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Variance decomposition for single-subject task-based fMRI activity estimates across many sessions

Abstract:

Here we report an exploratory within-subject variance decomposition analysis conducted on a task-based fMRI dataset with an unusually large number of repeated measures (i.e., 500 trials in each of three different subjects) distributed across 100 functional scans and 9 to 10 different sessions. Within-subject variance was segregated into four primary components: variance across-sessions, variance across-runs within a session, variance across-blocks within a run, and residual measurement/modeli...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.neuroimage.2016.10.024

Authors


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Role:
Author
ORCID:
0000-0002-6520-5125
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Institution:
University of Oxford
Division:
MSD
Department:
Nuffield Department of Population Health
Sub department:
Clinical Trial Service Unit
Role:
Author
ORCID:
0000-0002-4516-5103
National Institute of Neurological Disorders and Stroke More from this funder
Publisher:
Elsevier Publisher's website
Journal:
NeuroImage Journal website
Volume:
154
Pages:
206-218
Publication date:
2016-10-20
Acceptance date:
2016-10-14
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
Pmid:
27773827
Source identifiers:
908844
Language:
English
Keywords:
Pubs id:
pubs:908844
UUID:
uuid:148ecce6-1db3-4762-a2c5-4509f7fa8f81
Local pid:
pubs:908844
Deposit date:
2018-11-01

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