic and anatomically representative computational model of the dentate gyrus to examine this question. The 527-cell model, containing granule, mossy, basket, and hilar cells with axonal projections to the perforant-path termination zone, showed that even weak mossy fiber sprouting (10-15% of the strong sprouting observed in the pilocarpine model of epilepsy) resulted in the spread of seizure-like activity to the adjacent model hippocampal laminae after focal stimulation of the perforant path. See reference for more and details.
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. ..."
Effects of synaptic location and timing on synaptic integration (Rall 1964)
Reproduces figures 5 - 8 from Rall, W. Theoretical significance of dendritic trees for neuronal input-output relations. In: Neural Theory and Modeling, ed. Reiss, R.F., Palo Alto: Stanford University Press (1964).
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. ..."
Excitatory synaptic interactions in pyramidal neuron dendrites (Behabadi et al. 2012)
" ... We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. ..."
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.
Gamma oscillations in hippocampal interneuron networks (Bartos et al 2002)
To examine whether an interneuron network with fast inhibitory synapses can act as a gamma frequency oscillator, we developed an interneuron network model based on experimentally determined properties. In comparison to previous interneuron network models, our model was able to generate oscillatory activity with higher coherence over a broad range of frequencies (20-110 Hz). In this model, high coherence and flexibility in frequency control emerge from the combination of synaptic properties, network structure, and electrical coupling.
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.
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.
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.
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."
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).
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.
MEC layer II stellate cell: Synaptic mechanisms of grid cells (Schmidt-Hieber & Hausser 2013)
This study investigates the cellular mechanisms of grid field generation in Medial Entorhinal Cortex (MEC) layer II stellate cells.
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."
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. ..."
NAcc medium spiny neuron: effects of cannabinoid withdrawal (Spiga et al. 2010)
Cannabinoid withdrawal produces a hypofunction of dopaminergic neurons targeting medium spiny neurons (MSN) of the forebrain. Administration of a CB1 receptor antagonist to control rats provoked structural abnormalities, reminiscent of those observed in withdrawal conditions and support the regulatory role of cannabinoids in neurogenesis, axonal growth and synaptogenesis. Experimental observations were incorporated into a realistic computational model which predicts a strong reduction in the excitability of morphologically-altered MSN, yielding a significant reduction in action potential output. These paper provided direct morphological evidence for functional abnormalities associated with cannabinoid dependence at the level of dopaminergic neurons and their post synaptic counterpart, supporting a hypodopaminergic state as a distinctive feature of the “addicted brain”.
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
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.
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.
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.
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. ..."
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
STDP and NMDAR Subunits (Gerkin et al. 2007)
The paper argues for competing roles of NR2A- and NR2B-containing NMDARs in spike-timing-dependent plasticity. This simple dynamical model recapitulates the results of STDP experiments involving selective blockers of NR2A- and NR2B-containing NMDARs, for which the stimuli are pre- and postsynaptic spikes in varying combinations. Experiments were done using paired recordings from glutamatergic neurons in rat hippocampal cultures. This model focuses on the dynamics of the putative potentiation and depression modules themselves, and their interaction For detailed dynamics involving NMDARs and Ca2+ transients, see Rubin et al., J. Neurophys., 2005.
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.
Synaptic integration of an identified nonspiking interneuron in crayfish (Takashima et al 2006)
This GENESIS simulation shows how a single or compound excitatory synaptic potential evoked by mechanosensory stimulation spreads over the dendrites of the LDS interneuron that is one of the identified nonspiking interneurons in the central nervous system of crayfish Procambarus clarkii. The model is based on physiological experiments carried out by Akira Takashima using single-electrode voltage clamp techniques and also 3-D morphometry of the interneuron carried out by Ryou Hikosaka using confocal laser scanning microscopic techniques. The physiological and morphological studies were coordinated by Masakazu Takahata.
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.
Thalamocortical augmenting response (Bazhenov et al 1998)
In the cortical model, augmenting responses were more powerful in the "input" layer compared with those in the "output" layer. Cortical stimulation of the network model produced augmenting responses in cortical neurons in distant cortical areas through corticothalamocortical loops and low-threshold intrathalamic augmentation. ... The predictions of the model were compared with in vivo recordings from neurons in cortical area 4 and thalamic ventrolateral nucleus of anesthetized cats. The known intrinsic properties of thalamic cells and thalamocortical interconnections can account for the basic properties of cortical augmenting responses. See reference for details. NEURON implementation note: cortical SU cells are getting slightly too little stimulation - reason unknown.
Using Strahler’s analysis to reduce realistic models (Marasco et al, 2013)
Building on our previous work (Marasco et al., (2012)), we present a general reduction method based on Strahler's analysis of neuron morphologies. We show that, without any fitting or tuning procedures, it is possible to map any morphologically and biophysically accurate neuron model into an equivalent reduced version. Using this method for Purkinje cells, we demonstrate how run times can be reduced up to 200-fold, while accurately taking into account the effects of arbitrarily located and activated synaptic inputs. Reference: Marasco A, Limongiello A, & Migliore M (2013), Using Strahler’s analysis to reduce up to 200-fold the run time of realistic neuron models, Sci. Rep. 3, 2934; DOI:10.1038/srep02934 in press.
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.

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