The use of intentional signals to switch ON/OFF movement decoding in brain-machine interfaces

It is difficult to imagine anything more detrimental to one’s independence than paralysis. Dr. Bjørg Elisabeth Kilavik’s work may lead to a remarkable solution using brain-machine interfaces (BMIs). With BMIs, brain activity can be analyzed and used to generate movements by an external device (robot). She hopes to take it further by detecting the very intention to move, based on visual cues, allowing movement decoding to be switched on only when truly desired by the user. Efficient, portable BMI devices could one day change patients’ lives.
Visuomotor behavior relies on visual and motor processes that are interactive and overlapping in space and time. My research is aimed at understanding the local and inter-areal dynamics underlying visuomotor behavior, using combined intra-cortical and EEG recordings. I currently study the complementarity and interactions between motor cortical areas during visuomotor behavior. In relation to this, I will test whether activity patterns in the motor cortical local field potential related to movement intention can be used as a switch-signal for brain machine interfaces (BMIs) intended for paralyzed patients. As we do not always want to move, detecting intention would allow turning on movement decoding only when needed, thereby saving energy during rest.