Evidence map›Paper›PMID 40309789›Full record

ReviewBrain sciences2025

Invasive Brain-Computer Interface for Communication: A Scoping Review.

Shujhat Khan, Leonie Kallis, Harry Mee, Salim El Hadwe, Damiano Barone, Peter Hutchinson, Angelos Kolias

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Brain sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026
    Review
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

7 authors.

Shujhat KhanDepartment of Clinical Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK.ORCID 0000-0001-7125-4815
Leonie KallisDepartment of Medicine, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, UK.
Harry MeeDepartment of Clinical Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK.ORCID 0000-0002-1314-3962
Salim El HadweDepartment of Clinical Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK.
Damiano BaroneDepartment of Clinical Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK.ORCID 0000-0002-0091-385X
Peter HutchinsonDepartment of Clinical Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK.
Angelos KoliasDepartment of Clinical Neuroscience, University of Cambridge, Cambridge CB2 1TN, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid expansion of the brain-computer interface for patients with neurological deficits has garnered significant interest, and for patients, it provides an additional route where conventional rehabilitation has its limits. This has particularly been the case for patients who lose the ability to communicate. Circumventing neural injuries by recording from the intact cortex and subcortex has the potential to allow patients to communicate and restore self-expression. Discoveries over the last 10-15 years have been possible through advancements in technology, neuroscience, and computing. By examining studies involving intracranial brain-computer interfaces that aim to restore communication, we aimed to explore the advances made and explore where the technology is heading.

methodsFor this scoping review, we systematically searched PubMed and OVID Embase. After processing the articles, the search yielded 41 articles that we included in this review.

resultsThe articles predominantly assessed patients who had either suffered from amyotrophic lateral sclerosis, cervical cord injury, or brainstem stroke, resulting in tetraplegia and, in some cases, difficulty speaking. Of the intracranial implants, ten had ALS, six had brainstem stroke, and thirteen had a spinal cord injury. Stereoelectroencephalography was also used, but the results, whilst promising, are still in their infancy. Studies involving patients who were moving cursors on a screen could improve the speed of movement by optimising the interface and utilising better decoding methods. In recent years, intracortical devices have been successfully used for accurate speech-to-text and speech-to-audio decoding in patients who are unable to speak.

conclusionsHere, we summarise the progress made by BCIs used for communication. Speech decoding directly from the cortex can provide a novel therapeutic method to restore full, embodied communication to patients suffering from tetraplegia who otherwise cannot communicate.

Indexed as

ALSBCIbrain–computer interfacebrain–machine interfaceECoGmultielectrode arrayneurotechnologyparalysisspinal cordstereoelectroencephalographystroke

Identifiers

PMID40309789
PMCPMC12026362

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.