Movement control is among the top BCI/BMI application scenarios for potential end-users. The topic has been addressed from various directions, ranging from spiking activity tuned to attempted movements up to large-scale population activity modulated by mental tasks. Current approaches vary in numerous factors, including signal modality (single unit spiking activity up to EEG), neural correlates of movement, control strategies, and decoding algorithms and feedback modalities (visual, sensory, multimodal, intra-cortical stimulation). In spite of this diversity, there are shared key challenges that limit the translation to dependable assistive technology. In addition to safety, availability and portability, a dependable BCI has to eliminate or alleviate time-consuming system (re-)calibration processes, and generalize to various movement tasks with different dynamics.
The goal of this Research Topic is to share recent advances among diverse approaches and, thereby, facilitate exchange between groups and research directions. The scope ranges from original neuroscientific studies investigating neural correlates of goal-directed movements to neural engineering applications towards dependable BCIs/BMIs for movement control. We encourage submissions of original research, reviews, methods, data reports and case reports that relate brain activity (e.g., electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), local field potentials (LFP), spiking activity, etc.) with imagined/attempted/executed movements of end-effectors (e.g., extremities, virtual objects, robotic arms or neuroprostheses).
This Research Topic welcomes submission on topics related, but not limited, to:
- Neural correlates of executed/attempted goal-directed movements
- Interpretable models and artifact handling
- Decoders that generalize across movement tasks
- Transfer across sessions/subjects
- Eliminating or alleviating system re-calibration
- Closed-loop control and feedback
- Translational aspects and portability
- Mobile brain-body imaging (MoBI)
- Studies with end-users
Masayuki Hirata founded a start-up company (JiMED) and works as a part-time and unpaid director. He will receive a collaborative research grant from JiMED.
