Boundary vector cells in the goldfish central telencephalon encode spatial information.

Navigation is one of the most fundamental cognitive skills for the survival of fish, the largest vertebrate class, and almost all other animal classes. Space encoding in single neurons is a critical component of the neural basis of navigation. To study this fundamental cognitive component in fish, we recorded the activity of neurons in the central area of the goldfish telencephalon while the fish were freely navigating in a quasi-2D water tank embedded in a 3D environment. We found spatially modulated neurons with firing patterns that gradually decreased with the distance of the fish from a boundary in each cell's preferred direction, resembling the boundary vector cells found in the mammalian subiculum. Many of these cells exhibited beta rhythm oscillations. This type of spatial representation in fish brains is unique among space-encoding cells in vertebrates and provides insights into spatial cognition in this lineage.

Mini-review: The Role of the Cerebellum in Visuomotor Adaptation.

The incredible capability of the brain to quickly alter performance in response to ever-changing environment is rooted in the process of adaptation. The core aspect of adaptation is to fit an existing motor program to altered conditions. Adaptation to a visuomotor rotation or an external force has been well established as tools to study the mechanisms underlying sensorimotor adaptation. In this mini-review, we summarize recent findings from the field of visuomotor adaptation. We focus on the idea that the cerebellum plays a central role in the process of visuomotor adaptation and that interactions with cortical structures, in particular, the premotor cortex and the parietal cortex, may be crucial for this process. To this end, we cover a range of methodologies used in the literature that link cerebellar functions and visuomotor adaptation; behavioral studies in cerebellar lesion patients, neuroimaging and non-invasive stimulation approaches. The mini-review is organized as follows: first, we provide evidence that sensory prediction errors (SPE) in visuomotor adaptation rely on the cerebellum based on behavioral studies in cerebellar patients. Second, we summarize structural and functional imaging studies that provide insight into spatial localization as well as visuomotor adaptation dynamics in the cerebellum. Third, we discuss premotor - cerebellar interactions and how these may underlie visuomotor adaptation. And finally, we provide evidence from transcranial direct current and magnetic stimulation studies that link cerebellar activity, beyond correlational relationships, to visuomotor adaptation .

Recognition of natural objects in the archerfish.

Recognition of individual objects and their categorization is a complex computational task. Nevertheless, visual systems can perform this task in a rapid and accurate manner. Humans and other animals can efficiently recognize objects despite countless variations in their projection on the retina due to different viewing angles, distance, illumination conditions and other parameters. To gain a better understanding of the recognition process in teleosts, we explored it in archerfish, a species that hunts by shooting a jet of water at aerial targets and thus can benefit from ecologically relevant recognition of natural objects. We found that archerfish not only can categorize objects into relevant classes but also can do so for novel objects, and additionally they can recognize an individual object presented under different conditions. To understand the mechanisms underlying this capability, we developed a computational model based on object features and a machine learning classifier. The analysis of the model revealed that a small number of features was sufficient for categorization, and the fish were more sensitive to object contours than textures. We tested these predictions in additional behavioral experiments and validated them. Our findings suggest the existence of a complex visual process in the archerfish visual system that enables object recognition and categorization.

Individual differences in error-related frontal midline theta activity during visuomotor adaptation.

Post-feedback frontal midline EEG activity has been found to correlate with error magnitude during motor adaptation. However, the role of this neuronal activity remains to be elucidated. It has been hypothesized that post-feedback frontal midline activity may represent a prediction error, which in turn may be directly related to the adaptation process or to an unspecific orienting response. To address these hypotheses, we replicated a previous visuomotor adaptation experiment with very small perturbations, likely to invoke implicit adaptation, in a new group of 60 participants and combined it with EEG recordings. We found error-related peaks in the frontal midline electrodes in the time domain. However, these were best understood as modulations of frontal midline theta activity (FMT, 4-8 Hz). Trial-level differences in FMT correlated with error magnitude. This correlation was robust even for very small errors as well as in the absence of imposed perturbations, indicating that FMT does not depend on explicit or strategic re-aiming. Within participants, trial-level differences in FMT were not related to between-trial error corrections. Between participants, individual differences in FMT-error-sensitivity did not predict differences in adaptation rate. Taken together, these results imply that FMT does not drive implicit motor adaptation. Finally, individual differences in FMT-error-sensitivity negatively correlate to motor execution noise. This suggests that FMT reflects saliency: larger execution noise means a larger standard deviation of errors so that a fixed error magnitude is less salient. In conclusion, this study suggests that frontal midline theta activity represents a saliency signal and does not directly drive motor adaptation.

