Somatosensory inputs for arm control

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Theories of biological motor control often start from the view that motor behaviour tends towards optimal performance and, in general, such optimization criteria are extremely successful at reproducing a wide variety of findings. One influential scheme along these lines is based on optimal feedback control. Briefly, as applied to biological motor control the idea is that motor commands are computed based on the state of the body and a cost-function that describes the performance criteria of the behaviour being executed (e.g. reach the target while penalizing energy expenditure). The net result is that the nervous system creates goal-directed motor behaviour by adjusting the gains of feedback control loops over time and as a function of the behavioural task. Thus, under this framework, understanding how the nervous system processes sensory feedback is critical to understanding the control of movement. Our long-term objective is determining the functional capacity and neural organization of the fastest feedback loops (i.e. usually called stretch reflexes) that link sensory inputs from the muscles and skin to real-world behaviours like reaching, grasping, and object manipulation. My lab attacks this important long-term objective from all fronts including theoretical work, behavioural studies and detailed physiological investigations in humans and non-human primates. The work proposed in this proposal focuses on establishing the nature of the cost functions central under the optimal feedback control framework and specifically the minimum intervention principle, which is a fundamental prediction of optimal feedback control. The minimum intervention principle states that only errors that ultimately influence task success (as defined by the cost function) should be corrected. Errors that don't ultimately influence task success should not be corrected because doing so in the presence of noise may actually introduce errors that do influence task success. Thus, our short-term objectives, are to (1) detail the cost functions and underlying neural mechanisms that apply to somatosensory feedback loops in the context of postural control of the human arm, especially those fastest responses generated via circuits in the spinal cord, and (2) determine how the somatosensory feedback loops change with experience and learning when exposed to new cost functions. This work is important because determining how upper-limb stretch reflex responses are adjusted to task-demands and modified with experience is poorly understood relative to related processes in the context of voluntary motor control. It is likely to be of very high impact because our most recent findings suggest a hitherto unknown capacity of spinal circuits in this regard that we will now be the first to elaborate in detail.