Synchronization and computation in a chaotic neural network

Chaos generated by the internal dynamics of a large neural network can be correlated over large spatial scales. Modulating the spatial coherence of the chaotic fluctuations by the spatial pattern of the external input provides a robust mechanism for feature segmentation and binding, which cannot be accomplished by networks of oscillators with local noise. This is demonstrated by an investigation of synchronized chaos in a network model of bursting neurons responding to an inhomogeneous stimulus.

Authors: D. Hansel and H. Sompolinsky
Year of publication: 1992
Journal: Phys. Rev. Lett. 68, 718 – Published 3 February 1992

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“Working memory”