ArticleQuantitative imaging in medicine and surgery2025
Brain-computer interface training for multimodal functional recovery in patients with brain injury: a case series.
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The effect of brain-computer interface training on cognitive function in stroke patients: a systematic review and meta-analysis.Journal of neurology · 2026Pooled it
- Dynamic functional reorganization in post-stroke aphasia: a state-of-the-art fMRI review from disease evolution to intervention.Frontiers in neuroscience · 2026Review
- Comparative efficacy and mechanistic insights of non-invasive neuromodulation and motor rehabilitation on functional reorganization of the supplementary motor area in subacute stroke: a narrative review.Frontiers in physiology · 2026Review
- Brain-computer interface: an update for the clinicians.Frontiers in human neuroscience · 2026Review
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Patients with impaired brain function often face sequelae such as limb movement, cognitive, and language impairment, and there are limitations in the efficiency of traditional rehabilitation methods. This study examined whether motor imagery-based brain-computer interface (BCI) training could promote multimodal functional recovery-including limb movement, speech, and cognition-in patients with subacute brain injury. Unlike traditional BCI research focused on single functional domains, we combined multidimensional clinical assessments with multimodal neural analysis to examine cross-network plasticity. Methods: Five patients with subacute brain injury (four males and one female; mean age 54.4±10.3 years) underwent 5 weeks of BCI training between 2021 and 2023. Pre- and post-intervention evaluations included the Fugl-Meyer Assessment Scale (FMA), Modified Ashworth Scale (MAS), Western Aphasia Battery (WAB), and Mini-Mental State Examination (MMSE). Neurophysiological metrics included classification accuracy (CA), power spectral density (PSD), and electroencephalography (EEG) topography. Functional connectivity analyses were conducted with functional magnetic resonance imaging (fMRI) and individualized connectomics based on the Human Connectome Project parcellation. Results: All five patients showed clinical improvement in motor, cognitive, or language functions. The average motor imagery CA increased by 14.2%. PSD flattening and event-related desynchronization (ERD) were observed in the central motor regions. EEG topographies showed enhanced activation converging toward the sensorimotor cortex. Patient-specific functional connectivity analyses revealed strengthened interactions among sensorimotor, language, and attention networks-most notably in one patient with marked clinical gains. Distinct patterns of connectivity reorganization were observed between patients with cortical and subcortical lesions. A critical 3-week time window for neural plasticity was identified. Conclusions: Motor imagery-based BCI training may facilitate recovery across motor, language, and cognitive domains in patients with subacute brain injury. Functional gains were supported by neurophysiological and connectomics evidence of cross-network reorganization. These preliminary findings suggest that personalized BCI protocols could represent a promising avenue for multimodal neurorehabilitation.
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