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| Models | Description |
| A Fast Rhythmic Bursting Cell: in vivo cell modeling (Lee 2007) | |
| One of the cellular mechanisms underlying the generation of gamma oscillations is a type of cortical pyramidal neuron named fast rhythmic bursting (FRB) cells. After cells from cats' primary visual cortices were filled with Neurobiotin, the brains were cut, and the cells were photographed. One FRB cell was chosen to be confocaled, reconstructed with Neurolucida software, and generated a detailed multi-compartmental model in the NEURON program. We explore firing properties of FRB cells and the role of enhanced Na+ conductance. | |
| A Model of Multiple Spike Initiation Zones in the Leech C-interneuron (Crisp 2009) | |
| The leech C-interneuron and its electrical synapse with the S-interneuron exhibit unusual properties: an asymmetric delay when impulses travel from one soma to the other, and graded C-interneuron impulse amplitudes under elevated divalent cation concentrations. These properties have been simulated using a SNNAP model in which the C-interneuron has multiple, independent spike initiation zones associated with individual electrical junctions with the C-interneuron. | |
| A fast model of voltage-dependent NMDA Receptors (Moradi et al. 2012) | |
| These are two or triple-exponential models of the voltage-dependent NMDA receptors. Conductance of these receptors increase voltage-dependently with a "Hodgkin and Huxley-type" gating style that is also depending on glutamate-binding. Time course of the gating of these receptors in response to glutamate are also changing voltage-dependently. Temperature sensitivity and desensitization of these receptor are also taken into account. Three previous kinetic models that are able to simulate the voltage-dependence of the NMDARs are also imported to the NMODL. These models are not temperature sensitive. These models are compatible with the "event delivery system" of NEURON. Parameters that are reported in our paper are applicable to CA1 pyramidal cell dendrites. | |
| A kinetic model unifying presynaptic short-term facilitation and depression (Lee et al. 2009) | |
| "... Here, we propose a unified theory of synaptic short-term plasticity based on realistic yet tractable and testable model descriptions of the underlying intracellular biochemical processes. Analysis of the model equations leads to a closed-form solution of the resonance frequency, a function of several critical biophysical parameters, as the single key indicator of the propensity for synaptic facilitation or depression under repetitive stimuli. This integrative model is supported by a broad range of transient and frequency response experimental data including those from facilitating, depressing or mixed-mode synapses. ... the model provides the reasons behind the switching behavior between facilitation and depression observed in experiments. ..." | |
| A model of unitary responses from A/C and PP synapses in CA3 pyramidal cells (Baker et al. 2010) | |
| The model was used to reproduce experimentally determined mean synaptic response characteristics of unitary AMPA and NMDA synaptic stimulations in CA3 pyramidal cells with the objective of inferring the most likely response properties of the corresponding types of synapses. The model is primarily concerned with passive cells, but models of active dendrites are included. | |
| A network model of the vertebrate retina (Publio et al. 2009) | |
| In this work, we use a minimal conductance-based model of the ON rod pathways in the vertebrate retina to study the effects of electrical synaptic coupling via gap junctions among rods and among AII amacrine cells on the dynamic range of the retina. The model is also used to study the effects of the maximum conductance of rod hyperpolarization activated current Ih on the dynamic range of the retina, allowing a study of the interrelations between this intrinsic membrane parameter with those two retina connectivity characteristics. | |
| 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. | |
| An attractor network model of grid cells and theta-nested gamma oscillations (Pastoll et al., 2013) | |
| A two population spiking continuous attractor model of grid cells. This model combines the attractor dynamics with theta-nested gamma oscillatory activity. It reproduces the behavioural response of grid cells (grid fields) in medial entorhinal cortex, while at the same time allowing for nested gamma oscillations of post-synaptic currents. | |
| Application of a common kinetic formalism for synaptic models (Destexhe et al 1994) | |
| Application to AMPA, NMDA, GABAA, and GABAB receptors is given in a book chapter. The reference paper synthesizes a comprehensive general description of synaptic transmission with Markov kinetic models. This framework is applicable to modeling ion channels, synaptic release, and all receptors. Please see the references for more details. A simple introduction to this method is given in a seperate paper Destexhe et al Neural Comput 6:14-18 , 1994). More information and papers at http://cns.iaf.cnrs-gif.fr/Main.html and through email: Destexhe@iaf.cnrs-gif.fr | |
| BCM-like synaptic plasticity with conductance-based models (Narayanan Johnston, 2010) | |
