Consensus Paper: Cerebellum and Reward.

Cerebellum is a key-structure for the modulation of motor, cognitive, social and affective functions, contributing to automatic behaviours through interactions with the cerebral cortex, basal ganglia and spinal cord. The predictive mechanisms used by the cerebellum cover not only sensorimotor functions but also reward-related tasks. Cerebellar circuits appear to encode temporal difference error and reward prediction error. From a chemical standpoint, cerebellar catecholamines modulate the rate of cerebellar-based cognitive learning, and mediate cerebellar contributions during complex behaviours. Reward processing and its associated emotions are tuned by the cerebellum which operates as a controller of adaptive homeostatic processes based on interoceptive and exteroceptive inputs. Lobules VI-VII/areas of the vermis are candidate regions for the cortico-subcortical signaling pathways associated with loss aversion and reward sensitivity, together with other nodes of the limbic circuitry. There is growing evidence that the cerebellum works as a hub of regional dysconnectivity across all mood states and that mental disorders involve the cerebellar circuitry, including mood and addiction disorders, and impaired eating behaviors where the cerebellum might be involved in longer time scales of prediction as compared to motor operations. Cerebellar patients exhibit aberrant social behaviour, showing aberrant impulsivity/compulsivity. The cerebellum is a master-piece of reward mechanisms, together with the striatum, ventral tegmental area (VTA) and prefrontal cortex (PFC). Critically, studies on reward processing reinforce our view that a fundamental role of the cerebellum is to construct internal models, perform predictions on the impact of future behaviour and compare what is predicted and what actually occurs.

Consensus Paper: Cerebellum and Ageing.

Given the key roles of the cerebellum in motor, cognitive, and affective operations and given the decline of brain functions with aging, cerebellar circuitry is attracting the attention of the scientific community. The cerebellum plays a key role in timing aspects of both motor and cognitive operations, including for complex tasks such as spatial navigation. Anatomically, the cerebellum is connected with the basal ganglia via disynaptic loops, and it receives inputs from nearly every region in the cerebral cortex. The current leading hypothesis is that the cerebellum builds internal models and facilitates automatic behaviors through multiple interactions with the cerebral cortex, basal ganglia and spinal cord. The cerebellum undergoes structural and functional changes with aging, being involved in mobility frailty and related cognitive impairment as observed in the physio-cognitive decline syndrome (PCDS) affecting older, functionally-preserved adults who show slowness and/or weakness. Reductions in cerebellar volume accompany aging and are at least correlated with cognitive decline. There is a strongly negative correlation between cerebellar volume and age in cross-sectional studies, often mirrored by a reduced performance in motor tasks. Still, predictive motor timing scores remain stable over various age groups despite marked cerebellar atrophy. The cerebello-frontal network could play a significant role in processing speed and impaired cerebellar function due to aging might be compensated by increasing frontal activity to optimize processing speed in the elderly. For cognitive operations, decreased functional connectivity of the default mode network (DMN) is correlated with lower performances. Neuroimaging studies highlight that the cerebellum might be involved in the cognitive decline occurring in Alzheimer's disease (AD), independently of contributions of the cerebral cortex. Grey matter volume loss in AD is distinct from that seen in normal aging, occurring initially in cerebellar posterior lobe regions, and is associated with neuronal, synaptic and beta-amyloid neuropathology. Regarding depression, structural imaging studies have identified a relationship between depressive symptoms and cerebellar gray matter volume. In particular, major depressive disorder (MDD) and higher depressive symptom burden are associated with smaller gray matter volumes in the total cerebellum as well as the posterior cerebellum, vermis, and posterior Crus I. From the genetic/epigenetic standpoint, prominent DNA methylation changes in the cerebellum with aging are both in the form of hypo- and hyper-methylation, and the presumably increased/decreased expression of certain genes might impact on motor coordination. Training influences motor skills and lifelong practice might contribute to structural maintenance of the cerebellum in old age, reducing loss of grey matter volume and therefore contributing to the maintenance of cerebellar reserve. Non-invasive cerebellar stimulation techniques are increasingly being applied to enhance cerebellar functions related to motor, cognitive, and affective operations. They might enhance cerebellar reserve in the elderly. In conclusion, macroscopic and microscopic changes occur in the cerebellum during the lifespan, with changes in structural and functional connectivity with both the cerebral cortex and basal ganglia. With the aging of the population and the impact of aging on quality of life, the panel of experts considers that there is a huge need to clarify how the effects of aging on the cerebellar circuitry modify specific motor, cognitive, and affective operations both in normal subjects and in brain disorders such as AD or MDD, with the goal of preventing symptoms or improving the motor, cognitive, and affective symptoms.

