Biomedical subjects

R D Seidler

Publications and source records attributed to R D Seidler.

8 recordsLinked to original sources

PubMed2006

Bilateral basal ganglia activation associated with sensorimotor adaptation.

Sensorimotor adaptation tasks can be classified into two types. When subjects adapt movements to visual feedback perturbations such as in prism lens adaptation, they perform kinematic adaptations. When subjects adapt movements to force field perturbations such as with robotic manipulanda, they perform kinetic adaptations. Neuroimaging studies have shown basal ganglia involvement in kinetic adaptations, but have found little evidence of basal ganglia involvement in kinematic adaptations, despite reports of deficits in patients with diseases of the basal ganglia, such as Parkinson's and Huntington's disease, in these. In an effort to resolve such apparent discrepancy, we used FMRI to focus on the first few minutes of practice during kinematic adaptation. Human subjects adapted to visuomotor rotations in the context of a joystick aiming task while lying supine in a 3.0 T MRI scanner. As demonstrated previously, early adaptive processes were associated with BOLD activation in the cerebellum and the sensory and motor cortical regions. A novel finding of this study was bilateral basal ganglia activation. This suggests that, at least for early learning, the neural correlates of kinematic adaptation parallel those of other types of skill learning. We observed activation in the right globus pallidus and putamen, along with the right prefrontal, premotor and parietal cortex, which may support spatial cognitive processes of adaptation. We also observed activation in the left globus pallidus and caudate nucleus, along with the left premotor and supplementary motor cortex, which may support the sensorimotor processes of adaptation. These results are the first to demonstrate a clear involvement of basal ganglia activation in this type of kinematic motor adaptation.

Adaptation, Physiological↗

PubMed2005

Neural correlates of encoding and expression in implicit sequence learning.

In the domain of motor learning it has been difficult to separate the neural substrate of encoding from that of change in performance. Consequently, it has not been clear whether motor effector areas participate in learning or merely modulate changes in performance. Here, using a variant of the serial reaction time task that dissociated these two factors, we report that encoding during procedural motor learning does engage cortical motor areas and can be characterized by distinct early and late encoding phases. The highest correlation between activation and subsequent changes in motor performance was seen in the motor cortex during early encoding, and in the basal ganglia during the late encoding phase. Our results show that rapid encoding during procedural motor learning involves several distinct processes, and is represented primarily within motor system structures.

Adult↗

PubMed2004

Feedforward and feedback processes in motor control.

In this study, we utilized functional magnetic resonance imaging (fMRI) to examine which brain regions contribute to feedback and feedforward motor control processes. Several studies have investigated the contributions of cortical and subcortical brain regions to motor performance by independently varying factors such as movement rate, force, and speed, and observing the neural responses. Such studies have contributed greatly to our understanding of neural coding of movement variables. Under natural movement conditions, however, these factors interact in a complex manner to produce differing performance levels. In the current investigation, we induced performance changes in a less constrained way, by having subjects move a joystick to hit targets of differing sizes on an LCD screen. These parametric changes in target size resulted in the well-known speed-accuracy tradeoff effect, allowing us to examine the brain regions responsive to global shifts in motor performance levels. That is, movements made to larger targets relied more on feedforward control whereas movements made to smaller targets relied more on feedback control. Using functional MRI, we identified two sets of brain regions in which activation was modulated with task difficulty. Areas exhibiting activation that was positively correlated with increasing target size included primary motor cortex, premotor cortex, and the basal ganglia, regions that are typically classified as playing a role in force control and movement planning. Brain regions whose activation was negatively correlated with increasing target size included the ipsilateral sensorimotor cortex, multiple cerebellar regions, and the thalamus. These areas contributed to motor performance under higher levels of task difficulty. The results elucidate cortical and subcortical brain regions that are responsive to global shifts in motor performance, reflecting changes along the continuum of feedforward and feedback motor control.

Adult↗

PubMed2002

Cerebellum activation associated with performance change but not motor learning.

The issue of whether the cerebellum contributes to motor skill learning is controversial, principally because of the difficulty of separating the effects of motor learning from changes in performance. We performed a functional magnetic resonance imaging investigation during an implicit, motor sequence-learning task that was designed to separate these two processes. During the sequence-encoding phase, human participants performed a concurrent distractor task that served to suppress the performance changes associated with learning. Upon removal of the distractor, participants showed evidence of having learned. No cerebellar activation was associated with the learning phase, despite extensive involvement of other cortical and subcortical regions. There was, however, significant cerebellar activation during the expression of learning; thus, the cerebellum does not contribute to learning of the motor skill itself but is engaged primarily in the modification of performance.

Brain↗

PubMed2001

Patterns of transfer of adaptation among body segments.

