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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.

Cerebellar reserve refers to the capacity of the cerebellum to compensate for tissue damage or loss of function resulting from many different etiologies. When the inciting event produces acute focal damage (e.g., stroke, trauma), impaired cerebellar function may be compensated for by other cerebellar areas or by extracerebellar structures (i.e., structural cerebellar reserve). In contrast, when pathological changes compromise cerebellar neuronal integrity gradually leading to cell death (e.g., metabolic and immune-mediated cerebellar ataxias, neurodegenerative ataxias), it is possible that the affected area itself can compensate for the slowly evolving cerebellar lesion (i.e., functional cerebellar reserve). Here, we examine cerebellar reserve from the perspective of the three cornerstones of clinical ataxiology: control of ocular movements, coordination of voluntary axial and appendicular movements, and cognitive functions. Current evidence indicates that cerebellar reserve is potentiated by environmental enrichment through the mechanisms of autophagy and synaptogenesis, suggesting that cerebellar reserve is not rigid or fixed, but exhibits plasticity potentiated by experience. These conclusions have therapeutic implications. During the period when cerebellar reserve is preserved, treatments should be directed at stopping disease progression and/or limiting the pathological process. Simultaneously, cerebellar reserve may be potentiated using multiple approaches. Potentiation of cerebellar reserve may lead to compensation and restoration of function in the setting of cerebellar diseases, and also in disorders primarily of the cerebral hemispheres by enhancing cerebellar mechanisms of action. It therefore appears that cerebellar reserve, and the underlying plasticity of cerebellar microcircuitry that enables it, may be of critical neurobiological importance to a wide range of neurological/neuropsychiatric conditions.

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 + t_1 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 (R^2) decreased moderately from 0.89 to 0.86 when t_1 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.

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.

This review surveys the physiological, behavioral, and computational evidence converging to the view of the cerebrocerebellum as a locus for predictive computation. State prediction is a neural mechanism that enables rapid and stable control of the body, even when sensory feedback from the periphery has a temporal delay. This predictive computation is known as an internal forward model and hypothesized to locate in the cerebellar circuit. We revisit the classical work of Marr, Albus, and Ito and argue that the cerebellum operates as a regressor of continuous dynamics rather than a classifier conventionally assumed in the Marr-Albus perceptron model. Specifically, the cerebellar output at one moment is predictive of the cerebellar input in the future, supporting the internal-forward-model hypothesis of the cerebellum. Finally, we speculate on the computation within the cerebellum and in the cerebrocerebellar loop and summarize unresolved questions for future studies.

This chapter brings enigmatic connectivity of the cerebellar dentate nucleus (DN) and the cerebellar forward model hypothesis together to demonstrate the cerebrocerebellum as loci of Kalman filters. We start with a brief history of the cerebellar internal model hypothesis. Next we present two lines of new evidence for the forward model hypothesis. First, we show physiological evidence that the cerebellar outputs from DN are predictive for the inputs to the cerebrocerebellum. Second, we introduce an enigmatic MF collateral to DN and demonstrate it is an essential key to the Kalman filter model. We further discuss how the Kalman filter model for the motor cerebrocerebellum could be generalized to non-motor parts as a unifying principle for the diverse functions of the cerebrocerebellum. We conclude that the Kalman filter model also explains how parallel modules in the cerebrocerebellar communication loops are coordinated in a cascadic manner, providing a partial explanation for unity of mind.

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.

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.

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.

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.

Summary 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.

This paper investigates motor characteristics during circular tracking movements of human wrist. Ten subjects performed a visually guided target tracking task using two degrees-of-freedom wrist movements as a tracer. Based on trajectories of the tracer and the target, three control parameters in polar coordinates were considered: R error as an evaluation of the circular movement performance, theta error of the position-control precision, and omega error of the velocity-control precision. We then examined the influence of three different speeds (0.05, 0.1, and 0.2 Hz) and visibility of the target on the three parameters to observe changes in control strategy. The theta error particularly demonstrated that subjects were more dependent on position control for the lower tracking speed of 0.05 Hz with a visible target, where the highest percentage increase of 210.6% in theta errors from the target visible to the target invisible regions was reported. However, as the target speed increases, the subjects...

It is widely accepted that the cerebellum acquires and maintain internal models for motor control. An internal model simulates mapping between a set of causes and effects. There are two candidates of cerebellar internal models, forward models and inverse models. A forward model transforms a motor command into a prediction of the sensory consequences of a movement. In contrast, an inverse model inverts the information flow of the forward model. Despite the clearly different formulations of the two internal models, it is still controversial whether the cerebro-cerebellum, the phylogenetically newer part of the cerebellum, provides inverse models or forward models for voluntary limb movements or other higher brain functions. In this article, we review physiological and morphological evidence that suggests the existence in the cerebro-cerebellum of a forward model for limb movement. We will also discuss how the characteristic input–output organization of the cerebro-cerebellum may contribute to forward models for non-motor higher brain functions.

