Grant: Discovery Grants Program - Individual

Much of what we know about the behavioural and brain basis of sensorimotor learning comes from studying single muscle groups making repetitive movements. In limb movement studies, participants make planar reaching movements and adapt to visual alterations of their limb's position. In speech studies, isolated words are repeatedly produced and participants adapt their speech to real-time alterations in the sound of their voice. These experimental models of behaviour have been fundamental to our understanding of the neural control of movement. In particular, they show that when sensory feedback from movements differs from expectations the error between predicted and actual movement outcomes drives sensorimotor learning. However, real-world movements are not as simple as the isolated behaviours commonly studied in this work. In the real-world actions span more than one effector (e.g., co-speech hand gestures) and they occur in complex interacting sequences (e.g., fluid sentence production). The brain's capacity to predict the sensory consequences of movements that involve multiple motor domains or occur in complex interacting patterns remains largely untested. This proposal leverages and expands on recently developed experimental models of human motor control in complex movements. Using these models, we aim to elucidate the behavioural and brain-basis of sensorimotor learning in movements that approach or attain real world complexity. The proposal has four aims. Aims 1 and 2 use a novel dual-task paradigm to pair hand movements with speech production. Aim 1 tests the hypothesis that simultaneous sensorimotor learning in hand movements and speech relies on a common neural mechanism. Aim 2 tests the idea that when learning occurs simultaneously in two motor domains it is stored in a single neural representation. Aims 3 and 4 extend our recent work examining sensorimotor learning during fluid sentence production. Aim 3 uses noninvasive brain stimulation to test the hypothesis that, in fluid sentence-level speech, the cerebellum plays a key role in eliminating movement errors, while cortical motor areas are essential for the storage of sensorimotor learning. Aim 4 develops an experimental paradigm for studying sensorimotor learning in unscripted (i.e., real world) sentence production. Taken together, the proposed work has the potential to advance our understanding of the behavioural and neural mechanisms that control complex movements.