Motor memory and local minimization of error and effort, not global optimization, determine motor behavior.

Many real life tasks that require impedance control to minimize motion error are characterized by multiple solutions where the task can be performed either by co-contracting muscle groups, which requires a large effort, or, conversely, by relaxing muscles. However, human motor optimization studies have focused on tasks that are always satisfied by increasing impedance and that are characterized by a single error-effort optimum. To investigate motor optimization in the presence of multiple solutions and hence optima, we introduce a novel paradigm that enables us to let subjects repetitively (but inconspicuously) use different solutions and observe how exploration of multiple solutions affect their motor behavior. The results show that the behavior is largely influenced by motor memory with subjects tending to involuntarily repeat a recent suboptimal task-satisfying solution even after sufficient experience of the optimal solution. This suggests that the CNS does not optimize co-activation tasks globally but determines the motor behavior in a tradeoff of motor memory, error, and effort minimization.

Sparse linear regression for reconstructing muscle activity from human cortical fMRI.

In humans, it is generally not possible to use invasive techniques in order to identify brain activity corresponding to activity of individual muscles. Further, it is believed that the spatial resolution of non-invasive brain imaging modalities is not sufficient to isolate neural activity related to individual muscles. However, this study shows that it is possible to reconstruct muscle activity from functional magnetic resonance imaging (fMRI). We simultaneously recorded surface electromyography (EMG) from two antagonist muscles and motor cortices activity using fMRI, during an isometric task requiring both reciprocal activation and co-activation of the wrist muscles. Bayesian sparse regression was used to identify the parameters of a linear mapping from the fMRI activity in areas 4 (M1) and 6 (pre-motor, SMA) to EMG, and to reconstruct muscle activity in an independent test data set. The mapping obtained by the sparse regression algorithm showed significantly better generalization than those obtained from algorithms commonly used in decoding, i.e., support vector machine and least square regression. The two voxel sets corresponding to the activity of the antagonist muscles were intermingled but disjoint. They were distributed over a wide area of pre-motor cortex and M1 and not limited to regions generally associated with wrist control. These results show that brain activity measured by fMRI in humans can be used to predict individual muscle activity through Bayesian linear models, and that our algorithm provides a novel and non-invasive tool to investigate the brain mechanisms involved in motor control and learning in humans.

Faunal activity rhythms influencing early community succession of an implanted whale carcass offshore Sagami Bay, Japan.

Benthic community succession patterns at whale falls have been previously established by means of punctual submersible and ROV observations. The contribution of faunal activity rhythms in response to internal tides and photoperiod cues to that community succession dynamism has never been evaluated. Here, we present results from a high-frequency monitoring experiment of an implanted sperm whale carcass in the continental slope (500 m depth) offshore Sagami Bay, Japan. The benthic community succession was monitored at a high frequency in a prolonged fashion (i.e. 2-h intervals for 2.5 months) with a seafloor lander equipped with a time-lapse video camera and an acoustic Doppler profiler to concomitantly study current flow dynamics. We reported here for the first time, to the best of our knowledge, the occurrence of strong 24-h day-night driven behavioral rhythms of the most abundant species (Simenchelys parasitica; Macrocheira kaempferi, and Pterothrissus gissu). Those rhythms were detected in detriment of tidally-controlled ones. Evidence of a diel temporal niche portioning between scavengers and predators avoiding co-occurrence at the carcass, is also provided. The high-frequency photographic and oceanographic data acquisition also helped to precisely discriminate the transition timing between the successional stages previously described for whale falls' attendant communities.

The cerebellum and VOR/OKR learning models.

Although one particular model of the cerebellum, as proposed by Marr and Albus, provides a formal framework for understanding how heterosynaptic plasticity of Purkinje cells might be used for motor learning, the physiological details remain largely an engima. Developments in computational neuroscience and artificial neural networks applied to real control problems are essential to understand fully how workspace errors associated with movement performances can be converted into motor-command errors, and how these errors can then be used as one kind of synaptic input by motor-learning algorithms that are based on biologically plausible rules involving heterosynaptic plasticity. These developments, as well as recent advances in the study of cellular mechanisms of synaptic plasticity, form the basis for the detailed computational models of cerebellar motor learning that have been proposed. These models provide hints toward resolving a long-standing controversy in the oculomotor literature regarding the sites of adaptive changes in the vestibuloocular reflex (VOR) and the optokinetic eye movement response (OKR), and suggest new experiments to elucidate general mechanisms of sensory motor learning.

