Sub-second fluctuations between top-down and bottom-up modes distinguish diverse human brain states.
Youngjai Park, Younghwa Cha, Hyoungkyu Kim, Yukyung Kim, Jae Hyung Woo, Jehyeop Lee, Hanbyul Cho, George A. Mashour, Ting Xu, UnCheol Lee, Seok-Jun Hong, Christopher J Honey, Joon-Young Moon
Current biology : CB July 2, 2026 DOI: 10.1016/j.cub.2026.06.014 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational study with simultaneous EEG-fMRI and computational modeling Peer reviewed |
|---|---|
| Population | Human participants (wakefulness, anesthesia, and ADHD groups) |
| Keywords | ADHD Kuramoto model Cortical traveling waves Coupled-oscillator model General anesthesia Human brain dynamics Relative phase analysis Simultaneous EEG-FMRI Sub-second transitions |
| Key findings | Sub-second alternations between top-down and bottom-up modes of information flow occur approximately every 200 ms, are most prominent during wakefulness, diminish under anesthesia, and are pathologically imbalanced in ADHD. |
Abstract
Information continuously flows between regions of the human brain, forming patterns that shift across states of consciousness, cognitive modes, and neuropsychiatric conditions. While functional magnetic resonance imaging (fMRI) reveals large-scale activity changes over seconds, the electrophysiological dynamics governing sub-second reconfiguration remain poorly understood. Here, relative phase analysis (RPA), a method leveraging phase lead/lag relationships, is introduced to capture whole-brain dynamics with millisecond precision in real time from electroencephalography (EEG). RPA reveals sub-second alternations, occurring approximately every 200 ms, between two dominant modes of information flow: a top-down mode, where anterior regions drive posterior activity, and a bottom-up mode, characterized by reverse directionality. These dynamics are most prominent during wakefulness, gradually diminish under anesthesia, and exhibit pathological imbalance in attention-deficit/hyperactivity disorder (ADHD). Simultaneous EEG-fMRI recordings demonstrate that top-down dynamics coincide with increased activity of higher-order cognitive networks, whereas bottom-up dynamics correspond to heightened activity in sensory networks. A connectome-based coupled-oscillator model reproduces these transitions, indicating that sub-second fluctuations emerge naturally from inter-regional interactions shaped by underlying structural connectivity. This study establishes RPA as a framework for tracking whole-brain dynamics precisely in real time and identifies sub-second top-down/bottom-up alternations as a fundamental organizing principle of human brain function and consciousness.