Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/47430
Type of publication: research article
Type of publication (PDB): Straipsnis konferencijos medžiagoje kitose duomenų bazėse / Article in conference proceedings in other databases (P1c)
Field of Science: Informatika / Informatics (N009)
Author(s): Tamošiūnaitė, Minija;Porr, Bernd;Wörgötter, Florentin
Title: Temporally changing synaptic plasticity
Is part of: Advances in neural information processing systems : 19th annual conference, Vancouver, British Columbia, Canada, December 5-10, 2005 : proceedings. Cambridge, Massachusetts : MIT Press, 2006
Extent: p. 1337-1344
Date: 2006
Keywords: Synaptic plasticity;Hebbian learning;Dendritic spike
ISBN: 9780262232531
Abstract: Recent experimental results suggest that dendritic and back-propagating spikes can influence synaptic plasticity in different ways [1]. In this study we investigate how these signals could temporally interact at dendrites leading to changing plasticity properties at local synapse clusters. Similar to a previous study [2], we employ a differential Hebbian plasticity rule to emulate spike-timing dependent plasticity. We use dendritic (D-) and back-propagating (BP-) spikes as post-synaptic signals in the learning rule and investigate how their interaction will influence plasticity. We will analyze a situation where synapse plasticity characteristics change in the course of time, depending on the type of post-synaptic activity momentarily elicited. Starting with weak synapses, which only elicit local D-spikes, a slow, unspecific growth process is induced. As soon as the soma begins to spike this process is replaced by fast synaptic changes as the consequence of the much stronger and sharper BP-spike, which now dominates the plasticity rule. This way a winner-take-all-mechanism emerges in a two-stage process, enhancing the best-correlated inputs. These results suggest that synaptic plasticity is a temporal changing process by which the computational properties of dendrites or complete neurons can be substantially augmented
Internet: http://books.nips.cc/papers/files/nips18/NIPS2005_0169.pdf
Affiliation(s): Taikomosios informatikos katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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