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      Resting-state EEG activity predicts frontoparietal network reconfiguration and improved attentional performance

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          Abstract

          Mounting evidence indicates that resting-state EEG activity is related to various cognitive functions. To trace physiological underpinnings of this relationship, we investigated EEG and behavioral performance of 36 healthy adults recorded at rest and during visual attention tasks: visual search and gun shooting. All measures were repeated two months later to determine stability of the results. Correlation analyses revealed that within the range of 2–45 Hz, at rest, beta-2 band power correlated with the strength of frontoparietal connectivity and behavioral performance in both sessions. Participants with lower global beta-2 resting-state power (gB2rest) showed weaker frontoparietal connectivity and greater capacity for its modifications, as indicated by changes in phase correlations of the EEG signals. At the same time shorter reaction times and improved shooting accuracy were found, in both test and retest, in participants with low gB2rest compared to higher gB2rest values. We posit that weak frontoparietal connectivity permits flexible network reconfigurations required for improved performance in everyday tasks.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

          Yoav Benjamini, Yosef Hochberg (1995)
          Article 0 comments Cited 25153 times – based on 0 reviews     Review now
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            Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources.

            Cornelis Stam, Guido Nolte, Andreas Daffertshofer (2007)
            To address the problem of volume conduction and active reference electrodes in the assessment of functional connectivity, we propose a novel measure to quantify phase synchronization, the phase lag index (PLI), and compare its performance to the well-known phase coherence (PC), and to the imaginary component of coherency (IC). The PLI is a measure of the asymmetry of the distribution of phase differences between two signals. The performance of PLI, PC, and IC was examined in (i) a model of 64 globally coupled oscillators, (ii) an EEG with an absence seizure, (iii) an EEG data set of 15 Alzheimer patients and 13 control subjects, and (iv) two MEG data sets. PLI and PC were more sensitive than IC to increasing levels of true synchronization in the model. PC and IC were influenced stronger than PLI by spurious correlations because of common sources. All measures detected changes in synchronization during the absence seizure. In contrast to PC, PLI and IC were barely changed by the choice of different montages. PLI and IC were superior to PC in detecting changes in beta band connectivity in AD patients. Finally, PLI and IC revealed a different spatial pattern of functional connectivity in MEG data than PC. The PLI performed at least as well as the PC in detecting true changes in synchronization in model and real data but, at the same token and like-wise the IC, it was much less affected by the influence of common sources and active reference electrodes. Copyright 2007 Wiley-Liss, Inc.
            Article 0 comments Cited 591 times – based on 0 reviews     Review now
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              Competition between functional brain networks mediates behavioral variability.

              A. M. Clare Kelly, Lucina Q Uddin, Bharat Biswal … (2008)
              Increased intraindividual variability (IIV) is a hallmark of disorders of attention. Recent work has linked these disorders to abnormalities in a "default mode" network, comprising brain regions routinely deactivated during goal-directed cognitive tasks. Findings from a study of the neural basis of attentional lapses suggest that a competitive relationship between the "task-negative" default mode network and regions of a "task-positive" attentional network is a potential locus of dysfunction in individuals with increased IIV. Resting state studies have shown that this competitive relationship is intrinsically represented in the brain, in the form of a negative correlation or antiphase relationship between spontaneous activity occurring in the two networks. We quantified the negative correlation between these two networks in 26 subjects, during active (Eriksen flanker task) and resting state scans. We hypothesized that the strength of the negative correlation is an index of the degree of regulation of activity in the default mode and task-positive networks and would be positively related to consistent behavioral performance. We found that the strength of the correlation between the two networks varies across individuals. These individual differences appear to be behaviorally relevant, as interindividual variation in the strength of the correlation was significantly related to individual differences in response time variability: the stronger the negative correlation (i.e., the closer to 180 degrees antiphase), the less variable the behavioral performance. This relationship was moderately consistent across resting and task conditions, suggesting that the measure indexes moderately stable individual differences in the integrity of functional brain networks. We discuss the implications of these findings for our understanding of the behavioral significance of spontaneous brain activity, in both healthy and clinical populations.
              Article 0 comments Cited 396 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Jacek Rogala: j.rogala@nencki.edu.pl
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 19 March 2020
                Publication date PMC-release: 19 March 2020
                Publication date Collection: 2020
                Volume: 10
                Electronic Location Identifier: 5064
                Affiliations
                [1 ]ISNI 0000 0004 0621 558X, GRID grid.418932.5, Bioimaging Research Center, World Hearing Center, Institute of Physiology and Pathology of Hearing, ; Mokra 17 street, Kajetany, 05-830 Nadarzyn Poland
                [2 ]ISNI 0000 0001 1943 2944, GRID grid.419305.a, Instytut Biologii Doświadczalnej im. Marcelego Nenckiego, ; 3 Pasteur Street, 02-093 Warsaw, Poland
                [3 ]ISNI 0000 0001 1512 1639, GRID grid.69474.38, Military University of Technology, Physical Education, 3 gen, ; Sylwestra Kaliskiego street, 00-908 Warsaw, Poland
                [4 ]ISNI 0000 0004 1937 1290, GRID grid.12847.38, Department of Epistemology, Institute of Philosophy, University of Warsaw, ; 3 Krakowskie Przedmiescie street, 00-927 Warszawa, Poland
                Article
                Publisher ID: 61866
                DOI: 10.1038/s41598-020-61866-7
                PMC ID: 7081192
                PubMed ID: 32193502
                SO-VID: 4e1b3208-4af9-4d66-bacf-5e9688726095
                Copyright © © The Author(s) 2020
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 12 November 2019
                Date accepted : 5 March 2020
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2020

                ScienceOpen disciplines: Uncategorized
                Keywords: neuroscience,cognitive neuroscience,attention
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: neuroscience, cognitive neuroscience, attention

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