Prediction signals in the cerebellum: beyond supervised motor learning

Interpersonal synchronization: An overlooked factor in development, social cognition, and psychopathology

Intact social functioning relies on a combination of explicit and implicit behavioral, attentional, and interpersonal processes referred to as "social cognition". Characterizing these interpersonal processes forms a critical underpinning to understanding and treating psychopathology, particularly in disorders where deficits in social functioning do not emerge as a secondary symptom but rather as an essential feature of the disorder. Two of such disorders are autism spectrum disorders (ASD) and schizophrenia spectrum disorders (SZ). However, despite the substantial overlap in the features of social dysfunction between ASD and SZ, including social cognitive deficits in theory of mind, perspective-taking, and empathy, there is a limited understanding of the mechanisms underlying those shared deficits, and how to treat them. We suggest that disruptions of interpersonal functioning emerge over the course of development, and that interpersonal synchronization, a phenomenon in which behavioral and physiological cues align between interacting partners, forms a critical component of social cognition that underlies the disruption in social functioning in ASD and SZ. We present a conceptual review of typical and atypical development of social processes and highlight the role of interpersonal synchronization across the course of development. Then, we review the existing evidence suggesting impairments in both the intentional and spontaneous synchronization of interpersonal processes in ASD and SZ, as well as studies suggesting that interpersonal synchronization and clinical symptoms may be improved through body-oriented interventions within these disorders. Finally, we suggest potential mechanisms that may underpin typical and atypical development of interpersonal synchronization.

Reward signals in the motor cortex: from biology to neurotechnology

Over the past decade, research has shown that the primary motor cortex (M1), the brain's main output for movement, also responds to rewards. These reward signals may shape motor output in its final stages, influencing movement invigoration and motor learning. In this Perspective, we highlight the functional roles of M1 reward signals and propose how they could guide advances in neurotechnologies for movement restoration, specifically brain-computer interfaces and non-invasive brain stimulation. Understanding M1 reward signals may open new avenues for enhancing motor control and rehabilitation.

Neural representation dynamics reveal computational principles of cognitive task learning

During cognitive task learning, neural representations must be rapidly constructed for novel task performance, then optimized for robust practiced task performance. How the geometry of neural representations changes to enable this transition from novel to practiced performance remains unknown. We hypothesized that practice involves a shift from compositional representations (task-general activity patterns that can be flexibly reused across tasks) to conjunctive representations (task-specific activity patterns specialized for the current task). Functional MRI during learning of multiple complex tasks substantiated this dynamic shift from compositional to conjunctive representations, which was associated with reduced cross-task interference (via pattern separation) and behavioral improvement. Further, we found that conjunctions originated in subcortex (hippocampus and cerebellum) and slowly spread to cortex, extending multiple memory systems theories to encompass cognitive task learning. The strengthening of conjunctive representations hence serves as a computational signature of learning, reflecting cortical-subcortical dynamics that optimize task representations in the human brain.

Highlights

Learning shifts multi-task representations from compositional to conjunctive formatsCortical conjunctions uniquely associate with improved behavior and pattern separationThese conjunctions strengthen over separated learning events and index switch costsSubcortical regions are critical for cross-region binding of task rule information.

Acute Effects of Unplanned and Planned Hop-Landing Training on Neurocognitive Function and Knee Biomechanics

Background

Athletes with decreased baseline neurocognitive function may experience noncontact anterior cruciate ligament (ACL) injury in unanticipated athletic situations. Many ACL injury prevention programs (IPPs) focus on improving closed-skill movements (eg, planned landing). However, the more open-skill movements (eg, unplanned reactive movements) required in unpredictable sports scenarios are commonly absent from ACL IPPs, and the acute effects of open-skill training on neurocognitive function remain unclear.

Purpose

To investigate the acute effects of unplanned versus planned training on neurocognitive function and knee biomechanics associated with ACL injury risk during the side-step cutting motion.

Study Design

Controlled laboratory study.

