Center for Relativistic Laser Science

Detail

CAMIN lab (Computational Analysis for Multimodal Integrative Neuroimaging)

Introduction

We analyze multimodal brain MR imaging data using advanced connectomics and machine learning techniques to establish novel frameworks assessing multiscale brain organization. In particular, we aim to assess large-scale brain organization as well as structure-function coupling during typical and atypical development and young adults. Leveraging histology and imaging-genetics approaches, we provide biological underpinnings to the imaging findings. Methodologically, we study data mining, multimodal integration, and classification/prediction for big data.

Selected Recent Publications

1. B.-y. Park et. al., “Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy”, Brain, 2021.

2. B.-y. Park, H. Park, F. Morys, M. Kim, K. Byeon, H. Lee, S.-H. Kim, S. Valk, A. Dagher, B. C. Bernhardt, “Inter-individual body mass variations relate to fractionated functional brain hierarchies”, Communications Biology, 4:735, 2021.

3. B.-y. Park, S.-J. Hong, S. Valk, C. Paquola, O. Benkarim, R. A. I. Bethlehem, A. Di Martino, M. Milham, A. Gozzi, B. T. T. Yeo, J. Smallwood, and B. C. Bernhardt, “Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism”, Nature Communications, 12:2225, 2021.

4. B.-y. Park, R. A. I. Bethlehem, C. Paquola, S. Larivière, R. Rodríguez-Cruces, R. Vos de Wael, E. T. Bullmore, B. C. Bernhardt, “An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization”, eLife, 10:e64694, 2021.

5. B.-y. Park, R. Vos de Wael, C. Paquola, S. Larivière, O. Benkarim, J. Royer, S. Tavakol, R. Rodríguez-Cruces, Q. Li, S. L. Valk, D. S. Margulies, B. Mišić, D. Bzdok, J. Smallwood, and B. C. Bernhardt, “Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function”, NeuroImage, 224:117429, 2021.

I am a brand-new Assistant Professor at Sungkyunkwan University (SKKU) in South Korea, studying how the brain generates complex and intelligent behaviors. I am affiliated with the Institute for Basic Science (IBS) - Center for Neuroscience Imaging Research and the Department of Biomedical Engineering.

Previously, I was a postdoctoral associate/research scientist at MIT, working with Mehrdad Jazayeri, and at Yale, working with Daeyeol Lee. I obtained my Ph.D. in neuroscience from Seoul National University, mentored by Sang-hun Lee, and my master’s/undergrad from KAIST, mentored by Jaeseung Jeong.

My area of research is cognitive and systems neuroscience. I have been investigating how the brain measures and processes time using multiple approaches: behavioral experiments, computational modeling (e.g., Bayesian theory), human neuroimaging (EEG/fMRI), and electrophysiology in non-human primates. In my new lab, I will combine these techniques to study how the prefrontal and posterior parietal cortices process information about magnitude (time, number, and space).

In my spare time (if I have any!), I enjoy spending time with my daughters outdoors (camping,skiing) and would love to adopt a dog.

Recent Updates

February 2023: I start my own lab at Sungkyunkwan University (SKKU), Department of Biomedical Engineering & Institute for Basic Science - Center for Neuroscience Imaging Research

January 2023: Manuel & Nico’s work titled “Parametric control of flexible timing through low-dimensional neural manifolds”, which I am a part of, is published in Neuron

November 2022: Reza & Andrew’s work titled “A large-scale neural network training framework for generalized estimation of single-trial population dynamics”, which I am a part of, is published in Nature Methods

October 2022: Jason’s work that I mentored is accepted as an oral presentation in NeurIPS workshop

October 2021: My review paper with Devika titled “Neural implementations of Bayesian inference” is published in Current Opinion in Neurobiology

June 2021: My work titled “Validating model-based Bayesian integration using prior–cost metamers” is published in PNAS