bioRxivNeurosciencePreprint
Sub-second Fluctuation between Top-Down and Bottom-Up Modes Distinguishes Diverse Human Brain States
Youngjai ParkiD, Y.-H. ChaiD, Hyoungkyu KimiD, Yukyung KimiD, Jae Hyung WooiD, Hanbyul Cho, George A. MashouriD, Ting Xu, UnCheol LeeiD, Seok‐Jun HongiD, Christopher John HoneyiD, Joon-Young MooniD
Abstract
Information continuously flows between regions of the human brain, exhibiting distinct patterns that dynamically shift across states of consciousness, cognitive modes, and neuropsychiatric conditions. In this study, we introduce Relative Phase Analysis (RPA), a method that leverages phase-lead/lag relationships to reveal the real-time dynamics of dominant directional patterns and their rapid transitions. We demonstrate that the human brain switches on a sub-second timescale between a top-down mode-where anterior regions drive posterior activity-and a bottom-up mode, characterized by reverse directionality. These dynamics are most pronounced during full consciousness and gradually become less distinct as awareness diminishes. Furthermore, we find from simultaneous EEG-fMRI recordings that the top-down mode is expressed when higher-order cognitive networks are more active while the bottom-up mode is expressed when sensory systems are more active. Moreover, comparisons of an attention deficit hyperactivity disorder (ADHD) inattentive cohort with typically developing individuals reveal distinct imbalances in these transition dynamics, highlighting the potential of RPA as a diagnostic biomarker. Complementing our empirical findings, a coupled-oscillator model of the structural brain network recapitulates these emergent patterns, suggesting that such directional modes and transitions may arise naturally from inter-regional neural interactions. Altogether, this study provides a framework for understanding whole-brain dynamics in real-time and identifies sub-second fluctuations in top-down versus bottom-up directionality as a fundamental mechanism underlying human information processing.
- organism: human
- assay: electronic health records
- research focus: cell-cell communication
- research focus: benchmarking
- research focus: database / resource
- approach: statistical model
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Top-down and bottom-up interactions rely on nested brain oscillations.
Jelena Trajkovic, Domenica Veniero, … Gregor Thut·bioRxiv·May 23, 2024
- Spectral-switching analysis reveals real-time neuronal network representations of concurrent spontaneous naturalistic behaviors in human brain
Hongkun Zhu, Andrew J. Michalak, … Elizabeth M. C. Hillman·bioRxiv·Jul 8, 2024
- Convergent cortical temporal axis: common cortical oscillatory modes
Xiaobo Liu, Sanwang Wang, … Guoyuan Yang·bioRxiv·Mar 17, 2026
- Reorganization of Human Brain Waves Across Diverse States of Consciousness
Panagiotis Fotiadis, Hyunwoo Jang, … Zirui Huang·bioRxiv·Jun 1, 2026
- Two dominant brain states reflect optimal and suboptimal attention
Ayumu Yamashita, David Rothlein, … Michael S. Esterman·bioRxiv·Jan 31, 2020
- Brainwide hemodynamics predict EEG neural rhythms across sleep and wakefulness in humans
Leandro P. L. Jacob, Sydney M. Bailes, … Laura D. Lewis·PLoS Computational BiologyPeer-reviewed·Sep 19, 2025