Synchronous neural activity in scale-free network models versus random network models.

Geoffrey Grinstein; Ralph Linsker

doi:10.1073/pnas.0504127102

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PubMed · 15998732

Synchronous neural activity in scale-free network models versus random network models.

Geoffrey Grinstein·Ralph Linsker

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Abstract

Synchronous firing peaks at levels greatly exceeding background activity have recently been reported in neocortical tissue. A small subset of neurons is dominant in a large fraction of the peaks. To investigate whether this striking behavior can emerge from a simple model, we constructed and studied a model neural network that uses a modified Hopfield-type dynamical rule. We find that networks having a power-law ("scale-free") node degree distribution readily generate extremely large synchronous firing peaks dominated by a small subset of nodes, whereas random (Erdös-Rényi) networks do not. This finding suggests that network topology may play an important role in determining the nature and magnitude of synchronous neural activity.

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Geoffrey Grinstein, Ralph Linsker. 2005-07-05. Synchronous neural activity in scale-free network models versus random network models.. https://doi.org/10.1073/pnas.0504127102

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