Evidence map›Paper›PMID 40161811›Full record

ArticlebioRxiv : the preprint server for biology2025

Sub-Second Fluctuation between Top-Down and Bottom-Up Modes Distinguishes Diverse Human Brain States.

Youngjai Park, Younghwa Cha, Hyoungkyu Kim, Yukyung Kim, Jae Hyung Woo, Hanbyul Cho, George A Mashour, Ting Xu, Uncheol Lee, Seok-Jun Hong and 2 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Youngjai ParkCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.ORCID 0000-0002-1727-1996
Younghwa ChaCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.ORCID 0009-0000-7059-9547
Hyoungkyu KimCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.
Yukyung KimCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.
Jae Hyung WooDepartment of Psychological and Brain Sciences, Dartmouth College, Hanover, 03755, NH, USA.
Hanbyul ChoCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.
George A MashourDepartment of Anesthesiology, University of Michigan Medical School, Ann Arbor, 48109, MI, USA.
Ting XuCenter for the Developing Brain, Child Mind Institute, New York, 10022, NY, USA.
Uncheol LeeDepartment of Anesthesiology, University of Michigan Medical School, Ann Arbor, 48109, MI, USA.
Seok-Jun HongCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.
Christopher J HoneyDepartment of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, 21218, MD, USA.
Joon-Young MoonCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, 16419, Republic of Korea.ORCID 0000-0002-7842-5864

Funding

Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI Michael Peter Milham · 2017 to 2026
$25.3M
Integrating and separating information sequences in the human cerebral cortexR01MH119099 · NIMH · JOHNS HOPKINS UNIVERSITY · PI HONEY, CHRISTOPHER JOHN · 2019 to 2023
$2.5M
NIMH NIH HHS P50 MH109429NIMH NIH HHS R01 MH119099
6 · The paper itself

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.

Indexed as

Human Brain StateInternal-External Directionality FluctuationReletive Phase DynamicsSub-Second Fluctuation

Identifiers

PMID40161811
PMCPMC11952419

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.