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• W2320009085 abstract "Event Abstract Back to Event Intrinsic plasticity in autonomous recurrent neural networks Dimitrije Markovic1* and Claudius Gros1 1 J. W. Goethe University, Institute for Theoretical Physics, Germany We investigate generic properties of neural networks governed by autonomous self-regulation using a previously proposed model of intrinsic plasticity [1, 2]. The learning rules for the adaptation of _ring-rate neurons were derived from information-theoretical prin-ciples. We show that this polyhomeostatic optimization, which in contrast to homeostatic regulation aims at stabilization of a speci_c target distribution of neural activities, gives rise to non-trivial dynamical states when recurrent interactions are introduced. We consider individual self-coupled neurons and networks of _ring-rate neurons, with intrinsic plasticity trying to achieve maximal en-tropy of output _ring rates. We _nd, in particular, that the intro-duction of intrinsic adaption leads to a destruction of all attractors in Hop_eld-like network setup [3]. Surprisingly, for large networks, we observe either chaotic or intermittent bursting behavior [4], de- pending on the speci_ed average _ring rates. A property similar to networks of spiking neurons. Interestingly, both states are globally attracting in their respective phase spaces. Autonomous and poly-homeostatic self-control of dynamical systems may lead in general to non-trivial dynamical states and novel phenomena. References [1] M. Stemmler, C. Koch. Nature Neuroscience 2, 521 (1999). [2] J. Triesch, in Proceedings of ICANN 2005, W. Duch et al.(Eds.), LNCS 3696, 65 (2005). [3] C. Gros, New Journal of Physics 9, 109 (2007). [4] N. Platt, E.A. Spiegel, and C. Tresser, Phys. Rev. Lett. 70, 279(1993). 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: Markovic D and Gros C (2010). Intrinsic plasticity in autonomous recurrent neural networks. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00059 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: 16 Sep 2010; Published Online: 23 Sep 2010. * Correspondence: Mr. Dimitrije Markovic, J. W. Goethe University, Institute for Theoretical Physics, Frankfurt am Main, Germany, dimitrije.markovic@tu-dresden.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 Dimitrije Markovic Claudius Gros Google Dimitrije Markovic Claudius Gros Google Scholar Dimitrije Markovic Claudius Gros PubMed Dimitrije Markovic Claudius Gros 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." @default.
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• W2320009085 date "2010-01-01" @default.
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• W2320009085 title "Intrinsic plasticity in autonomous recurrent neural networks" @default.
• W2320009085 doi "https://doi.org/10.3389/conf.fncom.2010.51.00059" @default.
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