Internal models for motor control and trajectory planning.

A number of internal model concepts are now widespread in neuroscience and cognitive science. These concepts are supported by behavioral, neurophysiological, and imaging data; furthermore, these models have had their structures and functions revealed by such data. In particular, a specific theory on inverse dynamics model learning is directly supported by unit recordings from cerebellar Purkinje cells. Multiple paired forward inverse models describing how diverse objects and environments can be controlled and learned separately have recently been proposed. The 'minimum variance model' is another major recent advance in the computational theory of motor control. This model integrates two furiously disputed approaches on trajectory planning, strongly suggesting that both kinematic and dynamic internal models are utilized in movement planning and control.

Exploration of signal transduction pathways in cerebellar long-term depression by kinetic simulation.

Because multiple molecular signal transduction pathways regulate cerebellar long-term depression (LTD), which is thought to be a possible molecular and cellular basis of cerebellar learning, the systematic relationship between cerebellar LTD and the currently known signal transduction pathways remains obscure. To address this issue, we built a new diagram of signal transduction pathways and developed a computational model of kinetic simulation for the phosphorylation of AMPA receptors, known as a key step for expressing cerebellar LTD. The phosphorylation of AMPA receptors in this model consists of an initial phase and an intermediate phase. We show that the initial phase is mediated by the activation of linear cascades of protein kinase C (PKC), whereas the intermediate phase is mediated by a mitogen-activated protein (MAP) kinase-dependent positive feedback loop pathway that is responsible for the transition from the transient phosphorylation of the AMPA receptors to the stable phosphorylation of the AMPA receptors. These phases are dually regulated by the PKC and protein phosphatase pathways. Both phases also require nitric oxide (NO), although NO per se does not show any ability to induce LTD; this is consistent with a permissive role as reported experimentally (Lev-Ram et al., 1997). Therefore, the kinetic simulation is a powerful tool for understanding and exploring the behaviors of complex signal transduction pathways involved in cerebellar LTD.

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.

Internal models in the cerebellum.

This review will focus on the possibility that the cerebellum contains an internal model or models of the motor apparatus. Inverse internal models can provide the neural command necessary to achieve some desired trajectory. First, we review the necessity of such a model and the evidence, based on the ocular following response, that inverse models are found within the cerebellar circuitry. Forward internal models predict the consequences of actions and can be used to overcome time delays associated with feedback control. Secondly, we review the evidence that the cerebellum generates predictions using such a forward model. Finally, we review a computational model that includes multiple paired forward and inverse models and show how such an arrangement can be advantageous for motor learning and control.

Internal models for motor control.

The process of moving the hand to a target in space involves a series of sensorimotor transformations that translate visual and other sensory information about the location of the target object and the limbs into a set of motor commands that will bring the hand to the desired position. Recent work at various laboratories has provided strong support for the hypothesis that the CNS learns and maintains internal models of sensorimotor transformations. An internal model is a neural system that mimics the behaviour of the sensorimotor system and objects in the external environment. Internal models enable the CNS to predict the consequences of motor commands and to determine the motor commands required to perform specific tasks. In this chapter, we first summarize recent computational, behavioural and neurophysiological studies that address the theoretical necessity of internal models, the locations of internal models, and the neural mechanism for acquiring internal models through learning. Then, we propose a new computational model of multiple internal models.

Immunohistochemical and ultrastructural study of subacute thyroiditis, with special reference to multinucleated giant cells.

Twenty-four cases of subacute thyroiditis were examined immunohistochemically and ultrastructurally, with special attention being directed to the multinucleated giant cells that characterize the lesions of this condition. Immunohistochemical study revealed that 99 per cent of the giant cells contained lysozyme, 82 per cent contained vimentin, 66 per cent contained alpha 1-antitrypsin, and 61 per cent contained thyroxine. Only 17 per cent contained thyroglobulin, 5 per cent contained keratin, 16 per cent contained epithelial membrane antigen, and 4 per cent contained leukocyte common antigen. Mononuclear cells infiltrating the follicular spaces showed a staining pattern similar to that of the multinucleated giant cells. Desquamated follicular epithelial cells were strongly positive for thyroglobulin and thyroxine, while regenerated epithelia that formed small follicles were positive for thyroglobulin but negative for thyroxine. Electron microscopic examination of cell ultrastructure revealed that most multinucleated giant cells had structures identical with those of infiltrating mononuclear cells, particularly with histiocytes, and that giant cells were formed by mononuclear cell fusion. These findings indicate the majority of multinucleated giant cells in subacute thyroiditis are derived from mononuclear-histiocyte cells.

