Epileptic seizure model with Morris-Lecar neurons (Beverlin and Netoff 2011)

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Accession:144010
Here we use phase-response curves (PRC) from Morris-Lecar (M-L) model neurons with synaptic depression and gradually decrease input current to cells within a network simulation. This method effectively decreases firing rates resulting in a shift to greater network synchrony illustrating a possible mechanism of the transition phenomenon. PRCs are measured from the M-L conductance based model cell with a range of input currents within the limit cycle. A large network of 3000 excitatory neurons is simulated with a network topology generated from second-order statistics which allows a range of population synchrony. The population synchrony of the oscillating cells is measured with the Kuramoto order parameter, which reveals a transition from tonic to clonic phase exhibited by our model network.
Reference:
1 . Beverlin B, Kakalios J, Nykamp D, Netoff TI (2011) Dynamical changes in neurons during seizures determine tonic to clonic shift. J Comput Neurosci [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Hodgkin-Huxley neuron; Abstract Morris-Lecar neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Epilepsy;
Implementer(s): Beverlin, Bryce ;
This is the readme for the code for the paper:

Beverlin B, Kakalios J, Nykamp D, Netoff TI (2011) Dynamical changes
in neurons during seizures determine tonic to clonic shift. J Comput
Neurosci

These files are from B Beverlin.

Usage:

Included is the code for running the Tonic-clonic simulation
(ML_depress_sim.m) and the code for running the many network
simulations (ML_Net_Sweep.m). In addition, the user will need the
derivative file (ML_derivs.m).