| " ... Although the BCM-like plasticity framework has been a useful formulation to understand synaptic plasticity and metaplasticity, a mechanism for the activity-dependent regulation of this modification threshold has remained an open question. In this simulation study based on CA1 pyramidal cells, we use a modification of the calcium-dependent hypothesis proposed elsewhere and show that a change in the hyperpolarization-activated, nonspecific-cation h current is capable of shifting the modification threshold. ..." | |
| 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. | |
| CA1 pyramidal neuron dendritic spine with plasticity (O`Donnell et al. 2011) | |
| Biophysical model of a dendritic spine and adjacent dendrite with synapse. Model parameters adjusted to fit CA3-CA1 Shaffer collateral synapse data from literature. Model includes both electrical and Ca2+ dynamics, including AMPARs, NMDARs, 4 types of CaV channel, and leak conductance. Spine and synapse are plastic according to Ca2+ dependent rule. The aim of the model is to explore the effects of dendritic spine structural plasticity on the rules of synaptic plasticity. | |
| CA1 pyramidal neuron: calculation of MRI signals (Cassara et al. 2008) | |
| NEURON mod files from the paper: Cassarà AM, Hagberg GE, Bianciardi M, Migliore M, Maraviglia B. Realistic simulations of neuronal activity: A contribution to the debate on direct detection of neuronal currents by MRI. Neuroimage. 39:87-106 (2008). In this paper, we use a detailed calculation of the magnetic field produced by the neuronal currents propagating over a hippocampal CA1 pyramidal neuron placed inside a cubic MR voxel of length 1.2 mm to estimate the Magnetic Resonance signal. | |
| CA1 pyramidal neuron: dendritic spike initiation (Gasparini et al 2004) | |
| NEURON mod files from the paper: Sonia Gasparini, Michele Migliore, and Jeffrey C. Magee On the initiation and propagation of dendritic spikes in CA1 pyramidal neurons, J. Neurosci., J. Neurosci. 24:11046-11056 (2004). | |
| CA1 pyramidal neuron: depolarization block (Bianchi et al. 2012) | |
| NEURON files from the paper: On the mechanisms underlying the depolarization block in the spiking dynamics of CA1 pyramidal neurons by D.Bianchi, A. Marasco, A.Limongiello, C.Marchetti, H.Marie,B.Tirozzi, M.Migliore (2012). J Comput. Neurosci. In press. DOI: 10.1007/s10827-012-0383-y. Experimental findings shown that under sustained input current of increasing strength neurons eventually stop firing, entering a depolarization block. We analyze the spiking dynamics of CA1 pyramidal neuron models using the same set of ionic currents on both an accurate morphological reconstruction and on its reduction to a single-compartment. The results show the specic ion channel properties and kinetics that are needed to reproduce the experimental findings, and how their interplay can drastically modulate the neuronal dynamics and the input current range leading to depolarization block. | |
| CA1 pyramidal neuron: integration of subthreshold inputs from PP and SC (Migliore 2003) | |
| The model shows how the experimentally observed increase in the dendritic density of Ih and IA could have a major role in constraining the temporal integration window for the main CA1 synaptic inputs. | |
| 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: signal propagation in oblique dendrites (Migliore et al 2005) | |
| NEURON mod files from the paper: M. Migliore, M. Ferrante, GA Ascoli (2005). The model shows how the back- and forward propagation of action potentials in the oblique dendrites of CA1 neurons could be modulated by local properties such as morphology or active conductances. | |
| 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 (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. | |
| Calyx of Held, short term plasticity (Yang Z et al. 2009) | |
| This model investigates mechanisms contributing to short term plasticity at the calyx of Held, a giant glutamatergic synapse in the mammalian brainstem auditory system. It is a stochastic version of the model described in: Hennig, M., Postlethwaite, M., Forsythe, I.D. and Graham, B.P. (2007). A biophysical model of short-term plasticity at the calyx of Held. Neurocomputing, 70:1626-1629. This version introduces stochastic vesicle recycling and release. It has been used to investigate the information transmission properties of this synapse, as detailed in: Yang, Z., Hennig, M., Postlethwaite, M., Forsythe, I.D. and Graham, B.P. (2008). Wide-band information transmission at the calyx of Held. Neural Computation, 21(4):991-1018. | |
| 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. | |
| Coding of stimulus frequency by latency in thalamic networks (Golomb et al 2005) | |
| The paper presents models of the rat vibrissa processing system including the posterior medial (POm) thalamus, ventroposterior medial (VPm) thalamus, and GABAB- mediated feedback inhibition from the reticular thalamic (Rt) nucleus. A clear match between the experimentally measured spike-rates and the numerically calculated rates for the full model occurs when VPm thalamus receives stronger brainstem input and weaker GABAB-mediated inhibition than POm thalamus. | |
| 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) | |
