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Intracortical brain-computer interfaces for improved motor function: a systematic review

  • Matthew W. Holt ORCID logo EMAIL logo , Eric C. Robinson ORCID logo , Nathan A. Shlobin ORCID logo , Jacob T. Hanson ORCID logo and Ismail Bozkurt ORCID logo
Published/Copyright: October 17, 2023
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Reviews in the Neurosciences
From the journal Reviews in the Neurosciences Volume 35 Issue 2

Abstract

In this systematic review, we address the status of intracortical brain-computer interfaces (iBCIs) applied to the motor cortex to improve function in patients with impaired motor ability. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guidelines for Systematic Reviews. Risk Of Bias In Non-randomized Studies – of Interventions (ROBINS-I) and the Effective Public Health Practice Project (EPHPP) were used to assess bias and quality. Advances in iBCIs in the last two decades demonstrated the use of iBCI to activate limbs for functional tasks, achieve neural typing for communication, and other applications. However, the inconsistency of performance metrics employed by these studies suggests the need for standardization. Each study was a pilot clinical trial consisting of 1–4, majority male (64.28 %) participants, with most trials featuring participants treated for more than 12 months (55.55 %). The systems treated patients with various conditions: amyotrophic lateral sclerosis, stroke, spinocerebellar degeneration without cerebellar involvement, and spinal cord injury. All participants presented with tetraplegia at implantation and were implanted with microelectrode arrays via pneumatic insertion, with nearly all electrode locations solely at the precentral gyrus of the motor cortex (88.88 %). The development of iBCI devices using neural signals from the motor cortex to improve motor-impaired patients has enhanced the ability of these systems to return ability to their users. However, many milestones remain before these devices can prove their feasibility for recovery. This review summarizes the achievements and shortfalls of these systems and their respective trials.

Keywords: brain-computer interface; brain-machine interface; implant; motor cortex; intracortical
Corresponding author: Matthew W. Holt, Department of Natural Sciences, University of South Carolina Beaufort, 1 University Blvd, Bluffton, 29909, USA, E-mail:

Acknowledgments

Special thanks to Justin Campbell for his insight, edits, and advice.

  1. Research ethics: Not applicable.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission. The CRediT author statements are described below for the author contributions in this template. Matthew W Holt: Conceptualization, Methodology, Project Administration, Writing – Original Draft, Formal Analysis, Validation, Investigation Eric C Robinson: Investigation, Formal Analysis, Writing – Original Draft Nathan A Shlobin: Resources, Methodology, Investigation, Validation Jacob T Hanson: Writing – Original Draft Ismail Bozkurt: Supervision, Conceptualization, Writing – Original Draft, Resources, Methodology, Validation, Writing – review and editing.

  3. Competing interests: The author(s) state no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: The raw data can be obtained on request from the corresponding author.

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Received: 2023-07-18
Accepted: 2023-09-23
Published Online: 2023-10-17
Published in Print: 2024-02-26

© 2023 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/revneuro-2023-0077
Keywords for this article
brain-computer interface; brain-machine interface; implant; motor cortex; intracortical

Articles in the same Issue

  1. Frontmatter
  2. A review of neuroimaging-based data-driven approach for Alzheimer’s disease heterogeneity analysis
  3. Automated diagnosis of autism with artificial intelligence: State of the art
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