Learning to expect the unexpected: rapid updating in primate cerebellum during voluntary self-motion

Accounting for uncertainty: inhibition for neural inference in the cerebellum

Sensorimotor coordination is thought to rely on cerebellar-based internal models for state estimation, but the underlying neural mechanisms and specific contribution of the cerebellar components is unknown. A central aspect of any inferential process is the representation of uncertainty or conversely precision characterizing the ensuing estimates. Here, we discuss the possible contribution of inhibition to the encoding of precision of neural representations in the granular layer of the cerebellar cortex. Within this layer, Golgi cells influence excitatory granule cells, and their action is critical in shaping information transmission downstream to Purkinje cells. In this review, we equate the ensuing excitation-inhibition balance in the granular layer with the outcome of a precision-weighted inferential process, and highlight the physiological characteristics of Golgi cell inhibition that are consistent with such computations.

Loss of peripheral vestibular input alters the statistics of head movement experienced during natural self-motion

KEY POINTS

Sensory systems are adapted to the statistical structure of natural stimuli, thereby optimizing neural coding. Head motion during natural activities is first sensed and then processed by central vestibulo-motor pathways to influence subsequent behaviour, thereby establishing a feedback loop. To investigate the role of this vestibular feedback on the statistical structure of the head movements, we compared head movements in patients with unilateral vestibular loss and healthy controls. We show that the loss of vestibular feedback substantially alters the statistical structure of head motion for activities that require rapid online feedback control and predict this change by modelling the effects of increased movement variability. Our findings suggest that, following peripheral vestibular loss, changes in the reliability of the sensory input to central pathways impact the statistical structure of head motion during voluntary behaviours.

ABSTRACT

It is widely believed that sensory systems are adapted to optimize neural coding of their natural stimuli. Recent evidence suggests that this is the case for the vestibular system, which senses head movement and contributes to essential functions ranging from the most automatic reflexes to voluntary motor control. During everyday behaviours, head motion is sensed by the vestibular system. In turn, this sensory feedback influences subsequent behaviour, raising the questions of whether and how real-time feedback provided by the vestibular system alters the statistical structure of head movements. We predicted that a reduction in vestibular feedback would alter head movement statistics, particularly for tasks reliant on rapid vestibular feedback. To test this proposal, we recorded six-dimensional head motion in patients with variable degrees of unilateral vestibular loss during standard balance and gait tasks, as well as dynamic self-paced activities. While distributions of linear accelerations and rotational velocities were comparable for patients and age-matched healthy controls, comparison of power spectra revealed significant differences during more dynamic and challenging activities. Specifically, consistent with our prediction, head movement power spectra were significantly altered in patients during two tasks that required rapid online vestibular feedback: active repetitive jumping and walking on foam. Using computational methods, we analysed concurrently measured torso motion and identified increases in head-torso movement variability. Taken together, our results demonstrate that vestibular loss significantly alters head movement statistics and further suggest that increased variability and impaired feedback to internal models required for accurate motor control contribute to the observed changes.

Movement-induced hypoalgesia: behavioral characteristics and neural mechanisms

Pain is essential for our survival because it helps to protect us from severe injuries. Nociceptive signals may be exacerbated by continued physical activities but can also be interrupted or overridden by physical movements, a process called movement-induced hypoalgesia. Several neural mechanisms have been proposed to account for this effect, including the reafference principle, non-nociceptive interference, and top-down descending modulation. Given that the hypoalgesic effects of these mechanisms temporally overlap during movement execution, it is unclear whether movement-induced hypoalgesia results from a single neural mechanism or from the joint action of multiple neural mechanisms. To address this question, we conducted five experiments on 129 healthy humans by assessing the hypoalgesic effect after movement execution. Combining psychophysics and electroencephalographic recordings, we quantified the relationship between the strength of voluntary movement and the hypoalgesic effect, as well as the temporal and spatial characteristics of the hypoalgesic effect. Our findings demonstrated that movement-induced hypoalgesia results from the joint action of multiple neural mechanisms. This investigation is the first to disentangle the distinct contributions of different neural mechanisms to the hypoalgesic effect of voluntary movement, which extends our understanding of sensory attenuation arising from voluntary movement and may prove instrumental in developing new strategies for pain management.

A Network Perspective on Sensorimotor Learning

What happens in the brain when we learn? Ever since the foundational work of Cajal, the field has made numerous discoveries as to how experience could change the structure and function of individual synapses. However, more recent advances have highlighted the need for understanding learning in terms of complex interactions between populations of neurons and synapses. How should one think about learning at such a macroscopic level? Here, we develop a conceptual framework to bridge the gap between the different scales at which learning operates, from synapses to neurons to behavior. Using this framework, we explore the principles that guide sensorimotor learning across these scales, and set the stage for future experimental and theoretical work in the field.

Proprioception and the predictive sensing of active self-motion

As we actively explore the environment, our motion relative to the world stimulates numerous sensory systems. Notably, proprioceptors provide feedback about body and limb position, while the vestibular system detects and encodes head motion. When the vestibular system is functioning normally, we are unaware of a distinct sensation because vestibular information is integrated with proprioceptive and other sensory inputs to generate our sense of motion. However, patients with vestibular sensory loss experience impairments that provide important insights into the function of this essential sensory system. For these patients, everyday activities such as walking become difficult because even small head movements can produce postural and perceptual instability. This review describes recent research demonstrating how the proprioceptive and vestibular systems effectively work together to provide us with our “6^th sense” during everyday activities, and in particular considers the neural computations underlying the brain’s predictive sensing of head movement during voluntary self-motion.

A cerebello-olivary signal for negative prediction error is sufficient to cause extinction of associative motor learning

The brain generates negative prediction error (NPE) signals to trigger extinction, a type of inhibitory learning that is responsible for suppressing learned behaviors when they are no longer useful. Neurons encoding NPE have been reported in multiple brain regions. Here, we use an optogenetic approach to demonstrate that GABAergic cerebello-olivary neurons can generate a powerful NPE signal, capable of causing extinction of conditioned motor responses on its own.

