Thesis
Scalable and interpretable spatial models for neuroimaging applications
- Abstract:
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Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and structural MRI, have become essential tools for understanding function and pathology of the human brain. fMRI allows researchers to identify brain regions associated with specific cognitive and behavioural processes by measuring blood-oxygen-level-dependent (BOLD) signals. Structural MRI provides high-resolution mapping of brain anatomy, allowing for the identification of morphological alternations, such as w...
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- Files:
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(Preview, Dissemination version, pdf, 11.5MB, Terms of use)
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Authors
Contributors
+ Nichols, TE
- Institution:
- University of Oxford
- Division:
- MSD
- Department:
- Nuffield Department of Population Health
- Sub department:
- Big Data Institute - NDPH
- Role:
- Supervisor
- ORCID:
- 0000-0002-4516-5103
+ Griffanti, L
- Institution:
- University of Oxford
- Division:
- MSD
- Department:
- Psychiatry
- Oxford college:
- Kellogg College
- Role:
- Examiner
- ORCID:
- 0000-0002-0540-9353
+ Eickhoff, S
- Institution:
- Heinrich-Heine-Universität Düsseldorf
- Role:
- Examiner
+ National Institutes of Health
More from this funder
- Funder identifier:
- https://ror.org/01cwqze88
- Funding agency for:
- Yu, Y
- Nichols, TE
- Grant:
- H6R00550_CS00.01
- Programme:
- Large-scale image-based meta-analysis of functional MRI data
+ Engineering and Physical Sciences Research Council
More from this funder
- Funder identifier:
- https://ror.org/0439y7842
- DOI:
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Language:
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English
- Keywords:
- Subjects:
- Deposit date:
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2025-07-29
- ARK identifier:
Terms of use
- Copyright holder:
- Yifan Yu
- Copyright date:
- 2025
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