Chronic thyroiditis: thyroid function and histologic correlations in 601 cases.

Six hundred one patients with histologically proven "chronic thyroiditis" were assessed for the correlation of thyroid function to histologic findings. The histology of chronic thyroiditis was classified into four groups (oxyphilic, mixed, focal, and hyperplastic), and the thyroid function of patients was divided into hyperthyroid, euthyroid, latent hypothyroid, and overt hypothyroid, based on the laboratory data of serum triiodothyronine (T3), thyroxine (T4), and thyrotropin (TSH) levels, as well as thyrotropin-releasing hormone (TRH) tests. In the oxyphilic group (137 cases), 116 (85%) of the patients were classified as hypothyroid: 52 (38%) as latent hypothyroid and 64 (47%) as overt hypothyroid. In the mixed group (161 cases), the thyroid function of the patients varied. Thirty-seven (23%) of the patients were classified as hyperthyroid, 61 (39%) as euthyroid, 54 (33%) as latent hypothyroid, and nine (5%) as overt hypothyroid. In this group thyroid function was intimately related to the ratio of replacement by hyperplastic-changed follicles and oxyphilic-changed follicles. In the focal group (149 cases), 123 (83%) of the patients were classified as euthyroid, while 22 (14%) were classified as latent hypothyroid. The frequency of latent hypothyroid patients increased in parallel with the severity of cell infiltration. In the hyperplastic group (154 cases), 130 (85%) of the patients were classified as hyperthyroid. In this series 19 patients under 10 years of age were included, and no difference in the distribution of histologic varieties was observed between juvenile and adult patients. Thyroid needle biopsy is a useful and safe tool, not only for the histologic diagnosis of chronic thyroiditis, but also for the evaluation of thyroid function and the identification of causes for hyperthyroidism or hypothyroidism.

Histologic features of thyroid gland in a patient with bromide-induced hypothyroidism.

A case of a 22-year-old woman with bromide-induced hypothyroidism is presented. There have been no reports dealing with changes in thyroid function and thyroid morphologic characteristics associated with bromide intoxication. The characteristic histologic features of the affected thyroid gland included a marked hyperplasia of follicles lined by tall columnar follicular cells with foci of papillary proliferation and a loss of colloid materials in the follicular lumen. Ultrastructurally, thyroid follicular cells showed a marked dilatation of rough endoplasmic reticulum containing no electron-dense materials. X-ray microanalysis of the thyroid follicular cells revealed the presence of significant amounts of bromide and an absence of iodine. These indicated that severe hypothyroidism in this patient might be related to the accumulation of bromide in the thyroid follicular cells.

Disopyramide induces insulin secretion and plasma glucose diminution: studies using the in situ canine pancreas.

The mechanism of disopyramide-induced hypoglycemia, a life-threatening complication in the antiarrhythmic drug treatment, is still controversial. To elucidate this, we have evaluated plasma insulin (IRI) and glucagon (IRG) responses in the pancreatic vein (PV) of the in situ pancreas as well as responses of plasma IRI, IRG, and glucose in the femoral artery (FA) to disopyramide phosphate administration in anesthetized dogs. First, infusion of disopyramide at a dose of 50 mg for ten minutes directly into the pancreatic artery, but not the vehicle, increased significantly plasma IRI concentration in the PV (P less than .05 or less), where the IRI response started within three minutes and reached a peak of 2.8-fold preinfusion value at 30 minutes after starting the infusion (n = 7). Plasma IRI concentration in the FA also increased slightly but significantly (P less than .05). Plasma IRG concentration in the PV initially decreased significantly (P less than .05 or less) and in the FA at one point (P less than .05) during the infusion, and then increased significantly after cessation of the infusion, showing a peak of 1.9-fold preinfusion value at 60 minutes in the PV and the FA (P less than .05). Plasma glucose concentration in the FA decreased slowly and significantly after the infusion (P less than .05 or less) and fell by 16% of the baseline value at 60 minutes (P less than .05). Second, serum disopyramide concentration of 13.7 +/- 2.8 micrograms/mL at ten minutes, which corresponds to a twofold to threefold concentration of the human therapeutic level (n = 4).(ABSTRACT TRUNCATED AT 250 WORDS)

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.

