Mean-field systems and small scale neural networks (Ferguson et al. 2015)

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Accession:184140
We explore adaptation induced bursting as a mechanism for theta oscillations in hippocampal area CA1. To do this, we have developed a mean-field system for a network of fitted Izhikevich neurons with sparse coupling and heterogeneity. The code contained here runs the mean-field system pointwise or on a two-parameter mesh, in addition to networks of neurons that are smaller then those considered in the paper. The file README.pdf contains instructions on use. Note that the following file (peakfinder): http://www.mathworks.com/matlabcentral/fileexchange/25500-peakfinder-x0--sel--thresh--extrema--includeendpoints--interpolate- is required to compute burst frequencies in the mean-field system and must be downloaded and placed in the same root folder as MFSIMULATOR.mat
Reference:
1 . Ferguson KA, Njap F, Nicola W, Skinner FK, Campbell SA (2015) Examining the limits of cellular adaptation bursting mechanisms in biologically-based excitatory networks of the hippocampus. J Comput Neurosci 39:289-309 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Abstract Izhikevich neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Bursting;
Implementer(s): Nicola, Wilten [wnicola at uwaterloo.ca]; 
This is the readme for the archive associated with running the
mean-field systems and small scale networks in this archive associated
with this paper:

Ferguson KA, Njap F, Nicola W, Skinner FK, Campbell SA (2015)
Examining the limits of cellular adaptation bursting mechanisms in
biologically-based excitatory networks of the hippocampus. J Comput
Neurosci [PubMed]

Please see the README.pdf in this archive for detailed instructions.

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