Evidence map›Paper›PMID 41846866›Full record

ReviewEye and brain2026

Brain-Computer Interfaces for Vision Recovery in Precortical Vision Loss.

Christopher D Yang, Alan Guo, Ken Y Lin

Abstract readReview
In one paragraph

Review in Eye and brain, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Christopher D YangGavin Herbert Eye Institute, University of California Irvine, Irvine, CA, USA.ORCID 0000-0002-2090-1880
Alan GuoDepartment of Computer Science, University of California Irvine, Irvine, CA, USA.
Ken Y LinGavin Herbert Eye Institute, University of California Irvine, Irvine, CA, USA.ORCID 0000-0002-6467-7219

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Precortical vision loss remains a major global health challenge. Advances in brain-computer interfaces (BCIs) offer a new pathway towards restoring functional vision by bypassing damaged structures in the visual pathway. Methods: This narrative review aims to synthesize the current evidence on BCIs for precortical vision recovery, including non-invasive and invasive techniques. Device design, testing, and outcomes are discussed, with an emphasis on developments in technology and engineering. Results: Non-invasive BCIs induce neuroplasticity and may restore vision in conditions of precortical vision loss such as glaucoma and optic neuropathy. Cortical visual prostheses demonstrate the ability to evoke visual precepts and recover functional vision. Integration of artificial intelligence and high-density electrode arrays has improved image encoding and device adaptability to enhance user experience and rehabilitation potential. Patient selection, safety, and long-term outcomes remain active areas of investigation. Discussion: BCIs present a paradigm shift in treating precortical blindness that offers hope for patients with no alternative options. Yet, challenges persist, including surgical risks, durability, and variability in response. Personalization of stimulation protocols and further technical refinement are needed to optimize efficacy and accessibility. Conclusion: BCIs are a promising experimental modality for precortical vision restoration. Continued research and interdisciplinary collaboration are essential to address current limitations.

Indexed as

blindnessbrain computer interfacesneuroplasticityneuroprosthesesvision restoration

Identifiers

PMID41846866
PMCPMC12991285

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.