The role of cerebellum in the child neuropsychological functioning

This chapter proposes a review of neuropsychologic and behavior findings in pediatric pathologies of the cerebellum, including cerebellar malformations, pediatric ataxias, cerebellar tumors, and other acquired cerebellar injuries during childhood. The chapter also contains reviews of the cerebellar mutism/posterior fossa syndrome, reported cognitive associations with the development of the cerebellum in typically developing children and subjects born preterm, and the role of the cerebellum in neurodevelopmental disorders such as autism spectrum disorders and developmental dyslexia. Cognitive findings in pediatric cerebellar disorders are considered in the context of known cerebellocerebral connections, internal cellular organization of the cerebellum, the idea of a universal cerebellar transform and computational internal models, and the role of the cerebellum in specific cognitive and motor functions, such as working memory, language, timing, or control of eye movements. The chapter closes with a discussion of the strengths and weaknesses of the cognitive affective syndrome as it has been described in children and some conclusions and perspectives.

Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development

The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.

Brain circuits signaling the absence of emotion in body language

Adaptive social behavior and mental well-being depend on not only recognizing emotional expressions but also, inferring the absence of emotion. While the neurobiology underwriting the perception of emotions is well studied, the mechanisms for detecting a lack of emotional content in social signals remain largely unknown. Here, using cutting-edge analyses of effective brain connectivity, we uncover the brain networks differentiating neutral and emotional body language. The data indicate greater activation of the right amygdala and midline cerebellar vermis to nonemotional as opposed to emotional body language. Most important, the effective connectivity between the amygdala and insula predicts people's ability to recognize the absence of emotion. These conclusions extend substantially current concepts of emotion perception by suggesting engagement of limbic effective connectivity in recognizing the lack of emotion in body language reading. Furthermore, the outcome may advance the understanding of overly emotional interpretation of social signals in depression or schizophrenia by providing the missing link between body language reading and limbic pathways. The study thus opens an avenue for multidisciplinary research on social cognition and the underlying cerebrocerebellar networks, ranging from animal models to patients with neuropsychiatric conditions.

A History of Corollary Discharge: Contributions of Mormyrid Weakly Electric Fish

Corollary discharge is an important brain function that allows animals to distinguish external from self-generated signals, which is critical to sensorimotor coordination. Since discovery of the concept of corollary discharge in 1950, neuroscientists have sought to elucidate underlying neural circuits and mechanisms. Here, we review a history of neurophysiological studies on corollary discharge and highlight significant contributions from studies using African mormyrid weakly electric fish. Mormyrid fish generate brief electric pulses to communicate with other fish and to sense their surroundings. In addition, mormyrids can passively locate weak, external electric signals. These three behaviors are mediated by different corollary discharge functions including inhibition, enhancement, and predictive “negative image” generation. Owing to several experimental advantages of mormyrids, investigations of these mechanisms have led to important general principles that have proven applicable to a wide diversity of animal species.

Defining "active sensing" through an analysis of sensing energetics: homeoactive and alloactive sensing

The term "active sensing" has been defined in multiple ways. Most strictly, the term refers to sensing that uses self-generated energy to sample the environment (e.g., echolocation). More broadly, the definition includes all sensing that occurs when the sensor is moving (e.g., tactile stimuli obtained by an immobile versus moving fingertip) and, broader still, includes all sensing guided by attention or intent (e.g., purposeful eye movements). The present work offers a framework to help disambiguate aspects of the "active sensing" terminology and reveals properties of tactile sensing unique among all modalities. The framework begins with the well-described "sensorimotor loop," which expresses the perceptual process as a cycle involving four subsystems: environment, sensor, nervous system, and actuator. Using system dynamics, we examine how information flows through the loop. This "sensory-energetic loop" reveals two distinct sensing mechanisms that subdivide active sensing into homeoactive and alloactive sensing. In homeoactive sensing, the animal can change the state of the environment, while in alloactive sensing the animal can alter only the sensor's configurational parameters and thus the mapping between input and output. Given these new definitions, examination of the sensory-energetic loop helps identify two unique characteristics of tactile sensing: 1) in tactile systems, alloactive and homeoactive sensing merge to a mutually controlled sensing mechanism, and 2) tactile sensing may require fundamentally different predictions to anticipate reafferent input. We expect this framework may help resolve ambiguities in the active sensing community and form a basis for future theoretical and experimental work regarding alloactive and homeoactive sensing.

50 Years Since the Marr, Ito, and Albus Models of the Cerebellum

Fifty years have passed since David Marr, Masao Ito, and James Albus proposed seminal models of cerebellar functions. These models share the essential concept that parallel-fiber-Purkinje-cell synapses undergo plastic changes, guided by climbing-fiber activities during sensorimotor learning. However, they differ in several important respects, including holistic versus complementary roles of the cerebellum, pattern recognition versus control as computational objectives, potentiation versus depression of synaptic plasticity, teaching signals versus error signals transmitted by climbing-fibers, sparse expansion coding by granule cells, and cerebellar internal models. In this review, we evaluate different features of the three models based on recent computational and experimental studies. While acknowledging that the three models have greatly advanced our understanding of cerebellar control mechanisms in eye movements and classical conditioning, we propose a new direction for computational frameworks of the cerebellum, that is, hierarchical reinforcement learning with multiple internal models.