Methods

A total of 32 adult recreational athletes (16 female, 16 male) were randomly assigned to either an unplanned training (UT) group or a control (CON) group. The UT group performed unplanned hop-landing training while the CON group performed planned hop-landing training. Both before and after the training, neurocognitive function was evaluated using the Trail Making Test-part B and Stroop Color and Word Test. Additionally, unanticipated and anticipated side-step cutting tasks were performed while 3-dimensional kinematic and kinetic data for the dominant leg were collected. Neurocognitive test scores and biomechanical variables relevant to ACL injury were analyzed using 2-way repeated-measures analysis of variance to determine the main effects of training, group, and training × group interaction.

Results

Trail Making Test-part B and Stroop Color and Word Test scores significantly improved from pre- to posttraining in both groups (P < .001 for both). There was a significant training × group interaction for peak knee abduction angle during the unanticipated side-step cutting task (pre- vs posttraining: -8.81°± 7.23° vs -7.40°± 7.24° [UT group]; -8.23°± 9.40° vs -9.99°± 9.83° [CON group]; P = .02) and for peak vertical ground-reaction force during the anticipated side-step cutting task (pre- vs posttraining: 3.86 ± 0.59 vs 4.08 ± 0.74 percentage body weight [%BW] [UT group]; 3.70 ± 0.62 vs 3.34 ± 0.62 %BW [CON group]; P = .04).

Conclusion

Study findings showed a significant training × group interaction for knee abduction angle during the unanticipated side-step cutting task with unplanned training and for vertical ground-reaction force during the anticipated side-step cutting task with planned training.

Clinical Relevance

Designing ACL IPPs based on the sport type (ie, open skill or closed skill) may contribute to better preparation.

Learning to segment self-generated from externally caused optic flow through sensorimotor mismatch circuits

Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion need to be disentangled from object perception. To investigate how this is achieved in the visual system, predictive coding with sensorimotor mismatch detection is an attractive starting point. Indeed, experimental evidence for sensorimotor mismatch signals in early visual areas exists, but it is not understood how they are integrated into cortical networks that perform input segmentation and categorization. Our model advances a biologically plausible solution by extending predictive coding models with the ability to distinguish self-generated from externally caused optic flow. We first show that a simple three neuron circuit produces experience-dependent sensorimotor mismatch responses, in agreement with calcium imaging data from mice. This microcircuit is then integrated into a neural network with two generative streams. The motor-to-visual stream consists of parallel microcircuits between motor and visual areas and learns to spatially predict optic flow resulting from self-motion. The second stream bidirectionally connects a motion-selective higher visual area (mHVA) to V1, assigning a crucial role to the abundant feedback connections to V1: the maintenance of a generative model of externally caused optic flow. In the model, area mHVA learns to segment moving objects from the background, and facilitates object categorization. Based on shared neurocomputational principles across species, the model also maps onto primate visual cortex. Our work extends Hebbian predictive coding to sensorimotor settings, in which the agent actively moves - and learns to predict the consequences of its own movements.

Relating Human Error-Based Learning to Modern Deep RL Algorithms

In human error-based learning, the size and direction of a scalar error (i.e., the "directed error") are used to update future actions. Modern deep reinforcement learning (RL) methods perform a similar operation but in terms of scalar rewards. Despite this similarity, the relationship between action updates of deep RL and human error-based learning has yet to be investigated. Here, we systematically compare the three major families of deep RL algorithms to human error-based learning. We show that all three deep RL approaches are qualitatively different from human error-based learning, as assessed by a mirror-reversal perturbation experiment. To bridge this gap, we developed an alternative deep RL algorithm inspired by human error-based learning, model-based deterministic policy gradients (MB-DPG). We showed that MB-DPG captures human error-based learning under mirror-reversal and rotational perturbations and that MB-DPG learns faster than canonical model-free algorithms on complex arm-based reaching tasks, while being more robust to (forward) model misspecification than model-based RL.

Social and emotional learning in the cerebellum

The posterior cerebellum has a critical role in human social and emotional learning. Three systems and related neural networks support this cerebellar function: a biological action observation system as part of an extended sensorimotor integration network, a mentalizing system for understanding a person's mental and emotional state subserved by a mentalizing network, and a limbic network supporting core emotional (dis)pleasure and arousal processes. In this Review, I describe how these systems and networks support social and emotional learning via functional reciprocal connections initiating and terminating in the posterior cerebellum and cerebral neocortex. It is hypothesized that a major function of the posterior cerebellum is to identify and encode temporal sequences of events, which might help to fine-tune and automatize social and emotional learning. I discuss research using neuroimaging and non-invasive stimulation that provides converging evidence for this hypothesized function of cerebellar sequencing, but also other potential functional accounts of the posterior cerebellum's role in these social and emotional processes.

