Movement image training and brain-computer interface in cognitive rehabilitation

The paper provides an overview of studies on the use of movement image training and brain-computer interfaces (BCIs) for cognitive rehabilitation in patients with neurological diseases. Based on the analysis of studies published from 2004 to 2025, the effectiveness of these methods in recovering cognitive functions in patients with stroke (13 studies), Parkinson's disease (4 studies), and multiple sclerosis (2 studies) was evaluated. Most studies demonstrated a positive effect of movement image training on the cognitive functions of patients with neurological diseases and moderate cognitive deficits. The effectiveness of this approach is comparable to that of specialized cognitive training. In studies using BCI to control movement image training, an improvement in cognitive functions was also reported. Some studies showed a positive correlation between changes in cognitive indicators and the degree of motor recovery. In groups of patients with normal or near-normal baseline MoCA scores, no significant improvement in cognitive function was reported after a training course. The heterogeneity of the analyzed studies makes direct comparison between them difficult. The results of the analysis of published studies indicate the prospect of using the movement image training with BCI control in the cognitive rehabilitation of neurological patients. However, well-designed randomized controlled trials are necessary to study the mechanisms of the ideomotor training effects on cognitive functions and to develop standardized protocols for assessing their effectiveness.

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Publication Details

Journal
S S Korsakov Journal of Neurology and Psychiatry
Published
2025-12-09
DOI
https://doi.org/10.17116/jnevro202512511127
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

Movement image training and brain-computer interface in cognitive rehabilitation

R. Kh. Lyukmanov, Ekaterina S. Ikonnikova, Н. А. Супонева, Anastasiya N. Cherkasova et al.
S S Korsakov Journal of Neurology and Psychiatry
EEG and Brain-Computer Interfaces
article

Movement image training and brain-computer interface in cognitive rehabilitation

R. Kh. Lyukmanov, Ekaterina S. Ikonnikova, Н. А. Супонева, Anastasiya N. Cherkasova, О. А. Мокиенко, V.V. Labor
article en

Abstract

The paper provides an overview of studies on the use of movement image training and brain-computer interfaces (BCIs) for cognitive rehabilitation in patients with neurological diseases. Based on the analysis of studies published from 2004 to 2025, the effectiveness of these methods in recovering cognitive functions in patients with stroke (13 studies), Parkinson's disease (4 studies), and multiple sclerosis (2 studies) was evaluated. Most studies demonstrated a positive effect of movement image training on the cognitive functions of patients with neurological diseases and moderate cognitive deficits. The effectiveness of this approach is comparable to that of specialized cognitive training. In studies using BCI to control movement image training, an improvement in cognitive functions was also reported. Some studies showed a positive correlation between changes in cognitive indicators and the degree of motor recovery. In groups of patients with normal or near-normal baseline MoCA scores, no significant improvement in cognitive function was reported after a training course. The heterogeneity of the analyzed studies makes direct comparison between them difficult. The results of the analysis of published studies indicate the prospect of using the movement image training with BCI control in the cognitive rehabilitation of neurological patients. However, well-designed randomized controlled trials are necessary to study the mechanisms of the ideomotor training effects on cognitive functions and to develop standardized protocols for assessing their effectiveness.

S S Korsakov Journal of Neurology and PsychiatryVol. 125(11)
Lomonosov Moscow State University (RU), Moscow State University (TJ), Institute of Higher Nervous Activity and Neurophysiology (RU), Research Center of Neurology (RU)
Openalex Percentile: Top 60%
EEG and Brain-Computer Interfaces
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