Research Project
Grant-in-Aid for Scientific Research (C)
For the diagnosis of epilepsy, concurrent EEG and fMRI recording has been studied to detect epileptic spike train related brain blood flow. The standard method of data analysis is based on regression analysis and it employs convoluted epileptic spike trains on EEG data with canonical HRF as a reference function. It enables to graphically show epileptic blood flows in three dimensional space and detect the location of epileptic foci. Moreover it is possible to estimate some interaction or network system between foci. This achievement is very helpful for medication or surgical treatment objectives.However, there are some points in the data analysis to be improved. In the standard analysis, a canonical HRF in common shape is used for all regions in the brain and for all subjects. Therefore only the activation, whose temporal changing is morphologically similar to the reference function, can be detected. In this study, we introduce an innovation approach based on auto regressive(AR) model to detect dynamical difference during seizure comparing to seizure free epoch without employing reference function. Moreover we developed an algorithm to ecstatically evaluate the significance of abnormal blood flow and map on the anatomical brain image.
All 2012 2011 2010 2009 Other
All Journal Article (6 results) (of which Peer Reviewed: 3 results) Presentation (9 results) Remarks (1 results)
統計数理
Volume: (in press)
120006020413
Volume: (掲載確定)(巻未定)(頁未定)
IEEE Transactions on Medical Imaging
Volume: 30-3 Issue: 3 Pages: 859-866
10.1109/tmi.2011.2104419
Journal of Integrative Neuroscience
Volume: 9 Pages: 381-406
http://www.ism.ac.jp/souran/kenkyusya/miwakeichi_fumikazu.html
