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Journal article

Task-evoked dynamic network analysis through hidden Markov modelling

Abstract:

Complex thought and behaviour arise through dynamic recruitment of large-scale brain networks. The signatures of this process may be observable in electrophysiological data; yet robust modelling of rapidly changing functional network structure on rapid cognitive timescales remains a considerable challenge. Here, we present one potential solution using Hidden Markov Models (HMMs), which are able to identify brain states characterised by engaging distinct functional networks that reoccur over t...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.3389/fnins.2018.00603

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Oxford college:
St Edmund Hall
Role:
Author
ORCID:
0000-0003-2267-9897
More by this author
Institution:
University of Oxford
Division:
Medical Sciences
Department:
Psychiatry
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences
Department:
Experimental Psychology
Role:
Author
More from this funder
Funding agency for:
Nobre, A
Woolrich, M
Grant:
104571/Z/14/Z
106183/Z/14/Z
203139/Z/16/Z
National Institute for Health Research, Oxford Health Biomedical Research Centre More from this funder
Publisher:
Frontiers Media Publisher's website
Journal:
Frontiers in Neuroscience Journal website
Volume:
12
Publication date:
2018-08-28
Acceptance date:
2018-08-09
DOI:
EISSN:
1662-4548
Keywords:
Pubs id:
pubs:907544
UUID:
uuid:c5acfc98-f799-4eff-9841-ea47b3504107
Local pid:
pubs:907544
Deposit date:
2018-08-16

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