ModelDB: Hodgkin-Huxley models of different classes of cortical neurons (Pospischil et al. 2008)

Hodgkin-Huxley models of different classes of cortical neurons (Pospischil et al. 2008)

Accession: 123623

"We review here the development of Hodgkin– Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are “fast spiking”, “regular spiking”, “intrinsically bursting” and “low-threshold spike” cells. For each class, we fit “minimal” HH type models to experimental data. ..."
Reference: Pospischil M, Toledo-Rodriguez M, Monier C, Piwkowska Z, Bal T, Fregnac Y, Markram, Destexhe (2008) Minimal Hodgkin-Huxley type models for different classes of cortical and thalamic neurons. Biol Cybern 99:427-41 [PubMed]

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Model Information (Click on a link to find other models with that property)

Model Type:	Neuron or other electrically excitable cell; Channel;
Brain Region(s)/Organism:	Neocortex;
Cell Type(s):	Neocortical pyramidal neuron: deep; Neocortical pyramidal neuron: superficial; Neocortical Fast Spiking (FS) interneuron; Neocortical Regular Spiking (RS) neuron; Neocortical Low Threshold Spiking (LTS) neuron;
Channel(s):	I Na,t; I L high threshold; I T low threshold; I K; I M;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:	Neuron;
Model Concept(s):	Parameter Fitting; Simplified Models;
Implementer(s):	Destexhe, Alain [Destexhe at iaf.cnrs-gif.fr];

Search NeuronDB for information about: Neocortical pyramidal neuron: deep; Neocortical pyramidal neuron: superficial; I Na,t; I L high threshold; I T low threshold; I K; I M;

Model files

Help downloading and running models Versions

Simulation of single-compartment Hodgkin-Huxley models for different
classes of cortical neurons

The models are described in:

   Pospischil, M., Toledo-Rodriguez, M., Monier, C., Piwkowska, Z., 
   Bal, T., Fregnac, Y., Markram, H. and Destexhe, A.
   Minimal Hodgkin-Huxley type models for different classes of
   cortical and thalamic neurons.
   Biological Cybernetics 99: 427-441, 2008.

Intrinsic currents: INa, IKd for action potentials, IM for
spike-frequency adaptation, ICaL for high-threshold calcium current,
ICaT for the low-threshold calcium current, intracellular calcium
dynamics.  

demo_PY_RS.oc : simplified model of the "regular-spiking" neuron
demo_IN_FS.oc : simplified model of the "fast-spiking" interneuron
demo_PY_IB.oc : simplified model of the "intrinsically bursting" neuron
demo_PY_IBR.oc : simplified model of the "repetive bursting" neuron
demo_PY_LTS.oc : simplified model of the "low-threshold spike" neurons

Usage:
------

Simply auto-launch from ModelDB (after NEURON is installed) or
download and extract the archive.  Then under

linux/unix:
-----------

cd to the extracted folder.  Type at the shell prompt:

nrnivmodl
nrngui mosinit.hoc

MAC OS X:
---------

Drag and drop the extracted folder onto the mknrndll icon.  Drag and
drop the mosinit.hoc file onto the nrngui icon.

mswin:
------

Run mknrndll and cd to the extracted folder. Select to make the
nrnmech.dll.  Use windows explorer to view the contents of the
expanded folder from the archive. Double click on the mosinit.hoc
file.

Once the simulation is started:
-------------------------------

Click on a button to select a cell.  Reposition the windows and press
the Init & Run button.

For example selecting Bursting Pyramidal Cell and then Init & Run
should produce a figure like figure 5B from the paper:



20111102 The file IL_gutnick.mod was updated to use derivimplicit in the
solver.  See http://www.neuron.yale.edu/phpBB/viewtopic.php?f=28&t=592
for details.

20120216 the files IM_cortex.mod, IT_huguenard.mod, and
cadecay_destexhe.mod had solver methods updated from euler to cnexp,
cnexp, and derivimplicit respectively.  The IL_gutnick.mod was changed
from derivimplicit to cnexp. See www.neuron.yale.edu phpBB link above.

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