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