Sonja Grün, FZ Jülich

Identification of Cell Assemblies in Massively Parallel Spike Recordings

Fine temporal correlations between simultaneously recorded neurons have been interpreted as signatures of cell assemblies, i.e. groups of neurons that form processing units. Evidence was found on the level of pairwise correlations in simultaneous recordings of few neurons. Increasing the number of simultaneously recorded neurons makes cell assembly expressions more likely to be detected due to the larger sample size. Recent technological advances have enabled the recording of 100 or more neurons in parallel. However, these massively parallel spike train (MPST) data require novel statistical tools to be analyzed for correlations, because they raise considerable combinatorial and multiple testing issues. About 10 years ago such methods started to be developed. First approaches were based on population or pairwise measures of synchronization, and later led to methods for the detection of various types of higher-order synchronization and of spatio-temporal patterns. The latest techniques combine data mining with analysis of statistical significance. Analyses of MPST from monkey pre-/motor cortex show the occurrence of behavior specific spike patterns.

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GRK 1589