Target-specific inhibition in E-I recurrent networks creates three dynamical classes: quiescent or asynchronous chaos in balanced cases, and persistent activity with either synchronous chaos or coherent oscillations in excitation-dominated cases, where oscillations suppress chaos.
<i>Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. <i>Computational Neuroscience.</i></i><i> By</i> Peter Dayan<i> and </i>, L F Abbott.<i> Cambridge (Massachusetts): MIT Press</i>. $50.00. xv + 460 p; ill.; index. ISBN: 0–262–04199–5. 2001.
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From Chaos to Synchrony in Recurrent Excitatory-Inhibitory Networks with Target-Specific Inhibition
Target-specific inhibition in E-I recurrent networks creates three dynamical classes: quiescent or asynchronous chaos in balanced cases, and persistent activity with either synchronous chaos or coherent oscillations in excitation-dominated cases, where oscillations suppress chaos.