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The emerging field of cognitive brain-computer interfaces.

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Title: The emerging field of cognitive brain-computer interfaces.
Authors: Saez I; Departments of Neuroscience, Neurosurgery and Neurology, Friedman Brain Institute and Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, S10-113, New York, NY 10029, USA. Electronic address: ignacio.saez@mssm.edu.
Source: Trends in cognitive sciences [Trends Cogn Sci] 2026 Oct; Vol. 30 (10), pp. 881-902. Date of Electronic Publication: 2026 Jul 17.
Publication Type: Journal Article; Review
Language: English
Journal Info: Publisher: Elsevier Science Country of Publication: England NLM ID: 9708669 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-307X (Electronic) Linking ISSN: 13646613 NLM ISO Abbreviation: Trends Cogn Sci Subsets: MEDLINE
Imprint Name(s): Original Publication: Kidlington, Oxford, UK : Elsevier Science, c1997-
MeSH Terms: Cognition*/physiology , Brain*/physiology , Brain-Computer Interfaces*, Humans ; Animals
Abstract: Brain-computer interfaces (BCIs) have achieved transformative success in restoring movement and communication. However, extending these approaches to decoding or recovery of cognitive function, such as attention or memory, poses fundamentally new challenges. Cognitive BCIs will need to contend with distributed and dynamic neural processes that differ sharply from the more localized, stable representations underlying motor and language control, imposing new technical and conceptual demands. Conversely, neuromodulation, long used in neurological and psychiatric therapies, offers a complementary methodological path and initial translational applications through causal modulation of cognitive circuits. Integrating these approaches into adaptive, closed-loop systems could allow cognitive BCIs to restore mental function and bridge systems neuroscience and next-generation neurotherapeutics capable of monitoring and shaping human cognition in real time.
(Copyright © 2026. Published by Elsevier Ltd.)
Competing Interests: Declaration of interests The author declares no competing interests.
Contributed Indexing: Keywords: brain–computer interface; cognition; foundation models; neuromodulation; neurotechnology; therapeutics
Entry Date(s): Date Created: 20260717 Date Completed: 20261006 Latest Revision: 20261006
Update Code: 20261007
DOI: 10.1016/j.tics.2026.06.012
PMID: 42469083
Database: MEDLINE
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  Data: <searchLink fieldCode="AU" term="%22Saez+I%22">Saez I</searchLink>; Departments of Neuroscience, Neurosurgery and Neurology, Friedman Brain Institute and Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, 1470 Madison Ave, S10-113, New York, NY 10029, USA. Electronic address: ignacio.saez@mssm.edu.
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  Data: <searchLink fieldCode="JN" term="%229708669%22">Trends in cognitive sciences</searchLink> [Trends Cogn Sci] 2026 Oct; Vol. 30 (10), pp. 881-902. <i>Date of Electronic Publication: </i>2026 Jul 17.
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  Data: Brain-computer interfaces (BCIs) have achieved transformative success in restoring movement and communication. However, extending these approaches to decoding or recovery of cognitive function, such as attention or memory, poses fundamentally new challenges. Cognitive BCIs will need to contend with distributed and dynamic neural processes that differ sharply from the more localized, stable representations underlying motor and language control, imposing new technical and conceptual demands. Conversely, neuromodulation, long used in neurological and psychiatric therapies, offers a complementary methodological path and initial translational applications through causal modulation of cognitive circuits. Integrating these approaches into adaptive, closed-loop systems could allow cognitive BCIs to restore mental function and bridge systems neuroscience and next-generation neurotherapeutics capable of monitoring and shaping human cognition in real time.<br /> (Copyright © 2026. Published by Elsevier Ltd.)
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  Data: Declaration of interests The author declares no competing interests.
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  Data: <i>Keywords: </i>brain–computer interface; cognition; foundation models; neuromodulation; neurotechnology; therapeutics
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