My research interests are in biophysical models and statistical analyses for functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) data, which elucidates the underlying mechanism between neuronal activity and its induced hemodynamic changes during brain activation.
My present research uses dynamic causal modelling (DCM) for (i) making inference about changes in directed connectivity at the neuronal level (i.e., effective connectivity) from 7T fMRI data, and (ii) investigating changes in effective connectivity associated with cognitive and emotional information processing in depression.
A validation of dynamic causal modelling for 7T fMRI
Tak, S, Noh, J, Cheong, C, Zeidman, P, Razi, A, Penny, WD, Friston, KJ, 2018. J Neurosci Methods, 305, 36-45.
Dynamic causal modelling for functional near-infrared spectroscopy
Tak, S, Kempny, AM, Friston, KJ, Leff, AP, Penny, WD, 2015. NeuroImage, 111, 338-349.
Dynamic and static contributions of the cerebrovasculature to the resting-state BOLD signal
Tak, S, Wang, DJ, Polimeni, JR, Yan, L, Chen, JJ, 2014. NeuroImage 84, 672-680.
Quantitative analysis of hemodynamic and metabolic changes in subcortical vascular dementia using simultaneous near-infrared spectroscopy and fMRI measurements
Tak, S, Yoon, SJ, Jang, J, Yoo, K, Jeong, Y, Ye, JC, 2011. NeuroImage 55, 176-184.
Quantification of CMRO2 without hypercapnia using simultaneous near-infrared spectroscopy and fMRI measurements
Tak, S, Jang, J, Lee, K, Ye, JC, 2010. Phys Med Biol 55, 3249-3269.
NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy
Ye, JC*, Tak, S*, Jang, K, Jung, J, Jang, J, 2009. NeuroImage 44, 428-447. * co-first author
Dynamic Causal Modelling for fNIRS
Supervisor: Prof. William Penny
Cerebrovascular Effects on Resting-State fMRI Connectivity
Supervisor: Prof. Jean Chen
Thesis: Statistical Analysis for fNIRS Neuroimaging
Supervisor: Prof. Jong Chul Ye