{"id":11,"date":"2017-09-06T09:29:41","date_gmt":"2017-09-06T00:29:41","guid":{"rendered":"http:\/\/www.cns.atr.jp\/~oyamashi\/?page_id=11"},"modified":"2022-02-14T17:10:35","modified_gmt":"2022-02-14T08:10:35","slug":"profile","status":"publish","type":"page","link":"https:\/\/bicr.atr.jp\/~oyamashi\/profile\/?lang=en","title":{"rendered":"Profile"},"content":{"rendered":"

Okito Yamashita,<\/h2>\n

Department head of CBI in ATR and Team leader of RIKEN-AIP<\/h2>\n

\"Okito<\/p>\n\n\n\n\n\n\n
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  • Affiliation<\/strong><\/li>\n<\/ul>\n<\/td>\n
ATR , Neural Information Analysis Laboratories, Department of Computational Brain Imaging<\/p>\n

RIKEN-AIP, Computational Brain Dynamics team (link<\/a>)<\/td>\n<\/tr>\n

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  • Research Interest<\/strong><\/li>\n<\/ul>\n<\/td>\n
Applications of Bayesian inference to noninvasive brain imaging data such as fMRI, MEG, EEG and NIRS.<\/p>\n

Main applications are
\n– Diffusion optical tomography (2010- )
\n– MEG\/EEG Source Localization Problem\u00a0 (2001-)
\n– Brain Computer Interface (2007-)
\n– fMRI decoding.\u00a0 (2005-)<\/p>\n

Main tools\u00a0 in statistics are
\n– Time Series Analysis (AR model., Hidden Markov model, State Space model)
\n– Sparse Bayesian Learning (Automatic Relevance Determination Priors, Variational Bayesian algorithm).<\/td>\n<\/tr>\n

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  • Contact<\/strong><\/li>\n<\/ul>\n<\/td>\n
ADRESS : 2-2-2, Hikaridai, Seikacho, Sorakugun, Kyoto 619-0288, Japan
\nTELL\u00a0 : +81-774-95-1073
\nFAX \u00a0\u00a0 : +81-774-95-1259
\nE-mail : oyamashi(at)atr.jp<\/td>\n<\/tr>\n
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  • Employment History<\/strong><\/li>\n<\/ul>\n<\/td>\n
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2016 November\u00a0 –<\/td>\nRIKEN-AIP, Computational Brain Dynamics team (concurrent post)<\/p>\n
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  • Big data analysis of brain imaging data,\u00a0 method development for exploring brain imaging-based psychiatric bio-marker<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
2013 April –<\/td>\nATR, Neural Information Analysis Laboratories, Deparment head<\/p>\n
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  • Brain network dynamics estimation with the multimodal integration approach<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
2010 April – 2013 March<\/td>\nATR, Neural Information Analysis Laboratories, Senior Researcher<\/p>\n
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  • Cross-freuqency coupling of ECoG data (data analysis, method proposal)<\/li>\n
  • Diffusion optical tomography (experimental validation, data analysis, toolbox)<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
2004 Semptember – 2009 March<\/td>\nATR, Computational Neuroscience Laboratories, Researcher<\/p>\n
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  • Source localization method with MEG\/EEG-fMRI mutlimodal integration (method extension, toolbox)<\/li>\n
  • EEG\/NIRS combined brain machine interface (data analysis)<\/li>\n
  • Sparse classification for fMRI decoding and brain machine interface (method proposal, toolbox)<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
2004 April-August<\/td>\nInstitute of statistical mathematics,\u00a0 Part-time researcher<\/p>\n
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  • dynamic source localization extended to non-stationary case (method proposal)<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/td>\n<\/tr>\n
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  • Education<\/strong><\/li>\n<\/ul>\n<\/td>\n
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Ph.D. in Statitics, 2004<\/td>\nThe Graduate University for Advanced Studies, Department of Statistical Science<\/p>\n
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  • Application of the statistical timeseries analysis to neuroimaging data<\/li>\n
  • Effective connectivity estimation of fMRI\u00a0\u00a0 (Granger causality analysis)<\/li>\n
  • Dynamic source localization of EEG\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 (High dimensional Kalman filter)<\/li>\n<\/ul>\n

    Title of Ph.D. thesis <\/em>: Dynamical Inverse Problem and Causality Analysis of fMRI Data [PDF file]<\/a><\/td>\n<\/tr>\n

M.A. in Engineering, 2001<\/td>\nThe University of Tokyo, Faculty of Engineering, Department of Mathematical Engineering and Information Physics<\/p>\n
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  • Parameter estimation problem of\u00a0 non-linear AR model<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n
B.A. in Engineering, 1999<\/td>\nThe University of Tokyo, Faculty of Engineering, Department of Mathematical Engineering and Information Physics<\/p>\n