Methods matter: Your measures of explicit and implicit processes in visuomotor adaptation affect your results.

Visuomotor rotations are frequently used to study the different processes underlying motor adaptation. Explicit aiming strategies and implicit recalibration are two of these processes. Various methods, which differ in their underlying assumptions, have been used to dissociate the two processes. Direct methods, such as verbal reports, assume explicit knowledge to be verbalizable, where indirect methods, such as the exclusion, assume that explicit knowledge is controllable. The goal of this study was thus to directly compare verbal reporting with exclusion in two different conditions: during consistent reporting and during intermittent reporting. Our results show that our two conditions lead to a dissociation between the measures. In the consistent reporting group, all measures showed similar results. However, in the intermittent reporting group, verbal reporting showed more explicit re-aiming and less implicit adaptation than exclusion. Curiously, when exclusion was measured again, after the end of learning, the differences were no longer apparent. We suspect this may reflect selective decay in implicit adaptation, as has been reported previously. All told, our results clearly indicate that methods of measurement can affect the amount of explicit re-aiming and implicit adaptation that is measured. Since it has been previously shown that both explicit re-aiming and implicit adaptation have multiple components, discrepancies between these different methods may arise because different measures reflect different components.

A Revised Computational Neuroanatomy for Motor Control.

We discuss a new framework for understanding the structure of motor control. Our approach integrates existing models of motor control with the reality of hierarchical cortical processing and the parallel segregated loops that characterize cortical-subcortical connections. We also incorporate the recent claim that cortex functions via predictive representation and optimal information utilization. Our framework assumes that each cortical area engaged in motor control generates a predictive model of a different aspect of motor behavior. In maintaining these predictive models, each area interacts with a different part of the cerebellum and BG. These subcortical areas are thus engaged in domain-appropriate system identification and optimization. This refocuses the question of division of function among different cortical areas. What are the different aspects of motor behavior that are predictively modeled? We suggest that one fundamental division is between modeling of task and body whereas another is the model of state and action. Thus, we propose that the posterior parietal cortex, somatosensory cortex, premotor cortex, and motor cortex represent task state, body state, task action, and body action, respectively. In the second part of this review, we demonstrate how this division of labor can better account for many recent findings of movement encoding, especially in the premotor and posterior parietal cortices.

Long-range neural inhibition and stimulus competition in the archerfish optic tectum.

The archerfish, which is unique in its ability to hunt insects above the water level by shooting a jet of water at its prey, operates in a complex visual environment. The fish needs to quickly select one object from among many others. In animals other than the archerfish, long-range inhibition is considered to drive selection. As a result of long-range inhibition, a potential target outside a neuron's receptive field suppresses the activity elicited by another potential target within the receptive field. We tested whether a similar mechanism operates in the archerfish by recording the activity of neurons in the optic tectum while presenting a target stimulus inside the receptive field and a competing stimulus outside the receptive field. We held the features of the target constant while varying the size, speed, and distance of the competing stimulus. We found cells that exhibit long-range inhibition; i.e., inhibition that extends to a significant part of the entire visual field of the animal. The competing stimulus depressed the firing rate. In some neurons, this effect was dependent on the features of the competing stimulus. These findings suggest that long-range inhibition may play a crucial role in the target selection process in the archerfish.

Individual Movement Variability Magnitudes Are Explained by Cortical Neural Variability.