Morphological and Functional Principles Governing the Plasticity Reserve in the Cerebellum: The Cortico-Deep Cerebellar Nuclei Loop Model.

Cerebellar reserve compensates for and restores functions lost through cerebellar damage. This is a fundamental property of cerebellar circuitry. Clinical studies suggest (1) the involvement of synaptic plasticity in the cerebellar cortex for functional compensation and restoration, and (2) that the integrity of the cerebellar reserve requires the survival and functioning of cerebellar nuclei. On the other hand, recent physiological studies have shown that the internal forward model, embedded within the cerebellum, controls motor accuracy in a predictive fashion, and that maintaining predictive control to achieve accurate motion ultimately promotes learning and compensatory processes. Furthermore, within the proposed framework of the Kalman filter, the current status is transformed into a predictive state in the cerebellar cortex (prediction step), whereas the predictive state and sensory feedback from the periphery are integrated into a filtered state at the cerebellar nuclei (filtering step). Based on the abovementioned clinical and physiological studies, we propose that the cerebellar reserve consists of two elementary mechanisms which are critical for cerebellar functions: the first is involved in updating predictions in the residual or affected cerebellar cortex, while the second acts by adjusting its updated forecasts with the current status in the cerebellar nuclei. Cerebellar cortical lesions would impair predictive behavior, whereas cerebellar nuclear lesions would impact on adjustments of neuronal commands. We postulate that the multiple forms of distributed plasticity at the cerebellar cortex and cerebellar nuclei are the neuronal events which allow the cerebellar reserve to operate in vivo. This cortico-deep cerebellar nuclei loop model attributes two complementary functions as the underpinnings behind cerebellar reserve.

Development of Cerebellar Reserve.

The cerebellar reserve is defined as the capacity of the cerebellum for compensation and restoration following injury. This unique cerebellar ability is attributed to various forms of synaptic plasticity that incorporate multimodal and redundant cerebellar inputs, two major features of the cerebellar circuitry. It is assumed that the cerebellar reserve is acquired from the age of 12 years after the maturation of both the cerebellar adaptative behaviors and cerebellar functional connectivity. However, acquiring the cerebellar reserve is also affected by two other factors: vulnerability and growth potential in the developing cerebellum. First, cerebellar injury during the critical period of neural circuit formation (especially during fetal and neonatal life and infancy) leads to persistent dysfunction of the cerebellum and its targets, resulting in the limitation of the cerebellar reserve. Secondly, growth potential appears to facilitate cerebellar reserve during the stage when the cerebellar reserve is still immature. Based on these findings, the present mini-review proposes a possible developmental trajectory underlying the acquisition of cerebellar reserve. We highlight the importance of studies dedicated to the understanding of the cerebellar resilience to injuries.

Distributed sensory coding by cerebellar complex spikes in units of cortical segments.

Sensory processing is essential for motor control. Climbing fibers from the inferior olive transmit sensory signals to Purkinje cells, but how the signals are represented in the cerebellar cortex remains elusive. To examine the olivocerebellar organization of the mouse brain, we perform quantitative Ca2+ imaging to measure complex spikes (CSs) evoked by climbing fiber inputs over the entire dorsal surface of the cerebellum simultaneously. The surface is divided into approximately 200 segments, each composed of ∼100 Purkinje cells that fire CSs synchronously. Our in vivo imaging reveals that, although stimulation of four limb muscles individually elicits similar global CS responses across nearly all segments, the timing and location of a stimulus are derived by Bayesian inference from coordinated activation and inactivation of multiple segments on a single trial basis. We propose that the cerebellum performs segment-based, distributed-population coding that represents the conditional probability of sensory events.

Pathophysiology of Cerebellar Tremor: The Forward Model-Related Tremor and the Inferior Olive Oscillation-Related Tremor.

