Abstract
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.
Original language | English |
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Pages (from-to) | 718-721 |
Number of pages | 4 |
Journal | Physical Review Letters |
Volume | 68 |
Issue number | 5 |
DOIs | |
State | Published - 1992 |