Synergistic excitability plasticity in cerebellar functioning

The cerebellum, a universal processor for sensory acquisition and internal models, and its association with synaptic and nonsynaptic plasticity have been envisioned as the biological correlates of learning, perception, and even thought. Indeed, the cerebellum is no longer considered merely as the locus of motor coordination and its learning. Here, we introduce the mechanisms underlying the induction of multiple types of plasticity in cerebellar circuit and give an overview focusing on the plasticity of nonsynaptic intrinsic excitability. The discovery of long-term potentiation of synaptic responsiveness in hippocampal neurons led investigations into changes of their intrinsic excitability. This activity-dependent potentiation of neuronal excitability is distinct from that of synaptic efficacy. Systematic examination of excitability plasticity has indicated that the modulation of various types of Ca²⁺ - and voltage-dependent K⁺ channels underlies the phenomenon, which is also triggered by immune activity. Intrinsic plasticity is expressed specifically on dendrites and modifies the integrative processing and filtering effect. In Purkinje cells, modulation of the discordance of synaptic current on soma and dendrite suggested a novel type of cellular learning mechanism. This property enables a plausible synergy between synaptic efficacy and intrinsic excitability, by amplifying electrical conductivity and influencing the polarity of bidirectional synaptic plasticity. Furthermore, the induction of intrinsic plasticity in the cerebellum correlates with motor performance and cognitive processes, through functional connections from the cerebellar nuclei to neocortex and associated regions: for example, thalamus and midbrain. Taken together, recent advances in neuroscience have begun to shed light on the complex functioning of nonsynaptic excitability and the synergy.

Distinct Roles for the Cerebellum, Angular Gyrus, and Middle Temporal Gyrus in Action-Feedback Monitoring

Action-feedback monitoring is essential to ensure meaningful interactions with the external world. This process involves generating efference copy-based sensory predictions and comparing these with the actual action-feedback. As neural correlates of comparator processes, previous fMRI studies have provided heterogeneous results, including the cerebellum, angular and middle temporal gyrus. However, these studies usually comprised only self-generated actions. Therefore, they might have induced not only action-based prediction errors, but also general sensory mismatch errors. Here, we aimed to disentangle these processes using a custom-made fMRI-compatible movement device, generating active and passive hand movements with identical sensory feedback. Online visual feedback of the hand was presented with a variable delay. Participants had to judge whether the feedback was delayed. Activity in the right cerebellum correlated more positively with delay in active than in passive trials. Interestingly, we also observed activation in the angular and middle temporal gyri, but across both active and passive conditions. This suggests that the cerebellum is a comparator area specific to voluntary action, whereas angular and middle temporal gyri seem to detect more general intersensory conflict. Correlations with behavior and cerebellar activity nevertheless suggest involvement of these temporoparietal areas in processing and awareness of temporal discrepancies in action-feedback monitoring.

Prediction signals in the cerebellum: beyond supervised motor learning

While classical views of cerebellar learning have suggested that this structure predominantly operates according to an error-based supervised learning rule to refine movements, emerging evidence suggests that the cerebellum may also harness a wider range of learning rules to contribute to a variety of behaviors, including cognitive processes. Together, such evidence points to a broad role for cerebellar circuits in generating and testing predictions about movement, reward, and other non-motor operations. However, this expanded view of cerebellar processing also raises many new questions about how such apparent diversity of function arises from a structure with striking homogeneity. Hence, this review will highlight both current evidence for predictive cerebellar circuit function that extends beyond the classical view of error-driven supervised learning, as well as open questions that must be addressed to unify our understanding cerebellar circuit function.

The Ventral Posterior Lateral Thalamus Preferentially Encodes Externally Applied Versus Active Movement: Implications for Self-Motion Perception

Successful interaction with our environment requires that voluntary behaviors be precisely coordinated with our perception of self-motion. The vestibular sensors in the inner ear detect self-motion and in turn send projections via the vestibular nuclei to multiple cortical areas through 2 principal thalamocortical pathways, 1 anterior and 1 posterior. While the anterior pathway has been extensively studied, the role of the posterior pathway is not well understood. Accordingly, here we recorded responses from individual neurons in the ventral posterior lateral thalamus of macaque monkeys during externally applied (passive) and actively generated self-motion. The sensory responses of neurons that robustly encoded passive rotations and translations were canceled during comparable voluntary movement (~80% reduction). Moreover, when both passive and active self-motion were experienced simultaneously, neurons selectively encoded the detailed time course of the passive component. To examine the mechanism underlying the selective elimination of vestibular sensitivity to active motion, we experimentally controlled correspondence between intended and actual head movement. We found that suppression only occurred if the actual sensory consequences of motion matched the motor-based expectation. Together, our findings demonstrate that the posterior thalamocortical vestibular pathway selectively encodes unexpected motion, thereby providing a neural correlate for ensuring perceptual stability during active versus externally generated motion.

Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum during passive whole-body self-motion

Theories of cerebellar functions posit that the cerebellum implements internal models for online correction of motor actions and sensory estimation. As an example of such computations, an internal model resolves a sensory ambiguity where the peripheral otolith organs in the inner ear sense both head tilts and translations. Here we exploit the response dynamics of two functionally coupled Purkinje cell types in the vestibular part of the caudal vermis (lobules IX and X) to understand their role in this computation. We find that one population encodes tilt velocity, whereas the other, translation-selective, population encodes linear acceleration. We predict that an intermediate neuronal type should temporally integrate the output of tilt-selective cells into a tilt position signal.

Differentiating Cerebellar Impact on Thalamic Nuclei

The cerebellum plays a role in coordination of movements and non-motor functions. Cerebellar nuclei (CN) axons connect to various parts of the thalamo-cortical network, but detailed information on the characteristics of cerebello-thalamic connections is lacking. Here, we assessed the cerebellar input to the ventrolateral (VL), ventromedial (VM), and centrolateral (CL) thalamus. Confocal and electron microscopy showed an increased density and size of CN axon terminals in VL compared to VM or CL. Electrophysiological recordings in vitro revealed that optogenetic CN stimulation resulted in enhanced charge transfer and action potential firing in VL neurons compared to VM or CL neurons, despite that the paired-pulse ratio was not significantly different. Together, these findings indicate that the impact of CN input onto neurons of different thalamic nuclei varies substantially, which highlights the possibility that cerebellar output differentially controls various parts of the thalamo-cortical network.

