Spike train auto-structure impacts post-synaptic firing and timing-based plasticity

Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal s
Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a conductance-based integrate and fire neuron. Both the excitatory and inhibitory input was modeled by renewal gamma processes with varying shape factors for modeling regular and temporally random Poisson activity. We demonstrate that the temporal structure of mutually independent inputs affects the post-synaptic firing, while the strength of the effect depends on the firing rates of both the excitatory and inhibitory inputs. In a second step, we explore the effect of temporal structure of mutually independent inputs on a simple version of Hebbian learning, i.e., hard bound spike-timing-dependent plasticity. We explore both the equilibrium weight distribution and the speed of the transient weight dynamics for different mutually independent gamma processes. We find that both the equilibrium distribution of the synaptic weights and the speed of synaptic changes are modulated by the temporal structure of the input. Finally, we highlight that the sensitivity of both the post-synaptic firing as well as the spike-timing-dependent plasticity on the auto-structure of the input of a neuron could be used to modulate the learning rate of synaptic modification.
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Metadaten
Author:Bertram Scheller, Marta Castellano, Raul Vicente, Gordon Pipa
URN:urn:nbn:de:hebis:30:3-248573
DOI:http://dx.doi.org/10.3389/fncom.2011.00060
ISSN:1662-5188
Pubmed Id:http://www.ncbi.nlm.nih.gov/pubmed?term=22203800
Parent Title (English):Frontiers in computational neuroscience
Publisher:Frontiers Research Foundation
Place of publication:Lausanne
Document Type:Article
Language:English
Date of Publication (online):2011/12/16
Date of first Publication:2011/12/16
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2012/06/21
Tag:STDP; auto-structure; integrate and fire; non-Poissonian; spike train; temporal correlations
Volume:5
Issue:60
Pagenumber:16
First Page:1
Last Page:16
Institutes:Medizin
Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 3.0

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