Motor imagery (MI) ability is highly subjective, as indicated by the individual scores of the MIQ-3 questionnaire, and poor imagers compensate for the difficulty in performing MI with larger cerebral activations, as demonstrated by MI studies involving hands/limbs. In order to identify general, task-independent MI ability correlates, 16 volunteers were stratified with MIQ-3. The scores in the kinaesthetic (K) and 1st-person visual (V) perspectives were associated with EEG patterns obtained during K-MI and V-MI of the same complex MIQ-3 movements during these MI tasks (Spearman's correlation, significance at <0.05, SnPM corrected). EEG measures were relative to rest (relaxation, closed eyes), and based on six electrode clusters both for band spectral content and connectivity (Granger causality). Lower K-MI ability was associated with greater theta decreases during tasks in fronto-central clusters and greater inward information flow to prefrontal clusters for theta, high alpha and beta bands. On the other hand, power band relative decreases were associated with V-MI ability in fronto-central clusters for low alpha and left fronto-central and both centro-parietal clusters for beta bands. The results thus suggest different computational mechanisms for MI-V and MI-K. The association between low alpha/beta desynchronization and V-MIQ scores and between theta changes and K-MIQ scores suggest a cognitive effort with greater cerebral activation in participants with lower V-MI ability. The association between information flow to prefrontal hub and K-MI ability suggest the need for a continuous update of information to support MI-related executive functions in subjects with poor K-MI ability.
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http://dx.doi.org/10.1016/j.neuroscience.2020.07.038 | DOI Listing |
J Burn Care Res
January 2025
School of Physical and Occupational Therapy, McGill University.
Fear avoidance (FA) describes beliefs and behaviors related to avoiding movements or activities after a painful event. FA is a prevalent issue that limits the recovery outcomes and social reintegration of burn survivors. However, as current literature focuses on chronic conditions, understanding the impact and treatment of FA within sudden onset musculoskeletal (MSK) conditions, specifically in the burn survivor population, is lacking.
View Article and Find Full Text PDFAnn N Y Acad Sci
January 2025
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
Deep learning has revolutionized electroencephalograph (EEG) decoding, with convolutional neural networks (CNNs) being a predominant tool. However, CNNs struggle with long-term dependencies in sequential EEG data. Models like long short-term memory and transformers improve performance but still face challenges of computational efficiency and long sequences.
View Article and Find Full Text PDFRev Sci Instrum
January 2025
Shenyang Bluewisdom Technology Co., Ltd., Shenyang, Liaoning Province 110623, China.
Existing lower limb exoskeletons (LLEs) have demonstrated a lack of sufficient patient involvement during rehabilitation training. To address this issue and better incorporate the patient's motion intentions, this paper proposes an online brain-computer interface (BCI) system for LLE based motor imagery and stacked ensemble. The establishment of this online BCI system enables a comprehensive closed-loop control process, which includes the collection and decoding of brain signals, robotic control, and real-time feedback mechanisms.
View Article and Find Full Text PDFHRB Open Res
September 2024
UCD School of Public Health, Physiotherapy and Sports Science, Health Sciences Centre, University College Dublin, Dublin, Leinster, Ireland.
Background: Following Spinal Cord Injury (SCI), 53% of people develop neuropathic pain (NP). NP can be more debilitating than other consequences of SCI, and a persistent health issue. Pharmacotherapies are commonly recommended for NP management in SCI, although severe pain often remains refractory to these treatments in many sufferers.
View Article and Find Full Text PDFFront Neural Circuits
January 2025
Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Kanagawa, Japan.
Introduction: Motor-imagery-based Brain-Machine Interface (MI-BMI) has been established as an effective treatment for post-stroke hemiplegia. However, the need for long-term intervention can represent a significant burden on patients. Here, we demonstrate that motor imagery (MI) instructions for BMI training, when supplemented with somatosensory stimulation in addition to conventional verbal instructions, can help enhance MI capabilities of healthy participants.
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