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Younghwa Cha

3 papers in the library · publishing 2025-2026

Papers

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

Current Biology July 2, 2026 Youngjai Park, Younghwa Cha, Hyoungkyu Kim et al.

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...

DOI: 10.1016/j.cub.2026.06.014 (opens in new tab) Full text (opens in new tab) ADHD Kuramoto model Cortical traveling waves Coupled-oscillator model +5

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

bioRxiv : the preprint server for biology March 28, 2025 Youngjai Park, Younghwa Cha, Hyoungkyu Kim et al. preprint

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...

DOI: 10.1101/2025.03.12.642768 (opens in new tab) Full text (opens in new tab) Human brain state Internal-external directionality fluctuation Reletive phase dynamics Sub-second fluctuation

Human brain state classification via permutation entropy of EEG phase dynamics across consciousness levels and inattentive-type ADHD

Athokpam Langlen Chanu, Youngjai Park, Jaesung Choi et al. preprint

We analyze electroencephalography (EEG) signals using the ordinal pattern framework to investigate whether different human brain states can be distinguished based on the disorder of EEG dynamics. Rather than analyzing raw EEG signals, we focus on the principal mode of EEG phase dynamics, reflecting anterior–posterior information flow, and quantify disorder using permutation entropy. We apply...