Okito Yamashita, Department head of CBI in ATR

ATR , Neural Information Analysis Laboratories, Department of Computational Brain Imaging
RikenAIP, Computational Brain Dynamics team (link) 

Applications of Bayesian inference to noninvasive brain imaging data such as fMRI, MEG, EEG and NIRS.
Main applications are
– Diffusion optical tomography (2010 )
– MEG/EEG Source Localization Problem (2001)
– Brain Computer Interface (2007)
– fMRI decoding. (2005)
Main tools in statistics are
– Time Series Analysis (AR model., Hidden Markov model, State Space model)
– Sparse Bayesian Learning (Automatic Relevance Determination Priors, Variational Bayesian algorithm). 

ADRESS : 222, Hikaridai, Seikacho, Sorakugun, Kyoto 6190288, Japan
TELL : +81774951073
FAX : +81774951259
Email : oyamashi(at)atr.jp 

2016 November – 
RikenAIP, Computational Brain Dynamics team (concurrent post)
 Big data analysis of brain imaging data, method development for exploring brain imagingbased psychiatric biomarker

2013 April – 
ATR, Neural Information Analysis Laboratories, Deparment head
 Brain network dynamics estimation with the multimodal integration approach

2010 April – 2013 March 
ATR, Neural Information Analysis Laboratories, Senior Researcher
 Crossfreuqency coupling of ECoG data (data analysis, method proposal)
 Diffusion optical tomography (experimental validation, data analysis, toolbox)

2004 Semptember – 2009 March 
ATR, Computational Neuroscience Laboratories, Researcher
 Source localization method with MEG/EEGfMRI mutlimodal integration (method extension, toolbox)
 EEG/NIRS combined brain machine interface (data analysis)
 Sparse classification for fMRI decoding and brain machine interface (method proposal, toolbox)

2004 AprilAugust 
Institute of statistical mathematics, Parttime researcher
 dynamic source localization extended to nonstationary case (method proposal)



Ph.D. in Statitics, 2004 
The Graduate University for Advanced Studies, Department of Statistical Science
 Application of the statistical timeseries analysis to neuroimaging data
 Effective connectivity estimation of fMRI (Granger causality analysis)
 Dynamic source localization of EEG (High dimensional Kalman filter)
Title of Ph.D. thesis : Dynamical Inverse Problem and Causality Analysis of fMRI Data [PDF file] 
M.A. in Engineering, 2001 
The University of Tokyo, Faculty of Engineering, Department of Mathematical Engineering and Information Physics
 Parameter estimation problem of nonlinear AR model

B.A. in Engineering, 1999 
The University of Tokyo, Faculty of Engineering, Department of Mathematical Engineering and Information Physics
 Observation noise reduction of chaotic dynamical model


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