| 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 signals command firing dynamics in a Cerebellar Purkinje Cell model (Genet et al. 2010) | |
| This model endows the dendrites of a reconstructed Purkinje cells (PC) with the mechanism of Ca-dependent plateau potentials and spikes described in Genet, S., and B. Delord. 2002. A biophysical model of nonlinear dynamics underlying plateau potentials and calcium spikes in Purkinje cell dendrites. J. Neurophysiol. 88:2430–2444). It is a part of a comprehensive mathematical study suggesting that active electric signals in the dendrites of PC command epochs of firing and silencing of the PC soma. | |
| Dentate Gyrus Feed-forward inhibition (Ferrante et al. 2009) | |
| In this paper, the model was used to show how that FFI can change a steeply sigmoidal input-output (I/O) curve into a double-sigmoid typical of buffer systems. | |
| Dentate gyrus granule cell: 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. | |
| Duration-tuned neurons from the inferior colliculus of the big brown bat (Aubie et al. 2009) | |
| dtnet is a generalized neural network simulator written in C++ with an easy to use XML description language to generate arbitrary neural networks and then run simulations covering many different parameter values. For example, you can specify ranges of parameter values for several different connection weights and then automatically run simulations over all possible parameters. Graphing ability is built in as long as the free, open-source, graphing application GLE (http://glx.sourceforge.net/) is installed. Included in the examples folder are simulation descriptions that were used to generate the results in Aubie et al. (2009). Refer to the README file for instructions on compiling and running these examples. The most recent source code can be obtained from GitHub: https://github.com/baubie/dtnet | |
| Duration-tuned neurons from the inferior colliculus of vertebrates (Aubie et al. 2012) | |
| These models reproduce the responses of duration-tuned neurons in the auditory midbrain of the big brown bat, the rat, the mouse and the frog (Aubie et al. 2012). They are written in the Python interface to NEURON and a subset of the figures from Aubie et al. (2012) are pre-set in run.py (raw data is generated and a separate graphing program must be used to visualize the results). | |
| Dynamic dopamine modulation in the basal ganglia: Learning in Parkinson (Frank et al 2004,2005) | |
| See README file for all info on how to run models under different tasks and simulated Parkinson's and medication conditions. | |
| Efficient Method for Computing Synaptic Conductance (Destexhe et al 1994) | |
| A simple model of transmitter release is used to solve first order kinetic equations of neurotransmiter/receptor binding. This method is applied to a glutamate and gabaa receptor. See reference for more details. The method is extended to more complex kinetic schemes in a seperate paper (Destexhe et al J Comp Neuro 1:195-231, 1994). Application to AMPA, NMDA, GABAA, and GABAB receptors is given in a book chapter (Destexhe et al In: The Neurobiology of Computation, Edited by Bower, J., Kluwer Academic Press, Norwell MA, 1995, pp. 9-14.) More information and papers at http://cns.iaf.cnrs-gif.fr/Main.html and through email: Destexhe@iaf.cnrs-gif.fr | |
| Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011) | |
| "Coordination of neocortical oscillations has been hypothesized to underlie the “binding” essential to cognitive function. However, the mechanisms that generate neocortical oscillations in physiological frequency bands remain unknown. We hypothesized that interlaminar relations in neocortex would provide multiple intermediate loops that would play particular roles in generating oscillations, adding different dynamics to the network. We simulated networks from sensory neocortex using 9 columns of event-driven rule-based neurons wired according to anatomical data and driven with random white-noise synaptic inputs. ..." | |
| Emergent properties of networks of biological signaling pathways (Bhalla, Iyengar 1999) | |
| Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways. | |
| Epilepsy may be caused by very small functional changes in ion channels (Thomas et al. 2009) | |
| We used a previously published model of the dentate gyrus with varying degrees of mossy fibre sprouting.We preformed a sensitivity analysis where we systematically varied individual properties of ion channels. The results predict that genetic variations in the properties of sodium channels are likely to have the biggest impact on network excitability. Furthermore, these changes may be as small as 1mV, which is currently undetectable using standard experimental practices. | |
| Fast AMPA receptor signaling (Geiger et al 1997) | |
| Glutamatergic transmission at a principal neuron-interneuron synapse was investigated by dual whole-cell patch-clamp recording in rat hippocampal slices combined with morphological analysis and modeling. Simulations based on a compartmental model of the interneuron indicated that the rapid postsynaptic conductance change determines the shape and the somatodendritic integration of EPSPs, thus enabling interneurons to detect synchronous principal neuron activity. | |
| Frog second-order vestibular neuron models (Rössert et al. 2011) | |