Synaptic currents at interpositorubral and corticorubral excitatory synapses measured by a new iterative single-electrode voltage-clamp method.

A new iterative single-electrode voltage clamp method was applied to the measurement of synaptic currents in the red nucleus (RN) neuron of the cat. Voltage clamp was attained within 10 repetitions with great stability and the new algorithm was demonstrated to be superior to the original algorithm of iterative voltage clamp. With a conventional microelectrode, it was possible to measure the synaptic current with the time resolution of 50 microseconds. The synaptic currents evoked by stimulation of the contralateral interpositus nucleus (IP) had time-to-peak ranging from 200 to 540 microseconds and fitted well to alpha functions. Corticorubral (CR) synaptic current was also measured by making use of synaptic plasticity. The stimulation of the ipsilateral cerebral peduncle in cats with chronic lesion of the contralateral IP evoked fast rising EPSPs, as reported previously. The CR-EPSPs with times-to-peak less than 1 ms were subjected to voltage clamp. The CR synaptic currents had times-to-peak ranging from 350 to 880 microseconds. Since most of the interpositorubral (IR) synapses and a part of the CR synapses in IP-lesioned cats are situated on the somatic membrane of RN neurons and some of the CR synaptic currents were as rapid as the IR synaptic currents, the observed synaptic currents evoked by stimulation of the IP and those of the fast-rising CR-EPSPs were taken to originate from the synaptic membrane under space-clamp, i.e. soma. The present study provided additional evidence for the sprouting of the CR fibers as well as the time course of the synaptic current at the dendritic synapses remote from the soma, for the first time.

A mathematical model that reproduces vertical ocular following responses from visual stimuli by reproducing the simple spike firing frequency of Purkinje cells in the cerebellum.

A mathematical model that accurately reproduces eye movements from visual stimuli and incorporates intermediate neural signals is useful for quantitative analysis of the neural mechanisms involved in transforming visual stimuli to eye movements. Here we describe a mathematical model consisting of two systems: a non-linear system that relates retinal slip to simple spike firing frequency of Purkinje cells in the ventral paraflocculus (VPFL) and a linear system that relates VPFL simple spike firing frequency to eye movement. This model accurately reproduced the firing frequency of Purkinje cells and ocular following responses from visual stimulation paradigms used in physiological experiments.

A mathematical analysis of the characteristics of the system connecting the cerebellar ventral paraflocculus and extraoculomotor nucleus of alert monkeys during upward ocular following responses.

Movements of the visual scene evoke short-latency ocular-following-responses (OFR). Many studies suggest that a neural pathway containing the cerebellar-ventral-paraflocculus (VPFL) mediates OFR. The relationship between eye movement and simple-spike firing in the VPFL during OFR has been studied in detail using an inverse dynamics approach. The relationship between eye movement and cell firing in the extraoculomotor nucleus (MN) has already been reported. However, no studies have examined the information transformation that occurs between the VPFL and the MN during OFR. In this paper, using an inverse dynamics approach, we derive a transfer function that represents the characteristics of the structure connecting the VPFL and the MN during upward OFR. This structure appears to contain a kind of neural integrator, which constructs eye-velocity-and-position information from eye-acceleration-and-velocity information. We propose a diagram for the neural integration commonly at work during all types of upward eye movement. This is a closed-loop circuit containing a low-pass filter. The low-pass filter can construct eye-velocity-and-position information from an eye-acceleration-velocity-position command similar to the final motor command used commonly for all upward eye movements. Anatomical and electrophysiological data suggest that the vestibular nuclei-interstitial nucleus of Cajal-vestibular nuclei loop might perform such neural integration.

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.

Possible explanations for trajectory curvature in multijoint arm movements.

Although the straightness of hand paths is a widely accepted feature of human multijoint reaching movement, detailed examinations have revealed slight curvatures in some regions of the workspace. This observation raises the question of whether planned trajectories are straight or curved. If they are straight, 3 possible factors can explain the observed curvatures: (a) imperfect control, (b) visual distortion, or (c) interaction between straight virtual trajectories and the dynamics of the arm. Participants instructed to generate straight movement paths produced movements much straighter than those generated spontaneously. Participants generated spontaneously curved trajectories in the frontoparallel plane, where visual distortion is not expected. Electromyograms suggested that participants generated straighter paths without an increase in arm stiffness. These findings argue against the 3 factors. It follows that planned trajectories are likely to be curved.