Opher Donchin

Primary motor cortex is involved in bimanual coordination

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 cortex (MI) show activity specific to bimanual movements (bimanual-related activity), which is strikingly different from the activity of the same neurons during unimanual movements. Moreover, units in the supplementary motor area (SMA; the area of cortex most often associated with bimanual coordination) showed no more bimanual-related activity than units in MI. Our results challenge the classic view that MI controls the contralateral (opposite) side of the body and that SMA is responsible for the coordination of the arms. Rather, our data suggest that both cortical areas share the control of bilateral coordination.

Motor Adaptation as a Process of Reoptimization

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 well defined, theory allows one to predict the reoptimized trajectory. For example, if velocity-dependent forces perturb the hand perpendicular to the direction of a reaching movement, the best reach plan is not a straight line but a curved path that appears to overcompensate for the forces. If this environment is stochastic (changing from trial to trial), the reoptimized plan should take into account this uncertainty, removing the overcompensation. If the stochastic environment is zero-mean, peak velocities should increase to allow for more time to approach the target. Finally, if one is reaching through a via-point, the optimum plan in a zero-mean deterministic environment is a smooth movement but in a zero-mean stochastic environment is a segmented movement. We observed all of these tendencies in how people adapt to novel environments. Therefore, motor control in a novel environment is not a process of perturbation cancellation. Rather, the process resembles reoptimization: through practice in the novel environment, we learn internal models that predict sensory consequences of motor commands. Through reward-based optimization, we use the internal model to search for a better movement plan to minimize implicit motor costs and maximize rewards.

A Real-Time State Predictor in Motor Control: Study of Saccadic Eye Movements during Unseen Reaching Movements

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 saccadic eye movements, tracking an unseen reaching movement, would reflect the output of this state predictor. We found that in unperturbed reaching movements, saccade occurrence at any timet consistently provided an unbiased estimate of hand position at t + 196 msec. To investigate the behavior of this predictor during feedback error control, we applied 50 msec random-force perturbations to the moving hand. Saccades showed a sharp inhibition at 100 msec after perturbation. At ∼170 msec, there was a sharp increase in saccade probabilities. These postperturbation saccades were an unbiased estimator of hand position at saccade timet + 150 msec. The ability of the brain to guide saccades to the future position of the hand failed when a force field unexpectedly changed the dynamics of the hand immediately after perturbation. The behavior of the eyes suggested that during reaching movements, the brain computes an estimate of future hand position based on an internal model that relies on real-time proprioceptive feedback. When an error occurs in reaching movements, the estimate of future hand position is recomputed. The saccade inhibition period that follows the hand perturbation may indicate the length of time it takes for this computation to take place.

Adaptation to Visuomotor Rotation and Force Field Perturbation Is Correlated to Different Brain Areas in Patients With Cerebellar Degeneration

Although it is widely agreed that the cerebellum is necessary for learning and consolidation of new motor tasks, it is not known whether adaptation to kinematic and dynamic errors is processed by the same cerebellar areas or whether different parts play a decisive role. We investigated arm movements in a visuomotor (VM) rotation and a force field (FF) perturbation task in 14 participants with cerebellar degeneration and 14 age- and gender-matched controls. Magnetic resonance images were used to calculate the volume of cerebellar areas (medial, intermediate, and lateral zones of the anterior and posterior lobes) and to identify cerebellar structure important for the two tasks. Corroborating previous studies, cerebellar participants showed deficits in adaptation to both tasks compared with controls (P < 0.001). However, it was not possible to draw conclusions from the performance in one task on the performance in the other task because an individual participant could show severe impairment in one task and perform relatively well in the other (rho = 0.1; P = 0.73). We found that atrophy of distinct cerebellar areas correlated with impairment in different tasks. Whereas atrophy of the intermediate and lateral zone of the anterior lobe correlated with impairment in the FF task (rho = 0.72, 0.70; P = 0.003, 0.005, respectively), atrophy of the intermediate zone of the posterior lobe correlated with adaptation deficits in the VM task (rho = 0.64; P = 0.015). Our results suggest that adaptation to the different tasks is processed independently and relies on different cerebellar structures.

A Gain-Field Encoding of Limb Position and Velocity in the Internal Model of Arm Dynamics

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 position and velocity to another. To estimate how sensory cues are encoded by these neural elements, we designed experiments that quantified spatial generalization in environments where forces depended on both position and velocity of the limb. The patterns of error generalization suggest that the neural elements that compute the transformation encode limb position and velocity in intrinsic coordinates via a gain-field; i.e., the elements have directionally dependent tuning that is modulated monotonically with limb position. The gain-field encoding makes the counterintuitive prediction of hypergeneralization: there should be growing extrapolation beyond the trained workspace. Furthermore, nonmonotonic force patterns should be more difficult to learn than monotonic ones. We confirmed these predictions experimentally.