| This implements spiking Hodgkin-Huxley type models of tonic and phasic second-order vestibular neurons. Models fitted to intracellular spike and membrane potential recordings from frog (Rana temporaria). The models can be stimulated by intracellular step current, frequency current (ZAP) or synaptic stimulation. | |
| Functional impact of dendritic branch point morphology (Ferrante et al., 2013) | |
| " ... Here, we first quantified the morphological variability of branch points from two-photon images of rat CA1 pyramidal neurons. We then investigated the geometrical features affecting spike initiation, propagation, and timing with a computational model validated by glutamate uncaging experiments. The results suggest that even subtle membrane readjustments at branch point could drastically alter the ability of synaptic input to generate, propagate, and time action potentials." | |
| Gap junction coupled network of striatal fast spiking interneurons (Hjorth et al. 2009) | |
| Gap junctions between striatal FS neurons has very weak ability to synchronise spiking. Input uncorrelated between neighbouring neurons is shunted, while correlated input is not. | |
| 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. | |
| 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. | |
| Glutamate diffusion and AMPA receptor activation in the cerebellar glomerulus (Saftenku 2005) | |
| Synaptic conductances are influenced markedly by the geometry of the space surrounding the synapse since the transient glutamate concentration in the synaptic cleft is determined by this geometry. Our paper is an attempt to understand the reasons for slow glutamate diffusion in the cerebellar glomerulus, a structure situated around the enlarged mossy fiber terminal in the cerebellum and surrounded by a glial sheath. ... Our results suggest at least a 7- to 10-fold lower apparent diffusion coefficient of glutamate in the porous medium of the glomerulus than in water. ... See paper for details and more. | |
| Homosynaptic plasticity in the tail withdrawal circuit (TWC) of Aplysia (Baxter and Byrne 2006) | |
| The tail-withdrawal circuit of Aplysia provides a useful model system for investigating synaptic dynamics. Sensory neurons within the circuit manifest several forms of synaptic plasticity. Here, we developed a model of the circuit and investigated the ways in which depression (DEP) and potentiation (POT) contributed to information processing. DEP limited the amount of motor neuron activity that could be elicited by the monosynaptic pathway alone. POT within the monosynaptic pathway did not compensate for DEP. There was, however, a synergistic interaction between POT and the polysynaptic pathway. This synergism extended the dynamic range of the network, and the interplay between DEP and POT made the circuit respond preferentially to long-duration, low-frequency inputs. | |
| Impact of dendritic atrophy on intrinsic and synaptic excitability (Narayanan & Chattarji, 2010) | |
| These simulations examined the atrophy induced changes in electrophysiological properties of CA3 pyramidal neurons. We found these neurons change from bursting to regular spiking as atrophy increases. Region-specific atrophy induced region-specific increases in synaptic excitability in a passive dendritic tree. All dendritic compartments of an atrophied neuron had greater synaptic excitability and a larger voltage transfer to the soma than the control neuron. | |
| 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. | |
| KInNeSS : a modular framework for computational neuroscience (Versace et al. 2008) | |
| The xml files provided here implement a network of excitatory and inhibitory spiking neurons, governed by either Hodgkin-Huxley or quadratic integrate-and-fire dynamical equations. The code is used to demonstrate the capabilities of the KInNeSS software package for simulation of networks of spiking neurons. The simulation protocol used here is meant to facilitate the comparison of KInNeSS with other simulators reviewed in Brette et al. (2007). See the associated paper "Versace et al. (2008) KInNeSS : a modular framework for computational neuroscience." for an extensive description of KInNeSS . | |
| Ketamine disrupts theta modulation of gamma in a computer model of hippocampus (Neymotin et al 2011) | |
| "Abnormalities in oscillations have been suggested to play a role in schizophrenia. We studied theta-modulated gamma oscillations in a computer model of hippocampal CA3 in vivo with and without simulated application of ketamine, an NMDA receptor antagonist and psychotomimetic. Networks of 1200 multi-compartment neurons (pyramidal, basket and oriens-lacunosum moleculare, OLM, cells) generated theta and gamma oscillations from intrinsic network dynamics: basket cells primarily generated gamma and amplified theta, while OLM cells strongly contributed to theta. ..." | |
| Kinetic NMDA receptor model (Kampa et al 2004) | |
