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3D visualization of movements can amplify motor cortex activation during subsequent motor imagery
(2015)
A repetitive movement practice by motor imagery (MI) can influence motor cortical excitability in the electroencephalogram (EEG). This study investigated if a realistic visualization in 3D of upper and lower limb movements can amplify motor related potentials during subsequent MI. We hypothesized that a richer sensory visualization might be more effective during instrumental conditioning, resulting in a more pronounced event related desynchronization (ERD) of the upper alpha band (10–12 Hz) over the sensorimotor cortices thereby potentially improving MI based brain-computer interface (BCI) protocols for motor rehabilitation. The results show a strong increase of the characteristic patterns of ERD of the upper alpha band components for left and right limb MI present over the sensorimotor areas in both visualization conditions. Overall, significant differences were observed as a function of visualization modality (VM; 2D vs. 3D). The largest upper alpha band power decrease was obtained during MI after a 3-dimensional visualization. In total in 12 out of 20 tasks the end-user of the 3D visualization group showed an enhanced upper alpha ERD relative to 2D VM group, with statistical significance in nine tasks.With a realistic visualization of the limb movements, we tried to increase motor cortex activation during subsequent MI. The feedback and the feedback environment should be inherently motivating and relevant for the learner and should have an appeal of novelty, real-world relevance or aesthetic value (Ryan and Deci, 2000; Merrill, 2007). Realistic visual feedback, consistent with the participant’s MI, might be helpful for accomplishing successful MI and the use of such feedback may assist in making BCI a more natural interface for MI based BCI rehabilitation.
This study aimed at evaluating the performance of the Studentized Continuous Wavelet Transform (t-CWT) as a method for the extraction and assessment of event-related brain potentials (ERP) in data from a single subject. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of the t-CWT were assessed and compared to a variety of competing procedures using simulated EEG data at six low signal-to-noise ratios. Results show that the t-CWT combines high sensitivity and specificity with favorable PPV and NPV. Applying the t-CWT to authentic EEG data obtained from 14 healthy participants confirmed its high sensitivity. The t-CWT may thus be well suited for the assessment of weak ERPs in single-subject settings.