Behavioral effects of lipopolysaccharide in rats: involvement of endogenous opioids

Activation of the immune system in response to either infection or lipopolysaccharide (LPS) produces neurophysiological, neuroendocrine and behavioral changes. Some of the physiological consequences of LPS are mediated by endogenous opioid peptides. The following studies were designed to characterize the effects of LPS in several behavioral paradigms, and to determine the role of opioids in mediating these effects. The effects of LPS on locomotor and self-care activity were assessed in the open field test. Rats were injected with either saline or a dose of LPS (25, 50, 100, or 1000 micrograms/kg). 4 h later, the animals were placed in an open field and the numbers of line crossings, rearings and grooming episodes were counted. LPS significantly suppressed the three open field behaviors in a dose-related manner. The effect of LPS on sensitivity to pain was determined using the hot-plate and tail-flick tests. Administration of LPS (200 micrograms/kg) increased pain sensitivity in the hot plate test 30 min after drug administration, but produced a significant analgesic response 4 h after drug administration in both tests. Further characterization of LPS-induced analgesia demonstrated that it began about 2 h after and disappeared 30 h after the administration of LPS. Administration of naltrexone completely blocked the analgesic effects of LPS 4 h after its administration, but had no effect on LPS-induced suppression of activity in the open field. The effect of LPS on body temperature was biphasic, producing hypothermia at 2 h and hyperthermia at 8-30 h after its administration. Naltrexone had no effect on the body temperature changes induced by LPS.(ABSTRACT TRUNCATED AT 250 WORDS)

Neural interactions between motor cortical hemispheres during bimanual and unimanual arm movements

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 the arm area of motor cortex in both hemispheres of awake primates performing different bimanual and unimanual movements. By employing an adapted form of the joint peri‐stimulus time histogram technique, we discovered rapid movement‐related correlation changes between the local field potentials (LFPs) of the two hemispheres that escaped detection by time‐averaged cross‐correlation methods. The frequency and amplitude of dynamic modifications in correlations between the hemispheres were similar to those within the same hemisphere. As in previous EEG studies, we found that, on average, correlation decreased during movements. However, a subset of recording site pairs did show transiently increased correlations around movement onset (57% of all pairs and conditions in monkey G, 39% in monkey P). In interhemispheric pairs, these increases were consistently related to the mode of coupling between the two arms. Both the correlations between the movements themselves and the interhemispheric LFP correlation increases were strongest during bimanual symmetric movements, and weaker during bimanual asymmetric and unimanual movements. Increased correlations occurred mainly around movement onset, whilst decreases in correlation dominated during movement execution. The task‐specific way in which interhemispheric correlations are modulated is compatible with the notion that interactions between the hemispheres contribute to behavioural coupling between the arms.

Cerebellar regions involved in adaptation to force field and visuomotor perturbation

Studies with patients and functional magnetic resonance imaging investigations have demonstrated that the cerebellum plays an essential role in adaptation to visuomotor rotation and force field perturbation. To identify cerebellar structures involved in the two tasks, we studied 19 patients with focal lesions after cerebellar infarction. Focal lesions were manually traced on magnetic resonance images and normalized using a new spatially unbiased template of the cerebellum. In addition, we reanalyzed data from 14 patients with cerebellar degeneration using voxel-based morphometry. We found that adjacent regions with only little overlap in the anterior arm area (lobules IV to VI) are important for adaptation in both tasks. Although adaptation to the force field task lay more anteriorly (lobules IV and V), lobule VI was more important for the visuomotor task. In addition, regions in the posterolateral cerebellum (Crus I and II) contributed to both tasks. No consistent involvement of the posterior arm region (lobule VIII) was found. Independence of the two kinds of adaptation is further supported by findings that performance in one task did not correlate to performance in the other task. Our results show that the anterior arm area of the cerebellum is functionally divided into a more posterior part of lobule VI, extending into lobule V, related to visuomotor adaption, and a more anterior part including lobules IV and V, related to force field adaption. The posterolateral cerebellum may process common aspects of both tasks.

Neuronal populations in primary motor cortex encode bimanual arm movements

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 whether the population vector approach could produce reliable movement predictions also for bimanual movements. This study tests this question by comparing the predictive quality of population vectors for unimanual and bimanual arm movements. We designed a bimanual motor task that requires coordinated movements of the two arms, in which each arm may move in eight directions, and recorded single unit activity in the MI of two rhesus (Macaca mulatta) monkeys during the performance of unimanual and bimanual arm movements. We analysed the activity of 212 MI cells from both hemispheres and found that, despite bimanual related activity, the directional tuning and preferred directions of most cells were preserved in unimanual and bimanual movements. We demonstrate that population vectors, constructed from the activity of MI cells, predict accurately the direction of movement both for unimanual and for bimanual movements even when the two arms move simultaneously in different directions.

Acquisition of internal models of motor tasks in children with autism.

Children with autism exhibit a host of motor disorders including poor coordination, poor tool use and delayed learning of complex motor skills like riding a tricycle. Theory suggests that one of the crucial steps in motor learning is the ability to form internal models: to predict the sensory consequences of motor commands and learn from errors to improve performance on the next attempt. The cerebellum appears to be an important site for acquisition of internal models, and indeed the development of the cerebellum is abnormal in autism. Here, we examined autistic children on a range of tasks that required a change in the motor output in response to a change in the environment. We first considered a prism adaptation task in which the visual map of the environment was shifted. The children were asked to throw balls to visual targets with and without the prism goggles. We next considered a reaching task that required moving the handle of a novel tool (a robotic arm). The tool either imposed forces on the hand or displaced the cursor associated with the handle position. In all tasks, the children with autism adapted their motor output by forming a predictive internal model, as exhibited through after-effects. Surprisingly, the rates of acquisition and washout were indistinguishable from normally developing children. Therefore, the mechanisms of acquisition and adaptation of internal models in self-generated movements appeared normal in autism. Sparing of adaptation suggests that alternative mechanisms contribute to impaired motor skill development in autism. Furthermore, the findings may have therapeutic implications, highlighting a reliable mechanism by which children with autism can most effectively alter their behaviour.