| This kinetic NMDA receptor model is based on voltage-clamp recordings of NMDA receptor-mediated currents in nucleated patches of rat neocortical layer 5 pyramidal neurons (Kampa et al 2004 J Physiol), this model was fit with AxoGraph directly to experimental recordings in order to obtain the optimal values for the parameters. The demo shows the behaviour of a kinetic NMDA receptor model reproducing the data in figure 2. The NMDA receptor model uses realistic rates of magnesium block and its effects on channel desensitisation. Presynaptic transmitter release is necessary for glutamate binding to the receptor. This model was written by Bjoern Kampa, Canberra, 2004. | |
| Kinetic synaptic models applicable to building networks (Destexhe et al 1998) | |
| Simplified AMPA, NMDA, GABAA, and GABAB receptor models useful for building networks are described in a book chapter. One reference paper synthesizes a comprehensive general description of synaptic transmission with Markov kinetic models which is applicable to modeling ion channels, synaptic release, and all receptors. Also a simple introduction to this method is given in a seperate paper Destexhe et al Neural Comput 6:14-18 , 1994). More information and papers at http://cns.iaf.cnrs-gif.fr/Main.html and through email: Destexhe@iaf.cnrs-gif.fr | |
| 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). | |
| Layer V PFC pyramidal neuron used to study persistent activity (Sidiropoulou & Poirazi 2012) | |
| "... Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. ... Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression. " | |
| 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). | |
| MEG of Somatosensory Neocortex (Jones et al. 2007) | |
| "... To make a direct and principled connection between the SI (somatosensory primary neocortex magnetoencephalography) waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. ... our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception." | |
| Modeling temperature changes in AMPAR kinetics (Postlethwaite et al 2007) | |
| This model was used to simulate glutamatergic, AMPA receptor mediated mEPSCs (miniature EPSCs, resulting from spontaneous vesicular transmitter release) at the calyx of Held synapse. It was used to assess the influence of temperature (physiological vs. subphysiological) on the amplitude and time course of mEPSCs. In the related paper, simulation results were directly compared to the experimental data, and it was concluded that an increase of temperature accelerates AMPA receptor kinetics. | |
| Multiple mechanisms of short term plasticity at the calyx of Held (Hennig et al. 2008) | |
| This is a new model of the short-term dynamics of glutamatergic synaptic transmission, which incorporates multiple mechanisms acting at differing sites and across a range of different time scales (ms to tens of seconds). In the paper, we show that this model can accurately reproduce the experimentally measured time-course of short term depression across different stimulus frequencies at the calyx of Held. The model demonstrates how multiple forms of activity-dependent modulation of release probability and vesicle pool depletion interact, and shows how stimulus-history-dependent recovery from synaptic depression can arise from dynamics on multiple time scales. | |
| 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”. | |
| NMDA receptor saturation (Chen et al 2001) | |
| Experiments and modeling reported in the paper Chen N, Ren J, Raymond LA, and Murphy T (2001) support the hypothesis that glutamate has a relatively lower potency at NMDARs than previously thought from agonist application under equilibrium conditions. Further information and reprint requests are available from Dr T.H. Murphy thmurphy@interchange.ubc.ca | |
| Na channel mutations in the dentate gyrus (Thomas et al. 2009) | |
| These are source files to generate the data in Figure 6 from "Mossy fiber sprouting interacts with sodium channel mutations to increase dentate gyrus excitability" Thomas EA, Reid CA, Petrou S, Epilepsia (2009) | |
| 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 | |
| Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009) | |
| The Parker-Sochacki method is a new technique for the numerical integration of differential equations applicable to many neuronal models. Using this method, the solution order can be adapted according to the local conditions at each time step, enabling adaptive error control without changing the integration timestep. We apply the Parker-Sochacki method to the Izhikevich ‘simple’ model and a Hodgkin-Huxley type neuron, comparing the results with those obtained using the Runge-Kutta and Bulirsch-Stoer methods. | |
| Olfactory Bulb Network (Davison et al 2003) | |
| A biologically-detailed model of the mammalian olfactory bulb, incorporating the mitral and granule cells and the dendrodendritic synapses between them. The results of simulation experiments with electrical stimulation agree closely in most details with published experimental data. The model predicts that the time course of dendrodendritic inhibition is dependent on the network connectivity as well as on the intrinsic parameters of the synapses. In response to simulated odor stimulation, strongly activated mitral cells tend to suppress neighboring cells, the mitral cells readily synchronize their firing, and increasing the stimulus intensity increases the degree of synchronization. For more details, see the reference below. | |
| Olfactory bulb granule cell: effects of odor deprivation (Saghatelyan et al 2005) | |
