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