Ipsilesional trajectory control is related to contralesional arm paralysis after left hemisphere damage

We have recently shown ipsilateral dynamic deficits in trajectory control are present in left hemisphere damaged (LHD) patients with paresis, as evidenced by impaired modulation of torque amplitude as response amplitude increases. The purpose of the current study is to determine if these ipsilateral deficits are more common with contralateral hemiparesis and greater damage to the motor system, as evidenced by structural imaging. Three groups of right-handed subjects (healthy controls, LHD stroke patients with and without upper extremity paresis) performed single-joint elbow movements of varying amplitudes with their left arm in the left hemispace. Only the paretic group demonstrated dynamic deficits characterized by decreased modulation of peak torque (reflected by peak acceleration changes) as response amplitude increased. These results could not be attributed to lesion volume or peak velocity as neither variable differed across the groups. However, the paretic group had damage to a larger number of areas within the motor system than the non-paretic group suggesting that such damage increases the probability of ipsilesional deficits in dynamic control for modulating torque amplitude after left hemisphere damage

Movement Neuroscience foundations of Neurorehabilitation

Research into the neural control of movement has elucidated important principles that can provide guidelines to rehabilitation professionals for enhancing recovery of motor function in stroke patients. In this chapter, we elaborate principles that have been derived from research on neural control of movement, including optimal control, impedance control, motor lateralization, and principles of motor learning. Research on optimal control has indicated that two major categories of cost contribute to motor planning: explicit task-level costs, such as movement accuracy and speed, and implicit costs, such as energy and movement variability. Impedance control refers to neural mechanisms that modulate rapid sensorimotor circuits, such as reflexes, in order to impede perturbations that cannot be anticipated prior to movement. Research on motor lateralization has indicated that different aspects of motor control have been specialized to the two cerebral hemispheres. This organization leads to hemisphere-specific motor deficits in both the ipsilesional and contralesional arms of stroke patients. Ipsilesional deficits increase with severity of contralesional impairment level and have a substantial effect on functional independence. Finally, motor learning research has indicated that different neural mechanisms underlie different aspects of motor learning, such as adaptation vs skill learning, and that learning different aspects of tasks can generalize across different coordinates. In this chapter, we discuss the neurobiological basis of these principles and elaborate the implications for designing and implementing occupational and physical therapy treatment for movement deficits in stroke patients.by Robert L. Sainburg and Pratik K. Muth

Reflex circuits and their modulation in motor control: a historical perspective and current view

Sensorimotor reflexes have long been, and continue to be, an area of tremendous research in movement neuroscience. Here I aim to provide an account of some studies that have been crucial in advancing our understanding of the organization of reflex circuits, their function and their modulation during motor control. I review research ranging from early experiments in reduced animal preparations that investigated the basic building blocks of reflex circuits to more recent studies in humans that demonstrate remarkable tunability of reflexes in response to variety of contingencies related to the task, the body and the environment. By providing such an integrated account of the historical aspects and current view on reflex function, I attempt to bring out the stunning complexity of reflex machinery, as well as the incredible adaptability of this machinery despite its underlying complexity.by Pratik K. Muth