| The model supports the experimental findings on the effects of postnatal odor deprivation, and shows that a -10mV shift in the Na activation or a reduction in the dendritic length of newborn GC could independently explain the observed increase in excitability. | |
| Olfactory bulb mitral and granule cell column formation (Migliore et al. 2007) | |
| In the olfactory bulb, the processing units for odor discrimination are believed to involve dendrodendritic synaptic interactions between mitral and granule cells. There is increasing anatomical evidence that these cells are organized in columns, and that the columns processing a given odor are arranged in widely distributed arrays. Experimental evidence is lacking on the underlying learning mechanisms for how these columns and arrays are formed. We have used a simplified realistic circuit model to test the hypothesis that distributed connectivity can self-organize through an activity-dependent dendrodendritic synaptic mechanism. The results point to action potentials propagating in the mitral cell lateral dendrites as playing a critical role in this mechanism, and suggest a novel and robust learning mechanism for the development of distributed processing units in a cortical structure. | |
| Olfactory bulb mitral and granule cell: dendrodendritic microcircuits (Migliore and Shepherd 2008) | |
| This model shows how backpropagating action potentials in the long lateral dendrites of mitral cells, together with granule cell actions on mitral cells within narrow columns forming glomerular units, can provide a mechanism to activate strong local inhibition between arbitrarily distant mitral cells. The simulations predict a new role for the dendrodendritic synapses in the multicolumnar organization of the granule cells. | |
| Optimal deep brain stimulation of the subthalamic nucleus-a computational study (Feng et al. 2007) | |
| Here, we use a biophysically-based model of spiking cells in the basal ganglia (Terman et al., Journal of Neuroscience, 22, 2963-2976, 2002; Rubin and Terman, Journal of Computational Neuroscience, 16, 211-235, 2004) to provide computational evidence that alternative temporal patterns of DBS inputs might be equally effective as the standard high-frequency waveforms, but require lower amplitudes. Within this model, DBS performance is assessed in two ways. First, we determine the extent to which DBS causes Gpi (globus pallidus pars interna) synaptic outputs, which are burstlike and synchronized in the unstimulated Parkinsonian state, to cease their pathological modulation of simulated thalamocortical cells. Second, we evaluate how DBS affects the GPi cells' auto- and cross-correlograms. | |
| Parametric computation and persistent gamma in a cortical model (Chambers et al. 2012) | |
| Using the Traub et al (2005) model of the cortex we determined how 33 synaptic strength parameters control gamma oscillations. We used fractional factorial design to reduce the number of runs required to 4096. We found an expected multiplicative interaction between parameters. | |
| 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. | |
| Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012) | |
| This model is an extension of a model (138379) recently published in Frontiers in Computational Neuroscience. This model consists of 4700 event-driven, rule-based neurons, wired according to anatomical data, and driven by both white-noise synaptic inputs and a sensory signal recorded from a rat thalamus. Its purpose is to explore the effects of cortical damage, along with the repair of this damage via a neuroprosthesis. | |
| Rapid desynchronization of an electrically coupled Golgi cell network (Vervaeke et al. 2010) | |
| Electrical synapses between interneurons contribute to synchronized firing and network oscillations in the brain. However, little is known about how such networks respond to excitatory synaptic input. In addition to detailed electrophysiological recordings and histological investigations of electrically coupled Golgi cells in the cerebellum, a detailed network model of these cells was created. The cell models are based on reconstructed Golgi cell morphologies and the active conductances are taken from an earlier abstract Golgi cell model (Solinas et al 2007, accession no. 112685). Our results show that gap junction coupling can sometimes be inhibitory and either promote network synchronization or trigger rapid network desynchronization depending on the synaptic input. The model is available as a neuroConstruct project and can executable scripts can be generated for the NEURON simulator. | |
| Reinforcement learning of targeted movement (Chadderdon et al. 2012) | |
| Respiratory central pattern generator network in mammalian brainstem (Rubin et al. 2009) | |
| This model is a reduced version of a spatially organized respiratory central pattern generation network consisting of four neuronal populations (pre-I, early-I, post-I, and aug-E). In this reduction, each population is represented by a single neuron, in an activity-based framework (which includes the persistent sodium current for the pre-I population). The model includes three sources of external drive and can produce several experimentally observed rhythms. | |
| Ribbon Synapse (Sikora et al 2005) | |