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Cerebello-thalamic axons form terminals of varying size in distinct thalamic nuclei

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Cerebello-thalamic responses vary in amplitude in distinct thalamic nuclei

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Repetitive stimuli depress cerebello-thalamic responses in all thalamic nuclei

Vestibular modulation of visuomotor feedback gains in reaching

Humans quickly and sophisticatedly correct their movements in response to changes in the world, such as when reaching to a target that abruptly changes its location. The vigor of these movement corrections is time-dependent, increasing if the time left to make the correction decreases, which can be explained by optimal feedback control (OFC) theory as an increase of optimal feedback gains. It is unknown whether corrections for changes in the world are as sophisticated under full-body motion. For successful visually probed motor corrections during full-body motion, not only the motion of the hand relative to the body needs to be taken into account, but also the motion of the hand in the world should be considered, because their relative positions are changing. Here, in two experiments, we show that visuomotor feedback corrections in response to target jumps are more vigorous for faster passive full-body translational acceleration than for slower acceleration, suggesting that vestibular information modulates visuomotor feedback gains. Interestingly, these corrections do not demonstrate the time-dependent characteristics that body-stationary visuomotor feedback gains typically show, such that an optimal feedback control model fell short to explain them. We further show that the vigor of corrections generally decreased over the course of trials within the experiment, suggesting that the sensorimotor system adjusted its gains when learning to integrate the vestibular input into hand motor control.

NEW & NOTEWORTHY Vestibular information is used in the control of reaching movements to world-stationary visual targets, while the body moves. Here, we show that vestibular information also modulates the corrective reach responses when the target changes position during the body motion: visuomotor feedback gains increase for faster body acceleration. Our results suggest that vestibular information is integrated into fast visuomotor control of reaching movements.

The cerebellum is involved in processing of predictions and prediction errors in a fear conditioning paradigm

Prediction errors are thought to drive associative fear learning. Surprisingly little is known about the possible contribution of the cerebellum. To address this question, healthy participants underwent a differential fear conditioning paradigm during 7T magnetic resonance imaging. An event-related design allowed us to separate cerebellar fMRI signals related to the visual conditioned stimulus (CS) from signals related to the subsequent unconditioned stimulus (US; an aversive electric shock). We found significant activation of cerebellar lobules Crus I and VI bilaterally related to the CS+ compared to the CS-. Most importantly, significant activation of lobules Crus I and VI was also present during the unexpected omission of the US in unreinforced CS+ acquisition trials. This activation disappeared during extinction when US omission became expected. These findings provide evidence that the cerebellum has to be added to the neural network processing predictions and prediction errors in the emotional domain.

Cerebellar Prediction of the Dynamic Sensory Consequences of Gravity

As we go about our everyday activities, our brain computes accurate estimates of both our motion relative to the world and our orientation relative to gravity. However, how the brain then accounts for gravity as we actively move and interact with our environment is not yet known. Here, we provide evidence that, although during passive movements, individual cerebellar output neurons encode representations of head motion and orientation relative to gravity, these gravity-driven responses are cancelled when head movement is a consequence of voluntary generated movement. In contrast, the gravity-driven responses of primary otolith and semicircular canal afferents remain intact during both active and passive self-motion, indicating the attenuated responses of central neurons are not inherited from afferent inputs. Taken together, our results are consistent with the view that the cerebellum builds a dynamic prediction (e.g., internal model) of the sensory consequences of gravity during active self-motion, which in turn enables the preferential encoding of unexpected motion to ensure postural and perceptual stability.

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Studies of cerebellum-like circuits in fish have demonstrated that synaptic plasticity shapes the motor corollary discharge responses of granule cells into highly-specific predictions of self-generated sensory input. However, the functional significance of such predictions, known as negative images, has not been directly tested. Here we provide evidence for improvements in neural coding and behavioral detection of prey-like stimuli due to negative images. In addition, we find that manipulating synaptic plasticity leads to specific changes in circuit output that disrupt neural coding and detection of prey-like stimuli. These results link synaptic plasticity, neural coding, and behavior and also provide a circuit-level account of how combining external sensory input with internally generated predictions enhances sensory processing.

The Brain Compass: A Perspective on How Self-Motion Updates the Head Direction Cell Attractor

Head direction cells form an internal compass signaling head azimuth orientation even without visual landmarks. This property is generated by a neuronal ring attractor that is updated using rotation velocity cues. The properties and origin of this velocity drive remain, however, unknown. We propose a quantitative framework whereby this drive represents a multisensory self-motion estimate computed through an internal model that uses sensory prediction errors of vestibular, visual, and somatosensory cues to improve on-line motor drive. We show how restraint-dependent strength of recurrent connections within the attractor can explain differences in head direction cell firing between free foraging and restrained passive rotation. We also summarize recent findings on how gravity influences azimuth coding, indicating that the velocity drive is not purely egocentric. Finally, we show that the internal compass may be three-dimensional and hypothesize that the additional vertical degrees of freedom use global allocentric gravity cues.

A New Perspective on Predictive Motor Signaling

Adaptive behavior relies on complex neural processing in multiple interacting networks of both motor and sensory systems. One such interaction employs intrinsic neuronal signals, so-called 'corollary discharge' or 'efference copy', that may be used to predict the sensory consequences of a specific behavioral action, thereby enabling self-generated (reafferent) sensory information and extrinsic (exafferent) sensory inflow to be dissociated. Here, by using well-established examples, we seek to identify the distinguishing features of corollary discharge and efference copy within the framework of predictive motor-to-sensory system coordination. We then extend the more general concept of predictive signaling by showing how neural replicas of a particular motor command not only inform sensory pathways in order to gate reafferent stimulation, but can also be used to directly coordinate distinct and otherwise independent behaviors to the original motor task. Moreover, this motor-to-motor pairing may additionally extend to a gating of sensory input to either or both of the coupled systems. The employment of predictive internal signaling in such motor systems coupling and remote sensory input control thus adds to our understanding of how an organism's central nervous system is able to coordinate the activity of multiple and generally disparate motor and sensory circuits in the production of effective behavior.

