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Spatial vs. temporal features in ICA of resting-state fMRI - A quantitative and qualitative investigation in the context of response inhibition

Abstract:
Independent component analysis (ICA) can identify covarying functional networks in the resting brain. Despite its relatively widespread use, the potential of the temporal information (unlike spatial information) obtained by ICA from resting state fMRI (RS-fMRI) data is not always fully utilized. In this study, we systematically investigated which features in ICA of resting-state fMRI relate to behaviour, with stop signal reaction time (SSRT) in a stop-signal task taken as a test case. We did this by correlating SSRT with the following three kinds of measure obtained from RS-fMRI data: (1) the amplitude of each resting state network (RSN) (evaluated by the standard deviation of the RSN timeseries), (2) the temporal correlation between every pair of RSN timeseries, and (3) the spatial map of each RSN. For multiple networks, we found significant correlations not only between SSRT and spatial maps, but also between SSRT and network activity amplitude. Most of these correlations are of functional interpretability. The temporal correlations between RSN pairs were of functional significance, but these correlations did not appear to be very sensitive to finding SSRT correlations. In addition, we also investigated the effects of the decomposition dimension, spatial smoothing and Z-transformation of the spatial maps, as well as the techniques for evaluating the temporal correlation between RSN timeseries. Overall, the temporal information acquired by ICA enabled us to investigate brain function from a complementary perspective to the information provided by spatial maps.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pone.0066572

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Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author


Publisher:
Public Library of Science
Journal:
PloS ONE More from this journal
Volume:
8
Issue:
6
Pages:
ARTN e66572
Publication date:
2013-06-18
Acceptance date:
2013-05-08
DOI:
EISSN:
1932-6203
ISSN:
1932-6203


Language:
English
Keywords:
Pubs id:
409904
UUID:
uuid:01c06e09-1303-406a-bc87-590bd84fa088
Local pid:
pubs:409904
Source identifiers:
409904
Deposit date:
2013-11-16
ARK identifier:

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