Maximum entropy model to predict spatiotemporal spike patterns (Marre et al. 2009)

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This MATLAB code implements a model-based analysis of spike trains. The analysis predicts the occurrence of spatio-temporal patterns of spikes in the data, and is based on a maximum entropy principle by including both spatial and temporal correlations. The approach is applicable to unit recordings from any region of the brain. The code is based on Marre, et al., 2009. The MATLAB code was written by Sami El Boustani and Olivier Marre.
1 . Marre O, El Boustani S, Fregnac Y, Destexhe A (2009) Prediction of spatiotemporal patterns of neural activity from pairwise correlations. Phys Rev Lett 102:138101 [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: Neocortex;
Cell Type(s):
Gap Junctions:
Simulation Environment: MATLAB;
Model Concept(s): Maximum entropy models;
Implementer(s): El Boustani, Sami [elboustani at]; Marre, Olivier [marre at];