Unexpected Chaos in a Neural Model

Wednesday, September 4, 2013 - 15:00 to 16:00
703 Thackeray Hall

Abstract or Additional Information

Baseline activity in many brain regions is believed to be irregular, with little correlation in firing times of different neurons.  Indeed, excessive regularity has been associated with disorders such as Parkinson's disease.  Mathematically, neuronal irregularity has been represented as an asynchronous state that can be stable under so-called balance conditions that yield cancellation of correlations.   I will discuss a mechanism by which irregular, apparently chaotic activity emerges naturally in small inhibitory networks lacking such balance.  I will present a one-dimensional map that captures this activity as well as analysis of how expansion, folding, and contraction emerge in a corresponding phase plane, as expected in chaotic dynamics.