
ATR
Neural Information Analysis Laboratories
Department of Computational Brain Imaging 


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


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

