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Transition to chaos in random networks with cell-type-specific connectivity.

ABSTRACT: In neural circuits, statistical connectivity rules strongly depend on cell-type identity. We study dynamics of neural networks with cell-type-specific connectivity by extending the dynamic mean-field method and find that these networks exhibit a phase transition between silent and chaotic activity. By analyzing the locus of this transition, we derive a new result in random matrix theory: the spectral radius of a random connectivity matrix with block-structured variances. We apply our results to show how a small group of hyperexcitable neurons within the network can significantly increase the network's computational capacity by bringing it into the chaotic regime.

SUBMITTER: Aljadeff J

PROVIDER: S-EPMC4527561 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Transition to chaos in random networks with cell-type-specific connectivity.

Aljadeff Johnatan J Stern Merav M Sharpee Tatyana T

Physical review letters 20150223 8

In neural circuits, statistical connectivity rules strongly depend on cell-type identity. We study dynamics of neural networks with cell-type-specific connectivity by extending the dynamic mean-field method and find that these networks exhibit a phase transition between silent and chaotic activity. By analyzing the locus of this transition, we derive a new result in random matrix theory: the spectral radius of a random connectivity matrix with block-structured variances. We apply our results to ...[more]

PMID: 25768781

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