| A model of the ribbon synapse was developed to replicate both pre- and postsynaptic functions of this glutamatergic juncture. The presynaptic portion of the model is rich in anatomical and physiological detail and includes multiple release sites for each ribbon based on anatomical studies of presynaptic terminals, presynaptic voltage at the terminal, the activation of voltage-gated calcium channels and a calcium-dependent release mechanism whose rate varies as a function of the calcium concentration that is monitored at two different sites which control both an ultrafast, docked pool of vesicles and a release ready pool of tethered vesicles. See paper for more and details. | |
| Roles of essential kinases in induction of late hippocampal LTP (Smolen et al., 2006) | |
| "… Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. …" | |
| Roles of subthalamic nucleus and DBS in reinforcement conflict-based decision making (Frank 2006) | |
| Deep brain stimulation (DBS) of the subthalamic nucleus dramatically improves the motor symptoms of Parkinson's disease, but causes cognitive side effects such as impulsivity. This model from Frank (2006) simulates the role of the subthalamic nucleus (STN) within the basal ganglia circuitry in decision making. The STN dynamically modulates network decision thresholds in proportion to decision conflict. The STN ``hold your horses'' signal adaptively allows the system more time to settle on the best choice when multiple options are valid. The model also replicates effects in Parkinson's patients on and off DBS in experiments designed to test the model (Frank et al, 2007). | |
| 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). | |
| Short term plasticity at the cerebellar granule cell (Nieus et al. 2006) | |
| The model reproduces short term plasticity of the mossy fibre to granule cell synapse. To reproduce synaptic currents recorded in experiments, a model of presynaptic release was used to determine the concentration of glutamate in the synaptic cleft that ultimately determined a synaptic response. The parameters of facilitation and depression were determined deconvolving AMPA EPSCs. | |
| Short term plasticity of synapses onto V1 layer 2/3 pyramidal neuron (Varela et al 1997) | |
| This archive contains 3 mod files for NEURON that implement the short term synaptic plasticity model described in Varela, J.A., Sen, K., Gibson, J., Fost, J., Abbott, L.R., and Nelson, S.B.. A quantitative description of short-term plasticity at excitatory synapses in layer 2/3 of rat primary visual cortex. Journal of Neuroscience 17:7926-7940, 1997. Contact ted.carnevale@yale.edu if you have questions about this implementation of the model. | |
| Spike timing detection in different forms of LTD (Doi et al 2005) | |
| To understand the spike-timing detection mechanisms in cerebellar long-term depression (LTD), we developed a kinetic model of Ca dynamics within a Purkinje dendritic spine. In our kinetic simulation, IP3 was first produced via the metabotropic pathway of parallel fiber (PF) inputs, and the Ca influx in response to the climbing fiber (CF) input triggered regenerative Ca-induced Ca release from the internal stores via the IP3 receptors activated by the increased IP3. The delay in IP3 increase caused by the PF metabotropic pathway generated the optimal PF–CF interval. The Ca dynamics revealed a threshold for large Ca2 release that decreased as IP3 increased, and it coherently explained the different forms of LTD. See paper for more and details. | |
| 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 | |
| Spiking neuron model of the basal ganglia (Humphries et al 2006) | |
| A spiking neuron model of the basal ganglia (BG) circuit (striatum, STN, GP, SNr). Includes: parallel anatomical channels; tonic dopamine; dopamine receptors in striatum, STN, and GP; burst-firing in STN; GABAa, AMPA, and NMDA currents; effects of synaptic location. Model demonstrates selection and switching of input signals. Replicates experimental data on changes in slow-wave (<1 Hz) and gamma-band oscillations within BG nuclei following lesions and pharmacological manipulations. | |
| Spine neck plasticity controls postsynaptic calcium signals (Grunditz et al. 2008) | |
| This model was set up to dissect the relative contribution of different channels to the spine calcium transients measured at single spines. | |
| State dependent drug binding to sodium channels in the dentate gyrus (Thomas & Petrou 2013) | |
| A Markov model of sodium channels was developed that includes drug binding to fast inactivated states. This was incorporated into a model of the dentate gyrus to investigate the effects of anti-epileptic drugs on neuron and network properties. | |
| Striatal GABAergic microcircuit, dopamine-modulated cell assemblies (Humphries et al. 2009) | |
| To begin identifying potential dynamically-defined computational elements within the striatum, we constructed a new three-dimensional model of the striatal microcircuit's connectivity, and instantiated this with our dopamine-modulated neuron models of the MSNs and FSIs. A new model of gap junctions between the FSIs was introduced and tuned to experimental data. We introduced a novel multiple spike-train analysis method, and apply this to the outputs of the model to find groups of synchronised neurons at multiple time-scales. We found that, with realistic in vivo background input, small assemblies of synchronised MSNs spontaneously appeared, consistent with experimental observations, and that the number of assemblies and the time-scale of synchronisation was strongly dependent on the simulated concentration of dopamine. We also showed that feed-forward inhibition from the FSIs counter-intuitively increases the firing rate of the MSNs. | |
