<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>20</volume><submitter>Pavlova A</submitter><pubmed_abstract>The aim of the present study was to investigate the association between resting-state EEG functional connectivity and spatial working memory (SWM) in adolescents, using a graph-theoretical approach. Sixty-three healthy adolescents (38 females; &lt;i>M&lt;/i> = 16.8, SD = 0.47) participated in the study. Resting-state EEG was recorded by a wireless dry-sensor 32-channel headset (Cognionics Quick-32r) configured in a standard 10-20 montage. Graph metrics were calculated in alpha, theta, beta-low and beta-high frequency bands, using connection-strength thresholds of 50 and 80%. SWM performance was measured with the computerized Corsi Block-Tapping Task (CBT). Robust bootstrapped linear regressions revealed significant associations between graph metrics and CBT accuracy only for theta and beta-low f</pubmed_abstract><journal>Frontiers in human neuroscience</journal><pagination>1748183</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12920549</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Higher integration of the whole-brain resting state theta band network is associated with spatial working memory.</pubmed_title><pmcid>PMC12920549</pmcid><pubmed_authors>Pavlova A</pubmed_authors><pubmed_authors>Adamovich T</pubmed_authors><pubmed_authors>Malykh S</pubmed_authors></additional><is_claimable>false</is_claimable><name>Higher integration of the whole-brain resting state theta band network is associated with spatial working memory.</name><description>The aim of the present study was to investigate the association between resting-state EEG functional connectivity and spatial working memory (SWM) in adolescents, using a graph-theoretical approach. Sixty-three healthy adolescents (38 females; &lt;i>M&lt;/i> = 16.8, SD = 0.47) participated in the study. Resting-state EEG was recorded by a wireless dry-sensor 32-channel headset (Cognionics Quick-32r) configured in a standard 10-20 montage. Graph metrics were calculated in alpha, theta, beta-low and beta-high frequency bands, using connection-strength thresholds of 50 and 80%. SWM performance was measured with the computerized Corsi Block-Tapping Task (CBT). Robust bootstrapped linear regressions revealed significant associations between graph metrics and CBT accuracy only for theta and beta-low f</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026</publication><modification>2026-07-16T18:04:41.851Z</modification><creation>2026-07-09T11:10:59.52Z</creation></dates><accession>S-EPMC12920549</accession><cross_references><pubmed>41727845</pubmed><doi>10.3389/fnhum.2026.1748183</doi></cross_references></HashMap>