The effects of stochastic and deterministic adaptation currents on interspike interval histograms and correlations

Abstract

Event Abstract Back to Event The effects of stochastic and deterministic adaptation currents on interspike interval histograms and correlations Tilo Schwalger1*, Karin Fisch2, Jan Benda2 and Benjamin Lindner1 1 MPI for the Physics of Complex Systems, MPI, Germany 2 Ludwig-Maximilians-Universität München, Division of Neurobiology, Department Biology II, Germany The spiking patterns of neurons can be often highly variable. In many cases, the origin of this neural noise is not known and might be difficult to access directly. Here, we explore the possibility to distinguish between two different kinds of intrinsic noise solely by measuring the interspike interval (ISI) statistics of a neuron. Specifically, we consider adaptive neuron models in which fluctuations (channel noise) are either associated with fast ionic currents or with slow adaptation currents that are observed in many neurons. We show by means of analytical techniques and extensive numerical simulations that the shape of the ISI histograms and the ISI correlations are markedly different in both cases: For fast current fluctuations and deterministic adaptation, the ISI density is well approximated by an inverse Gaussian and the ISI correlations are negative. In contrast, for stochastic adaptation currents, the density is more peaked and has a heavier tail than an inverse Gaussian density and the serial correlations are positive. For the theoretical analysis we use an analytically tractable integrate-and-fire model. The results are qualitatively confirmed by simulations of a biophysically more realistic Hodgkin-Huxley type model. Our results could be used to infer the dominant source of noise in neurons from their ISI statistics Keywords: computational neuroscience Conference: Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010. Presentation Type: Poster Abstract Topic: Bernstein Conference on Computational Neuroscience Citation: Schwalger T, Fisch K, Benda J and Lindner B (2010). The effects of stochastic and deterministic adaptation currents on interspike interval histograms and correlations. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00016 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 Sep 2010; Published Online: 23 Sep 2010. * Correspondence: Dr. Tilo Schwalger, MPI for the Physics of Complex Systems, MPI, Dresden, Germany, tilo.schwalger@epfl.ch Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Tilo Schwalger Karin Fisch Jan Benda Benjamin Lindner Google Tilo Schwalger Karin Fisch Jan Benda Benjamin Lindner Google Scholar Tilo Schwalger Karin Fisch Jan Benda Benjamin Lindner PubMed Tilo Schwalger Karin Fisch Jan Benda Benjamin Lindner Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.