Reward-driven cerebellar climbing fiber activity influences both neural and behavioral learning

The cerebellum plays a key role in motor coordination and learning. In contrast with classical supervised learning models, recent work has revealed that CFs can signal reward-predictive information in some behaviors. This raises the question of whether CFs may also operate according to principles similar to those described by reinforcement learning models. To test how CFs operate during reward-guided behavior, and evaluate the role of reward-related CF activity in learning, we have measured CF responses in Purkinje cells of the lateral cerebellum during a Pavlovian task using 2-photon calcium imaging. Specifically, we have performed multi-stimulus experiments to determine whether CF activity meets the requirements of a reward prediction error (rPE) signal for transfer from an unexpected reward to a reward-predictive cue. We find that once CF activity is transferred to a conditioned stimulus, and there is no longer a response to reward, CFs cannot generate learned responses to a second conditioned stimulus that carries the same reward prediction. In addition, by expressing the inhibitory opsin GtACR2 in neurons of the inferior olive, and optically inhibiting these neurons across behavioral training at the time of unexpected reward, we find that the transfer of CF signals to the conditioned stimulus is impaired. Moreover, this optogenetic inhibition also impairs learning, resulting in a deficit in anticipatory lick timing. Together, these results indicate that CF signals can exhibit several characteristics in common with rPEs during reinforcement learning, and that the cerebellum can harness these learning signals to generate accurately timed motor behavior.

Cerebellar climbing fibers signal flexible, rapidly adapting reward predictions

Classical models of cerebellar computation posit that climbing fibers (CFs) operate according to supervised learning rules, correcting movements by signaling the occurrence of motor errors. However, recent findings suggest that in some behaviors, CF activity can exhibit features that resemble the instructional signals necessary for reinforcement learning, namely reward prediction errors (rPEs). Despite these initial observations, many key properties of reward-related CF responses remain unclear, thus limiting our understanding of how they operate to guide cerebellar learning. Here, we have measured the postsynaptic responses of CFs onto cerebellar Purkinje cells using two-photon calcium imaging to test how they respond to learned stimuli that either do or do not predict reward. We find that CFs can develop generalized responses to similar cues of the same modality, regardless of whether they are reward predictive. However, this generalization depends on temporal context, and does not extend across sensory modalities. Further, learned CF responses are flexible, and can be rapidly updated according to new reward contingencies. Together these results suggest that CFs can generate learned, reward-predictive responses that flexibly adapt to the current environment in a context-sensitive manner.

Converging and Diverging Cerebellar Pathways for Motor and Social Behaviors in Mice

Evidence from clinical and preclinical studies has shown that the cerebellum contributes to cognitive functions, including social behaviors. Now that the cerebellum's role in a wider range of behaviors has been confirmed, the question arises whether the cerebellum contributes to social behaviors via the same mechanisms with which it modulates movements. This review seeks to answer whether the cerebellum guides motor and social behaviors through identical pathways. It focuses on studies in which cerebellar cells, synapses, or genes are manipulated in a cell-type specific manner followed by testing of the effects on social and motor behaviors. These studies show that both anatomically restricted and cerebellar cortex-wide manipulations can lead to social impairments without abnormal motor control, and vice versa. These studies suggest that the cerebellum employs different cellular, synaptic, and molecular pathways for social and motor behaviors. Future studies warrant a focus on the diverging mechanisms by which the cerebellum contributes to a wide range of neural functions.

