Sub-second fluctuations between top-down and bottom-up modes distinguish diverse human brain states.

The human brain's information flow alternates between two dominant modes roughly every 200 milliseconds: a top-down mode where anterior brain regions drive posterior activity, and a bottom-up mode with reverse directionality. These sub-second alternations are most prominent during wakefulness, gradually diminish under anesthesia, and show pathological imbalance in attention-deficit/hyperactivity disorder (ADHD). Simultaneous EEG-fMRI recordings reveal that top-down dynamics coincide with increased activity in higher-order cognitive networks, while bottom-up dynamics correspond to heightened sensory network activity. A connectome-based coupled-oscillator model reproduces these transitions, suggesting they emerge naturally from structural connectivity. Relative phase analysis (RPA) enables tracking these whole-brain dynamics with millisecond precision in real time from electroencephalography.

Study at a glance

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.