Opher Donchin

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During reaching movements, the brain's internal models map desired limb motion into predicted forces. When the forces in the task change, these models adapt. Adaptation is guided by generalization: errors in one movement influence prediction in other types of movement. If the mapping is accomplished with population coding, combining basis elements that(More)
Accurate performance of reaching movements depends on adaptable neural circuitry that learns to predict forces and compensate for limb dynamics. In earlier experiments, we quantified generalization from training at one arm position to another position. The generalization patterns suggested that neural elements learning to predict forces coded a limb's state(More)
Many voluntary movements involve coordination between the limbs. However, there have been very few attempts to study the neuronal mechanisms that mediate this coordination. Here we have studied the activity of cortical neurons while monkeys performed tasks that required coordination between the two arms. We found that most neurons in the primary motor(More)
Adaptation is sometimes viewed as a process in which the nervous system learns to predict and cancel effects of a novel environment, returning movements to near baseline (unperturbed) conditions. An alternate view is that cancellation is not the goal of adaptation. Rather, the goal is to maximize performance in that environment. If performance criteria are(More)
Where r is robot, s is subject, p is robot joint angles, q is subject joint angles, I is an inertial matrix, G is a coriolis-centripetal matrix, and E and C are forces actively generated by the robot and subject respectively. Fhandle is a coupling term that represents the force that the robot and subject apply to each other. The active subject torques,(More)
Theoretical motor control predicts that because of delays in sensorimotor pathways, a neural system should exist in the brain that uses efferent copy of commands to the arm, sensory feedback, and an internal model of the dynamics of the arm to predict the future state of the hand (i.e., a forward model). We tested this theory under the hypothesis that(More)
Adaptability of reaching movements depends on a computation in the brain that transforms sensory cues, such as those that indicate the position and velocity of the arm, into motor commands. Theoretical consideration shows that the encoding properties of neural elements implementing this transformation dictate how errors should generalize from one limb(More)
Previous studies have shown that activity of neuronal populations in the primary motor cortex (MI), processed by the population vector method, faithfully predicts upcoming movements. In our previous studies we found that single neurons responded differently during movements of one arm vs. combined movements of the two arms. It was, therefore, not clear(More)
Cortico-cortical connections through the corpus callosum are a major candidate for mediating bimanual coordination. However, aside from the deficits observed after lesioning this connection, little positive evidence indicates its function in bimanual tasks. In order to address this issue, we simultaneously recorded neuronal activity at multiple sites within(More)
An internal model of the dynamics of a tool or an object is part of the motor memory acquired when learning to use the tool or to manipulate the object. Changes in synaptic efficacy may underlie acquisition and storage of memories. Here we studied the effect of pharmacological agents that interfere with synaptic plasticity on acquisition of new motor(More)