{"id":672,"date":"2013-12-12T12:51:17","date_gmt":"2013-12-12T12:51:17","guid":{"rendered":"http:\/\/bel.reading.ac.uk\/?page_id=672"},"modified":"2020-02-03T09:51:08","modified_gmt":"2020-02-03T09:51:08","slug":"investigation-of-submovement-microstates-via-phase-synchronisation","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/bel\/projects\/investigation-of-submovement-microstates-via-phase-synchronisation\/","title":{"rendered":"Investigation of Submovement Microstates via Phase Synchronisation"},"content":{"rendered":"

Description<\/h2>\n

While the motion of our limbs may often feel continuous and smooth, there is significant evidence to suggest that this is not how the brain actually encodes our movements; rather, it instructs the muscles to make a series of discrete movements, which blend together into what appears to be a fluid action. These discrete movements are known as submovements; they can be observed in infants who are still learning basic motor skills, stroke patients who have lost motor function, and healthy adults when forced to make a rapid adjustment to an ongoing movement (e.g. tracking an erratic target with their hand).<\/p>\n

Submovement Microstates are the spatial patterns of EEG across the scalp associated with the onset of submovements; in previous work done by MIT, these were spatial patterns of electrical potential across the scalp. From these EEG evidence supporting the existence of submovements was gained, but information on the movements themselves were lacking; moving the wrist in one direction created a near identical microstate to that of any other direction.<\/p>\n

This project is therefore investigating an alternative means of measuring submovement microstates; instead of measuring potential, phase synchronisation across the scalp will be measured. As there is much evidence to suggest that statistically significant phase synchronisation in EEG indicates communication between areas of the brain, this will result in us being able to glean some insight into the mechanics underpinning submovements, and possibly allow us to determine directional information about the movement itself from the EEG.<\/p>\n

In addition to revealing fundamental properties of information encoding in brain signals, this research will have significant implications for language parsing systems which could be used as part of the assistive technology augmenting communication for subject with linguistic impairments.<\/p>\n

Project Research Group<\/h2>\n

Slawomir Nasuto<\/a><\/h3>\n

Professor of Cybernetics, University of Reading<\/em><\/p>\n

William S. Harwin<\/a><\/h3>\n

Professor of Cybernetics, University of Reading<\/em><\/p>\n

Yoshikatsu Hayashi <\/a><\/h3>\n

Dr of Robotics, University of Reading<\/em><\/p>\n

Matthew Pitkin<\/h3>\n

MSc Student, School of Systems Engineering, University of Reading<\/em><\/p>\n

Funding Body<\/h2>\n

<\/h3>\n","protected":false},"excerpt":{"rendered":"

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