Consensus Paper: Cerebellum and Reward

Cerebellum is a key-structure for the modulation of motor, cognitive, social and affective functions, contributing to automatic behaviours through interactions with the cerebral cortex, basal ganglia and spinal cord. The predictive mechanisms used by the cerebellum cover not only sensorimotor functions but also reward-related tasks. Cerebellar circuits appear to encode temporal difference error and reward prediction error. From a chemical standpoint, cerebellar catecholamines modulate the rate of cerebellar-based cognitive learning, and mediate cerebellar contributions during complex behaviours. Reward processing and its associated emotions are tuned by the cerebellum which operates as a controller of adaptive homeostatic processes based on interoceptive and exteroceptive inputs. Lobules VI-VII/areas of the vermis are candidate regions for the cortico-subcortical signaling pathways associated with loss aversion and reward sensitivity, together with other nodes of the limbic circuitry. There is growing evidence that the cerebellum works as a hub of regional dysconnectivity across all mood states and that mental disorders involve the cerebellar circuitry, including mood and addiction disorders, and impaired eating behaviors where the cerebellum might be involved in longer time scales of prediction as compared to motor operations. Cerebellar patients exhibit aberrant social behaviour, showing aberrant impulsivity/compulsivity. The cerebellum is a master-piece of reward mechanisms, together with the striatum, ventral tegmental area (VTA) and prefrontal cortex (PFC). Critically, studies on reward processing reinforce our view that a fundamental role of the cerebellum is to construct internal models, perform predictions on the impact of future behaviour and compare what is predicted and what actually occurs.

Altered local intrinsic neural activity and molecular architecture in internet use disorders

BACKGROUND

Internet gaming disorder (IGD) is mainly characterized by its core dysfunction in higher-order brain cortices involved in inhibitory control, whose neurobiological basis remains unclear. Then, we will investigate local intrinsic neural activity (INA) alterations in IGD, ascertain whether these potential alterations are related to clinical characteristics, and further explore the underlying molecular architecture.

METHOD

In this study, we performed the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) derived from resting-state functional magnetic resonance imaging (rs-fMRI) to explore the impact of IGD on local INA. Correlation analysis revealed the relationship between ReHo and fALFF in terms of group differences and clinical characteristics. Moreover, correlations between fALFF, ReHo, and PET- and SPECT-driven maps were investigated to elucidate the specific molecular architecture alternations in IGD. Finally, receiver operating characteristic curve (ROC) analysis was used to show the potential abilities of fALFF and ReHo in distinguishing individuals with IGD (IGDs) from healthy controls (HCs).

RESULT

Compared with HCs, IGDs revealed increased ReHo and fALFF in the prefrontal cortex. Significantly decreased ReHo was observed in the temporal lobe, occipital lobe, and cerebellum. In addition, the ReHo values in the cerebellum_7b_R were positively correlated with internet addiction severity. ROC curve analysis showed that ReHo and fALFF-altered brain regions could effectively distinguish IGDs from HCs. More importantly, cross-modal correlations revealed local INA changes in brain regions associated with the monoamine neurotransmitter system and the less studied cholinergic/GABAergic system.

CONCLUSION

These results suggest that local functional impairments are shown in the audiovisual and inhibitory control circuits in IGDs. This may be associated with underlying neurotransmitter system alterations. Therefore, this study provides the possibility of GABAergic receptor agonists and cholinergic receptor inhibitors for the treatment of IGD.

Control of action potential afterdepolarizations in the inferior olive by inactivating A-type currents through KV4 channels

Neurons of the inferior olive (IO) fire action potentials with large, long-lasting afterdepolarizations (ADPs). Broader ADPs support more spikes in climbing fibre axons and evoke longer bursts of complex spikes in Purkinje cells, which affect the magnitude and sign of cerebellar synaptic plasticity. In the present study, we investigated the ionic mechanisms that regulate IO action potential waveforms by making whole-cell recordings in brainstem slices from C57BL6/J mice. IO spikes evoked from rest had ADPs of ∼30 ms. After 500-ms hyperpolarizations, however, evoked action potentials were brief (1-2 ms), lacking ADPs altogether. Because such preconditioning should maximally recruit depolarizing Ih and T-type currents and minimize repolarizing Ca-dependent currents known to shape the ADP, the rapid action potential downstroke suggested additional, dominant recovery of voltage-gated K currents at negative voltages. Under voltage clamp, outward currents evoked from -98 mV included large, voltage-gated, rapidly inactivating 'A-type' K currents. These currents had a steep availability curve with half-inactivation at -85 mV, suitable for recruitment by small hyperpolarizations. The fast decay time constant increased with depolarization, as is typical of KV4 channels. The KV4 channel blocker AmmTx3 almost eliminated inactivating currents and broadened action potentials evoked from strongly negative potentials by ∼8-fold. Optogenetic stimulation of inhibitory cerebellar nucleo-olivary terminals hyperpolarized IO cells sufficiently to abolish the ADP. The data support the idea that currents through KV4 channels control action potential waveforms in IO cells, shortening ADPs during synaptic inhibition or troughs of membrane potential oscillations, thereby controlling the number of climbing fibre action potentials that propagate to the cerebellum. KEY POINTS: Neurons in the mouse inferior olive (IO) express a large, inactivating, voltage-gated A-type K current carried by KV4 channels. IO action potentials evoked from rest have large, long afterdepolarizations that disappear with pre-spike hyperpolarizations of 5-15 mV. The steep voltage-sensitivity and rapid recovery of KV4 channels regulates the duration of the afterdepolarization over more than one order of magnitude. Factors such as synaptic inhibition are sufficient to recruit KV4 channels and eliminate afterdepolarization (ADP). By controlling the ADP, KV4 channels can set the number of climbing fibre action potentials relayed to the cerebellum and regulate plasticity implicated in motor learning.

