Highlights d Neural activity for observed and executed movements occupies a shared subspace d The shared subspace is composed of both congruent and incongruent neurons d Neural dynamics are more similar within the shared subspace than outside it d Observation and execution also have a context-specific exclusive subspace

Sensorimotor rhythm (SMR)-based brain–computer interfaces (BCIs) provide an alternative pathway for users to perform motor control using motor imagery. Despite the non-invasiveness, ease of use, and low cost, this kind of BCI has limitations due to long training times and BCI inefficiency—that is, the SMR BCI control paradigm may not work well on a subpopulation of users. Meditation is a mental training method to improve mindfulness and awareness and is reported to have positive effects on one’s mental state. Here, we investigated the behavioral and electrophysiological differences between experienced meditators and meditation naïve subjects in one-dimensional (1D) and two-dimensional (2D) cursor control tasks. We found numerical evidence that meditators outperformed control subjects in both tasks (1D and 2D), and there were fewer BCI inefficient subjects in the meditator group. Finally, we also explored the neurophysiological difference between the two groups and showed that the meditators had a higher resting SMR predictor, more stable resting mu rhythm, and a larger control signal contrast than controls during the task.

Sensorimotor rhythm (SMR) based brain-computer interfaces (BCIs) provide an alternative pathway for users to perform motor control using motor imagery (MI). Despite the non-invasiveness, ease of use and low cost, this kind of BCI has limitation due to long training times and BCI inefficiency— where a subpopulation cannot generate decodable EEG signals to perform the control task. Meditation is a mental training method to improve mindfulness and awareness, and is reported to have a positive effect on one’s mental state. Here we investigate the behavioral and electrophysiological differences between experienced meditators and meditation naïve subjects in 1-dimensional and 2-dimensional cursor control tasks. We found that within subjects who have room for improvement, meditators outperformed control subjects in both tasks, and there were fewer BCI insufficient subjects in the meditator group. Finally, we also explored the neurophysiological difference between the two groups, and showed that meditators had higher SMR predictor and were better able to generate decodable EEG signals to achieve SMR BCI control.

Highlights Evaluation of epilepsy source extent estimation from MEG measurements. FAST-IRES gave robust location and extent estimation under different noise levels. Epileptic sources were estimated from interictal discharges in drug-resistant epilepsy patients. FAST-IRES outperformed LCMV in both simulation and patient data analysis.

Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients’ interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.