Perception Action Cognition Occasional Talks
Motor Control Theory and Brain Machine Interfaces
Brain-computer interfaces, or brain-machine interfaces (BMIs), have seen wide development over the last decade. BMIs measure or stimulate neurons in the brain directly and decode neuronal firings to generate information. However, it is impossible to measure all neuron activities in the brain because of the enormous quantity of neurons. It is also difficult to decode brain signals because of the functional complexity and numerous unknowns. Therefore, anatomical knowledge, such as the cortical homunculus of the primary motor cortex (M1) and the primary somatosensory cortex, the neural representation of M1, is used. These areas are related to movement and tactile sensation. In the field of motor control, motor command generation is still an open problem, and many theories have been proposed. In this talk, we introduce a new motor control hypothesis in which trajectory planning is not needed, and final position is the only information used to produce motion. Exact duration time is also a result of movement and is not needed for planning. Also, this hypothesis reproduces the experimental results of Bizzi which rejected the end point control hypothesis. Until now, several hypotheses have been proposed for the relationship between neural activity in M1 and motor control. Among these are hypotheses that neural activity of M1 encodes movement direction, force, and both of movement direction and force. Nevertheless, we have yet to discover the exact relationship between the neural activity in M1 and motor control. BMI techniques are useful in evaluating and verifying these hypotheses.