A cerebellar granule cell-climbing fiber computation to learn to track long time intervals

In classical cerebellar learning, Purkinje cells (PkCs) associate climbing fiber (CF) error signals with predictive granule cells (GrCs) that were active just prior (∼150 ms). The cerebellum also contributes to behaviors characterized by longer timescales. To investigate how GrC-CF-PkC circuits might learn seconds-long predictions, we imaged simultaneous GrC-CF activity over days of forelimb operant conditioning for delayed water reward. As mice learned reward timing, numerous GrCs developed anticipatory activity ramping at different rates until reward delivery, followed by widespread time-locked CF spiking. Relearning longer delays further lengthened GrC activations. We computed CF-dependent GrC→PkC plasticity rules, demonstrating that reward-evoked CF spikes sufficed to grade many GrC synapses by anticipatory timing. We predicted and confirmed that PkCs could thereby continuously ramp across seconds-long intervals from movement to reward. Learning thus leads to new GrC temporal bases linking predictors to remote CF reward signals-a strategy well suited for learning to track the long intervals common in cognitive domains.

Language and the Cerebellum: Structural Connectivity to the Eloquent Brain

Neurobiological models of receptive language have focused on the left-hemisphere perisylvian cortex with the assumption that the cerebellum supports peri-linguistic cognitive processes such as verbal working memory. The goal of this study was to identify language-sensitive regions of the cerebellum then map the structural connectivity profile of these regions. Functional imaging data and diffusion-weighted imaging data from the Human Connectome Project (HCP) were analyzed. We found that (a) working memory, motor activity, and language comprehension activated partially overlapping but mostly unique subregions of the cerebellum; (b) the linguistic portion of the cerebello-thalamo-cortical circuit was more extensive than the linguistic portion of the cortico-ponto-cerebellar tract; (c) there was a frontal-lobe bias in the connectivity from the cerebellum to the cerebrum; (d) there was some degree of specificity; and (e) for some cerebellar tracts, individual differences in picture identification ability covaried with fractional anisotropy metrics. These findings yield insights into the structural connectivity of the cerebellum as relates to the uniquely human process of language comprehension.

The Role of the Cerebellum in Learning to Predict Reward: Evidence from Cerebellar Ataxia

Recent findings in animals have challenged the traditional view of the cerebellum solely as the site of motor control, suggesting that the cerebellum may also be important for learning to predict reward from trial-and-error feedback. Yet, evidence for the role of the cerebellum in reward learning in humans is lacking. Moreover, open questions remain about which specific aspects of reward learning the cerebellum may contribute to. Here we address this gap through an investigation of multiple forms of reward learning in individuals with cerebellum dysfunction, represented by cerebellar ataxia cases. Nineteen participants with cerebellar ataxia and 57 age- and sex-matched healthy controls completed two separate tasks that required learning about reward contingencies from trial-and-error. To probe the selectivity of reward learning processes, the tasks differed in their underlying structure: while one task measured incremental reward learning ability alone, the other allowed participants to use an alternative learning strategy based on episodic memory alongside incremental reward learning. We found that individuals with cerebellar ataxia were profoundly impaired at reward learning from trial-and-error feedback on both tasks, but retained the ability to learn to predict reward based on episodic memory. These findings provide evidence from humans for a specific and necessary role for the cerebellum in incremental learning of reward associations based on reinforcement. More broadly, the findings suggest that alongside its role in motor learning, the cerebellum likely operates in concert with the basal ganglia to support reinforcement learning from reward.

