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Human learning of noninvasive brain-computer interfaces via manifold geometry.

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Τίτλος: Human learning of noninvasive brain-computer interfaces via manifold geometry.
Συγγραφείς: Busch EL; Department of Psychology, Yale University, New Haven, CT, USA.; Wu Tsai Institute, Yale University, New Haven, CT, USA., Fincke EC; Department of Psychology, Yale University, New Haven, CT, USA., Lajoie G; Department of Mathematics and Statistics, Université de Montréal, Montreal, Quebec, Canada.; Mila, Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada., Krishnaswamy S; Wu Tsai Institute, Yale University, New Haven, CT, USA. smita.krishnaswamy@yale.edu.; Mila, Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada. smita.krishnaswamy@yale.edu.; Department of Computer Science, Yale University, New Haven, CT, USA. smita.krishnaswamy@yale.edu.; Department of Genetics, Yale University, New Haven, CT, USA. smita.krishnaswamy@yale.edu.; Program in Applied Mathematics, Yale University, New Haven, CT, USA. smita.krishnaswamy@yale.edu., Turk-Browne NB; Department of Psychology, Yale University, New Haven, CT, USA. nicholas.turk-browne@yale.edu.; Wu Tsai Institute, Yale University, New Haven, CT, USA. nicholas.turk-browne@yale.edu.
Πηγή: Nature neuroscience [Nat Neurosci] 2026 Oct; Vol. 29 (10), pp. 2429-2437. Date of Electronic Publication: 2026 Jun 09.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Nature Publishing Group Country of Publication: United States NLM ID: 9809671 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1546-1726 (Electronic) Linking ISSN: 10976256 NLM ISO Abbreviation: Nat Neurosci Subsets: MEDLINE
Imprint Name(s): Publication: <2002->: New York, NY : Nature Publishing Group
Original Publication: New York, NY : Nature America Inc., c1998-
Ιατρικοί όροι (MeSH): Brain*/physiology , Brain*/diagnostic imaging , Learning*/physiology , Brain-Computer Interfaces*, Magnetic Resonance Imaging/methods ; Brain Mapping/methods ; Spatial Navigation/physiology ; Humans ; Avatar ; Female ; Male ; Video Games ; Adult ; Young Adult
Περίληψη: Brain-computer interfaces (BCIs) promise to restore and enhance human capabilities. Yet, their adoption has been limited by slow and inconsistent learning across users. We show that BCI learning is accelerated by leveraging the naturally occurring geometry, or intrinsic manifold, of brain activity, extracted using data diffusion. Participants were trained with real-time functional magnetic resonance imaging to control an avatar in a video game by self-modulating activity in brain regions supporting spatial navigation. We perturbed the mapping between brain activity and avatar movement to test how neural manifolds constrain human BCI learning. When new mappings relied on directions of significant variance on the intrinsic manifold, participants successfully gained control by realigning brain activity along these directions. When new mappings did not follow the intrinsic manifold, participants could not learn to control the avatar. These findings show how manifold geometry in higher-order brain regions guides human learning of complex cognitive tasks, identifying a principle for improving future neurotechnologies.
(© 2026. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Competing Interests: Competing interests: S.K. is a cofounder and CSO of Latent Alpha. The other authors declare no competing interests.
Σχόλια: Update of: bioRxiv. 2025 Apr 03:2025.03.29.646109. doi: 10.1101/2025.03.29.646109.. (PMID: 40236074)
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Grant Information: R01GM135929 U.S. Department of Health & Human Services | National Institutes of Health (NIH); R01 GM130847 United States GM NIGMS NIH HHS; R01MH069456 U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH); 1839308 National Science Foundation (NSF); R01 GM135929 United States GM NIGMS NIH HHS; 2139841 National Science Foundation (NSF); R01GM130847 U.S. Department of Health & Human Services | National Institutes of Health (NIH); 2047856 National Science Foundation (NSF); FG-2021-15883 Alfred P. Sloan Foundation; R01 MH069456 United States MH NIMH NIH HHS
Entry Date(s): Date Created: 20260609 Date Completed: 20261002 Latest Revision: 20261005
Update Code: 20261005
PubMed Central ID: PMC13318486
DOI: 10.1038/s41593-026-02311-2
PMID: 42265352
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1546-1726
DOI:10.1038/s41593-026-02311-2