The capacity to learn new motor and perceptual calibrations develops concurrently in childhood

Learning new movements through an error-based process called motor adaptation is thought to involve multiple mechanisms which are still largely not understood. Previous studies have shown that young children adapt movement more slowly than adults, perhaps supporting the involvement of distinct neural circuits that come online at different stages of development. Recent studies in adults have shown that in addition to recalibrating a movement, motor adaptation also leads to changes in the perception of that movement. However, we do not yet understand the relationship between the processes that underlie motor and perceptual recalibration. Here we studied motor and perceptual recalibration with split-belt walking adaptation in adults and children aged 6-8 years. Consistent with previous work, we found that this group of children adapted their walking patterns more slowly than adults, though individual children ranged from slow to adult-like in their adaptation rates. Perceptual recalibration was also reduced in the same group of children compared to adults, with individual children ranging from having no recalibration to having adult-like recalibration. In sum, faster motor adaptation and the ability to recalibrate movement perception both come online within a similar age-range, raising the possibility that the same sensorimotor mechanisms underlie these processes.

Predictive Sensing: The Role of Motor Signals in Sensory Processing

The strategy of integrating motor signals with sensory information during voluntary behavior is a general feature of sensory processing. It is required to distinguish externally applied (exafferent) from self-generated (reafferent) sensory inputs. This distinction, in turn, underlies our ability to achieve both perceptual stability and accurate motor control during everyday activities. In this review, we consider the results of recent experiments that have provided circuit-level insight into how motor-related inputs to sensory areas selectively cancel self-generated sensory inputs during active behaviors. These studies have revealed both common strategies and important differences across systems. Sensory reafference is suppressed at the earliest stages of central processing in the somatosensory, vestibular, and auditory systems, with the cerebellum and cerebellum-like structures playing key roles. Furthermore, motor-related inputs can also suppress reafferent responses at higher levels of processing such as the cortex-a strategy preferentially used in visual processing. These recent findings have important implications for understanding how the brain achieves the flexibility required to continuously calibrate relationships between motor signals and the resultant sensory feedback, a computation necessary for our subjective awareness that we control both our actions and their sensory consequences.

Vestibular processing during natural self-motion: implications for perception and action

How the brain computes accurate estimates of our self-motion relative to the world and our orientation relative to gravity in order to ensure accurate perception and motor control is a fundamental neuroscientific question. Recent experiments have revealed that the vestibular system encodes this information during everyday activities using pathway-specific neural representations. Furthermore, new findings have established that vestibular signals are selectively combined with extravestibular information at the earliest stages of central vestibular processing in a manner that depends on the current behavioural goal. These findings have important implications for our understanding of the brain mechanisms that ensure accurate perception and behaviour during everyday activities and for our understanding of disorders of vestibular processing.

Mathematical models for dynamic, multisensory spatial orientation perception

Mathematical models have been proposed for how the brain interprets sensory information to produce estimates of self-orientation and self-motion. This process, spatial orientation perception, requires dynamically integrating multiple sensory modalities, including visual, vestibular, and somatosensory cues. Here, we review the progress in mathematical modeling of spatial orientation perception, focusing on dynamic multisensory models, and the experimental paradigms in which they have been validated. These models are primarily "black box" or "as if" models for how the brain processes spatial orientation cues. Yet, they have been effective scientifically, in making quantitative hypotheses that can be empirically assessed, and operationally, in investigating aircraft pilot disorientation, for example. The primary family of models considered, the observer model, implements estimation theory approaches, hypothesizing that internal models (i.e., neural systems replicating the behavior/dynamics of physical systems) are used to produce expected sensory measurements. Expected signals are then compared to actual sensory afference, yielding sensory conflict, which is weighted to drive central perceptions of gravity, angular velocity, and translation. This approach effectively predicts a wide range of experimental scenarios using a small set of fixed free parameters. We conclude with limitations and applications of existing mathematical models and important areas of future work.

Impaired cerebellar Purkinje cell potentiation generates unstable spatial map orientation and inaccurate navigation

Cerebellar activity supported by PKC-dependent long-term depression in Purkinje cells (PCs) is involved in the stabilization of self-motion based hippocampal representation, but the existence of cerebellar processes underlying integration of allocentric cues remains unclear. Using mutant-mice lacking PP2B in PCs (L7-PP2B mice) we here assess the role of PP2B-dependent PC potentiation in hippocampal representation and spatial navigation. L7-PP2B mice display higher susceptibility to spatial map instability relative to the allocentric cue and impaired allocentric as well as self-motion goal-directed navigation. These results indicate that PP2B-dependent potentiation in PCs contributes to maintain a stable hippocampal representation of a familiar environment in an allocentric reference frame as well as to support optimal trajectory toward a goal during navigation.

It is known that Purkinje cell PKC-dependent depression is involved in the stabilization of self-motion based hippocampal representation. Here the authors describe decreased stability of hippocampal place cells based on allocentric cues in mice lacking Purkinje cell PP2B-dependent potentiation.

Corollary Discharge Signals in the Cerebellum

The cerebellum is known to make movements fast, smooth, and accurate. Many hypotheses emphasize the role of the cerebellum in computing learned predictions important for sensorimotor calibration and feedforward control of movements. Hypotheses of the computations performed by the cerebellum in service of motor control borrow heavily from control systems theory, with models that frequently invoke copies of motor commands, called corollary discharge. This review describes evidence for corollary discharge inputs to the cerebellum and highlights the hypothesized roles for this information in cerebellar motor-related computations. Insights into the role of corollary discharge in motor control, described here, are intended to inform the exciting but still untested roles of corollary discharge in cognition, perception, and thought control relevant in psychiatric disorders.

Internal Models in Biological Control

Rationality principles such as optimal feedback control and Bayesian inference underpin a probabilistic framework that has accounted for a range of empirical phenomena in biological sensorimotor control. To facilitate the optimization of flexible and robust behaviors consistent with these theories, the ability to construct internal models of the motor system and environmental dynamics can be crucial. In the context of this theoretic formalism, we review the computational roles played by such internal models and the neural and behavioral evidence for their implementation in the brain.

Magnetoencephalographic evaluation for the myoelectric hand prosthesis with tacit learning system

BACKGROUND

The effect of tacit learning systems (TLSs) on brain plasticity are as of yet unknown. We developed a myoelectric hand prosthesis equipped with a TLS to auto-regulate forearm rotation in response to upper extremity movement patterns.

