Information Theoretic Analysis of Connection Structure from Spike Trains

We have attempted to use information theoretic quantities for analyzing neuronal connection structure from spike trains. Two point mu tual information and its maximum value, channel capacity, between a pair of neurons were found to be useful for sensitive detection of crosscorrelation and for estimation of synaptic strength, respectively. Three point mutual information among three neurons could give their interconnection structure. Therefore, our information theoretic analysis was shown to be a very powerful technique for deducing neuronal connection structure. Some concrete examples of its application to simulated spike trains are presented.