Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.

Spike timing-dependent plasticity (STDP) modifies synaptic strengths based on timing information available locally at each synapse. Despite this, it induces global structures within a recurrently connected network. We study such structures both through simulations and by analyzing the effects of STD...

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Autores principales:	Baktash Babadi, L F Abbott
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/41327ba17b21465d8a3238d165414f6d
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spelling	oai:doaj.org-article:41327ba17b21465d8a3238d165414f6d2021-11-18T05:52:26ZPairwise analysis can account for network structures arising from spike-timing dependent plasticity.1553-734X1553-735810.1371/journal.pcbi.1002906https://doaj.org/article/41327ba17b21465d8a3238d165414f6d2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23436986/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Spike timing-dependent plasticity (STDP) modifies synaptic strengths based on timing information available locally at each synapse. Despite this, it induces global structures within a recurrently connected network. We study such structures both through simulations and by analyzing the effects of STDP on pair-wise interactions of neurons. We show how conventional STDP acts as a loop-eliminating mechanism and organizes neurons into in- and out-hubs. Loop-elimination increases when depression dominates and turns into loop-generation when potentiation dominates. STDP with a shifted temporal window such that coincident spikes cause depression enhances recurrent connections and functions as a strict buffering mechanism that maintains a roughly constant average firing rate. STDP with the opposite temporal shift functions as a loop eliminator at low rates and as a potent loop generator at higher rates. In general, studying pairwise interactions of neurons provides important insights about the structures that STDP can produce in large networks.Baktash BabadiL F AbbottPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 2, p e1002906 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Baktash Babadi L F Abbott Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
description	Spike timing-dependent plasticity (STDP) modifies synaptic strengths based on timing information available locally at each synapse. Despite this, it induces global structures within a recurrently connected network. We study such structures both through simulations and by analyzing the effects of STDP on pair-wise interactions of neurons. We show how conventional STDP acts as a loop-eliminating mechanism and organizes neurons into in- and out-hubs. Loop-elimination increases when depression dominates and turns into loop-generation when potentiation dominates. STDP with a shifted temporal window such that coincident spikes cause depression enhances recurrent connections and functions as a strict buffering mechanism that maintains a roughly constant average firing rate. STDP with the opposite temporal shift functions as a loop eliminator at low rates and as a potent loop generator at higher rates. In general, studying pairwise interactions of neurons provides important insights about the structures that STDP can produce in large networks.
format	article
author	Baktash Babadi L F Abbott
author_facet	Baktash Babadi L F Abbott
author_sort	Baktash Babadi
title	Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
title_short	Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
title_full	Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
title_fullStr	Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
title_full_unstemmed	Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
title_sort	pairwise analysis can account for network structures arising from spike-timing dependent plasticity.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/41327ba17b21465d8a3238d165414f6d
work_keys_str_mv	AT baktashbabadi pairwiseanalysiscanaccountfornetworkstructuresarisingfromspiketimingdependentplasticity AT lfabbott pairwiseanalysiscanaccountfornetworkstructuresarisingfromspiketimingdependentplasticity
_version_	1718424721411801088

Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.

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