Lesions in the Guillain-Mollaret (G-M) triangle frequently cause various types of tremors or tremor-like movements. Nevertheless, we know relatively little about their generation mechanisms. The deep cerebellar nuclei (DCN), which is a primary node of the triangle, has two main output paths: the primary excitatory path to the thalamus, the red nucleus (RN), and other brain stem nuclei, and the secondary inhibitory path to the inferior olive (IO). The inhibitory path contributes to the dentato-olivo-cerebellar loop (the short loop), while the excitatory path contributes to the cerebrocerebellar loop (the long loop). We propose a novel hypothesis: each loop contributes to physiologically distinct type of tremors or tremor-like movements. One type of irregular tremor-like movement is caused by a lesion in the cerebrocerebellar loop, which includes the primary path. A lesion in this loop affects the cerebellar forward model and deteriorates its accuracy of prediction and compensation of the feedback delay, resulting in irregular instability of voluntary motor control, i.e., cerebellar ataxia (CA). Therefore, this type of tremor, such as kinetic tremor, is usually associated with other symptoms of CA such as dysmetria. We call this type of tremor forward model-related tremor. The second type of regular tremor appears to be correlated with synchronized oscillation of IO neurons due, at least in animal models, to reduced degrees of freedom in IO activities. The regular burst activity of IO neurons is precisely transmitted along the cerebellocerebral path to the motor cortex before inducing rhythmical reciprocal activities of agonists and antagonists, i.e., tremor. We call this type of tremor IO-oscillation-related tremor. Although this type of regular tremor does not necessarily accompany ataxia, the aberrant IO activities (i.e., aberrant CS activities) may induce secondary maladaptation of cerebellar forward models through aberrant patterns of long-term depression (LTD) and/or long-term potentiation (LTP) of the cerebellar circuitry. Although our hypothesis does not cover all tremors or tremor-like movement disorders, our approach integrates the latest theories of cerebellar physiology and provides explanations how various lesions in or around the G-M triangle results in tremors or tremor-like movements. We propose that tremor results from errors in predictions carried out by the cerebellar circuitry.

Physiology of Cerebellar Reserve: Redundancy and Plasticity of a Modular Machine.

The cerebellum is endowed with the capacity for compensation and restoration after pathological injury, a property known as cerebellar reserve. Such capacity is attributed to two unique morphological and physiological features of the cerebellum. First, mossy fibers that convey peripheral and central information run mediolaterally over a wide area of the cerebellum, resulting in the innervation of multiple microzones, commonly known as cerebellar functional units. Thus, a single microzone receives redundant information that can be used in pathological conditions. Secondly, the circuitry is characterized by a co-operative interplay among various forms of synaptic plasticity. Recent progress in understanding the mechanisms of redundant information and synaptic plasticity has allowed outlining therapeutic strategies potentiating these neural substrates to enhance the cerebellar reserve, taking advantage of the unique physiological properties of the cerebellum which appears as a modular and potentially reconfiguring brain structure.

The critical need to develop tools assessing cerebellar reserve for the delivery and assessment of non-invasive cerebellar stimulation.

Non-invasive cerebellar stimulation (NICS) aims to modulate cerebello-cerebral loops and cerebro-spinal loops, both for research and clinical applications. It is of paramount importance to establish and validate morphological and functional tools to quantify cerebellar reserve, defined as the capacity for restoration and compensation to pathology of the cerebellum. Using NICS without efforts to estimate cerebellar reserve will end up in conflicting results due to the very high heterogeneity of cerebellar disorders encountered in daily practice.

Dysmetria and Errors in Predictions: The Role of Internal Forward Model.