OBJECTIVE

To evaluate the effects of tacit learning on the central nervous system during a prosthesis control exercise.

METHODS

The experienced prosthetic user performed a series of simple mechanical tasks with the TLS inactivated (the baseline condition) and then with it activated (the enhanced, experimental condition). The process was video recorded. Subsequently, the participant viewed video recordings of each condition (baseline and experimental) during magnetoencephalography and electroencephalography recordings.

RESULTS

Stronger connections between the motor area and other cortical areas were observed, as indicated by a significant increase in coherence values.

CONCLUSIONS

Integration and interoperability may underlie tacit learning and promote motor function-related adaptive neuroplasticity.

Vestibular and Multi-Sensory Influences Upon Self-Motion Perception and the Consequences for Human Behavior

In this manuscript, we comprehensively review both the human and animal literature regarding vestibular and multi-sensory contributions to self-motion perception. This covers the anatomical basis and how and where the signals are processed at all levels from the peripheral vestibular system to the brainstem and cerebellum and finally to the cortex. Further, we consider how and where these vestibular signals are integrated with other sensory cues to facilitate self-motion perception. We conclude by demonstrating the wide-ranging influences of the vestibular system and self-motion perception upon behavior, namely eye movement, postural control, and spatial awareness as well as new discoveries that such perception can impact upon numerical cognition, human affect, and bodily self-consciousness.

Re-evaluating Circuit Mechanisms Underlying Pattern Separation

When animals interact with complex environments, their neural circuits must separate overlapping patterns of activity that represent sensory and motor information. Pattern separation is thought to be a key function of several brain regions, including the cerebellar cortex, insect mushroom body, and dentate gyrus. However, recent findings have questioned long-held ideas on how these circuits perform this fundamental computation. Here, we re-evaluate the functional and structural mechanisms underlying pattern separation. We argue that the dimensionality of the space available for population codes representing sensory and motor information provides a common framework for understanding pattern separation. We then discuss how these three circuits use different strategies to separate activity patterns and facilitate associative learning in the presence of trial-to-trial variability.

Cerebellum, Predictions and Errors

Making predictions and validating the predictions against actual sensory information is thought to be one of the most fundamental functions of the nervous system. A growing body of evidence shows that the neural mechanisms controlling behavior, both in motor and non-motor domains, rely on prediction errors, the discrepancy between predicted and actual information. The cerebellum has been viewed as a key component of the motor system providing predictions about upcoming movements and receiving feedback about motor errors. Consequentially, studies of cerebellar function have focused on the motor domain with less consideration for the wider context in which movements are generated. However, motor learning experiments show that cognition makes important contributions to motor adaptation that involves the cerebellum. One of the more successful theoretical frameworks for understanding motor control and cerebellar function is the forward internal model which states that the cerebellum predicts the sensory consequences of the motor commands and is involved in computing sensory prediction errors by comparing the predictions to the sensory feedback. The forward internal model was applied and tested mainly for effector movements, raising the question whether cerebellar encoding of behavior reflects task performance measures associated with cognitive involvement. Electrophysiological studies based on pseudo-random tracking in monkeys show that the discharge of Purkinje cell, the sole output neurons of the cerebellar cortex, encodes predictive and feedback signals not only of the effector kinematics but also of task performance. The implications are that the cerebellum implements both effector and task performance forward models and the latter are consistent with the cognitive contributions observed during motor learning. The implications of these findings include insights into recent psychophysical observations on moving with reduced feedback and motor learning. The findings also support the cerebellum's place in hierarchical generative models that work in concert to refine predictions about behavior and the world. Therefore, cerebellar representations bridge motor and non-motor domains and provide a better understanding of cerebellar function within the functional architecture of the brain.

Corollary discharge in precerebellar nuclei of sleeping infant rats

In week-old rats, somatosensory input arises predominantly from external stimuli or from sensory feedback (reafference) associated with myoclonic twitches during active sleep. A previous study suggested that the brainstem motor structures that produce twitches also send motor copies (or corollary discharge, CD) to the cerebellum. We tested this possibility by recording from two precerebellar nuclei—the inferior olive (IO) and lateral reticular nucleus (LRN). In most IO and LRN neurons, twitch-related activity peaked sharply around twitch onset, consistent with CD. Next, we identified twitch-production areas in the midbrain that project independently to the IO and LRN. Finally, we blocked calcium-activated slow potassium (SK) channels in the IO to explain how broadly tuned brainstem motor signals can be transformed into precise CD signals. We conclude that the precerebellar nuclei convey a diversity of sleep-related neural activity to the developing cerebellum to enable processing of convergent input from CD and reafferent signals.

Human perception of whole body roll-tilt orientation in a hypogravity analog: underestimation and adaptation

Overestimation of roll tilt in hypergravity ("G-excess" illusion) has been demonstrated, but corresponding sustained hypogravic conditions are impossible to create in ground laboratories. In this article we describe the first systematic experimental evidence that in a hypogravity analog, humans underestimate roll tilt. We studied perception of self-roll tilt in nine subjects, who were supine while spun on a centrifuge to create a hypogravity analog. By varying the centrifuge rotation rate, we modulated the centripetal acceleration (G_C) at the subject's head location (0.5 or 1 G_C) along the body axis. We measured orientation perception using a subjective visual vertical task in which subjects aligned an illuminated bar with their perceived centripetal acceleration direction during tilts (±11.5-28.5°). As hypothesized, based on the reduced utricular otolith shearing, subjects initially underestimated roll tilts in the 0.5 G_C condition compared with the 1 G_C condition (mean perceptual gain change = -0.27, P = 0.01). When visual feedback was given after each trial in 0.5 G_C, subjects' perceptual gain increased in approximately exponential fashion over time (time constant = 16 tilts or 13 min), and after 45 min, the perceptual gain was not significantly different from the 1 G_C baseline (mean gain difference between 1 G_C initial and 0.5 G_C final = 0.16, P = 0.3). Thus humans modified their interpretation of sensory cues to more correctly report orientation during this hypogravity analog. Quantifying the acute orientation perceptual learning in such an altered gravity environment may have implications for human space exploration on the moon or Mars. NEW & NOTEWORTHY Humans systematically overestimate roll tilt in hypergravity. However, human perception of orientation in hypogravity has not been quantified across a range of tilt angles. Using a centrifuge to create a hypogravity centripetal acceleration environment, we found initial underestimation of roll tilt. Providing static visual feedback, perceptual learning reduced underestimation during the hypogravity analog. These altered gravity orientation perceptual errors and adaptation may have implications for astronauts.

