dc.contributor.authorDai, Zhongxiang
dc.contributor.authorde Souza, Joshua
dc.contributor.authorLim, Julian
dc.contributor.authorHo, Paul M.
dc.contributor.authorChen, Yu
dc.contributor.authorLi, Junhua
dc.contributor.authorThakor, Nitish
dc.contributor.authorBezerianos, Anastasios
dc.contributor.authorSun, Yu
dc.date.accessioned2018-07-30T06:48:40Z
dc.date.available2018-07-30T06:48:40Z
dc.date.issued2017
dc.identifier.citationDai, Z., de Souza, J., Lim, J., Ho, P. M., Chen, Y., Li, J., et al. (2017). EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands. Frontiers in Human Neuroscience, 11, 237-.en_US
dc.identifier.urihttp://hdl.handle.net/10220/45379
dc.description.abstractNumerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n-back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks.en_US
dc.description.sponsorshipMOE (Min. of Education, S’pore)en_US
dc.format.extent13 p.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesFrontiers in Human Neuroscienceen_US
dc.rights© 2017 Dai, de Souza, Lim, Ho, Chen, Li, Thakor, Bezerianos and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these termsen_US
dc.subjectCortical Functional Connectivityen_US
dc.subjectEEGen_US
dc.titleEeg cortical connectivity analysis of working memory reveals topological reorganization in theta and alpha bandsen_US
dc.typeJournal Article
dc.contributor.researchComputational Intelligence Laben_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.3389/fnhum.2017.00237
dc.description.versionPublished versionen_US
dc.contributor.organizationComputational Intelligence Laben_US


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