The Role of the Human Cerebellum for Learning from and Processing of External Feedback in Non-Motor Learning: A Systematic Review

This review aimed to systematically identify and comprehensively review the role of the cerebellum in performance monitoring, focusing on learning from and on processing of external feedback in non-motor learning. While 1078 articles were screened for eligibility, ultimately 36 studies were included in which external feedback was delivered in cognitive tasks and which referenced the cerebellum. These included studies in patient populations with cerebellar damage and studies in healthy subjects applying neuroimaging. Learning performance in patients with different cerebellar diseases was heterogeneous, with only about half of all patients showing alterations. One patient study using EEG demonstrated that damage to the cerebellum was associated with altered neural processing of external feedback. Studies assessing brain activity with task-based fMRI or PET and one resting-state functional imaging study that investigated connectivity changes following feedback-based learning in healthy participants revealed involvement particularly of lateral and posterior cerebellar regions in processing of and learning from external feedback. Cerebellar involvement was found at different stages, e.g., during feedback anticipation and following the onset of the feedback stimuli, substantiating the cerebellum's relevance for different aspects of performance monitoring such as feedback prediction. Future research will need to further elucidate precisely how, where, and when the cerebellum modulates the prediction and processing of external feedback information, which cerebellar subregions are particularly relevant, and to what extent cerebellar diseases alter these processes.

Neural underpinnings of fine motor skills under stress and anxiety: A review

This review offers a comprehensive examination of how stress and anxiety affect motor behavior, particularly focusing on fine motor skills and gait adaptability. We explore the role of several neurochemicals, including brain-derived neurotrophic factor (BDNF) and dopamine, in modulating neural plasticity and motor control under these affective states. The review highlights the importance of developing therapeutic strategies that enhance motor performance by leveraging the interactions between key neurochemicals. Additionally, we investigate the complex interplay between emotional-cognitive states and sensorimotor behaviors, showing how stress and anxiety disrupt neural integration, leading to impairments in skilled movements and negatively impacting quality of life. Synthesizing evidence from human and rodent studies, we provide a detailed understanding of the relationships among stress, anxiety, and motor behavior. Our findings reveal neurophysiological pathways, behavioral outcomes, and potential therapeutic targets, emphasizing the intricate connections between neurobiological mechanisms, environmental factors, and motor performance.

Exploring the Therapeutic Effects and Mechanisms of Transcranial Alternating Current Stimulation on Improving Walking Ability in Stroke Patients via Modulating Cerebellar Gamma Frequency Band-a Narrative Review

The cerebellum plays an important role in maintaining balance, posture control, muscle tone, and lower limb coordination in healthy individuals and stroke patients. At the same time, the relationship between cerebellum and motor learning has been widely concerned in recent years. Due to the relatively intact structure preservation and high plasticity after supratentorial stroke, non-invasive neuromodulation targeting the cerebellum is increasingly used to treat abnormal gait in stroke patients. The gamma frequency of transcranial alternating current stimulation (tACS) is commonly used to improve motor learning. It is an essential endogenous EEG oscillation in the gamma range during the swing phase, and rhythmic movement changes in the gait cycle. However, the effect of cerebellar tACS in the gamma frequency band on balance and walking after stroke remains unknown and requires further investigation.

