Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experiment...

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Main Authors:	Ladenbauer, Josef, Augustin, Moritz, Shiau, LieJune, Obermayer, Klaus
Format:	Online
Language:	English
Published:	Public Library of Science 2012
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3325187/

id	pubmed-3325187
recordtype	oai_dc
spelling	pubmed-33251872012-04-17 Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons Ladenbauer, Josef Augustin, Moritz Shiau, LieJune Obermayer, Klaus Research Article The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies. Public Library of Science 2012-04-12 /pmc/articles/PMC3325187/ /pubmed/22511861 http://dx.doi.org/10.1371/journal.pcbi.1002478 Text en Ladenbauer et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Ladenbauer, Josef Augustin, Moritz Shiau, LieJune Obermayer, Klaus
spellingShingle	Ladenbauer, Josef Augustin, Moritz Shiau, LieJune Obermayer, Klaus Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons
author_facet	Ladenbauer, Josef Augustin, Moritz Shiau, LieJune Obermayer, Klaus
author_sort	Ladenbauer, Josef
title	Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons
title_short	Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons
title_full	Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons
title_fullStr	Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons
title_full_unstemmed	Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons
title_sort	impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons
description	The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies.
publisher	Public Library of Science
publishDate	2012
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3325187/
_version_	1611520660374290432

Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

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