Evidence map›Paper›PMID 41582168›Full record

ArticleScientific reports2026

Virtual reality mediated brain-computer interface training improves sensorimotor neuromodulation in unimpaired and post spinal cord injury individuals.

Malik Muhammad Naeem Mannan, Dinesh B Palipana, Kyle Mulholland, Evan Jurd, Ewan C R Lloyd, Alastair R J Quinn, Claire B Crossley, Mohammad Fazle Rabbi, David G Lloyd, Yang D Teng and 1 more

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

11 authors.

Malik Muhammad Naeem MannanSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Dinesh B PalipanaAustralian Centre for Precision Health and Technology (PRECISE), Griffith University, Gold Coast, QLD, Australia.
Kyle MulhollandSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Evan JurdSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Ewan C R LloydSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Alastair R J QuinnSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Claire B CrossleySchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Mohammad Fazle RabbiSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
David G LloydSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia.
Yang D TengThe Visiting Professor Program, Griffith University, Gold Coast, QLD, Australia. yang.teng@griffith.edu.au.
Claudio PizzolatoSchool of Allied Health, Sport and Social Work, Griffith University, Gold Coast, QLD, Australia. c.pizzolato@griffith.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-time brain-computer interfaces (BCIs) that decode electroencephalograms (EEG) during motor imagery (MI) are powerful adjuncts to rehabilitation after neurotrauma. Further, immersive virtual reality (VR) could complement BCIs by delivering visual and auditory sensory feedback (VR biofeedback) congruent to user's MI, enabling task-oriented therapies. Yet, therapeutic outcomes rely on user's proficiency in evoking MI to attain volitional BCI-commanded VR interaction. While previous studies have explored multi-session BCIs, we investigated the impact of longitudinal training on sensorimotor neuromodulation using BCI combined with VR-mediated externally-cued and self-paced lower-limb MI tasks. The EEG-based BCI was coupled with real-time VR biofeedback congruent with the MI task. Over multiple training sessions in laboratory conditions, five unimpaired individuals progressively learnt to improve control over their EEG during MI virtual walking, corresponding with increased BCI classification accuracy. Further, similar improvements were found with four individuals with chronic complete spinal cord injury (SCI) using the system in real-world neurorehabilitation settings. These findings demonstrate that unimpaired and SCI impaired individuals learnt to control their sensorimotor EEG associated with MI tasks through VR-mediated BCI training, which was associated with improved BCI classification accuracy. Our findings highlight the potential of VR-mediated BCIs in enhancing neuromodulation, providing a foundation for future rehabilitation therapies.

Indexed as

Brain-Computer InterfacesSpinal Cord InjuriesVirtual RealityAdultElectroencephalographyFeedback, SensoryFemaleHumansMaleMiddle AgedBrain-computer interface (BCI)Common spatial pattern (CSP)Consumer-grade dry-electrodesElectroencephalogram (EEG)Linear discriminant analysis (LDA)Lower-limbMirror therapyMotor imagerySensorimotor learningSpinal cord injury (SCI)Virtual reality

Identifiers

PMID41582168
PMCPMC12905311

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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.