Background: Motor imagery based brain-computer interfaces (MI-BCIs) are systems that detect the mental rehearsal of movement from brain activity signals (EEG) for controlling devices that can potentiate motor neurorehabilitation. Considering the problem that MI proficiency requires training and it is not always achieved, EEG desirable features should be investigated to propose indicators of successful MI training.
Methods: Nine healthy right-handed subjects trained with a MI-BCI for four sessions. In each session, EEG was recorded for 30 trials that consisted of a rest and a dominant-hand MI sequence, which were used for calibrating the system. Then, the subject participated in 160 trials in which a cursor was displaced on a screen by performing MI or relaxing to hit a target. The session's accuracy was calculated. For each trial from the calibration phase of the first session, the power spectral density (PSD) and the partial directed coherence (PDC) of the rest and MI EEG segments were obtained to estimate the event-related synchronization changes (ERS) and the connectivity patterns of the , , and bands that are associated with high BCI control (accuracy above 70% in at least one session). Finally, t-tests and rank-sum tests ( , with Benjamini-Hochberg correction) were used to compare the ERS/ERD and PDC values of subjects with high and low accuracy, respectively.
Results: Proficient users showed greater ERD on the right-hand motor cortex (left hemisphere). Furthermore, the PDC related to the ipsilateral motor cortex is commonly weakened during motor imagery, while the contralateral motor cortex PDC is enhanced.
Conclusions: Motor imagery proficiency is related to the focused and lateralized event-related desynchronization patterns and the lateralization of and PDC. Future analysis of these features could allow complimenting the information for assessment of subject-specific BCI control and the prediction of the effectiveness of motor-imagery training.
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http://dx.doi.org/10.1186/s12984-025-01571-6 | DOI Listing |
Cureus
February 2025
Department of Neurophysiotherapy, Ravi Nair Physiotherapy College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Traumatic brachial plexus injury (TBPI) is a serious neurological condition most often resulting from trauma. This condition is among the most debilitating injuries affecting the upper limb. The injury is typically categorized as preganglionic or postganglionic based on the site of trauma, proximal to or distal to the dorsal root ganglion (DRG).
View Article and Find Full Text PDFNeuroscience
March 2025
Brain, Action, and Skill Laboratory (BAS-Lab), Institute of Neuroscience (Cognition and Systems Division), UCLouvain, Belgium.
The Hand Laterality Judgement Task (HLJT) is considered a measure of the ability to manipulate motor images. The 'biomechanical constraints' effect (longer reaction times for hand rotations towards anatomically difficult versus biomechanically easier movements) is considered the behavioural hallmark indicating motor imagery is being used. Previous work has used diverse HLJT paradigms, and there is no standardized procedure for the task.
View Article and Find Full Text PDFJ Neural Eng
March 2025
Department of Biomedical Engineering, The University of Melbourne, Parkville, Melbourne, Victoria, 3052, AUSTRALIA.
There is limited work investigating Brain-Computer Interface (BCI) technology in people with Multiple Sclerosis (pwMS), a neurodegenerative disorder of the central nervous system. Present work is limited to recordings at the scalp, which may be significantly altered by changes within the cortex due to volume conduction. The recordings obtained from the sensors, therefore, combine disease-related alterations and task-relevant neural signals, as well as signals from other regions of the brain that are not relevant.
View Article and Find Full Text PDFJ Multidiscip Healthc
March 2025
Department of Rehabilitation Medicine, The First Affiliated Hospital of the Naval Medical University, Shanghai, 200433, People's Republic of China.
Objective: This study aims to conduct a bibliometric analysis of the application of brain- computer interface (BCI) in rehabilitation medicine, assessing the current state, developmental trends, and future potential of this field. By systematically analyzing relevant literature, we seek to identify key research themes and enhance understanding of BCI technology in rehabilitation.
Methods: We utilized bibliometric analysis tools such as VOSviewer and CiteSpace to screen and analyze 426 relevant articles from the Web of Science Core Collection (WoSCC) database.
Med Biol Eng Comput
March 2025
Department of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Noninvasive brain-computer interfaces (BCIs) have rapidly developed over the past decade. This new technology utilizes magneto-electrical recording or hemodynamic imaging approaches to acquire neurophysiological signals noninvasively, such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). These noninvasive signals have different temporal resolutions ranging from milliseconds to seconds and various spatial resolutions ranging from centimeters to millimeters.
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