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Complexity distribution as a measure for assembly size and temporal precision

Authors
Journal
Neural Networks
0893-6080
Publisher
Elsevier
Publication Date
Volume
23
Issue
6
Identifiers
DOI: 10.1016/j.neunet.2010.05.004
Keywords
  • Spike Synchrony
  • Higher-Order Correlation
  • Massively Parallel Spike Trains
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract The efficient detection of higher-order synchronization in massively parallel data is of great importance in understanding computational processes in the cortex and represents a significant statistical challenge. To overcome the combinatorial explosion of different spike patterns taking place as the number of neurons increases, a method based on population measures would prove very useful. Following previous work in this direction, we examine the distribution of spike counts across neurons per time bin (‘complexity distribution’) and devise a method to reliably extract the size and temporal precision of synchronous groups of neurons, even in the presence of strong rate covariations.

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