Wani Woo
Sungkyunkwan University
About the Lab
Professor Wani Woo's research lab specializes in computational neuroscience and brain network dynamics, focusing on how brain lesions disrupt functional networks to produce clinical symptoms. The lab develops advanced neuroimaging and computational modeling techniques—such as lesion-network mapping and free-energy minimizing attractor theory—to understand brain function in health, disease, and during spontaneous thought. A key focus is on linking neural network organization with behavior and cognition, particularly through the integration of functional MRI, body perception maps, and language-based computational models. The lab also emphasizes open science, providing reproducible data pipelines and tools for neural data analysis.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
4Background and Purpose Similar-sized stroke lesions at similar locations can have different prognoses in clinical practice. Lesion-network mapping elucidates network-level effects of lesions that cause specific neurologic symptoms and signs, and also provides a group-level understanding. This study visualized the effects of stroke lesions on the functional brain networks of individual patients. Methods We enrolled patients with ischemic stroke who were hospitalized within 1 week of the stroke oc
Functional connectivity reveals brain attractors that match predictions of free‑energy‑minimizing attractor theory, yielding an interpretable generative model of brain dynamics in rest, task, and disease.
Data and scripts for Lux, B. K., et al. Body map-based predictive models of spontaneous thought This repository contains the MATLAB implementation for the processing, modeling, and neural analysis of bodily sensation maps associated with spontaneous thought. Article Title: Body map-based predictive models of spontaneous thought. Article Authors: Byeol Kim Lux, Hyemin Shin, Hong Ji Kim, Choong-Wan Woo System Requirements Software: MATLAB (R2021a or later recommended) Toolboxes: CanlabCore CocoanC
Modeling Spontaneous Thought: A Network- and Langauge-based Computational Method This repository includes the data and codes to generate analysis results and figures. Data anonymization To ensure participant confidentiality, we replaced all reported concepts and details—including names mentioned in their personal narratives—with alphanumeric codes. This anonymization process did not compromise the integrity of our analysis, and the results align with our published findings. Dependencies CanlabCo
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