Literature DB >> 26025291

Measuring directionality between neuronal oscillations of different frequencies.

Haiteng Jiang1, Ali Bahramisharif2, Marcel A J van Gerven3, Ole Jensen3.   

Abstract

It is well established that neuronal oscillations at different frequencies interact with each other in terms of cross-frequency coupling (CFC). In particular, the phase of slower oscillations modulates the power of faster oscillations. This is referred to as phase-amplitude coupling (PAC). Examples are alpha phase to gamma power coupling as observed in humans and theta phase to gamma power coupling as observed in the rat hippocampus. We here ask if the interaction between alpha and gamma oscillations is in the direction of the phase of slower oscillations driving the power of faster oscillations or conversely from the power of faster oscillations driving the phase of slower oscillations. To answer this question, we introduce a new measure to estimate the cross-frequency directionality (CFD). This measure is based on the phase-slope index (PSI) between the phase of slower oscillations and the power envelope of faster oscillations. Further, we propose a randomization framework for statistically evaluating the coupling measures when controlling for multiple comparisons over the investigated frequency ranges. The method was firstly validated on simulated data and next applied to resting state electrocorticography (ECoG) data. These results demonstrate that the method works reliably. In particular, we found that the power envelope of gamma oscillations drives the phase of slower oscillations in the alpha band. This surprising finding is not easily reconcilable with theories suggesting that feedback controlled alpha oscillations modulate feedforward processing reflected in the gamma band.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cross-frequency coupling; Cross-frequency directionality; Neuronal oscillations

Mesh:

Year:  2015        PMID: 26025291     DOI: 10.1016/j.neuroimage.2015.05.044

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  36 in total

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10.  Electrophysiological Brain Connectivity: Theory and Implementation.

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