Event Abstract

Adaptation Reduces Vriability of the Neuronal Population Code.

  • 1 Freie Universität Berlin, Neuroinformatics and Theoretical Neuroscience, Institute of Biology, Germany
  • 2 EPFL, Laboratory of Computational Neuroscience, Switzerland

Sequences of events in the vast majority of spiking neurons in the nervous systems of diverse species exhibit a negative dependence between event intervals as their activity is often modulated by an intrinsic slow variable of self-inhibition, the so-called spike-frequency adaptation.
Here, we employ a master equation for general non-renewal processes and we derive adaptation induced effects on the event count variability, and we link these findings to the read-out properties of a post-synaptic neural decoder as adapative population activty enhanced informational gain.In addition, we provide an experimental example of neural ensemble data in the mammalian neocortex to illustrate the application of our theoretical framework to a biological system with non-renewal properties.

Keywords: computational neuroscience

Conference: Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010.

Presentation Type: Presentation

Topic: Bernstein Conference on Computational Neuroscience

Citation: Farkhooi F, Muller E and Nawrot M (2010). Adaptation Reduces Vriability of the Neuronal Population Code.. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00056

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Received: 16 Sep 2010; Published Online: 23 Sep 2010.

* Correspondence: Dr. Farzad Farkhooi, Freie Universität Berlin, Neuroinformatics and Theoretical Neuroscience, Institute of Biology, Berlin, Germany, farzad.farkhooi@gmail.com