Brain oscillatory activity, synchronized rhythmic patterns of electrical activity detectable with invasive (e.g. ECoG, DBS) and non-invasive (e.g. EEG, MEG) brain recording techniques, play a central role in regulating neuronal communication. As such, brain rhythms sustain cognitive, perceptual, and motor functions, and are altered in several neurological and neuropsychiatric disorders.
Movement and sensorimotor processing are associated with different oscillatory patterns in specific frequency bands: while beta and mu oscillatory activity is prominent at rest, transient increases (event-related synchronization- ERS) or decreases (event-related desynchronization- ERD) in mu, beta, and gamma oscillatory activity characterize movement planning and execution as well as sensorimotor processing.
While researchers are still debating over the functional meaning of these synchronization and desynchronization patterns of rhythmic activity, practical applications based on the accumulated knowledge have been emerging for the last two decades.
Resting and movement-related brain oscillatory activity in the sensorimotor system can be used as biomarkers to formulate a diagnosis as well as to predict, monitor, and personalize rehabilitation protocols.
Improving our knowledge on sensorimotor rhythmic activity could also advance technologies to improve motor functioning: some studies have already shown promising results in modulating brain oscillations with Non-Invasive Brain Stimulation (NIBS) and neurofeedback with positive effects on motor performance or symptoms.
Further, during the last decades, improvements in biomedical engineering allowed the development of Brain-Computer Interfaces (BCI) as tools to replace and restore functions in a vast range of clinical conditions.
The applicative realm of brain oscillations for motor functioning is not limited to clinical populations: sports science has been yearning for reliable neural biomarkers to provide quantitative feedback on athletes’ physical status and for boosting performance. Interestingly, this drive has led to the first criticisms on the legitimacy of “neurodoping” interventions in professional athletes.
Besides sports science, spontaneous and movement-related brain oscillatory dynamics can also be investigated during the acquisition of professional and non-professional sensorimotor skills, including those involved in surgical and medical procedures.
Despite the extensive amount of research covering the role of brain rhythms on sensorimotor functioning and motor learning, an extension and refinement of the available evidence is needed to advance the field and improve practical interventions.
Contributions from different scientific fields (e.g. clinical, neuroscientific, engineering) are particularly desired for this research topic; indeed, gathering all-round evidence on sensorimotor functioning can ultimately provide a comprehensive perspective on the topic and bridge the gap between different theories and practice.
This Research Topic thus aims to gather a comprehensive body of research on the brain oscillatory correlates of motor control and sensorimotor learning, as well as practical applications to guide NIBS, Neurofeedback, and BCI-based interventions.
Any original research and review article on human sensorimotor control and learning based on EEG, MEG, NIBS, Neurofeedback, and BCI techniques in healthy subjects and patients is welcome alongside research in animal models and computational work. Studies focusing on the following areas are particularly of interest:
• Brain oscillatory correlates of sensorimotor control, learning, and re-learning in healthy and clinical populations. This includes basic motor control (e.g. brain oscillatory correlates of a finger tapping task), sensorimotor adaptation and learning studies, as well as complex rehabilitative/training studies.
• NIBS and neurofeedback protocols targeting sensorimotor rhythms to enhance motor performance and recovery in clinical and healthy populations (including elderly, professional musicians, sport science, surgical and medical training).
• Recent advancements in the development and application of non-invasive EEG-based Brain Computer Interfaces and other technical solutions based on EEG/MEG signal for clinical (e.g. control of prosthetic and robotic systems) and non-clinical purposes
Brain oscillatory activity, synchronized rhythmic patterns of electrical activity detectable with invasive (e.g. ECoG, DBS) and non-invasive (e.g. EEG, MEG) brain recording techniques, play a central role in regulating neuronal communication. As such, brain rhythms sustain cognitive, perceptual, and motor functions, and are altered in several neurological and neuropsychiatric disorders.
Movement and sensorimotor processing are associated with different oscillatory patterns in specific frequency bands: while beta and mu oscillatory activity is prominent at rest, transient increases (event-related synchronization- ERS) or decreases (event-related desynchronization- ERD) in mu, beta, and gamma oscillatory activity characterize movement planning and execution as well as sensorimotor processing.
While researchers are still debating over the functional meaning of these synchronization and desynchronization patterns of rhythmic activity, practical applications based on the accumulated knowledge have been emerging for the last two decades.
Resting and movement-related brain oscillatory activity in the sensorimotor system can be used as biomarkers to formulate a diagnosis as well as to predict, monitor, and personalize rehabilitation protocols.
Improving our knowledge on sensorimotor rhythmic activity could also advance technologies to improve motor functioning: some studies have already shown promising results in modulating brain oscillations with Non-Invasive Brain Stimulation (NIBS) and neurofeedback with positive effects on motor performance or symptoms.
Further, during the last decades, improvements in biomedical engineering allowed the development of Brain-Computer Interfaces (BCI) as tools to replace and restore functions in a vast range of clinical conditions.
The applicative realm of brain oscillations for motor functioning is not limited to clinical populations: sports science has been yearning for reliable neural biomarkers to provide quantitative feedback on athletes’ physical status and for boosting performance. Interestingly, this drive has led to the first criticisms on the legitimacy of “neurodoping” interventions in professional athletes.
Besides sports science, spontaneous and movement-related brain oscillatory dynamics can also be investigated during the acquisition of professional and non-professional sensorimotor skills, including those involved in surgical and medical procedures.
Despite the extensive amount of research covering the role of brain rhythms on sensorimotor functioning and motor learning, an extension and refinement of the available evidence is needed to advance the field and improve practical interventions.
Contributions from different scientific fields (e.g. clinical, neuroscientific, engineering) are particularly desired for this research topic; indeed, gathering all-round evidence on sensorimotor functioning can ultimately provide a comprehensive perspective on the topic and bridge the gap between different theories and practice.
This Research Topic thus aims to gather a comprehensive body of research on the brain oscillatory correlates of motor control and sensorimotor learning, as well as practical applications to guide NIBS, Neurofeedback, and BCI-based interventions.
Any original research and review article on human sensorimotor control and learning based on EEG, MEG, NIBS, Neurofeedback, and BCI techniques in healthy subjects and patients is welcome alongside research in animal models and computational work. Studies focusing on the following areas are particularly of interest:
• Brain oscillatory correlates of sensorimotor control, learning, and re-learning in healthy and clinical populations. This includes basic motor control (e.g. brain oscillatory correlates of a finger tapping task), sensorimotor adaptation and learning studies, as well as complex rehabilitative/training studies.
• NIBS and neurofeedback protocols targeting sensorimotor rhythms to enhance motor performance and recovery in clinical and healthy populations (including elderly, professional musicians, sport science, surgical and medical training).
• Recent advancements in the development and application of non-invasive EEG-based Brain Computer Interfaces and other technical solutions based on EEG/MEG signal for clinical (e.g. control of prosthetic and robotic systems) and non-clinical purposes