The terminology of cerebellar dysmetria embraces a ubiquitous symptom in motor deficits, oculomotor symptoms, and cognitive/emotional symptoms occurring in cerebellar ataxias. Patients with episodic ataxia exhibit recurrent episodes of ataxia, including motor dysmetria. Despite the consensus that cerebellar dysmetria is a cardinal symptom, there is still no agreement on its pathophysiological mechanisms to date since its first clinical description by Babinski. We argue that impairment in the predictive computation for voluntary movements explains a range of characteristics accompanied by dysmetria. Within this framework, the cerebellum acquires and maintains an internal forward model, which predicts current and future states of the body by integrating an estimate of the previous state and a given efference copy of motor commands. Two of our recent studies experimentally support the internal-forward-model hypothesis of the cerebellar circuitry. First, the cerebellar outputs (firing rates of dentate nucleus cells) contain predictive information for the future cerebellar inputs (firing rates of mossy fibers). Second, a component of movement kinematics is predictive for target motions in control subjects. In cerebellar patients, the predictive component lags behind a target motion and is compensated with a feedback component. Furthermore, a clinical analysis has examined kinematic and electromyography (EMG) features using a task of elbow flexion goal-directed movements, which mimics the finger-to-nose test. Consistent with the hypothesis of the internal forward model, the predictive activations in the triceps muscles are impaired, and the impaired predictive activations result in hypermetria (overshoot). Dysmetria stems from deficits in the predictive computation of the internal forward model in the cerebellum. Errors in this fundamental mechanism result in undershoot (hypometria) and overshoot during voluntary motor actions. The predictive computation of the forward model affords error-based motor learning, coordination of multiple degrees of freedom, and adequate timing of muscle activities. Both the timing and synergy theory fit with the internal forward model, microzones being the elemental computational unit, and the anatomical organization of converging inputs to the Purkinje neurons providing them the unique property of a perceptron in the brain. We propose that motor dysmetria observed in attacks of ataxia occurs as a result of impaired predictive computation of the internal forward model in the cerebellum.

The Cerebro-Cerebellum as a Locus of Forward Model: A Review.

This review surveys physiological, behavioral, and morphological evidence converging to the view of the cerebro-cerebellum as loci of internal forward models. The cerebro-cerebellum, the phylogenetically newest expansion in the cerebellum, receives convergent inputs from cortical, subcortical, and spinal sources, and is thought to perform the predictive computation for both motor control, motor learning, and cognitive functions. This predictive computation is known as an internal forward model. First, we elucidate the theoretical foundations of an internal forward model and its role in motor control and motor learning within the framework of the optimal feedback control model. Then, we discuss a neural mechanism that generates various patterns of outputs from the cerebro-cerebellum. Three lines of supporting evidence for the internal-forward-model hypothesis are presented in detail. First, we provide physiological evidence that the cerebellar outputs (activities of dentate nucleus cells) are predictive for the cerebellar inputs [activities of mossy fibers (MFs)]. Second, we provide behavioral evidence that a component of movement kinematics is predictive for target motion in control subjects but lags behind a target motion in patients with cerebellar ataxia. Third, we provide morphological evidence that the cerebellar cortex and the dentate nucleus receive separate MF projections, a prerequisite for optimal estimation. Finally, we speculate that the predictive computation in the cerebro-cerebellum could be deployed to not only motor control but also to non-motor, cognitive functions. This review concludes that the predictive computation of the internal forward model is the unifying algorithmic principle for understanding diverse functions played by the cerebro-cerebellum.

Assessment and Rating of Motor Cerebellar Ataxias With the Kinect v2 Depth Sensor: Extending Our Appraisal.

Current assessment of patients with cerebellar disorders is based on conventional neurological examination that is dependent on subjective judgements. Quantitative measurement of cerebellar ataxias (CAs) is essential for assessment of evidence-based treatments and the monitoring of the progress or recovery of diseases. It may provide us a useful tool to navigate future treatments for ataxia. We developed a Kinect v2. sensor system with a novel algorithm to measure and evaluate movements for two tests of Scale for the Assessment and Rating of Ataxia (SARA): the nose-finger test and gait. For the nose-finger test, we evaluated and compared accuracy, regularities and smoothness in the movements of the index finger and the proximal limbs between cerebellar patients and control subjects. For the task of walking, we evaluated and compared stability between the two groups. The precision of the system for evaluation of movements was smaller than 2 mm. For the nose-finger test, the mildly affected patients tended to show more instability than the control subjects. For a severely affected patient, our system quantified the instability of movements of the index finger using kinematic parameters, such as fluctuations and average speed. The average speed appears to be the most sensitive parameter that contrasts between patients with CAs and control subjects. Furthermore, our system also detected the adventitious movements of more proximal body parts, such as the elbow, shoulder and head. Assessment of walking was possible only in patients with mild CAs. They demonstrated large sways and compensatory wide stances. These parameters appeared to show higher accuracy than SARA. This examiner-independent device measures movements of the points of interest of SARA more accurately than eye and further provides additional information about the ataxic movements (e.g., the adventitious movements of the elbow, shoulder and head in the nose-finger test and the wide-based walking with large oscillation in the gait task), which is out of the scope of SARA. Our new system enables more accurate scoring of SARA and further provides additional information that is not currently evaluated with SARA. Therefore, it provides an easier, more accurate and more systematic description of CAs.

