Evidence map›Paper›PMID 40731219›Full record

ReviewTrends in cognitive sciences2026

Brain-computer interfaces as a causal probe for scientific inquiry.

Asma Motiwala, Joana Soldado-Magraner, Aaron P Batista, Matthew A Smith, Byron M Yu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Trends in cognitive sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Live Spike Sorting of Large-scale Neural Recordings.bioRxiv : the preprint server for biology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Asma MotiwalaDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Joana Soldado-MagranerDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Aaron P BatistaDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA 15213, USA.
Matthew A SmithDepartment of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Byron M YuDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: byronyu@cmu.edu.

Funding

Shaping Neural Population Dynamics to Facilitate LearningR01HD071686 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BATISTA, AARON PAUL, CHASE, STEVEN M · 2011 to 2021
$3.7M
Memory Formation in Motor CortexR01NS129584 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Aaron Paul Batista, Steven M Chase · 2022 to 2026
$2.8M
Interrogating and Perturbing Neural DynamicsR01NS105318 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Aaron Paul Batista, Steven M Chase · 2017 to 2026
$2.3M
CRCNS: Modulating Neural Population Interactions between Cortical AreasR01MH118929 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI SMITH, MATTHEW A, YU, BYRON M. · 2018 to 2022
$1.7M
NICHD NIH HHS R01 HD071686NIMH NIH HHS R01 MH118929NINDS NIH HHS R01 NS105318NINDS NIH HHS R01 NS129584
6 · The paper itself

Abstract

Establishing causal relationships between neural activity and brain function requires experimental perturbations of neural activity. Many existing perturbation methods modify activity by directly applying external signals to the brain. We review an alternative approach where brain-computer interfaces (BCIs) leverage volitional control of neural activity to manipulate and causally perturb it. We highlight the potential of BCIs to manipulate neural activity in ways that are flexible, accurate, and adhere to intrinsic biophysical and network-level constraints to investigate the consequences of configuring neural population activity in specified ways. We discuss the advantages and disadvantages of using BCIs as a perturbation tool compared with other perturbation methods and how BCIs can expand the scope of questions that can be addressed about brain function.

Indexed as

BrainBrain-Computer InterfacesHumansbrain–computer interfacebrain stimulationclosed-loopneural activity perturbationsneural population activityneurofeedback

Identifiers

PMID40731219
PMCPMC12313151

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.