Humans exhibit considerable motor variability even across trivial reaching movements. This variability can be separated into specific kinematic components such as extent and direction that are thought to be governed by distinct neural processes. Here, we report that individual subjects (males and females) exhibit different magnitudes of kinematic variability, which are consistent (within individual) across movements to different targets and regardless of which arm (right or left) was used to perform the movements. Simultaneous fMRI recordings revealed that the same subjects also exhibited different magnitudes of fMRI variability across movements in a variety of motor system areas. These fMRI variability magnitudes were also consistent across movements to different targets when performed with either arm. Cortical fMRI variability in the posterior-parietal cortex of individual subjects explained their movement-extent variability. This relationship was apparent only in posterior-parietal cortex and not in other motor system areas, thereby suggesting that individuals with more variable movement preparation exhibit larger kinematic variability. We therefore propose that neural and kinematic variability are reliable and interrelated individual characteristics that may predispose individual subjects to exhibit distinct motor capabilities.SIGNIFICANCE STATEMENT Neural activity and movement kinematics are remarkably variable. Although intertrial variability is rarely studied, here, we demonstrate that individual human subjects exhibit distinct magnitudes of neural and kinematic variability that are reproducible across movements to different targets and when performing these movements with either arm. Furthermore, when examining the relationship between cortical variability and movement variability, we find that cortical fMRI variability in parietal cortex of individual subjects explained their movement extent variability. This enabled us to explain why some subjects performed more variable movements than others based on their cortical variability magnitudes.

Effector-Invariant Movement Encoding in the Human Motor System.

Ipsilateral motor areas of cerebral cortex are active during arm movements and even reliably predict movement direction. Is coding similar during ipsilateral and contralateral movements? If so, is it in extrinsic (world-centered) or intrinsic (joint-configuration) coordinates? We addressed these questions by examining the similarity of multivoxel fMRI patterns in visuomotor cortical regions during unilateral reaching movements with both arms. The results of three complementary analyses revealed that fMRI response patterns were similar across right and left arm movements to identical targets (extrinsic coordinates) in visual cortices, and across movements with equivalent joint-angles (intrinsic coordinates) in motor cortices. We interpret this as evidence for the existence of distributed neural populations in multiple motor system areas that encode ipsilateral and contralateral movements in a similar manner: according to their intrinsic/joint coordinates.SIGNIFICANCE STATEMENT Cortical motor control exhibits clear lateralization: each hemisphere controls the motor output of the contralateral body. Nevertheless, neural populations in ipsilateral areas across the visuomotor hierarchy are active during unilateral movements. We show that fMRI response patterns in the motor cortices are similar for both arms if the movement direction is mirror-reversed across the midline. This suggests that in both ipsilateral and contralateral motor cortices, neural populations have effector-invariant coding of movements in intrinsic coordinates. This not only affects our understanding of motor control, it may serve in the development of brain machine interfaces that also use ipsilateral neural activity.

Stimulation of PPC Affects the Mapping between Motion and Force Signals for Stiffness Perception But Not Motion Control.

How motion and sensory inputs are combined to assess an object's stiffness is still unknown. Here, we provide evidence for the existence of a stiffness estimator in the human posterior parietal cortex (PPC). We showed previously that delaying force feedback with respect to motion when interacting with an object caused participants to underestimate its stiffness. We found that applying theta-burst transcranial magnetic stimulation (TMS) over the PPC, but not the dorsal premotor cortex, enhances this effect without affecting movement control. We explain this enhancement as an additional lag in force signals. This is the first causal evidence that the PPC is not only involved in motion control, but also has an important role in perception that is disassociated from action. We provide a computational model suggesting that the PPC integrates position and force signals for perception of stiffness and that TMS alters the synchronization between the two signals causing lasting consequences on perceptual behavior. SIGNIFICANCE STATEMENT: When selecting an object such as a ripe fruit or sofa, we need to assess the object's stiffness. Because we lack dedicated stiffness sensors, we rely on an as yet unknown mechanism that generates stiffness percepts by combining position and force signals. Here, we found that the posterior parietal cortex (PPC) contributes to combining position and force signals for stiffness estimation. This finding challenges the classical view about the role of the PPC in regulating position signals only for motion control because we highlight a key role of the PPC in perception that is disassociated from action. Altogether this sheds light on brain mechanisms underlying the interaction between action and perception and may help in the development of better teleoperation systems and rehabilitation of patients with sensory impairments.

