{"id":12661,"date":"2026-06-29T17:11:20","date_gmt":"2026-06-29T08:11:20","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&#038;p=12661"},"modified":"2026-06-29T17:11:20","modified_gmt":"2026-06-29T08:11:20","slug":"oscillatory-network-efficiency-predicts-mood-and-fatigue-during-sleep-deprivation-seunghun-lee","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/oscillatory-network-efficiency-predicts-mood-and-fatigue-during-sleep-deprivation-seunghun-lee\/","title":{"rendered":"Oscillatory network efficiency predicts mood and fatigue during sleep deprivation &#8211; Seunghun Lee"},"content":{"rendered":"<p>In this talk, we discuss the paper \u201cOscillatory network efficiency predicts mood and fatigue during sleep deprivation\u201d by David Negelspach et al., <em>communications biology<\/em>, 2026.<\/p>\n<p>Abstract:<\/p>\n<p>Fluctuations in performance and mood across the day have been traced to circadian and homeostatic modulation of motor and affective systems, although their combined influence on network topology is rarely considered. We applied a data-driven curve-fitting algorithm to capture both circadian and infradian rhythms (\u2009\u2265\u200924\u2009hours) in frontolimbic and sensorimotor regions using\u00a0functional magnetic resonance imaging (fMRI) measures of connectivity. Across the course of sleep deprivation, functional network structure was not static but changed in tandem with objective and subjective behavioral measures. Oscillatory patterns in network efficiency suggest that circadian rhythmicity extends to higher-order network topology. Sleep deprivation affects functional networks in a region-specific manner, highlighting local vulnerability. Distinct cortical regions exhibited unique circadian phases of network reorganization, revealing that connectivity rhythms are spatially as well as temporally differentiated across the brain. Time-dependent alterations in connectome topology offer a systems-level framework for understanding how internal timekeeping and sleep pressure modulate non-linear trends in psychomotor vigilance, mood, and fatigue across extended wakefulness.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this talk, we discuss the paper \u201cOscillatory network efficiency predicts mood and fatigue during sleep deprivation\u201d by David Negelspach et al., communications biology, 2026. Abstract: Fluctuations in performance and &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/oscillatory-network-efficiency-predicts-mood-and-fatigue-during-sleep-deprivation-seunghun-lee\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Oscillatory network efficiency predicts mood and fatigue during sleep deprivation &#8211; Seunghun Lee&#8221;<\/span><\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[219],"class_list":["post-12661","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-journal-club","cat_journal-club"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Oscillatory network efficiency predicts mood and fatigue during sleep deprivation - Seunghun Lee - Biomedical Mathematics Group<\/title>\n<meta name=\"description\" content=\"Fluctuations in performance and mood across the day have been traced to circadian and homeostatic modulation of motor and affective systems, although their combined influence on network topology is rarely considered. We applied a data-driven curve-fitting algorithm to capture both circadian and infradian rhythms (\u2009\u2265\u200924\u2009hours) in frontolimbic and sensorimotor regions using\u00a0functional magnetic resonance imaging (fMRI) measures of connectivity. Across the course of sleep deprivation, functional network structure was not static but changed in tandem with objective and subjective behavioral measures. Oscillatory patterns in network efficiency suggest that circadian rhythmicity extends to higher-order network topology. Sleep deprivation affects functional networks in a region-specific manner, highlighting local vulnerability. Distinct cortical regions exhibited unique circadian phases of network reorganization, revealing that connectivity rhythms are spatially as well as temporally differentiated across the brain. Time-dependent alterations in connectome topology offer a systems-level framework for understanding how internal timekeeping and sleep pressure modulate non-linear trends in psychomotor vigilance, mood, and fatigue across extended wakefulness.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/oscillatory-network-efficiency-predicts-mood-and-fatigue-during-sleep-deprivation-seunghun-lee\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Oscillatory network efficiency predicts mood and fatigue during sleep deprivation - Seunghun Lee - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\"Fluctuations in performance and mood across the day have been traced to circadian and homeostatic modulation of motor and affective systems, although their combined influence on network topology is rarely considered. We applied a data-driven curve-fitting algorithm to capture both circadian and infradian rhythms (\u2009\u2265\u200924\u2009hours) in frontolimbic and sensorimotor regions using\u00a0functional magnetic resonance imaging (fMRI) measures of connectivity. Across the course of sleep deprivation, functional network structure was not static but changed in tandem with objective and subjective behavioral measures. Oscillatory patterns in network efficiency suggest that circadian rhythmicity extends to higher-order network topology. Sleep deprivation affects functional networks in a region-specific manner, highlighting local vulnerability. Distinct cortical regions exhibited unique circadian phases of network reorganization, revealing that connectivity rhythms are spatially as well as temporally differentiated across the brain. 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