Dynamic Modulation of a Learned Motor Skill for Its Recruitment.

Humans learn motor skills (MSs) through practice and experience and may then retain them for recruitment, which is effective as a rapid response for novel contexts. For an MS to be recruited for novel contexts, its recruitment range must be extended. In addressing this issue, we hypothesized that an MS is dynamically modulated according to the feedback context to expand its recruitment range into novel contexts, which do not involve the learning of an MS. The following two sub-issues are considered. We previously demonstrated that the learned MS could be recruited in novel contexts through its modulation, which is driven by dynamically regulating the synergistic redundancy between muscles according to the feedback context. However, this modulation is trained in the dynamics under the MS learning context. Learning an MS in a specific condition naturally causes movement deviation from the desired state when the MS is executed in a novel context. We hypothesized that this deviation can be reduced with the additional modulation of an MS, which tunes the MS-produced muscle activities by using the feedback gain signals driven by the deviation from the desired state. Based on this hypothesis, we propose a feedback gain signal-driven tuning model of a learned MS for its robust recruitment. This model is based on the neurophysiological architecture in the cortico-basal ganglia circuit, in which an MS is plausibly retained as it was learned and is then recruited by tuning its muscle control signals according to the feedback context. In this study, through computational simulation, we show that the proposed model may be used to neurophysiologically describe the recruitment of a learned MS in novel contexts.

Contribution of the Cerebellum to Predictive Motor Control and Its Evaluation in Ataxic Patients.

Goal-directed movements are predictive and multimodal in nature, especially for moving targets. For instance, during a reaching movement for a moving target, humans need to predict both motion of the target and movement of the limb. Recent computational studies show that the cerebellum predicts current and future states of the body and its environment using internal forward models. Sensory feedback signals from the periphery have delays in reaching the central nervous system, ranging between tens to hundreds of milliseconds. It is well known in engineering that feedback control based on time-delayed inputs can result in oscillatory and often unstable movements. In contrast, the brain predicts a current state from a previous state using forward models. This predictive mechanism most likely underpins stable and dexterous control of reaching movements. Although the cerebro-cerebellum has long been suggested as loci of various forward models, few methods are available to evaluate accuracy of the forward models in patients with cerebellar ataxia. Recently, we developed a non-invasive method to analyze receipt of motor commands in terms of movement kinematics for the wrist joint (Br/Kr ratio). In the present study, we have identified two components (F1 and F2) of the smooth pursuit movement. We found that the two components were in different control modes with different Br/Kr ratios. The major F1 component in a lower frequency range encodes both velocity and position of the moving target (higher Br/Kr ratio) to synchronize movement of the wrist joint with motion of the target in a predictive manner. The minor F2 component in a higher frequency range is biased to position control in order to generate intermittent small step-wise movements. In cerebellar patients, the F1 component shows a selective decrease in the Br/Kr ratio, which is correlated with decrease in accuracy of the pursuit movement. We conclude that the Br/Kr ratio of the F1 component provides a unique parameter to evaluate accuracy of the predictive control. We also discuss the pathophysiological and clinical implications for clinical ataxiology.

Neural Evidence of the Cerebellum as a State Predictor.

We here provide neural evidence that the cerebellar circuit can predict future inputs from present outputs, a hallmark of an internal forward model. Recent computational studies hypothesize that the cerebellum performs state prediction known as a forward model. To test the forward-model hypothesis, we analyzed activities of 94 mossy fibers (inputs to the cerebellar cortex), 83 Purkinje cells (output from the cerebellar cortex to dentate nucleus), and 73 dentate nucleus cells (cerebellar output) in the cerebro-cerebellum, all recorded from a monkey performing step-tracking movements of the right wrist. We found that the firing rates of one population could be reconstructed as a weighted linear sum of those of preceding populations. We then went on to investigate if the current outputs of the cerebellum (dentate cells) could predict the future inputs of the cerebellum (mossy fibers). The firing rates of mossy fibers at time t + t1 could be well reconstructed from as a weighted sum of firing rates of dentate cells at time t, thereby proving that the dentate activities contained predictive information about the future inputs. The average goodness-of-fit (R2) decreased moderately from 0.89 to 0.86 when t1 was increased from 20 to 100 ms, hence indicating that the prediction is able to compensate the latency of sensory feedback. The linear equations derived from the firing rates resembled those of a predictor known as Kalman filter composed of prediction and filtering steps. In summary, our analysis of cerebellar activities supports the forward-model hypothesis of the cerebellum.

