Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA

Jörn Anemüller; Jeng Ren Duann; Terrence J. Sejnowski; Scott Makeig

doi:10.1007/978-3-540-30110-3_139

Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA

Jörn Anemüller, Jeng Ren Duann, Terrence J. Sejnowski, Scott Makeig

認知神經科學研究所

研究成果: 書貢獻/報告類型 › 篇章 › 同行評審

3 引文斯高帕斯（Scopus）

摘要

Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatiotemporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA approach: spatial complex ICA applied to frequency-domain fMRI data. In several frequency-bands, we identify components pertaining to activity in primary visual cortex (V1) and blood supply vessels. One such component, obtained in the 0.10-Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1¹.

原文	???core.languages.en_GB???
主出版物標題	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編輯	Carlos G. Puntonet, Alberto Prieto
發行者	Springer Verlag
頁面	1103-1110
頁數	8
ISBN（電子）	3540230564, 9783540230564
DOIs	https://doi.org/10.1007/978-3-540-30110-3_139
出版狀態	已出版 - 2004

出版系列

名字	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	3195
ISSN（列印）	0302-9743
ISSN（電子）	1611-3349

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10.1007/978-3-540-30110-3_139

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Anemüller, J., Duann, J. R., Sejnowski, T. J., & Makeig, S. (2004). Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA. 於 C. G. Puntonet, & A. Prieto (編輯), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (頁 1103-1110). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 3195). Springer Verlag. https://doi.org/10.1007/978-3-540-30110-3_139

Anemüller, Jörn ; Duann, Jeng Ren ; Sejnowski, Terrence J. 等. / Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 編輯 / Carlos G. Puntonet ; Alberto Prieto. Springer Verlag, 2004. 頁 1103-1110 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Anemüller, J, Duann, JR, Sejnowski, TJ & Makeig, S 2004, Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA. 於 CG Puntonet & A Prieto (編輯), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 3195, Springer Verlag, 頁 1103-1110. https://doi.org/10.1007/978-3-540-30110-3_139

Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA. / Anemüller, Jörn; Duann, Jeng Ren; Sejnowski, Terrence J. 等.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 編輯 / Carlos G. Puntonet; Alberto Prieto. Springer Verlag, 2004. p. 1103-1110 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 3195).

研究成果: 書貢獻/報告類型 › 篇章 › 同行評審

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AB - Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatiotemporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA approach: spatial complex ICA applied to frequency-domain fMRI data. In several frequency-bands, we identify components pertaining to activity in primary visual cortex (V1) and blood supply vessels. One such component, obtained in the 0.10-Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V11.

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Anemüller J, Duann JR, Sejnowski TJ, Makeig S. Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA. 於 Puntonet CG, Prieto A, 編輯, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2004. p. 1103-1110. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-30110-3_139

Unraveling spatio-temporal dynamics in fMRI recordings using complex ICA

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