The cerebellum coordinates eye and hand tracking movements.

The cerebellum is thought to help coordinate movement. We tested this using functional magnetic resonance imaging (fMRI) of the human brain during visually guided tracking tasks requiring varying degrees of eye-hand coordination. The cerebellum was more active during independent rather than coordinated eye and hand tracking. However, in three further tasks, we also found parametric increases in cerebellar blood oxygenation signal (BOLD) as eye-hand coordination increased. Thus, the cerebellar BOLD signal has a non-monotonic relationship to tracking performance, with high activity during both coordinated and independent conditions. These data provide the most direct evidence from functional imaging that the cerebellum supports motor coordination. Its activity is consistent with roles in coordinating and learning to coordinate eye and hand movement.

Composition and decomposition of internal models in motor learning under altered kinematic and dynamic environments.

The learning process of reaching movements was examined under novel environments whose kinematic and dynamic properties were altered. We used a kinematic transformation (visuomotor rotation), a dynamic transformation (viscous curl field), and a combination of these transformations. When the subjects learned the combined transformation, reaching errors were smaller if the subject first learned the separate kinematic and dynamic transformations. Reaching errors under the kinematic (but not the dynamic) transformation were smaller if subjects first learned the combined transformation. These results suggest that the brain learns multiple internal models to compensate for each transformation and has some ability to combine and decompose these internal models as called for by the occasion.

Cerebro-cerebellar functional connectivity revealed by the laterality index in tool-use learning.

The function of the lateral part of the human cerebellum was investigated through cerebro-cerebellar functional connectivity. We propose a laterality index method to reveal a functional and possibly anatomical pathway between the cerebral cortex and the cerebellum. The brain activity involved in learning a visually-guided tracking skill using a novel computer mouse was measured by functional magnetic resonance imaging. The imaging data analyzed using the method suggest that the simple lobule and semilunar lobule of the lateral cerebellum have connections with the pars opercularis and pars triangularis in the inferior frontal gyrus. A possible function of this cerebro-cerebellar communication loop is tool usage, which is in-between the cognitive and motor functions of the human cerebellum.

The locus of visual-motor learning at the task or manipulator level: implications from intermanual transfer.

To assess the functional locus of visual-motor learning, the computational concepts of "task level" programming (determination of the trajectory of a hand during arm reaching in the Cartesian coordinates) and "manipulator level" programming (determination of the joint coordinates) was adopted. Because the former is likely to be hand nonspecific and the latter is hand specific, it is assumed that learning at the task level should be transferred to the unpracticed hand, whereas that at the manipulator level it should not. Under this assumption, the paradigm of intermanual transfer was used in an aiming task under rotated visual feedback. Nearly 100% intermanual transfer from the practiced hand to the unpracticed hand in the performance time of aiming was found, concluding that the locus of visual-motor learning should be at the task level rather than at the manipulator level.

Internal representations of the motor apparatus: implications from generalization in visuomotor learning.

Recent computational studies have proposed that the motor system acquires internal models of kinematic transformations, dynamic transformations, or both by learning. Computationally, internal models can be characterized by 2 extreme representations: structured and tabular (C. G. Atkeson, 1989). Tabular models do not need prior knowledge about the structure of the motor apparatus, but they lack the capability to generalize learned movements. Structured models, on the other hand, can generalize learned movements, but they require an analytical description of the motor apparatus. In investigating humans' capacity to generalize kinematic transformations, we examined which type of representation humans' motor system might use. Results suggest that internal representations are nonstructured and nontabular. Findings may be due to a neural network model with a medium number of neurons and synapses.

Adaptive internal model of intrinsic kinematics involved in learning an aiming task.

The elbow-joint angle and the shoulder-joint angle of participants aiming at targets were multiplied in an experiment that used a position-recording system and a cathode-ray tube screen. The linear transformation in joint angles (intrinsic coordinates) corresponded to a nonlinear transformation between the hand coordinates and the screen coordinates (extrinsic coordinates). We examined whether participants could learn this transformation in the intrinsic coordinates or in the extrinsic coordinates by investigating intermanual (between-hands) transfer under an intrinsically consistent condition and an extrinsically consistent condition. Positive intermanual transfer was observed in the former condition but not in the latter condition. Results suggest that participants can learn the linear transformation in joint angles under the intrinsic coordinates and that the central nervous system adaptively represents the intrinsic kinematics.

An exploratory study of mirror-image shape discrimination in young children: vision and touch.

30 children (18 boys and 12 girls) with a mean age of 4 yr., 8. mo. were subjects in an experiment testing the relative dominance of visual and tactual modalities in mirror-image shape discrimination. The sets of unfamiliar stimuli (written and wooden letters of the English alphabet, P, B, C, U, R, F) were presented to the children randomly. Children matched the stimulus with either another visual or another tactual shape. Analysis suggests touch is not inferior to vision in mirror-image shape discrimination. These results are different from those of previous reports comparing tactual and visual discrimination with nonmirror-image patterns.

Accurate real-time feedback of surface EMG during fMRI.

