Multi-modal Modeling of Human Brain Activity.
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My research focuses on developing new analysis methods to study neural information processing, with an emphasis on dynamic aspects of human brain activity.
Real-life behaviour such as conversation, sports, household tasks and so on, depend on the dynamic coordination of brain activity in multiple brain regions. Elucidating the nature of such inter-regional communication is critical for us to understand behaviour. Currently, we have a number of non-invasive human brain measurement techniques available: fMRI, MEG, EEG and NIRS, each with its advantages and disadvantages but with no single technique sufficient to comprehensively understand the brain. My research focuses on multi-modal integration analysis – developing quantitative models that combine information for multiple measurement techniques. In particular we pursue integration of MEG and fMRI data to provide high temporal and high spatial resolution. Our approach is based on constructing a generative model of the dynamics of brain activity, and inferring the model structure using Bayesian statistics.
One of our current projects is construction of sophisticated models of the network dynamics of brain activity so that we can perform realistic simulations of signals recordable by MEG, EEG, fMRI, and NIRS. In particular, we are developing methods to incorporate anatomical network information within these models. Elsewhere, we are developing new diffuse optical tomography algorithms to make NIRS measurements a more reliable tool for ambulant brain activity measurement.
Shimokawa T, Kosaka T, Yamashita O, Hiroe N, Amita T, Inoue Y, and Sato M (2012),
"Hierarchical Bayesian estimation improves depth accuracy and spatial resolution of diffuse optical tomography", Optics Express, Vol.20, 20427-20446
Fukushima M, Yamashita O, Kanemura a, Ishii S, Kawato M, and Sato M (2012),"A State-Space Modeling Approach for Localization of Focal Current Sources From MEG". IEEE Transaction on Biomed. Eng., Vol.59,1561-1571
Miyawaki Y, Uchida H, Yamashita O, Sato M, Morito Y, Tanabe H, Sadato N, Kamitani Y (2008), "Visual image reconstruction from human brain activity using a combination of multiscale local image decoders". Neuron, Vol.60(5):915-29.
Yamashita O, Sato M, Yoshioka T, Tong F, Kamitani Y (2008). "Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns". Neuroimage. Vol.42(4):1414-29.
Yamashita O, Galka a, Ozaki T, Biscay R and Valdes-Sosa P (2004), "Recursive Penalized Least Squares Solution for Dynamical Inverse Problems of EEG Generation", Human Brain Mapping, Vol.21, Issue 4, pp.221-235
2013 Department head in ATR, Department of Computational Brain Imaging
2004-2013 Researcher in ATR, Computational Neuroscience Laboratories
2004 Phd in statistics, The Graduate University for Advanced Studies, Department of Statistical Science
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