Thesis
Mapping dynamic brain networks with MEG data using machine learning
- Abstract:
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This thesis mainly concerns the analysis of non-invasive electrophysiological data, focusing on development of new methodologies for extracting more information from existing datasets. The primary object of interest is the temporal structure in brain network activity, in particular, time-varying functional connectivity (FC), which has been linked to cognition, demographics and disease states. Statistical machine learning and deep learning allows researchers to formulate generative models s...
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- Files:
-
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(Preview, Dissemination version, pdf, 23.0MB, Terms of use)
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Authors
Contributors
+ Gohil, C
- Institution:
- University of Oxford
- Division:
- MSD
- Department:
- Psychiatry
- Role:
- Supervisor
- ORCID:
- 0000-0002-0888-1207
+ Woolrich, M
- Institution:
- University of Oxford
- Division:
- MSD
- Department:
- Psychiatry
- Role:
- Supervisor
+ Parker Jones, O
- Institution:
- University of Oxford
- Division:
- MPLS
- Department:
- Engineering Science
- Role:
- Examiner
+ Nagarajan, S
- Role:
- Examiner
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- https://ror.org/0439y7842
- Funding agency for:
- Huang, R
- Grant:
- EP/S02428X/1
- Programme:
- EPSRC Centre for Doctoral Training in Health Data Science
+ Wellcome Trust
More from this funder
- Funder identifier:
- https://ror.org/029chgv08
- Funding agency for:
- Gohil, C
- Woolrich, M
- Grant:
- 215573/Z/19/Z
- 106183/Z/14/Z
- 215573/Z/19/Z
+ Medical Research Council
More from this funder
- Funder identifier:
- https://ror.org/03x94j517
- Funding agency for:
- Woolrich, M
- Grant:
- RG94383
- RG89702
+ National Institute for Health Research
More from this funder
- Funder identifier:
- https://ror.org/0187kwz08
- Funding agency for:
- Woolrich, M
- Grant:
- NIHR203316
- DOI:
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Language:
-
English
- Keywords:
- Subjects:
- Pubs id:
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2095930
- Local pid:
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pubs:2095930
- Deposit date:
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2025-03-12
- ARK identifier:
Terms of use
- Copyright holder:
- Rukuang Huang
- Copyright date:
- 2024
- Licence:
- CC Attribution (CC BY)
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