Estimating the sensorimotor components of cybersickness

The user base of the virtual reality (VR) medium is growing, and many of these users will experience cybersickness. Accounting for the vast interindividual variability in cybersickness forms a pivotal step in solving the issue. Most studies of cybersickness focus on a single factor (e.g., balance, sex, or vection), while other contributors are overlooked. Here, we characterize the complex relationship between cybersickness and several measures of sensorimotor processing. In a single session, we conducted a battery of tests of balance control, vection responses, and vestibular sensitivity to self-motion. Following this, we measured cybersickness after VR exposure. We constructed a principal components regression model using the measures of sensorimotor processing. The model significantly predicted 37% of the variability in cybersickness measures, with 16% of this variance being accounted for by a principal component that represented balance control measures. The strongest predictor was participants' sway path length during vection, which was inversely related to cybersickness [ r(28) = -0.53, P = 0.002] and uniquely accounted for 7.5% of the variance in cybersickness scores across participants. Vection strength reports and measures of vestibular sensitivity were not significant predictors of cybersickness. We discuss the possible role of sensory reweighting in cybersickness that is suggested by these results, and we identify other factors that may account for the remaining variance in cybersickness. The results reiterate that the relationship between balance control and cybersickness is anything but straightforward. NEW & NOTEWORTHY The advent of consumer virtual reality provides a pressing need for interventions that combat sickness in simulated environments (cybersickness). This research builds on multiple theories of cybersickness etiology to develop a predictive model that distinguishes between individuals who are/are not likely to experience cybersickness. In the future this approach can be adapted to provide virtual reality users with curated content recommendations based on more efficient measurements of sensorimotor processing.

Forecast or Fall: Prediction's Importance to Postural Control

To interact successfully with an uncertain environment, organisms must be able to respond to both unanticipated and anticipated events. For unanticipated events, organisms have evolved stereotyped motor behaviors mapped to the statistical regularities of the environment, which can be trigged by specific sensory stimuli. These “reflexive” responses are more or less hardwired to prevent falls and represent, maybe, the best available solution to maintaining posture given limited available time and information. With the gift of foresight, however, motor behaviors can be tuned or prepared in advance, improving the ability of the organism to compensate for, and interact with, the changing environment. Indeed, foresight's improvement of our interactive capacity occurs through several means, such as better action selection, processing, and conduction delay compensation and by providing a prediction with which to compare our actual behaviors to, thereby facilitating error identification and learning. Here we review the various roles foresight (prediction) plays in maintaining our postural equilibrium. We start by describing some of the more recent findings related to the prediction of instability. Specifically, we cover recent advancements in the understanding of anticipatory postural behaviors that are used broadly to stabilize volitional movement and compensate for impending postural disturbances. We also describe anticipatory changes in the state, or set, of the nervous system that may facilitate anticipatory behaviors. From changes in central set, we briefly discuss prediction of postural instability online before moving into a discussion of how predictive mechanisms, such as internal models, permit us to tune, perhaps our highest level predictive behaviors, namely the priming associated with motor affordances. Lastly, we explore methods best suited to expose the contribution of prediction to postural equilibrium control across a variety of contexts.

Sensorimotor Manipulations of the Balance Control Loop-Beyond Imposed External Perturbations

Standing balance relies on the integration of multiple sensory inputs to generate the motor commands required to stand. Mechanical and sensory perturbations elicit compensatory postural responses that are interpreted as a window into the sensorimotor processing involved in balance control. Popular methods involve imposed external perturbations that disrupt the control of quiet stance. Although these approaches provide critical information on how the balance system responds to external disturbances, the control mechanisms involved in correcting for these errors may differ from those responsible for the regulation of quiet standing. Alternative approaches use manipulations of the balance control loop to alter the relationship between sensory and motor cues. Coupled with imposed perturbations, these manipulations of the balance control loop provide unique opportunities to reveal how sensory and motor signals are integrated to control the upright body. In this review, we first explore imposed perturbation approaches that have been used to investigate the neural control of standing balance. We emphasize imposed perturbations that only elicit balance responses when the disturbing stimuli are relevant to the balance task. Next, we highlight manipulations of the balance control loop that, when carefully implemented, replicate and/or alter the sensorimotor dynamics of quiet standing. We further describe how manipulations of the balance control loop can be used in combination with imposed perturbations to characterize mechanistic principles underlying the control of standing balance. We propose that recent developments in the use of robotics and sensory manipulations will continue to enable new possibilities for simulating and/or altering the sensorimotor control of standing beyond compensatory responses to imposed external perturbations.

Predictive Processing: A Canonical Cortical Computation

This perspective describes predictive processing as a computational framework for understanding cortical function in the context of emerging evidence, with a focus on sensory processing. We discuss how the predictive processing framework may be implemented at the level of cortical circuits and how its implementation could be falsified experimentally. Lastly, we summarize the general implications of predictive processing on cortical function in healthy and diseased states.

