Interplay of multiple pathways and activity-dependent rules in STDP.

Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbia...

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Main Authors: Gaëtan Vignoud, Laurent Venance, Jonathan D Touboul
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-08-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC6112684?pdf=render
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author Gaëtan Vignoud
Laurent Venance
Jonathan D Touboul
author_facet Gaëtan Vignoud
Laurent Venance
Jonathan D Touboul
author_sort Gaëtan Vignoud
collection DOAJ
description Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.
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spelling doaj.art-1fb22ebd4811409ba015bfe6cc459c192022-12-21T19:31:29ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582018-08-01148e100618410.1371/journal.pcbi.1006184Interplay of multiple pathways and activity-dependent rules in STDP.Gaëtan VignoudLaurent VenanceJonathan D TouboulHebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.http://europepmc.org/articles/PMC6112684?pdf=render
spellingShingle Gaëtan Vignoud
Laurent Venance
Jonathan D Touboul
Interplay of multiple pathways and activity-dependent rules in STDP.
PLoS Computational Biology
title Interplay of multiple pathways and activity-dependent rules in STDP.
title_full Interplay of multiple pathways and activity-dependent rules in STDP.
title_fullStr Interplay of multiple pathways and activity-dependent rules in STDP.
title_full_unstemmed Interplay of multiple pathways and activity-dependent rules in STDP.
title_short Interplay of multiple pathways and activity-dependent rules in STDP.
title_sort interplay of multiple pathways and activity dependent rules in stdp
url http://europepmc.org/articles/PMC6112684?pdf=render
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