An innovation approach for epileptic fMRI data analysis based on spatio-temporal filtering method
| Project/Area Number |
21500295
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Bioinformatics/Life informatics
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| Research Institution | The Institute of Statistical Mathematics |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
WATANABE Job 平成帝京大学, 薬学部, 准教授 (90409756)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 時空間データ解析 / 異常値検出 / てんかん |
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| Research Abstract |
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.
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Report
(4 results)
Research Products
(16 results)
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[Journal Article] Spatio-temporal correlations from fMRI time series based on the NN-ARx model2010
Author(s)
J. Bosch-Bayard, J. Riera-Diaz, R. Biscay-Lirio, K. Wong, A. Galka, O. Yamashita, N. Sadato, R. Kawashima, E. Aubert-Vazquez, R. Rodriguez-Rojas, P. Valdes-Sosa, F. Miwakeichi and T. Ozaki
Volume
9(4)
Pages
381-406
Related Report
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[Journal Article] Spatio-temporal correlations from fMRI time series based on the NN-ARx model2010
Author(s)
Bosch-Bayard, J., Riera-Diaz, J., Biscay-Lirio, R., Wong,., Galka, A., Yamashita, O., Sadato, N., Kawashima, R., Aubert-Vazquez, E., Rodriguez-Rojas, R., Valdes-Sosa, P., Miwakeichi, F., Tohru, O.
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Journal Title
Journal of Integrative Neuroscience
Volume: 9
Pages: 381-406
Related Report
Peer Reviewed
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