A linear model of phase-dependent power correlations in neuronal oscillations

Recently, it has been suggested that effective interactions between two neuronal populations are supported by the phase difference between the oscillations in these two populations, a hypothesis referred to as communication through coherence (CTC). Experimental work quantified effective interactions...

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Main Authors: David eEriksson, Raul eVicente, Kerstin eSchmidt
Format: Article
Language:English
Published: Frontiers Media S.A. 2011-07-01
Series:Frontiers in Computational Neuroscience
Subjects:
CTC
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2011.00034/full
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spelling doaj-9e68fb970f314f1593af174e7c1012ab2020-11-24T21:32:20ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882011-07-01510.3389/fncom.2011.0003410064A linear model of phase-dependent power correlations in neuronal oscillationsDavid eEriksson0Raul eVicente1Kerstin eSchmidt2Max Planck InstituteMax-Planck-Institute for Brain ResearchMax Planck InstituteRecently, it has been suggested that effective interactions between two neuronal populations are supported by the phase difference between the oscillations in these two populations, a hypothesis referred to as communication through coherence (CTC). Experimental work quantified effective interactions by means of the power correlations between the two populations, where power was calculated on the local field potential and/or multiunit activity. Here, we present a linear model of interacting oscillators that accounts for the phase dependency of the power correlation between the two populations and that can be used as a reference for detecting non-linearities such as gain control. In the experimental analysis, trials were sorted according to the coupled phase difference of the oscillators while the putative interaction between oscillations was taking place. Taking advantage of the modelling, we further studied the dependency of the power correlation on the uncoupled phase difference, connection strength and topology, and frequency mismatch. Since the uncoupled phase difference, i.e., the phase relation before the effective interaction, is the causal variable in the CTC hypothesis we also describe how power correlations depend on such variable. For uni-directional connectivity we observe that the width of the uncoupled phase dependency is broader than for the coupled phase. Furthermore, the analytical results show that the characteristics of the phase dependency change when a bidirectional connection is assumed as well as when there is a frequency mismatch between the oscillations. The width of the phase dependency indicates which oscillation frequencies are optimal for a given connection delay distribution. We propose that a certain width enables a stimulus-contrast dependent weighting of feed-forward and lateral connections.http://journal.frontiersin.org/Journal/10.3389/fncom.2011.00034/fullneuronal oscillationsnonlinearityaxonal delayscommunication though coherenceCTCgain control
collection DOAJ
language English
format Article
sources DOAJ
author David eEriksson
Raul eVicente
Kerstin eSchmidt
spellingShingle David eEriksson
Raul eVicente
Kerstin eSchmidt
A linear model of phase-dependent power correlations in neuronal oscillations
Frontiers in Computational Neuroscience
neuronal oscillations
nonlinearity
axonal delays
communication though coherence
CTC
gain control
author_facet David eEriksson
Raul eVicente
Kerstin eSchmidt
author_sort David eEriksson
title A linear model of phase-dependent power correlations in neuronal oscillations
title_short A linear model of phase-dependent power correlations in neuronal oscillations
title_full A linear model of phase-dependent power correlations in neuronal oscillations
title_fullStr A linear model of phase-dependent power correlations in neuronal oscillations
title_full_unstemmed A linear model of phase-dependent power correlations in neuronal oscillations
title_sort linear model of phase-dependent power correlations in neuronal oscillations
publisher Frontiers Media S.A.
series Frontiers in Computational Neuroscience
issn 1662-5188
publishDate 2011-07-01
description Recently, it has been suggested that effective interactions between two neuronal populations are supported by the phase difference between the oscillations in these two populations, a hypothesis referred to as communication through coherence (CTC). Experimental work quantified effective interactions by means of the power correlations between the two populations, where power was calculated on the local field potential and/or multiunit activity. Here, we present a linear model of interacting oscillators that accounts for the phase dependency of the power correlation between the two populations and that can be used as a reference for detecting non-linearities such as gain control. In the experimental analysis, trials were sorted according to the coupled phase difference of the oscillators while the putative interaction between oscillations was taking place. Taking advantage of the modelling, we further studied the dependency of the power correlation on the uncoupled phase difference, connection strength and topology, and frequency mismatch. Since the uncoupled phase difference, i.e., the phase relation before the effective interaction, is the causal variable in the CTC hypothesis we also describe how power correlations depend on such variable. For uni-directional connectivity we observe that the width of the uncoupled phase dependency is broader than for the coupled phase. Furthermore, the analytical results show that the characteristics of the phase dependency change when a bidirectional connection is assumed as well as when there is a frequency mismatch between the oscillations. The width of the phase dependency indicates which oscillation frequencies are optimal for a given connection delay distribution. We propose that a certain width enables a stimulus-contrast dependent weighting of feed-forward and lateral connections.
topic neuronal oscillations
nonlinearity
axonal delays
communication though coherence
CTC
gain control
url http://journal.frontiersin.org/Journal/10.3389/fncom.2011.00034/full
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