Real-time acquisition of EMG during functional MRI (fMRI) provides a novel method of controlling motor experiments in the scanner using feedback of EMG. Because of the redundancy in the human muscle system, this is not possible from recordings of joint torque and kinematics alone, because these provide no information about individual muscle activation. This is particularly critical during brain imaging because brain activations are not only related to joint torques and kinematics but are also related to individual muscle activation. However, EMG collected during imaging is corrupted by large artifacts induced by the varying magnetic fields and radio frequency (RF) pulses in the scanner. Methods proposed in literature for artifact removal are complex, computationally expensive, and difficult to implement for real-time noise removal. We describe an acquisition system and algorithm that enables real-time acquisition for the first time. The algorithm removes particular frequencies from the EMG spectrum in which the noise is concentrated. Although this decreases the power content of the EMG, this method provides excellent estimates of EMG with good resolution. Comparisons show that the cleaned EMG obtained with the algorithm is, like actual EMG, very well correlated with joint torque and can thus be used for real-time visual feedback during functional studies.

Multi-joint arm movements to investigate motor control with FMRI.

Performing multi-joint arm movements in controllable dynamic environments during functional magnetic resonance imaging (fMRI) could provide important insights into the brain mechanisms involved in human motor control and related dysfunctions. In order to obtain useful data, these movements must be possible and comfortable for the subject within the narrow bore of the scanner and should not create any movement artifacts in the image. We found that commonly studied arm movements involving the shoulder create movement artifacts, and investigated alternative multijoint arm movements within a mock-up of an MR scanner. We selected movements involving the elbow and wrist joints, with an extension attached to the hand, and propose a dedicated kinematic structure using the MR compatible actuators we have previously developed.

Activation of the cerebellum in co-ordinated eye and hand tracking movements: an fMRI study.

Dysfunction of the cerebellum leads to significant deterioration of movements performed under visual guidance and of co-ordinated eye and hand movement. Visually guided tracking tasks combine both of these control features, as the eyes and hand together track a visual target. To better understand the involvement of the cerebellum in tracking tasks, we used functional magnetic-resonance imaging to study the activation of cerebellar structures in visually guided tracking movements of the eye and hand. Subjects were tested performing ocular tracking, manual tracking without eye movement or combined eye and hand tracking of a smoothly moving visual target. Three areas were activated in the cerebellum: a bilateral region in the ansiform lobule of the lateral hemisphere, a region in the ipsilateral paramedian lobule and a region in the oculomotor vermis. The ansiform and paramedian areas were most strongly activated by hand movement, although the vermal site was also active. The reverse was found for ocular tracking, with predominantly vermal activation. Activation of these cerebellar cortical areas related to movement of eyes or hand alone was significantly enhanced when the subjects performed co-ordinated eye and hand tracking of a visual target. These results provide the first direct evidence from a functional-imaging study for cerebellar activation in eye and hand co-ordination.

Quantitative examinations of internal representations for arm trajectory planning: minimum commanded torque change model.

Quantitative examinations of internal representations for arm trajectory planning: minimum commanded torque change model. A number of invariant features of multijoint planar reaching movements have been observed in measured hand trajectories. These features include roughly straight hand paths and bell-shaped speed profiles where the trajectory curvatures between transverse and radial movements have been found to be different. For quantitative and statistical investigations, we obtained a large amount of trajectory data within a wide range of the workspace in the horizontal and sagittal planes (400 trajectories for each subject). A pair of movements within the horizontal and sagittal planes was set to be equivalent in the elbow and shoulder flexion/extension. The trajectory curvatures of the corresponding pair in these planes were almost the same. Moreover, these curvatures can be accurately reproduced with a linear regression from the summation of rotations in the elbow and shoulder joints. This means that trajectory curvatures systematically depend on the movement location and direction represented in the intrinsic body coordinates. We then examined the following four candidates as planning spaces and the four corresponding computational models for trajectory planning. The candidates were as follows: the minimum hand jerk model in an extrinsic-kinematic space, the minimum angle jerk model in an intrinsic-kinematic space, the minimum torque change model in an intrinsic-dynamic-mechanical space, and the minimum commanded torque change model in an intrinsic-dynamic-neural space. The minimum commanded torque change model, which is proposed here as a computable version of the minimum motor command change model, reproduced actual trajectories best for curvature, position, velocity, acceleration, and torque. The model's prediction that the longer the duration of the movement the larger the trajectory curvature was also confirmed. Movements passing through via-points in the horizontal plane were also measured, and they converged to those predicted by the minimum commanded torque change model with training. Our results indicated that the brain may plan, and learn to plan, the optimal trajectory in the intrinsic coordinates considering arm and muscle dynamics and using representations for motor commands controlling muscle tensions.

Human cerebellar activity reflecting an acquired internal model of a new tool.

Theories of motor control postulate that the brain uses internal models of the body to control movements accurately. Internal models are neural representations of how, for instance, the arm would respond to a neural command, given its current position and velocity. Previous studies have shown that the cerebellar cortex can acquire internal models through motor learning. Because the human cerebellum is involved in higher cognitive function as well as in motor control, we propose a coherent computational theory in which the phylogenetically newer part of the cerebellum similarly acquires internal models of objects in the external world. While human subjects learned to use a new tool (a computer mouse with a novel rotational transformation), cerebellar activity was measured by functional magnetic resonance imaging. As predicted by our theory, two types of activity were observed. One was spread over wide areas of the cerebellum and was precisely proportional to the error signal that guides the acquisition of internal models during learning. The other was confined to the area near the posterior superior fissure and remained even after learning, when the error levels had been equalized, thus probably reflecting an acquired internal model of the new tool.