| Striatal GABAergic microcircuit, spatial scales of dynamics (Humphries et al, 2010) | |
| The main thrust of this paper was the development of the 3D anatomical network of the striatum's GABAergic microcircuit. We grew dendrite and axon models for the MSNs and FSIs and extracted probabilities for the presence of these neurites as a function of distance from the soma. From these, we found the probabilities of intersection between the neurites of two neurons given their inter-somatic distance, and used these to construct three-dimensional striatal networks. These networks were examined for their predictions for the distributions of the numbers and distances of connections for all the connections in the microcircuit. We then combined the neuron models from a previous model (Humphries et al, 2009; ModelDB ID: 128874) with the new anatomical model. We used this new complete striatal model to examine the impact of the anatomical network on the firing properties of the MSN and FSI populations, and to study the influence of all the inputs to one MSN within the network. | |
| Surround Suppression in V1 via Withdraw of Balanced Local Excitation in V1 (Shushruth 2012) | |
| The model is mean-field network models, which is set up as a so-called ring-model, i. e. it is a highly idealized model of an orientation hypercolumn in primary visual cortex. Long-range intra-areal and inter-areal feedback connections are modeled phenomenologically as an external input. In this model, there are recurrent interactions via short-range local connections between orientation columns, but not between hypercolumns. | |
| 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 plasticity: pyramid->pyr and pyr->interneuron (Tsodyks et al 1998) | |
| An implementation of a model of short-term synaptic plasticity with NEURON. The model was originally described by Tsodyks et al., who assumed that the synapse acted as a current source, but this implementation treats it as a conductance change. Tsodyks, M., Pawelzik, K., Markram, H. Neural networks with dynamic synapses. Neural Computation 10:821-835, 1998. Tsodyks, M., Uziel, A., Markram, H. Synchrony generation in recurrent networks with frequency-dependent synapses. J. Neurosci. 2000 RC50. | |
| Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013) | |
| Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered. | |
| Synaptic transmission at the calyx of Held (Graham et al 2001) | |
| This model allows the user to investigate faciliation and depression in a complex Monte Carlo model of the calyx of Held, a giant synapse in the mammalian auditory system (Graham et al, 2001) | |
| Synthesis of spatial tuning functions from theta cell spike trains (Welday et al., 2011) | |
| A single compartment model reproduces the firing rate maps of place, grid, and boundary cells by receiving inhibitory inputs from theta cells. The theta cell spike trains are modulated by the rat's movement velocity in such a way that phase interference among their burst pattern creates spatial envelope function which simulate the firing rate maps. | |
| Thalamic neuron, zebra finch DLM: Integration of pallidal and cortical inputs (Goldberg et al. 2012) | |
| This is a single-compartment model of a zebra finch thalamic relay neuron from nucleus DLM. It is used to explore the interaction between cortex-like glutamatergic input and pallidum-like GABAergic input as they control the spiking output of these neurons. | |
| Thalamic quiescence of spike and wave seizures (Lytton et al 1997) | |
| A phase plane analysis of a two cell interaction between a thalamocortical neuron (TC) and a thalamic reticularis neuron (RE). | |
| 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. | |
| Theta phase precession in a model CA3 place cell (Baker and Olds 2007) | |
| "... The present study concerns a neurobiologically based computational model of the emergence of theta phase precession in which the responses of a single model CA3 pyramidal cell are examined in the context of stimulation by realistic afferent spike trains including those of place cells in entorhinal cortex, dentate gyrus, and other CA3 pyramidal cells. Spike-timing dependent plasticity in the model CA3 pyramidal cell leads to a spatially correlated associational synaptic drive that subsequently creates a spatially asymmetric expansion of the model cell’s place field. ... Through selective manipulations of the model it is possible to decompose theta phase precession in CA3 into the separate contributing factors of inheritance from upstream afferents in the dentate gyrus and entorhinal cortex, the interaction of synaptically controlled increasing afferent drive with phasic inhibition, and the theta phase difference between dentate gyrus granule cell and CA3 pyramidal cell activity." | |
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