Cerebellar patients do not benefit from cerebellar or M1 transcranial direct current stimulation during force-field reaching adaptation.

Several studies have identified transcranial direct current stimulation (tDCS) as a potential tool in the rehabilitation of cerebellar disease. Here, we tested whether tDCS could alleviate motor impairments of subjects with cerebellar degeneration. Three groups took part in this study: 20 individuals with cerebellar degeneration, 20 age-matched controls, and 30 young controls. A standard reaching task with force-field perturbations was used to compare motor adaptation among groups and to measure the effect of stimulation of the cerebellum or primary motor cortex (M1). Cerebellar subjects and age-matched controls were tested during each stimulation type (cerebellum, M1, and sham) with a break of 1 wk among each of the three sessions. Young controls were tested during one session under one of three stimulation types (anodal cerebellum, cathodal cerebellum, or sham). As expected, individuals with cerebellar degeneration had a reduced ability to adapt to motor perturbations. Importantly, cerebellar patients did not benefit from anodal stimulation of the cerebellum or M1. Furthermore, no stimulation effects could be detected in aging and young controls. The present null results cannot exclude more subtle tDCS effects in larger subject populations and between-subject designs. Moreover, it is still possible that tDCS affects motor adaptation in cerebellar subjects and control subjects under a different task or with alternative stimulation parameters. However, for tDCS to become a valuable tool in the neurorehabilitation of cerebellar disease, stimulation effects should be present in group sizes commonly used in this rare patient population and be more consistent and predictable across subjects and tasks.NEW & NOTEWORTHY Transcranial direct current stimulation (tDCS) has been identified as a potential tool in the rehabilitation of cerebellar disease. We investigated whether tDCS of the cerebellum and primary motor cortex could alleviate motor impairments of subjects with cerebellar degeneration. The present study did not find stimulation effects of tDCS in young controls, aging controls, and individuals with cerebellar degeneration during reach adaptation. Our results require a re-evaluation of the clinical potential of tDCS in cerebellar patients.

Representing delayed force feedback as a combination of current and delayed states.

To adapt to deterministic force perturbations that depend on the current state of the hand, internal representations are formed to capture the relationships between forces experienced and motion. However, information from multiple modalities travels at different rates, resulting in intermodal delays that require compensation for these internal representations to develop. To understand how these delays are represented by the brain, we presented participants with delayed velocity-dependent force fields, i.e., forces that depend on hand velocity either 70 or 100 ms beforehand. We probed the internal representation of these delayed forces by examining the forces the participants applied to cope with the perturbations. The findings showed that for both delayed forces, the best model of internal representation consisted of a delayed velocity and current position and velocity. We show that participants relied initially on the current state, but with adaptation, the contribution of the delayed representation to adaptation increased. After adaptation, when the participants were asked to make movements with a higher velocity for which they had not previously experienced with the delayed force field, they applied forces that were consistent with current position and velocity as well as delayed velocity representations. This suggests that the sensorimotor system represents delayed force feedback using current and delayed state information and that it uses this representation when generalizing to faster movements.NEW & NOTEWORTHY The brain compensates for forces in the body and the environment to control movements, but it is unclear how it does so given the inherent delays in information transmission and processing. We examined how participants cope with delayed forces that depend on their arm velocity 70 or 100 ms beforehand. After adaptation, participants applied opposing forces that revealed a partially correct representation of the perturbation using the current and the delayed information.

Long Pauses in Cerebellar Interneurons in Anesthetized Animals.