Simple spike patterns and synaptic mechanisms encoding sensory and motor signals in Purkinje cells and the cerebellar nuclei

Whisker stimulation in awake mice evokes transient suppression of simple spike probability in crus I/II Purkinje cells. Here, we investigated how simple spike suppression arises synaptically, what it encodes, and how it affects cerebellar output. In vitro, monosynaptic parallel fiber (PF)-excitatory postsynaptic currents (EPSCs) facilitated strongly, whereas disynaptic inhibitory postsynaptic currents (IPSCs) remained stable, maximizing relative inhibitory strength at the onset of PF activity. Short-term plasticity thus favors the inhibition of Purkinje spikes before PFs facilitate. In vivo, whisker stimulation evoked a 2-6 ms synchronous spike suppression, just 6-8 ms (∼4 synaptic delays) after sensory onset, whereas active whisker movements elicited broadly timed spike rate increases that did not modulate sensory-evoked suppression. Firing in the cerebellar nuclei (CbN) inversely correlated with disinhibition from sensory-evoked simple spike suppressions but was decoupled from slow, non-synchronous movement-associated elevations of Purkinje firing rates. Synchrony thus allows the CbN to high-pass filter Purkinje inputs, facilitating sensory-evoked cerebellar outputs that can drive movements.

Modulation of movement-related oscillatory signatures by cognitive interference in healthy aging

Age-related changes in the neurophysiology underlying motor control are well documented, but whether these changes are specific to motor function or more broadly reflect age-related alterations in fronto-parietal circuitry serving attention and other higher-level processes remains unknown. Herein, we collected high-density magnetoencephalography (MEG) in 72 healthy adults (age 28-63 years) as they completed an adapted version of the multi-source interference task that involved two subtypes of cognitive interference (i.e., flanker and Simon) and their integration (i.e., multi-source). All MEG data were examined for age-related changes in neural oscillatory activity using a whole-brain beamforming approach. Our primary findings indicated robust behavioral differences in task performance based on the type of interference, as well as stronger beta oscillations with increasing age in the right dorsolateral prefrontal cortices (flanker and multi-source conditions), left parietal (flanker and Simon), and medial parietal regions (multi-source). Overall, these data indicate that healthy aging is associated with alterations in higher-order association cortices that are critical for attention and motor control in the context of cognitive interference.

Reinforcement Motor Learning After Cerebellar Damage Is Related to State Estimation

Recent work showed that individuals with cerebellar degeneration could leverage intact reinforcement learning (RL) to alter their movement. However, there was marked inter-individual variability in learning, and the factors underlying it were unclear. Cerebellum-dependent sensory prediction may contribute to RL in motor contexts by enhancing body state estimates, which are necessary to solve the credit-assignment problem. The objective of this study was to test the relationship between the predictive component of state estimation and RL in individuals with cerebellar degeneration. Individuals with cerebellar degeneration and neurotypical control participants completed two tasks: an RL task that required them to alter the angle of reaching movements and a state estimation task that tested the somatosensory perception of active and passive movement. The state estimation task permitted the calculation of the active benefit shown by each participant, which is thought to reflect the cerebellum-dependent predictive component of state estimation. We found that the cerebellar and control groups showed similar magnitudes of learning with reinforcement and active benefit on average, but there was substantial variability across individuals. Using multiple regression, we assessed potential predictors of RL. Our analysis included active benefit, somatosensory acuity, clinical ataxia severity, movement variability, movement speed, and age. We found a significant relationship in which greater active benefit predicted better learning with reinforcement in the cerebellar, but not the control group. No other variables showed significant relationships with learning. Overall, our results support the hypothesis that the integrity of sensory prediction is a strong predictor of RL after cerebellar damage.

A chronometric study of the posterior cerebellum's function in emotional processing

The posterior cerebellum is a recently discovered hub of the affective and social brain, with different subsectors contributing to different social functions. However, very little is known about when the posterior cerebellum plays a critical role in social processing. Due to its location and anatomy, it has been difficult to use traditional approaches to directly study the chronometry of the cerebellum. To address this gap in cerebellar knowledge, here we investigated the causal contribution of the posterior cerebellum to social processing using a chronometric transcranial magnetic stimulation (TMS) approach. We show that the posterior cerebellum is recruited at an early stage of emotional processing (starting from 100 ms after stimulus onset), simultaneously with the posterior superior temporal sulcus (pSTS), a key node of the social brain. Moreover, using a condition-and-perturb TMS approach, we found that the recruitment of the pSTS in emotional processing is dependent on cerebellar activation. Our results are the first to shed light on chronometric aspects of cerebellar function and its causal functional connectivity with other nodes of the social brain.

