[Article] Meditation for mind-control

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Alpha power contrast between motor imagery and rest is widespread. (A) The Fisher score was used to plot the difference between the distributions of alpha power during motor imagery versus rest at each electrode throughout training (x-axis = session number). During the UD task, the control group (top row) displayed the expected pattern in that the difference between motor imagery and rest is determined by the presence or absence of activity over the motor cortex. However, the MBSR group produced an entirely different pattern of contrast that evolves throughout training. Brighter colors represent greater differences in alpha power between trial types. (B) Comparing the change in Fisher score across the cortex during UD control revealed the MBSR group learned to generate greater alpha power contrast between motor imagery and rest than controls across a wide range of electrodes (CBPT, P = 0.01). (C) Source imaging of the group difference in Fisher score change during the UD task again confirms the differences in learned alpha power modulation are widespread (CBPT, P < 0.001).

The team found that those with training in mindfulness-based attention and training (MBAT) were more successful in controlling the BCI, both initially and over time. Interestingly, the researchers found that differences in brain activity between the two sample groups corresponded directly with their success. The meditation group showed significantly enhanced capability of modulating their alpha rhythm, the activity pattern monitored by the BCI system to mentally control the movement of a computer cursor.

His findings are very important for the process of BCI training and the overall feasibility of non-invasive BCI control via EEG. This work shows that just a short period of MBAT training can significantly improve a subject’s skill with a BCI. This suggests that education in MBAT could provide a significant addition to BCI training.

https://neurosciencenews.com/meditation-mind-control-17071/
Mindfulness Improves Brain–Computer Interface Performance by Increasing Control Over Neural Activity in the Alpha Band James R Stieger, Stephen Engel, Haiteng Jiang, Christopher C Cline, Mary Jo Kreitzer, Bin He