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
Actions
Authors
Funding
+ Wellcome Trust
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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
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Bibliographic Details
- 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
Item Description
- Keywords:
- Pubs id:
-
pubs:907544
- UUID:
-
uuid:c5acfc98-f799-4eff-9841-ea47b3504107
- Local pid:
- pubs:907544
- Deposit date:
- 2018-08-16
Terms of use
- Copyright holder:
- Quinn et al
- Copyright date:
- 2018
- Notes:
-
Copyright © 2018 Quinn, Vidaurre, Abeysuriya, Becker, Nobre and Woolrich. This
is an open-access article distributed under the terms of the Creative Commons
Attribution License (CC BY). The use, distribution or reproduction in other forums
is permitted, provided the original author(s) and the copyright owner(s) are credited
and that the original publication in this journal is cited, in accordance with accepted
academic practice. No use, distribution or reproduction is permitted which does not
comply with these terms.
- Licence:
- CC Attribution (CC BY)
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