Are long pauses in the firing of cerebellar interneurons (CINs) related to Purkinje cell (PC) pauses? If PC pauses affect the larger network, then we should find a close relationship between CIN pauses and those in PCs. We recorded activity of 241 cerebellar cortical neurons (206 CINs and 35 PCs) in three anesthetized cats. One fifth of the CINs and more than half of the PCs were identified as pausing. Pauses in CINs and PCs showed some differences: CIN mean pause length was shorter, and, after pauses, only CINs had sustained reduction in their firing rate (FR). Almost all pausing CINs fell into same cluster when we used different methods of clustering CINs by their spontaneous activity. The mean spontaneous firing rate of that cluster was approximately 53 Hz. We also examined cross-correlations in simultaneously recorded neurons. Of 39 cell pairs examined, 14 (35 %) had cross-correlations significantly different from those expected by chance. Almost half of the pairs with two CINs showed statistically significant negative correlations. In contrast, PC/CIN pairs did not often show significant effects in the cross-correlation (12/15 pairs). However, for both CIN/CIN and PC/CIN pairs, pauses in one unit tended to correspond to a reduction in the firing rate of the adjacent unit. In our view, our results support the possibility that previously reported PC bistability is part of a larger network response and not merely a biophysical property of PCs. Any functional role for PC bistability should probably be sought in the context of the broader network.

Dissociating visual and motor directional selectivity using visuomotor adaptation.

Directional selectivity during visually guided hand movements is a fundamental characteristic of neural populations in multiple motor areas of the primate brain. In the current study, we assessed how directional selectivity changes when reaching movements are dissociated from their visual feedback by rotating the visual field. We recorded simultaneous movement kinematics and fMRI activity while human subjects performed out-and-back movements to four peripheral targets before and after adaptation to a 45° visuomotor rotation. A classification algorithm was trained to identify movement direction according to voxel-by-voxel fMRI patterns in each of several brain areas. The direction of movements was successfully decoded with above-chance accuracy in multiple motor and visual areas when training and testing the classifier on trials within each condition, thereby demonstrating the existence of directionally selective fMRI patterns within each stage of the experiment. Most importantly, when training the classifier on baseline trials and decoding rotated trials, motor brain areas exhibited above-chance decoding according to the original movement direction and visual brain areas exhibited above-chance decoding according to the rotated visual target location, while posterior parietal cortex (PPC) exhibited chance-level decoding according to both. These results reveal that directionally selective fMRI patterns in motor system areas faithfully represent movement direction regardless of visual feedback, while fMRI patterns in visual system areas faithfully represent target location regardless of movement direction. Directionally selective fMRI patterns in PPC, however, were altered following adaptation learning, thereby suggesting that the novel visuomotor mapping, which was learned during visuomotor adaptation, is stored in PPC.

Spontaneous activity does not predict morphological type in cerebellar interneurons.

The effort to determine morphological and anatomically defined neuronal characteristics from extracellularly recorded physiological signatures has been attempted with varying success in different brain areas. Recent studies have attempted such classification of cerebellar interneurons (CINs) based on statistical measures of spontaneous activity. Previously, such efforts in different brain areas have used supervised clustering methods based on standard parameterizations of spontaneous interspike interval (ISI) histograms. We worried that this might bias researchers toward positive identification results and decided to take a different approach. We recorded CINs from anesthetized cats. We used unsupervised clustering methods applied to a nonparametric representation of the ISI histograms to identify groups of CINs with similar spontaneous activity and then asked how these groups map onto different cell types. Our approach was a fuzzy C-means clustering algorithm applied to the Kullbach-Leibler distances between ISI histograms. We found that there is, in fact, a natural clustering of the spontaneous activity of CINs into six groups but that there was no relationship between this clustering and the standard morphologically defined cell types. These results proved robust when generalization was tested to completely new datasets, including datasets recorded under different anesthesia conditions and in different laboratories and different species (rats). Our results suggest the importance of an unsupervised approach in categorizing neurons according to their extracellular activity. Indeed, a reexamination of such categorization efforts throughout the brain may be necessary. One important open question is that of functional differences of our six spontaneously defined clusters during actual behavior.

Behavioural and neural basis of anomalous motor learning in children with autism.

Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to abnormalities in how they learn motor control throughout development. Here, we used behavioural techniques to quantify motor learning in autism spectrum disorder, and structural brain imaging to investigate the neural basis of that learning in the cerebellum. Twenty children with autism spectrum disorder and 20 typically developing control subjects, aged 8-12, made reaching movements while holding the handle of a robotic manipulandum. In random trials the reach was perturbed, resulting in errors that were sensed through vision and proprioception. The brain learned from these errors and altered the motor commands on the subsequent reach. We measured learning from error as a function of the sensory modality of that error, and found that children with autism spectrum disorder outperformed typically developing children when learning from errors that were sensed through proprioception, but underperformed typically developing children when learning from errors that were sensed through vision. Previous work had shown that this learning depends on the integrity of a region in the anterior cerebellum. Here we found that the anterior cerebellum, extending into lobule VI, and parts of lobule VIII were smaller than normal in children with autism spectrum disorder, with a volume that was predicted by the pattern of learning from visual and proprioceptive errors. We suggest that the abnormal patterns of motor learning in children with autism spectrum disorder, showing an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error, may be associated with abnormalities in the cerebellum.

Ageing shows a pattern of cerebellar degeneration analogous, but not equal, to that in patients suffering from cerebellar degenerative disease.

Ageing generally leads to impairments in cognitive function and the ability to execute and learn new movements. While the causes of these impairments are often multi-factorial, integrity of the cerebellum in an elderly population is an important predictive factor of both motor function and cognitive function. A similar association between cerebellar integrity and function is true for cerebellar patients. We set out to investigate the analogies between the pattern of cerebellar degeneration of a healthy ageing population and cerebellar patients. We quantified cerebellar regional volumes by applying voxel-based morphometry (VBM) to a publicly available dataset of MR images obtained in 313 healthy subjects aged between 18 and 96 years and a dataset of MR images of 21 cerebellar patients. We observed considerable overlap in regions with the strongest loss of cerebellar volume in the two datasets. In both datasets, the anterior lobe of the cerebellum (lobules I-V) and parts of the superior cerebellum (primarily lobule VI) showed the strongest degeneration of cerebellar volume. However, the most significant voxels in cerebellar patients were shifted posteriorly (lobule VII) compared to the voxels that degenerate most with age in the healthy population. The results showed a pattern of significant degeneration of the posterior motor region (lobule VIIIb) in both groups, and significant degeneration of lobule IX and X in the healthy population, but not in cerebellar patients. Furthermore, we saw strong volumetric degeneration of functionally defined cerebellar regions associated with cerebral somatomotor function in both groups. Predominance of degeneration in the anterior lobe and lobule VI suggests impairment of motor function in both groups, while we suggest that the posterior shift of degeneration in cerebellar patients would be associated with relatively stronger impairment of higher motor function and cognitive function. Thus, these results may explain the specific symptomology associated with cerebellar degeneration in ageing and in cerebellar patients.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation.

Cerebellar transcranial direct current stimulation effects on saccade adaptation.

Saccade adaptation is a cerebellar-mediated type of motor learning in which the oculomotor system is exposed to repetitive errors. Different types of saccade adaptations are thought to involve distinct underlying cerebellar mechanisms. Transcranial direct current stimulation (tDCS) induces changes in neuronal excitability in a polarity-specific manner and offers a modulatory, noninvasive, functional insight into the learning aspects of different brain regions. We aimed to modulate the cerebellar influence on saccade gains during adaptation using tDCS. Subjects performed an inward (n = 10) or outward (n = 10) saccade adaptation experiment (25% intrasaccadic target step) while receiving 1.5 mA of anodal cerebellar tDCS delivered by a small contact electrode. Compared to sham stimulation, tDCS increased learning of saccadic inward adaptation but did not affect learning of outward adaptation. This may imply that plasticity mechanisms in the cerebellum are different between inward and outward adaptation. TDCS could have influenced specific cerebellar areas that contribute to inward but not outward adaptation. We conclude that tDCS can be used as a neuromodulatory technique to alter cerebellar oculomotor output, arguably by engaging wider cerebellar areas and increasing the available resources for learning.