Two experiments were conducted in order to determine the patterns of transfer of visuomotor adaptation between arm and head pointing. An altered gain of display of pointing movements was used to induce a conflict between visual and somatosensory representations. Two subject groups participated in Experiment 1: group 1 adapted shoulder pointing movements, and group 2 adapted wrist pointing movements to a 0.5 gain of display. Following the adaptation regimen, subjects performed a transfer test in which the shoulder group performed wrist movements and the wrist group performed shoulder movements. The results demonstrated that both groups displayed typical adaptation curves, initially undershooting the target followed by a return to baseline performance. Transfer tests revealed that both groups had high transfer of the acquired adaptation to the other joint. Experiment 2 followed a similar design except that group 1 adapted head pointing movements and group 2 adapted arm pointing movements. The arm adaptation had high transfer to head pointing while the head adaptation had very little transfer to arm pointing. These results imply that, while the arm segments may share a common target representation for goal-directed actions, individual but functionally dependent target representations may exist for the control of head and arm movements.

Adaptation, Physiological↗

PubMed2001

Context-dependent arm pointing adaptation.

We sought to determine the effectiveness of head posture as a contextual cue to facilitate adaptive transitions in manual control during visuomotor distortions. Subjects performed arm pointing movements by drawing on a digitizing tablet, with targets and movement trajectories displayed in real time on a computer monitor. Adaptation was induced by presenting the trajectories in an altered gain format on the monitor. The subjects were shown visual displays of their movements that corresponded to either 0.5 or 1.5 scaling of the movements made. Subjects were assigned to three groups: the head orientation group tilted the head towards the right shoulder when drawing under a 0.5 gain of display and towards the left shoulder when drawing under a 1.5 gain of display; the target orientation group had the home and target positions rotated counterclockwise when drawing under the 0.5 gain and clockwise for the 1.5 gain; the arm posture group changed the elbow angle of the arm they were not drawing with from full flexion to full extension with 0.5 and 1.5 gain display changes. To determine if contextual cues were associated with display alternations, the gain changes were returned to the standard (1.0) display. Aftereffects were assessed to determine the efficacy of the head orientation contextual cue compared to the two control cues. The head orientation cue was effectively associated with the multiple gains. The target orientation cue also demonstrated some effectiveness while the arm posture cue did not. The results demonstrate that contextual cues can be used to switch between multiple adaptive states. These data provide support for the idea that static head orientation information is a crucial component to the arm adaptation process. These data further define the functional linkage between head posture and arm pointing movements.

Adult↗

PubMed2001

Multijoint movement control in Parkinson's disease.

Impairments in the performance of complex actions in Parkinson's disease (PD) patients are well documented. The aim of the present study was to investigate potential mechanisms that may be contributing to impaired movement performance in PD patients. PD patients and age-matched control subjects performed rapid pointing movements to a series of four tabletop targets. The height of the table was adjusted until the targets could be achieved with arm movements in the horizontal plane. The targets were arranged such that target 1 required elbow extension only and targets 2-4 required increasing amounts of horizontal shoulder flexion in addition to the elbow extension. While the control subjects accelerated and decelerated the elbow and shoulder joints simultaneously regardless of the target location, the PD patients decomposed motion during the acceleration phase by accelerating first the shoulder and then the elbow joint. For PD patients this decomposition of arm segments was associated with greater coactivation of the muscles about the elbow when elbow extension and shoulder flexion were simultaneously required (targets 2-4), in contrast to the single joint action. The control subjects decreased elbow joint coactivation while the patients increased it across the four targets. The resulting peak interaction torques at both the elbow and shoulder joints occurred relatively later for the PD patients. The coactivation patterns observed in PD patients may reduce the ability to take advantage of interaction torques and may also contribute to joint motion decomposition.

Aged↗

PubMed2000

Trunk-assisted prehension: specification of body segments with imposed temporal constraints.

The authors used a trunk-assisted prehension task to examine intersegment coordination. Participants (N = 7) reached to grasp an object placed beyond full arm extension, thus requiring trunk flexion to achieve the target object, under 4 varying temporal constraints. Kinematic analyses were performed in which the motions of the arm, the trunk, and the endpoint were characterized. The spatial trajectories and the segments' peak velocity data revealed that under high temporal constraints the arm was more responsible for endpoint motion than the trunk, whereas in the unconstrained condition the trunk was more involved. In addition, the arm exhibited a decline in spatial variability toward the end of the movement in all conditions, whereas the trunk did not. The present study is the first to show that when temporal demand is increased for a trunk-assisted prehensile task, the arm plays a larger role than the trunk in the transport of the hand to the object. The data also suggest that the arm participates in the fine accuracy control of the reach, whereas the trunk does not.

Adult↗