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Authors
Neville, Vikki
Finnegan, Emily
Paul, Elizabeth S.
Davidson, Molly
Dayan, Peter
Mendl, Michael
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Funding
Funding for this research was provided by:
Biotechnology and Biological Sciences Research Council (BB/X009696/1, BB/T002654/1, BB/T002654/1, BB/M009122/1, BB/T002654/1)
Max-Planck-Gesellschaft
Alexander von Humboldt-Stiftung
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Article History
Received: 23 February 2024
Accepted: 20 May 2024
First Online: 26 June 2024
Additional Information
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: VN is funded by a Biotechnology and Biological Sciences Research Council (BBSRC) Discovery Fellowship (BB/X009696/1). MD is funded by the BBSRC SWBio DTP PhD programme (MD: BB/M009122/1). PD is funded by the Max Planck Society and the Humboldt Foundation. PD is a member of the Machine Learning Cluster of Excellence, EXC number 2064/1 - Project number 39072764 and of the Else Kröner Medical Scientist Kolleg ‘ClinbrAIn: Artificial Intelligence for Clinical Brain Research’. This work was also supported by the Biotechnology and Biological Sciences Research Council (BBSRC) grant BB/T002654/1 (PI: MM).
: The authors declare no competing interests.
: Data is provided within the manuscript or supplementary information files.
: Conceptualization: VN, MM, PD, EP. Methodology: all authors. Data collection: EF, MD, VN. Formal analysis: VN, PD, MM. Writing — original draft: VN, PD, MM. Writing — review and editing: all authors.
: This study was conducted at the University of Bristol and received ethical approval (UK Home Office Project License no: P2556FBFE).
: Not applicable
