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

Cerebellar Purkinje cells in male macaques combine sensory and motor information to predict the sensory consequences of active self-motion

Accurate perception and behavior rely on distinguishing sensory signals arising from unexpected events from those originating from our own voluntary actions. In the vestibular system, sensory input that is the consequence of active self-motion is canceled early at the first central stage of processing to ensure postural and perceptual stability. However, the source of the required cancellation signal was unknown. Here, we show that the cerebellum combines sensory and motor-related information to predict the sensory consequences of active self-motion. Recordings during attempted but unrealized head movements in two male rhesus monkeys, revealed that the motor-related signals encoded by anterior vermis Purkinje cells explain their altered sensitivity to active versus passive self-motion. Further, a model combining responses from ~40 Purkinje cells accounted for the cancellation observed in early vestibular pathways. These findings establish how cerebellar Purkinje cells predict sensory outcomes of self-movements, resolving a long-standing issue of sensory signal suppression during self-motion.

Total sleep deprivation reduces the table tennis anticipation performance of young men: A functional magnetic resonance imaging study

This study explored whether and how sleep deprivation (SD) affects sport-related anticipation. Twenty table tennis players and 28 non-athletes completed a table tennis anticipation task before and after 36 h SD. Functional magnetic resonance imaging (fMRI) data were acquired simultaneously. The results showed that, compared with the non-athletes, table tennis players had higher neural efficiency, manifested by their higher anticipation accuracy and lower frontal lobe activation. SD impaired anticipation performance, accompanied by decreased activation of the occipital and temporal lobes. Compensatory activation occurred in the left hippocampus and orbital part of the right inferior frontal gyrus (IFG) after SD in the table tennis player group, but not in the non-athlete group. The decreased accuracy of non-athletes was positively correlated with decreased activation of orbital part of the right IFG. This study's findings improve the understanding of the cognitive neuroscience mechanisms by which SD affects sport-related anticipation.

ANALYSIS OF HITTING METHOD AND WRIST STRENGTH OF STUDENT TENNIS PLAYERS

ABSTRACT Introduction: Wrist joint strength is important in tennis for angle control and racquet direction. Objective: Study the changes in muscle strength in the wrist region and the characteristics of joint movement under different tennis stroke styles. Methods: 50 students from a professional tennis club team at a university were selected as study subjects, and systematic professional wrist strength training was performed in the experimental group. In contrast, routine training was performed in the control class. The experimental training lasted for six weeks. During this period, the learning time of all groups remained the same, and no additional training or learning was added. Results: The experimental group's stability increased significantly, from 1.78 ± 0.67 to 2.25 ± 1.34 before training, and backstroke strength increased significantly, from 6.21 to 10.21; total stroke score also increased from 8.02 to 12.69. Conclusion: Improving wrist strength in tennis students may improve overall sports performance. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Distinct representations of body and head motion are dynamically encoded by Purkinje cell populations in the macaque cerebellum

The ability to accurately control our posture and perceive our spatial orientation during self-motion requires knowledge of the motion of both the head and body. However, while the vestibular sensors and nuclei directly encode head motion, no sensors directly encode body motion. Instead, the integration of vestibular and neck proprioceptive inputs is necessary to transform vestibular information into the body-centric reference frame required for postural control. The anterior vermis of the cerebellum is thought to play a key role in this transformation, yet how its Purkinje cells transform multiple streams of sensory information into an estimate of body motion remains unknown. Here, we recorded the activity of individual anterior vermis Purkinje cells in alert monkeys during passively applied whole-body, body-under-head, and head-on-body rotations. Most Purkinje cells dynamically encoded an intermediate representation of self-motion between head and body motion. Notably, Purkinje cells responded to both vestibular and neck proprioceptive stimulation with considerable heterogeneity in their response dynamics. Furthermore, their vestibular responses were tuned to head-on-body position. In contrast, targeted neurons in the deep cerebellar nuclei are known to unambiguously encode either head or body motion across conditions. Using a simple population model, we established that combining responses of~40-50 Purkinje cells could explain the responses of these deep cerebellar nuclei neurons across all self-motion conditions. We propose that the observed heterogeneity in Purkinje cell response dynamics underlies the cerebellum’s capacity to compute the dynamic representation of body motion required to ensure accurate postural control and perceptual stability in our daily lives.

Synchronous spiking of cerebellar Purkinje cells during control of movements

SignificanceThe information that one region of the brain transmits to another is usually viewed through the lens of firing rates. However, if the output neurons could vary the timing of their spikes, then, through synchronization, they would spotlight information that may be critical for control of behavior. Here we report that, in the cerebellum, Purkinje cell populations that share a preference for error convey, to the nucleus, when to decelerate the movement, by reducing their firing rates and temporally synchronizing the remaining spikes.

