Spatio-temporal dynamics in fMRI recordings revealed with complex independent component analysis

被引:17
作者
Anemuller, Jorn
Duann, Jeng-Ren
Sejnowski, Terrence J.
Makeig, Scott
机构
[1] Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA USA
[2] Salk Inst Biol Studies, Computat Neurobiol Lab, La Jolla, CA USA
关键词
complex independent component analysis (complex ICA); convolution model; spatio-temporal dynamics; functional magnetic resonance imaging (fMRI); hemodynamic response; primary visual cortex (VI); biomedical signal analysis; statistical signal processing;
D O I
10.1016/j.neucom.2005.12.029
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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 spatio-temporal 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 (VI) 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 V1. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1502 / 1512
页数:11
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