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.

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.

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.

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.

Quantitative evaluation of human motor function is a key technology for diagnosing and evaluating movement disorders such as cerebellar ataxia, Parkinson's disease, or stroke. In addition, it is ideal to make the evaluation anywhere, anytime (e.g. at home) for wider clinical applications. Thus, a number of studies have been done to achieve this goal. In our previous study, we developed a novel system for quantitative evaluation of wrist movement using a simple tracking task with a manipulandum. Although the evaluation system was effective, its custom-made input device was expensive. Therefore it was difficult to use it at home to capture daily or weekly changes of patients' conditions repeatedly. To overcome these problems, we have developed a new system for quantitative evaluation of motor function using a Kinect v2 sensor (Microsoft Inc.), which is easily available with low cost. A smooth tracking task employed in our previous system was also used in this study. We examined whether the new system with Kinect v2 sensor had sufficient accuracy and quality of data. We also tested the same analytical methods proposed in our previous study. Preliminary test showed promising performance of the new system for quantitative evaluation of motor function. We are going to connect the system with a cloud database system (e.g., Microsoft Azure) so that the system will be available for patients anywhere, anytime.

Once people have a well-trained motor skill, their performance becomes stabilized and achieving substantial improvement is difficult. Recently, we have shown that even a plateaued hand motor skill can be upgraded with short-period electrical stimulation to the hand prior to the task. Here, we identify the neuronal substrates underlying the improvement of the plateaued skill by examining the enhanced functional connectivity in the sensory-motor regions that are associated with motor learning. We measured brain activity using functional magnetic resonance imaging and performed psychophysiological interaction analysis. We recruited seven right-handed very-well trained participants, whose motor performance of continuously rotating two balls with their right hands became stabilized at higher performance levels. We prepared two experiments, in each of which they repeated an experimental run 16 times. In each run, they performed this cyclic rotation as many times as possible in 16 s. In the thenar-stimulation experiment, we applied 60-s stimulation to the thenar muscle before each of the 5th - 12th runs, and the others were preceded by ineffective sham stimulation. In the control experiment, the sham was always provided. Thenar stimulation enabled the participants to perform the movements at higher cycles. In association with this performance improvement, we found enhanced activity couplings between the primary motor cortex and the sensorimotor territory of the putamen and between the cerebellum and the primary sensorimotor cortices, without any quantitative activity increase. Neither behavioral change nor these increased activity couplings were observed in the control.Thus, in contrast to the stable neuronal states in the cortico-subcortical motor circuits when the well-learned task is repeated at the later stages of motor skill learning, plastic changes in the motor circuits seem to be required when the plateaued skill is upgraded, and the stimulation may entail a state of readiness for the plastic change that allows subsequent performance improvement.

A classic hypothesis for motor control assumes that the predictive controller (PC) and the feedback controller (FBC) work in parallel. Nevertheless, dissociation of outputs from the two controllers has never been possible, preventing evaluation of motor functions in movement disorders. Here we demonstrate a new method to separate outputs from PC and FBC. Subjects performed a tracking movement to pursue a slowly moving target, while we recorded movement with a manipulandum or a Kinect v2 sensor. We identified three components of tracking movement that were separable with FFT and identified in terms of their function. The primary, a lower frequency component ( 3.0 Hz), which showed characteristic increases in patients with Parkinson’s disease or stroke. Each of the three components provides unique parameters to quantify motor function of patients with movement disorders. Our new method provides a new framework to characterize movement disorders.

Holmes proposed not only the term ataxia, but also opposite clinical signs related to muscle recruitment, which have escaped clinical attention; (1) asthenia, representing delay in initiating muscle contraction and slowness in attaining exertion of full power, and (2) adventitiousness, representing adventitious movements. Recent physiological studies have shown that cerebellar outputs are modified by release or facilitation of Purkinje cell-mediated inhibition on dentate neurons. We believe that asthenia and adventitiousness, which correlate with deficits in the control of disinhibition and inhibition, respectively, deserve more attention in clinical examination.

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.

To examine whether mossy fibers (MFs) in the cerebellar hemisphere show delay activity, we recorded MF activity during a wrist movement task with a random instructed delay period in two monkeys. Among 155 task-related MFs, 70 MFs (45%) demonstrated significant delay activity. Those MFs were widely distributed in the cerebellar hemisphere. Some of the activities were evoked by instruction cue presentation, whereas other activity started in anticipation of the upcoming go signal. For most MFs, the delay activities showed directional tuning. These patterns of the activity were in common with those of neurons in the cerebral motor cortices.

