Abstract
We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors ("patterns") we add a slow coupling dynamics that makes the visited patterns lose stability, leading to an itinerant behavior in the form of punctuated equilibria. One finds that the transition frequency matrix for transitions between patterns shows non-trivial statistical properties in the chaotic itinerant regime. We show that mixture input patterns can be temporally segmented by the itinerant dynamics. The viability of a combinatorial spatio-temporal neural code is also demonstrated.
Original language | English (US) |
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Pages (from-to) | 1-5 |
Number of pages | 5 |
Journal | Physica D: Nonlinear Phenomena |
Volume | 237 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2008 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Statistical and Nonlinear Physics
- Mathematical Physics
- Condensed Matter Physics
- Applied Mathematics
Keywords
- Chaotic itinerancy
- Combinatorial codes
- Neural codes
- Neural networks
- Olfactory system
- Sensory systems