Electromyogram refinement using muscle synergy based regulation of uncertain information.

Electromyogram signal (EMG) measurement frequently experiences uncertainty attributed to issues caused by technical constraints such as cross talk and maximum voluntary contraction. Due to these problems, individual EMGs exhibit uncertainty in representing their corresponding muscle activations. To regulate this uncertainty, we proposed an EMG refinement, which refines EMGs with regulating the contribution redundancy of the signals from EMGs to approximating torques through EMG-driven torque estimation (EDTE) using the muscular skeletal forward dynamic model. To regulate this redundancy, we must consider the synergistic contribution redundancy of muscles, including "unmeasured" muscles, to approximating torques, which primarily causes redundancy of EDTE. To suppress this redundancy, we used the concept of muscle synergy, which is a key concept of analyzing the neurophysiological regulation of contribution redundancy of muscles to exerting torques. Based on this concept, we designed a muscle-synergy-based EDTE as a framework for EMG refinement, which regulates the abovementioned uncertainty of individual EMGs in consideration of unmeasured muscles. In achieving the proposed EMG refinement, the most considerable point is to suppress a large change such as overestimation attributed to enhancement of the contribution of particular muscles to estimating torques. Therefore it is reasonable to refine EMGs by minimizing the change in EMGs. To evaluate this model, we used a Bland-Altman plot, which quantitatively evaluates the proportional bias of refined signals to EMGs. Through this evaluation, we showed that the proposed EDTE minimizes the bias while approximating torques. Therefore this minimization optimally regulates the uncertainty of EMGs and thereby leads to optimal EMG refinement.

Physiological and Morphological Principles Underpinning Recruitment of the Cerebellar Reserve.

BACKGROUND: In order to optimize outcomes of novel therapies for cerebellar ataxias (CAs), it is desirable to start these therapies while declined functions are restorable: i.e. while the so-called cerebellar reserve remains. OBJECTIVE: In this mini-review, we tried to define and discuss the cerebellar reserve from physiological and morphological points of view. METHOD: The cerebellar neuron circuitry is designed to generate spatiotemporally organized outputs, regardless of the region. Therefore, the cerebellar reserve may be defined as a mechanism to restore its proper input-output organization of the cerebellar neuron circuitry, when it is damaged. Then, the following four components are essential for recruitment of the cerebellar reserve: operational local neuron circuitry; proper combination of mossy fiber inputs to be integrated; climbing fiber inputs to instruct favorable reorganization of the integration; deep cerebellar nuclei to generate reorganized outputs. RESULTS: We discussed three topics related to these resources, 1) principles of generating organized cerebellar outputs, 2) redundant mossy fiber inputs to the cerebellum, 3) plasticity of the cerebellar neuron circuitry. CONCLUSION: To make most of the cerebellar reserve, it is desirable to start any intervention as early as possible when the cerebellar cell loss is minimal or even negligible. Therefore, an ideal future therapy for degenerative cerebellar diseases should start before consuming the cerebellar reserve at all. In the meantime, our real challenge is to establish a reliable method to identify the decrease in the cerebellar reserve as early as possible.

Muscle Synergy-Driven Robust Motion Control.

Humans are able to robustly maintain desired motion and posture under dynamically changing circumstances, including novel conditions. To accomplish this, the brain needs to optimize the synergistic control between muscles against external dynamic factors. However, previous related studies have usually simplified the control of multiple muscles using two opposing muscles, which are minimum actuators to simulate linear feedback control. As a result, they have been unable to analyze how muscle synergy contributes to motion control robustness in a biological system. To address this issue, we considered a new muscle synergy concept used to optimize the synergy between muscle units against external dynamic conditions, including novel conditions. We propose that two main muscle control policies synergistically control muscle units to maintain the desired motion against external dynamic conditions. Our assumption is based on biological evidence regarding the control of multiple muscles via the corticospinal tract. One of the policies is the group control policy (GCP), which is used to control muscle group units classified based on functional similarities in joint control. This policy is used to effectively resist external dynamic circumstances, such as disturbances. The individual control policy (ICP) assists the GCP in precisely controlling motion by controlling individual muscle units. To validate this hypothesis, we simulated the reinforcement of the synergistic actions of the two control policies during the reinforcement learning of feedback motion control. Using this learning paradigm, the two control policies were synergistically combined to result in robust feedback control under novel transient and sustained disturbances that did not involve learning. Further, by comparing our data to experimental data generated by human subjects under the same conditions as those of the simulation, we showed that the proposed synergy concept may be used to analyze muscle synergy-driven motion control robustness in humans.