Background: Fundamental cytological changes of amyotrophic lateral sclerosis (ALS) were looked for by comparing relatively preserved Onuf’s nucleus (ON) and severely affected neighboring motor neuron groups (dorsolateral alpha motoneurons (DL) and other anterior horn neurons (OAH)). The second sacral segments from 11 ALS patients and 5 controls were initially quadruple-labeled for phosphorylated and non-phosphorylated TAR DNA-binding protein of 43 kDa (TDP43), and p62 with DAPI to identify TDP43-related changes. After digital recording of these fluorescence data encompassing the entire specimen at a high resolution, the same sections were stained with Kluver-Barrera method to obtain their exact bright-field counterparts. This novel approach facilitated exact identification of ON. Furthermore, this cell to cell comparison enabled to correlate quantitative indices of the neuronal cell bodies: perimeter, area and circularity index (CI) i.e. the ratio of (perimeter/2π) divided by the square root of (area/π), which decreases with dendritic retraction, overall number of neurons and inclusions. Results: In addition to known preservation of ON neuron number relative to DL and OAH, size reduction of ON neurons was not significant even in the advanced stage. Significant size reduction in DL was counteracted in the presence of TDP43-positive inclusions. Early increase of neuronal size in OAH was further enhanced by the presence of TDP43-positive inclusions. Even with these heterogeneous cytopathological changes, a decrease in CI was consistent in all groups at an early phase and was correlated with neuronal loss. Conclusions: Among variable cytological changes of ALS, a decrease in CI is a consistent early feature shared between non-atrophic ON neurons and other anterior horn neurons with either decreased (DL) or even increased (OAH) size and profounder neuronal loss. This decrease in CI, representative of dendritic retraction, is fundamental to ALS pathogenesis, not necessarily linked to cell size and pathological inclusions.

The ventral premotor area (PMv) is a major source of input to the primary motor cortex (M1). To examine the potential hierarchical processing between these motor areas, we recorded the activity of PMv neurons in a monkey trained to perform wrist movements in different directions with the wrist in three different postures. The task dissociated three major variables of wrist movement: muscle activity, direction of joint movement and direction of movement in space. Many PMv neurons were directionally tuned. Nearly all of these neurons (61/65, 94%) were 'extrinsic-like'; they seemed to encode the direction of movement in space independent of forearm posture. These results are strikingly different from results from M1 of the same animal, and suggest that intracortical processing between PMv and M1 may contribute to a sensorimotor transformation between extrinsic and intrinsic coordinate frames.

Muscle activity is the final signal for motion control from the brain. Based on this biological characteristic, Electromyogram (EMG) signals have been applied to various systems that interface human with external environments such as external devices. In order to use EMG signals as input control signal for this kind of system, the current EMG driven torque estimation models generally employ the mathematical model that estimates the nonlinear transformation function between the input signal and the output torque. However, these models need to estimate too many parameters and this process cause its estimation versatility in various conditions to be poor. Moreover, as these models are designed to estimate the joint torque, the input EMG signals are tuned out of consideration for the physiological synergetic contributions of multiple muscles for motion control. To overcome these problems of the current models, we proposed a new tuning model based on the synergy control mechanism between multiple muscles in the cortico-spinal tract. With this synergetic tuning model, the estimated contribution of multiple muscles for the motion control is applied to tune the EMG signals. Thus, this cortico-spinal control mechanism-based process improves the precision of torque estimation. This system is basically a forward dynamics model that transforms EMG signals into the joint torque. It should be emphasized that this forward dynamics model uses a musculo-skeletal model as a constraint. The musculo-skeletal model is designed with precise musculo-skeletal data, such as origins and insertions of individual muscles or maximum muscle force. Compared with the mathematical model, the proposed model can be a versatile model for the torque estimation in the various conditions and estimates the torque with improved accuracy. In this paper, we also show some preliminary experimental results for the discussion about the proposed model.

Quantitative evaluation of cerebellar ataxia is crucial for precise evaluation of cerebellar diseases. In particular, it is essential to capture anomaly of the causal motor commands as well as the resultant movement for the ataxia. In this paper, we propose a new method to make a quantitative evaluation of the cerebellar ataxia based on EMG signals. As an experimental task, we asked subjects to perform step-tracking wrist movements with a manipulandum, and recorded wrist joint movements and muscle activities of four wrist prime movers with surface electrodes. The subjects included fourteen patients with cerebellar diseases and thirteen normal controls. We succeeded to extract two parameters from the EMG signals of the four wrist prime movers, which characterize the pathological patterns of muscle activities for the cerebellar ataxia, Total Co-contraction Level (TCL) and Directionality of Muscle Activity (DMA). We found that the two parameters were useful to characterize pathological patterns of muscle activities in cerebellar ataxia. Consequently, it is expected that our proposed method is useful not only in tracking condition of cerebellar patients but also in evaluating the effects of a treatment or neuro-rehabilitation aiming at the normalization of motor commands.