Prominent Changes in Cerebro-Cerebellar Functional Connectivity During Continuous Cognitive Processing

While task-dependent responses of specific brain areas during cognitive tasks are well established, much less is known about the changes occurring in resting state networks (RSNs) in relation to continuous cognitive processing. In particular, the functional involvement of cerebro-cerebellar loops connecting the posterior cerebellum to associative cortices, remains unclear. In this study, 22 healthy volunteers underwent a multi-session functional magnetic resonance imaging (fMRI) protocol composed of four consecutive 8-min resting state fMRI (rs-fMRI) scans. After a first control scan, participants listened to a narrated story for the entire duration of the second rs-fMRI scan; two further rs-fMRI scans followed the end of story listening. The story plot was purposely designed to stimulate specific cognitive processes that are known to involve the cerebro-cerebellar loops. Almost all of the identified 15 RSNs showed changes in functional connectivity (FC) during and for several minutes after the story. The FC changes mainly occurred in the frontal and prefrontal cortices and in the posterior cerebellum, especially in Crus I-II and lobule VI. The FC changes occurred in cerebellar clusters belonging to different RSNs, including the cerebellar network (CBLN), sensory networks (lateral visual network, LVN; medial visual network, MVN) and cognitive networks (default mode network, DMN; executive control network, ECN; right and left ventral attention networks, RVAN and LVAN; salience network, SN; language network, LN; and working memory network, WMN). Interestingly, a k-means analysis of FC changes revealed clustering of FCN, ECN, and WMN, which are all involved in working memory functions, CBLN, DMN, and SN, which play a key-role in attention switching, and RSNs involved in visual imagery. These results show that the cerebellum is deeply entrained in well-structured network clusters, which reflect multiple aspects of cognitive processing, during and beyond the conclusion of auditory stimulation.

Cortical modulation of sensory flow during active touch in the rat whisker system

Sensory gating, where responses to stimuli during sensor motion are reduced in amplitude, is a hallmark of active sensing systems. In the rodent whisker system, sensory gating has been described only at the thalamic and cortical stages of sensory processing. However, does sensory gating originate at an even earlier synaptic level? Most importantly, is sensory gating under top-down or bottom-up control? To address these questions, we used an active touch task in behaving rodents while recording from the trigeminal sensory nuclei. First, we show that sensory gating occurs in the brainstem at the first synaptic level. Second, we demonstrate that sensory gating is pathway-specific, present in the lemniscal but not in the extralemniscal stream. Third, using cortical lesions resulting in the complete abolition of sensory gating, we demonstrate its cortical dependence. Fourth, we show accompanying decreases in whisking-related activity, which could be the putative gating signal.

During active touch, sensory responses to object touch are gated at the level of thalamus and cortex. Here, the authors report gating at the level of the brainstem and show that an intact somatosensory cortex is essential for this response modulation.

A virtual reality approach identifies flexible inhibition of motion aftereffects induced by head rotation

As we move in space, our retinae receive motion signals from two causes: those resulting from motion in the world and those resulting from self-motion. Mounting evidence has shown that vestibular self-motion signals interact with visual motion processing profoundly. However, most contemporary methods arguably lack portability and generality and are incapable of providing measurements during locomotion. Here we developed a virtual reality approach, combining a three-space sensor with a head-mounted display, to quantitatively manipulate the causality between retinal motion and head rotations in the yaw plane. Using this system, we explored how self-motion affected visual motion perception, particularly the motion aftereffect (MAE). Subjects watched gratings presented on a head-mounted display. The gratings drifted at the same velocity as head rotations, with the drifting direction being identical, opposite, or perpendicular to the direction of head rotations. We found that MAE lasted a significantly shorter time when subjects' heads rotated than when their heads were kept still. This effect was present regardless of the drifting direction of the gratings, and was also observed during passive head rotations. These findings suggest that the adaptation to retinal motion is suppressed by head rotations. Because the suppression was also found during passive head movements, it should result from visual-vestibular interaction rather than from efference copy signals. Such visual-vestibular interaction is more flexible than has previously been thought, since the suppression could be observed even when the retinal motion direction was perpendicular to head rotations. Our work suggests that a virtual reality approach can be applied to various studies of multisensory integration and interaction.

The parieto-insular vestibular cortex in humans: more than a single area?

Here, we review the structure and function of a core region in the vestibular cortex of humans that is located in the midposterior Sylvian fissure and referred to as the parieto-insular vestibular cortex (PIVC). Previous studies have investigated PIVC by using vestibular or visual motion stimuli and have observed activations that were distributed across multiple anatomical structures, including the temporo-parietal junction, retroinsula, parietal operculum, and posterior insula. However, it has remained unclear whether all of these anatomical areas correspond to PIVC and whether PIVC responds to both vestibular and visual stimuli. Recent results suggest that the region that has been referred to as PIVC in previous studies consists of multiple areas with different anatomical correlates and different functional specializations. Specifically, a vestibular but not visual area is located in the parietal operculum, close to the posterior insula, and likely corresponds to the nonhuman primate PIVC, while a visual-vestibular area is located in the retroinsular cortex and is referred to, for historical reasons, as the posterior insular cortex area (PIC). In this article, we review the anatomy, connectivity, and function of PIVC and PIC and propose that the core of the human vestibular cortex consists of at least two separate areas, which we refer to together as PIVC+. We also review the organization in the nonhuman primate brain and show that there are parallels to the proposed organization in humans.

Visuomotor Prediction Errors Modulate EEG Activity Over Parietal Cortex

The parietal cortex is thought to be involved in visuomotor adaptation, yet it remains unclear whether it is specifically modulated by visuomotor prediction errors (i.e. PEs; mismatch between the predicted and actual visual consequences of the movement). One reason for this is that PEs tend to be associated with task errors, as well as changes in motor output and visual input, making them difficult to isolate. Here this issue is addressed using electroencephalography. A strategy (STR) condition, in which participants were instructed on how to counter a 45° visuomotor rotation, was compared to a condition in which participants had adapted to the rotation (POST). Both conditions were matched for task errors and movement kinematics, with the only difference being the presence of PEs in STR. Results revealed strong parietal modulations in current source density and low theta (2–4 Hz) power shortly after movement onset in STR vs. POST, followed by increased alpha/low beta (8–18 Hz) power during much of the post-movement period. Given recent evidence showing that feedforward and feedback information is respectively carried by theta and alpha/beta oscillations, the observed power modulations may reflect the bottom-up propagation of PEs and the top-down revision of predictions.