ArticleFrontiers in neurology2023
Evidence of neuroplasticity with brain-computer interface in a randomized trial for post-stroke rehabilitation: a graph-theoretic study of subnetwork analysis.
Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.
What it found
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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.
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.
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Who cites it
12 citing papers in PubMed, 4 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Comparative efficacy of brain-computer interface-coupled robotic rehabilitation, robot-assisted therapy, and motor imagery for upper-limb motor recovery after stroke: a systematic review and network meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- Brain-computer interface for post-stroke upper-limb recovery: a systematic review integrating clinical efficacy with neuroplasticity evidence.Frontiers in neurology · 2026Pooled it
- Effects of brain-computer interface based training on post-stroke upper-limb rehabilitation: a meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- The effect of rehabilitation training based on brain-computer interface on limb function in stroke patients: a systematic review and meta-analyses.Frontiers in neurologyPooled it
- EEG vs. Hybrid EEG-fNIRS BCI for FES Control in Healthy Subjects: A Blind Randomized Study and an Open Dataset.Sensors (Basel, Switzerland) · 2026Trial
- Dual Transcranial Direct Current Stimulation Modulates Hierarchical Functional Network Organization in Post-Stroke Cognitive Impairment: A Randomized Controlled Trial.CNS neuroscience & therapeutics · 2026Trial
- Motor imagery-based brain-computer interface rehabilitation programs enhance upper extremity performance and cortical activation in stroke patients.Journal of neuroengineering and rehabilitation · 2024Trial
- Closed-loop brain-computer interfaces for post-stroke sensorimotor loop restoration.Frontiers in neuroscience · 2026Review
- Brain-Computer Interfaces for Stroke Motor Rehabilitation.Bioengineering (Basel, Switzerland) · 2025Review
- Relationship between resting-state functional connectivity and change in motor function after motor imagery intervention in patients with stroke: a scoping review.Journal of neuroengineering and rehabilitation · 2023Article
- Brain-Computer Interfaces for Upper Limb Motor Recovery after Stroke: Current Status and Development Prospects (Review).Sovremennye tekhnologii v meditsine · 2023Review
- Advancing stroke rehabilitation: the potential and challenges of closed-loop brain-computer interface technology.Frontiers in neurologyReview
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Brain-computer interface (BCI) has been widely used for functional recovery after stroke. Understanding the brain mechanisms following BCI intervention to optimize BCI strategies is crucial for the benefit of stroke patients. Methods: Forty-six patients with upper limb motor dysfunction after stroke were recruited and randomly divided into the control group or the BCI group. The primary outcome was measured by the assessment of Fugl-Meyer Assessment of Upper Extremity (FMA-UE). Meanwhile, we performed resting-state functional magnetic resonance imaging (rs-fMRI) in all patients, followed by independent component analysis (ICA) to identify functionally connected brain networks. Finally, we assessed the topological efficiency of both groups using graph-theoretic analysis in these brain subnetworks. Results: The FMA-UE score of the BCI group was significantly higher than that of the control group after treatment ( Conclusion: Brain-computer interface can promote the recovery of upper limbs after stroke by regulating VN and DAN. The correlation trend of weak intensity proves that functional recovery in stroke patients is likely to be related to the brain's visuospatial processing ability, which can be used to optimize BCI strategies. Clinical Trial Registration: The trial is registered in the Chinese Clinical Trial Registry, number ChiCTR2000034848. Registered 21 July 2020.
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Registered trials
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.