Abstract
We discuss how to characterize long-time dynamics of non-smooth dynamical systems, such as integrate-and-fire (I&F) like neuronal network, using Lyapunov exponents and present a stable numerical method for the accurate evaluation of the spectrum of Lyapunov exponents for this large class of dynamics. These dynamics contain (i) jump conditions as in the firing-reset dynamics and (ii) degeneracy such as in the refractory period in which voltage-like variables of the network collapse to a single constant value. Using the networks of linear I&F neurons, exponential I&F neurons, and I&F neurons with adaptive threshold, we illustrate our method and discuss the rich dynamics of these networks.
Original language | English (US) |
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Pages (from-to) | 229-245 |
Number of pages | 17 |
Journal | Journal of Computational Neuroscience |
Volume | 28 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2010 |
Keywords
- Firing-reset
- Integrate-and-fire
- Lyapunov exponents
- Non-smooth
- Refractory-induced degeneracy
ASJC Scopus subject areas
- Sensory Systems
- Cognitive Neuroscience
- Cellular and Molecular Neuroscience