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Journal Article

Dynamical Entropy Production in Spiking Neuron Networks in the Balanced State

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Monteforte,  Michael
Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Wolf,  Fred
Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Monteforte, M., & Wolf, F. (2010). Dynamical Entropy Production in Spiking Neuron Networks in the Balanced State. Physical Review Letters, 105: 268104. doi:10.1103/PhysRevLett.105.268104.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0029-1201-A
Abstract
We demonstrate deterministic extensive chaos in the dynamics of large sparse networks of theta neurons in the balanced state. The analysis is based on numerically exact calculations of the full spectrum of Lyapunov exponents, the entropy production rate, and the attractor dimension. Extensive chaos is found in inhibitory networks and becomes more intense when an excitatory population is included. We find a strikingly high rate of entropy production that would limit information representation in cortical spike patterns to the immediate stimulus response.