Non-Linear Frequency Dependence of Neurovascular Coupling in the Cerebellar Cortex Implies Vasodilation-Vasoconstriction Competition

Neurovascular coupling (NVC) is the process associating local cerebral blood flow (CBF) to neuronal activity (NA). Although NVC provides the basis for the blood oxygen level dependent (BOLD) effect used in functional MRI (fMRI), the relationship between NVC and NA is still unclear. Since recent studies reported cerebellar non-linearities in BOLD signals during motor tasks execution, we investigated the NVC/NA relationship using a range of input frequencies in acute mouse cerebellar slices of vermis and hemisphere. The capillary diameter increased in response to mossy fiber activation in the 6-300 Hz range, with a marked inflection around 50 Hz (vermis) and 100 Hz (hemisphere). The corresponding NA was recorded using high-density multi-electrode arrays and correlated to capillary dynamics through a computational model dissecting the main components of granular layer activity. Here, NVC is known to involve a balance between the NMDAR-NO pathway driving vasodilation and the mGluRs-20HETE pathway driving vasoconstriction. Simulations showed that the NMDAR-mediated component of NA was sufficient to explain the time course of the capillary dilation but not its non-linear frequency dependence, suggesting that the mGluRs-20HETE pathway plays a role at intermediate frequencies. These parallel control pathways imply a vasodilation-vasoconstriction competition hypothesis that could adapt local hemodynamics at the microscale bearing implications for fMRI signals interpretation.

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.

Functional Abnormalities of Cerebellum and Motor Cortex in Spinal Muscular Atrophy Mice

Spinal muscular atrophy (SMA) is a devastating genetic neuromuscular disease. Diffuse neuropathology has been reported in SMA patients and mouse models, however, functional changes in brain regions have not been studied. In the SMNΔ7 mouse model, we identified three types of differences in neuronal function in the cerebellum and motor cortex from two age groups: P7-9 (P7) and P11-14 (P11). Microelectrode array studies revealed significantly lower spontaneous firing and network activity in the cerebellum of SMA mice in both age groups, but it was more profound in the P11 group. In the motor cortex, however, neural activity was not different in either age group. Whole-cell patch-clamp was used to study the function of output neurons in both brain regions. In cerebellar Purkinje cells (PCs) of SMA mice, the input resistance was larger at P7, while capacitance was smaller at P11. In the motor cortex, no difference was observed in the passive membrane properties of layer V pyramidal neurons (PN5s). The action potential threshold of both types of output neurons was depolarized in the P11 group. We also observed lower spontaneous excitatory and inhibitory synaptic activity in PN5s and PCs respectively from P11 SMA mice. Overall, these differences suggest functional alterations in the neural network in these motor regions that change during development. Our results also suggest that neuronal dysfunction in these brain regions may contribute to the pathology of SMA. Comprehensive treatment strategies may consider motor regions outside of the spinal cord for better outcomes.

Population coding in the cerebellum: a machine learning perspective

The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron is a prediction that is compared with the actual observation, resulting in an error signal that originates in the inferior olive. Efficient learning requires that the error signal reach the DCN neurons, as well as the P-cells that project onto them. However, this basic rule of learning is violated in the cerebellum: the olivary projections to the DCN are weak, particularly in adulthood. Instead, an extraordinarily strong signal is sent from the olive to the P-cells, producing complex spikes. Curiously, P-cells are grouped into small populations that converge onto single DCN neurons. Why are the P-cells organized in this way, and what is the membership criterion of each population? Here, I apply elementary mathematics from machine learning and consider the fact that P-cells that form a population exhibit a special property: they can synchronize their complex spikes, which in turn suppress activity of DCN neuron they project to. Thus complex spikes cannot only act as a teaching signal for a P-cell, but through complex spike synchrony, a P-cell population may act as a surrogate teacher for the DCN neuron that produced the erroneous output. It appears that grouping of P-cells into small populations that share a preference for error satisfies a critical requirement of efficient learning: providing error information to the output layer neuron (DCN) that was responsible for the error, as well as the hidden layer neurons (P-cells) that contributed to it. This population coding may account for several remarkable features of behavior during learning, including multiple timescales, protection from erasure, and spontaneous recovery of memory.

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.

Neural Circuits of Inputs and Outputs of the Cerebellar Cortex and Nuclei

This article is dedicated to the memory of Masao Ito. Masao Ito made numerous important contributions revealing the function of the cerebellum in motor control. His pioneering contributions to cerebellar physiology began with his discovery of inhibition and disinhibition of target neurons by cerebellar Purkinje cells, and his discovery of the presence of long-term depression in parallel fiber-Purkinje cell synapses. Purkinje cells formed the nodal point of Masao Ito's landmark model of motor control by the cerebellum. These discoveries became the basis for his ideas regarding the flocculus hypothesis, the adaptive motor control system, and motor learning by the cerebellum, inspiring many new experiments to test his hypotheses. This article will trace the achievements of Ito and colleagues in analyzing the neural circuits of the input-output organization of the cerebellar cortex and nuclei, particularly with respect to motor control. The article will discuss some of the important issues that have been solved and also those that remain to be solved for our understanding of motor control by 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.

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.

