Thesis
Decoding non-invasive brain activity with novel deep-learning approaches
- Abstract:
-
This thesis delves into the world of non-invasive electrophysiological brain signals like electroencephalography (EEG) and magnetoencephalography (MEG), focusing on modelling and decoding such data. The research aims to investigate what happens in the brain when we perceive visual stimuli or engage in covert speech (inner speech) and enhance the decoding performance of such stimuli. The findings have significant implications for the development of brain-computer interfaces (BCIs), leading ...
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Authors
Contributors
+ Woolrich, M
Institution:
University of Oxford
Role:
Supervisor
+ Parker Jones, O
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
+ van Es, M
Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Supervisor
+ Lukasiewicz, T
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Supervisor
ORCID:
0000-0002-7644-1668
Funding
+ Wellcome Centre for Integrative Neuroimaging
More from this funder
Funder identifier:
https://ror.org/0172mzb45
Grant:
MSD2021_1362642
Programme:
WIN studentship
Bibliographic Details
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- DOI:
Item Description
- Language:
-
English
- Keywords:
- Subjects:
- Deposit date:
-
2024-04-27
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