Quantitative evaluation of age-related decline in control of preprogramed movement.

In this paper, we examined the age-related changes in control of preprogramed movement, with emphasis on its accuracy. Forty-nine healthy subjects participated in this study, and were divided into three groups depending on their ages: the young group (20-39 years) (n = 16), the middle-age group (40-59 years) (n = 16), and the elderly group (60-79 years) (n = 17). We asked the subjects to perform step-tracking movements of the wrist joint with a manipulandum, and recorded the movements. We evaluated the accuracy of control of preprogramed movement in the three groups in terms of the primary submovement, which was identified as the first segment of the step-tracking movement based on the bell-shaped velocity profile, and calculated the distance between the end position of the primary submovement and the target (i.e. error). The error in the young group was found to be significantly smaller than that in the middle-age and elderly groups, i.e., the error was larger for the higher age groups. These results suggest that young subjects have better control of preprogramed movement than middle-age or elderly subjects. Finally, we examined the temporal property of the primary submovement and its age-related changes. The duration of the primary submovement tended to be longer for the aged groups, although significance was reached only for the elderly group. In particular, the ratio of the duration of the primary submovement to total movement time tended to be lower for the aged groups, suggesting that the proportion of additional movements that are required to compensate for the incomplete control in the preprogramed movement, which are under feedback control, was higher for the aged groups. Consequently, our results indicate that the distance between the end point of the primary submovement and the target center (i.e. error) in the step-tracking movement is a useful parameter to evaluate the age-related changes in control of preprogramed movement.

Diverse coordinate frames on sensorimotor areas in visuomotor transformation.

The visuomotor transformation during a goal-directed movement may involve a coordinate transformation from visual 'extrinsic' to muscle-like 'intrinsic' coordinate frames, which might be processed via a multilayer network architecture composed of neural basis functions. This theory suggests that the postural change during a goal-directed movement task alters activity patterns of the neurons in the intermediate layer of the visuomotor transformation that recieves both visual and proprioceptive inputs, and thus influence the multi-voxel pattern of the blood oxygenation level dependent signal. Using a recently developed multi-voxel pattern decoding method, we found extrinsic, intrinsic and intermediate coordinate frames along the visuomotor cortical pathways during a visuomotor control task. The presented results support the hypothesis that, in human, the extrinsic coordinate frame was transformed to the muscle-like frame over the dorsal pathway from the posterior parietal cortex and the dorsal premotor cortex to the primary motor cortex.

Information processing in the hemisphere of the cerebellar cortex for control of wrist movement.

A region of cerebellar lobules V and VI makes strong loop connections with the primary motor (M1) and premotor (PM) cortical areas and is assumed to play essential roles in limb motor control. To examine its functional role, we compared the activities of its input, intermediate, and output elements, i.e., mossy fibers (MFs), Golgi cells (GoCs), and Purkinje cells (PCs), in three monkeys performing wrist movements in two different forearm postures. The results revealed distinct steps of information processing. First, MF activities displayed temporal and directional properties that were remarkably similar to those of M1/PM neurons, suggesting that MFs relay near copies of outputs from these motor areas. Second, all GoCs had a stereotyped pattern of activity independent of movement direction or forearm posture. Instead, GoC activity resembled an average of all MF activities. Therefore, inhibitory GoCs appear to provide a filtering function that passes only prominently modulated MF inputs to granule cells. Third, PCs displayed highly complex spatiotemporal patterns of activity, with coordinate frames distinct from those of MF inputs and directional tuning that changed abruptly before movement onset. The complexity of PC activities may reflect rapidly changing properties of the peripheral motor apparatus during movement. Overall, the cerebellar cortex appears to transform a representation of outputs from M1/PM into different movement representations in a posture-dependent manner and could work as part of a forward model that predicts the state of the peripheral motor apparatus.