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 cere-bellar 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, re-gardless 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 follow-ing four components are essential for recruitment of the cerebellar reserve: operational local neuron cir-cuitry; proper combination of mossy fiber inputs to be integrated; climbing fiber inputs to instruct favor-able 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 cere-bellar 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 re-serve as early as possible.

Proprioceptive Recognition with Artificial Neural Networks Based on Organizations of Spinocerebellar Tract and Cerebellum

Muscle kinematics and kinetics are nonlinearly encoded by proprioceptors, and the changes in muscle length and velocity are integrated into Ia afferent. Besides, proprioceptive signals from multiple muscles are probably mixed in afferent pathways, which all lead to difficulties in proprioceptive recognition for the cerebellum. In this study, the artificial neural networks, whose organizations are biologically based on the spinocerebellar tract and cerebellum, are utilized to decode the proprioceptive signals. Consistent with the controversy of the proprioceptive division in the dorsal spinocerebellar tract, the spinocerebellar tract networks incorporated two distinct inferences, (1) the centralized networks, which mixed Ia, II, and Ib and processed them together; (2) the decentralized networks, which processed Ia, II, and Ib afferents separately. The cerebellar networks were based on the Marr-Albus model to recognize the kinematic states. The networks were trained by a specific movement, and the trained networks were subsequently required to predict kinematic states of six movements. The results demonstrated that the centralized networks, which were more consistent with the physiological findings in recent years, had better recognition accuracy than the decentralized networks, and the networks were still effective even when proprioceptive afferents from multiple muscles were integrated.

Dynamics of directional tuning and reference frames in humans: A high-density EEG study

Recent developments in EEG recording and signal processing have made it possible to record in an unconstrained, natural movement task, therefore EEG provides a promising approach to understanding the neural mechanisms of upper-limb reaching control. This study specifically addressed how EEG dynamics in the time domain encoded finger movement directions (directional tuning) and posture dependence (movement reference frames) by applying representational similarity analysis. High-density EEG covering the entire scalp was recorded while participants performed eight-directional, center-out reaching movements, thereby allowing us to explore directional selectivity of EEG sources over the brain beyond somatosensory areas. A majority of the source processes exhibited statistically significant directional tuning during peri-movement periods. In addition, directional tuning curves shifted systematically when the shoulder angle was rotated to perform the task within a more laterally positioned workspace, the degree of tuning curve rotation falling between that predicted by models assuming extrinsic and shoulder-based reference frames. We conclude that temporal dynamics of neural mechanisms for motor control can be studied noninvasively in humans using high-density EEG and that directional sensitivity of motor and non-motor processing is not limited within the sensorimotor areas but extends to the whole brain areas.

Assessing cerebellar brain inhibition (CBI) via transcranial magnetic stimulation (TMS): A systematic review

The inhibitory tone that the cerebellum exerts on the primary motor cortex (M1) is known as cerebellar brain inhibition (CBI). Studies show CBI to be relevant to several motor functions, including adaptive motor learning and muscle control. CBI can be assessed noninvasively via transcranial magnetic stimulation (TMS) using a double-coil protocol. Variability in parameter choice and controversy surrounding the protocol's ability to isolate the cerebellothalamocortical pathway casts doubt over its validity in neuroscience research. This justifies a systematic review of both the protocol, and its application. The following review examines studies using the double-coil protocol to assess CBI in healthy adults. Parameters and CBI in relation to task-based studies, other non-invasive protocols, over different muscles, and in clinical samples are reviewed. Of the 1398 studies identified, 24 met selection criteria. It was found that methodological design and selection of parameters in several studies may have reduced the validity of outcomes. Further systematic testing of CBI protocols is warranted, both from a parameter and task-based perspective.

The Cerebellum: Adaptive Prediction for Movement and Cognition

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops.

Implicit Timing as the Missing Link between Neurobiological and Self Disorders in Schizophrenia?

Disorders of consciousness and the self are at the forefront of schizophrenia symptomatology. Patients are impaired in feeling themselves as the authors of their thoughts and actions. In addition, their flow of consciousness is disrupted, and thought fragmentation has been suggested to be involved in the patients' difficulties in feeling as being one unique, unchanging self across time. Both impairments are related to self disorders, and both have been investigated at the experimental level. Here we review evidence that both mechanisms of motor control and the temporal structure of signal processing are impaired in schizophrenia patients. Based on this review, we propose that the sequencing of action and perception plays a key role in the patients' impairments. Furthermore, the millisecond time scale of the disorders, as well as the impaired sequencing, highlights the cooperation between brain networks including the cerebellum, as proposed by Andreasen (1999). We examine this possibility in the light of recent knowledge on the anatomical and physiological properties of the cerebellum, its role in timing, and its involvement in known physiological impairments in patients with schizophrenia, e.g., resting states and brain dynamics. A disruption in communication between networks involving the cerebellum, related to known impairments in dopamine, glutamate and GABA transmission, may help to better explain why patients experience reduced attunement with the external world and possibly with themselves.