Unraveling spatio-temporal dynamics in fMRI recordings using complex RCA
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作者:
Anemüller, J
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机构:
Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA USAUniv Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA USA
Anemüller, J
[1
]
Duann, JR
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机构:Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA USA
Duann, JR
Sejnowski, TJ
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机构:Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA USA
Sejnowski, TJ
Makeig, S
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机构:Univ Calif San Diego, Inst Neural Computat, Swartz Ctr Computat Neurosci, La Jolla, CA USA
Makeig, S
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
来源:
INDEPENDENT COMPONENT ANALYSIS AND BLIND SIGNAL SEPARATION
|
2004年
/
3195卷
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D O I:
暂无
中图分类号:
TP301 [理论、方法];
学科分类号:
081202 ;
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.