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Discovering dynamic brain networks from big data in rest and task

Abstract:

Brain activity is a dynamic combination of the responses to sensory inputs and its own spontaneous processing. Consequently, such brain activity is continuously changing whether or not one is focusing on an externally imposed task. Previously, we have introduced an analysis method that allows us, using Hidden Markov Models (HMM), to model task or rest brain activity as a dynamic sequence of distinct brain networks, overcoming many of the limitations posed by sliding window approaches. Here, w...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.neuroimage.2017.06.077

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Institution:
University of Oxford
Oxford college:
St Edmund Hall
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
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Funding agency for:
Vidaurre, D
Grant:
Strategic Award (098369/Z/12/Z
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Funding agency for:
Woolrich, M
Grant:
MEG Partnership Grant (MR/K005464/1
More from this funder
Funding agency for:
Woolrich, M
Grant:
MEG Partnership Grant (MR/K005464/1
Publisher:
Elsevier Publisher's website
Journal:
NeuroImage Journal website
Volume:
180
Issue:
B
Pages:
646-656
Publication date:
2017-06-28
Acceptance date:
2017-06-29
DOI:
ISSN:
1053-8119
Language:
English
Keywords:
Pubs id:
pubs:707823
UUID:
uuid:86678704-f293-4a95-a392-5922b259cdad
Local pid:
pubs:707823
Deposit date:
2017-07-13

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