Abstract
Event Abstract Back to Event When less is more: Non-monotonic spike sequence processing in neurons Hinrich Kielblock1, 2*, Birk Urmersbach1, Shuwen Chang3, Holger Taschenberger3 and Marc Timme1, 2 1 Max Planck Institute for Dynamics and Self-Organization, Network Dynamics Group, Germany 2 Berstein Center for Computational Neuroscience Göttingen, Germany 3 Max Planck Institute for Biophysical Chemistry, Membrane Biophysics Department, Germany The computational capabilities of neural circuits centrally rely on the input-output relations of single neurons. It is commonly accepted that neurons respond to inputs monotonically such that increasing the input implies increasing the output. Yet, most theoretical and experimental input-output studies have so far focused on continuous-time inputs, whereas most neurons communicate via exchanging electrical pulses (spikes) at discrete times. Here we show that the stationary response to regular spike sequences is typically non-monotonic such that increasing the input frequency to a neuron may decrease its output frequency. The underlying mechanism relies solely on a combination of the discrete nature of the communication by spikes and generically limited resources required for input sequence processing. As a consequence, this phenomenon universally emerges across a variety of spiking neural systems. It may support stabilizing the generation of spike sequences in neural circuits. Acknowledgements We thank D. Bibichkov and S. Schreiber for valuable discussions. Partially supported by the BMBF Germany under grant no. 01GQ1005B and by a grant from the Max Planck Society to Marc Timme. Keywords: excitability, locking, Neurons, networks and dynamical systems, spike sequence processing Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011. Presentation Type: Demonstration Topic: neurons, networks and dynamical systems (please use "neurons, networks and dynamical systems" as keywords) Citation: Kielblock H, Urmersbach B, Chang S, Taschenberger H and Timme M (2011). When less is more: Non-monotonic spike sequence processing in neurons. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00163 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 Aug 2011; Published Online: 04 Oct 2011. * Correspondence: Mr. Hinrich Kielblock, Max Planck Institute for Dynamics and Self-Organization, Network Dynamics Group, Göttingen, Germany, hinrich@nld.ds.mpg.de 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 Hinrich Kielblock Birk Urmersbach Shuwen Chang Holger Taschenberger Marc Timme Google Hinrich Kielblock Birk Urmersbach Shuwen Chang Holger Taschenberger Marc Timme Google Scholar Hinrich Kielblock Birk Urmersbach Shuwen Chang Holger Taschenberger Marc Timme PubMed Hinrich Kielblock Birk Urmersbach Shuwen Chang Holger Taschenberger Marc Timme 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.
Highlights
Most neurons in the nervous system communicate by sending and receiving stereotyped electrical pulses called action potentials or spikes [1]
Brain function relies on robust communication between a huge number of nerve cells that exchange short-lasting electrical pulses at certain times
Our theoretical analysis predicts that spiking neurons commonly exhibit such non-monotonic response properties
Summary
Most neurons in the nervous system communicate by sending and receiving stereotyped electrical pulses called action potentials or spikes [1]. The computational capabilities of neural circuits centrally rely on the input-output relations of single neurons This relation is commonly characterized by its output spike rate in response to a temporally continuous constant input current I, sometimes in the presence of additional current fluctuations [2,3,4,5]. Neurons are dynamically classified according to such response curves (so-called f-I-curves), into type-I neurons, with their output spike rates increasing from zero above a critical current Ic, and type-II neurons which start spiking with a macroscopic, nonzero rate upon increasing I beyond some Ic [10, 11]. Neuronal output spike frequencies depend monotonically on the input I
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