Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

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Siebenhühner , F , Wang , S H , Arnulfo , G , Lampinen , A , Nobili , L , Palva , J M & Palva , S 2020 , ' Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings ' , PLoS Biology , vol. 18 , no. 5 , 3000685 . https://doi.org/10.1371/journal.pbio.3000685

Title: Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings
Author: Siebenhühner, Felix; Wang, Sheng H.; Arnulfo, Gabriele; Lampinen, Anna; Nobili, Lino; Palva, J. Matias; Palva, Satu
Contributor organization: Neuroscience Center
Helsinki Institute of Life Science HiLIFE
University of Helsinki
BioMag Laboratory
HUS Medical Imaging Center
Matias Palva / Principal Investigator
University Management
Date: 2020-05
Language: eng
Number of pages: 40
Belongs to series: PLoS Biology
ISSN: 1544-9173
DOI: https://doi.org/10.1371/journal.pbio.3000685
URI: http://hdl.handle.net/10138/316218
Abstract: Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.
Description: cited By 0
Subject: 3112 Neurosciences
CORTICAL CORRELATION STRUCTURE
NEURONAL OSCILLATIONS
PHASE-SYNCHRONIZATION
GAMMA OSCILLATIONS
WORKING-MEMORY
BAND OSCILLATIONS
BRAIN NETWORKS
MEG
CORTEX
THETA
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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