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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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 |
work_keys_str_mv |
AT davideeriksson alinearmodelofphasedependentpowercorrelationsinneuronaloscillations AT raulevicente alinearmodelofphasedependentpowercorrelationsinneuronaloscillations AT kerstineschmidt alinearmodelofphasedependentpowercorrelationsinneuronaloscillations AT davideeriksson linearmodelofphasedependentpowercorrelationsinneuronaloscillations AT raulevicente linearmodelofphasedependentpowercorrelationsinneuronaloscillations AT kerstineschmidt linearmodelofphasedependentpowercorrelationsinneuronaloscillations |
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