IBS Institute for Basic Science
Search

  • Seok-Jun Hong
  • Assistant Professor
  • Computational neuroimaging, Developmental disorders, biophysical brain network modeling
  • Department of Biomedical Engineering
  • hongseokjunskku.edu
  • https://combinelab.net
  • CV

Detail


Computational Brain Imaging and Network Modeling Lab
(COMBINE LAB)


 

Introduction


We are the research group of Computational Brain Imaging and Network Modeling (COMBINE) at IBS Center for Neuroscience Imaging Research (CNIR) and Sungkyunkwan University (SKKU) in South Korea. “COMBINE” is not a simply eye-catching acronym for the lab title but represents the main research perspective we are pursuing. Using diverse neuroimaging and computational modeling approaches, our research aims at identifying system-level principles for large-scale organization of the brain and its neurodynamics in both typical and atypcial conditions. In performing the research, we are seeking to combine multi-method (connectomics, computational modeling), multi-modal (structure and function), and multi-scale (circuit-level, large-scale network and behhaviors) analytical approaches to understand brain working principles and capture individual variations in complex behavioral and clinical outcomes. Based on these research tools, ultimately we are targeting to develop effective imaging-based biomarkers for normal cognition and clinical diagnosis.


 

Selected Recent Publications


1. Hong SJ, Vogelstein J, Gozzi A, Bernhardt BC, Yeo B.T.T, Milham MP, Di Martino A, Towards Neurosubtypes in Autism. Biological Psychiatry 2020 


2. Hong SJ, Vos de Wael R, Bethlehem R, Lariviere R, Paquola C, Valk SL, Di Martino A, Milham MP, Smallwood J, Margulies D, Bernhardt BC. Atypical functional connectome hierarchy in autism. Nature Communications. 2019, 10 (1):1022

 

3. Hong SJ, Lee HM, Gill RS, Bernhardt BC, Bernasconi N, Bernasconi A. A connectome-based mechanistic model of epileptogenic focal cortical developmental malformations. Brain. 2019, 142 (3):688-699