Dynamic changes in somatosensory and cerebellar activity mediate temporal recalibration of self-touch

An organism's ability to accurately anticipate the sensations caused by its own actions is crucial for a wide range of behavioral, perceptual, and cognitive functions. Notably, the sensorimotor expectations produced when touching one's own body attenuate such sensations, making them feel weaker and less ticklish and rendering them easily distinguishable from potentially harmful touches of external origin. How the brain learns and keeps these action-related sensory expectations updated is unclear. Here we employ psychophysics and functional magnetic resonance imaging to pinpoint the behavioral and neural substrates of dynamic recalibration of expected temporal delays in self-touch. Our psychophysical results reveal that self-touches are less attenuated after systematic exposure to delayed self-generated touches, while responses in the contralateral somatosensory cortex that normally distinguish between delayed and nondelayed self-generated touches become indistinguishable. During the exposure, the ipsilateral anterior cerebellum shows increased activity, supporting its proposed role in recalibrating sensorimotor predictions. Moreover, responses in the cingulate areas gradually increase, suggesting that as delay adaptation progresses, the nondelayed self-touches trigger activity related to cognitive conflict. Together, our results show that sensorimotor predictions in the simplest act of touching one's own body are upheld by a sophisticated and flexible neural mechanism that maintains them accurate in time.

Altered resting-state brain function in endurance athletes

Previous research has confirmed significant differences in regional brain activity and functional connectivity between endurance athletes and non-athletes. However, no studies have investigated the differences in topological efficiency of the brain functional network between endurance athletes and non-athletes. Here, we compared differences in regional activities, functional connectivity, and topological properties to explore the functional basis associated with endurance training. The results showed significant correlations between Regional Homogeneity in the motor cortex, visual cortex, cerebellum, and the training intensity parameters. Alterations in functional connectivity among the motor cortex, visual cortex, cerebellum, and the inferior frontal gyrus and cingulate gyrus were significantly correlated with training intensity parameters. In addition, the graph theoretical analysis results revealed a significant reduction in global efficiency among athletes. This decline is mainly caused by decreased nodal efficiency and nodal local efficiency of the cerebellar regions. Notably, the sensorimotor regions, such as the precentral gyrus and supplementary motor areas, still exhibit increased nodal efficiency and nodal local efficiency. This study not only confirms the improvement of regional activity in brain regions related to endurance training, but also offers novel insights into the mechanisms through which endurance athletes undergo changes in the topological efficiency of the brain functional network.

Neurorestorative effects of cerebellar transcranial direct current stimulation on social prediction of adolescents and young adults with congenital cerebellar malformations

BACKGROUND

Converging evidence points to impairments of the predictive function exerted by the cerebellum as one of the causes of the social cognition deficits observed in patients with cerebellar disorders.

OBJECTIVE

We tested the neurorestorative effects of cerebellar transcranial direct current stimulation (ctDCS) on the use of contextual expectations to interpret actions occurring in ambiguous sensory sceneries in a sample of adolescents and young adults with congenital, non-progressive cerebellar malformation (CM).

METHODS

We administered an action prediction task in which, in an implicit-learning phase, the probability of co-occurrence between actions and contextual elements was manipulated to form either strongly or moderately informative expectations. Subsequently, in a testing phase, we probed the use of these contextual expectations for predicting ambiguous (i.e., temporally occluded) actions. In a sham-controlled, within-subject design, participants received anodic or sham ctDCS during the task.

RESULTS

Anodic ctDCS, compared to sham, improved patients' ability to use contextual expectations to predict the unfolding of actions embedded in moderately, but not strongly, informative contexts.

CONCLUSIONS

These findings corroborate the role of the cerebellum in using previously learned contextual associations to predict social events and document the efficacy of ctDCS to boost social prediction in patients with congenital cerebellar malformation. The study encourages the further exploration of ctDCS as a neurorestorative tool for the neurorehabilitation of social cognition abilities in neurological, neuropsychiatric, and neurodevelopmental disorders featured by macro- or micro-structural alterations of the cerebellum.

Cerebellar interpositus nucleus exhibits time-dependent errors and predictive responses

Learning is a functional state of the brain that should be understood as a continuous process, rather than being restricted to the very moment of its acquisition, storage, or retrieval. The cerebellum operates by comparing predicted states with actual states, learning from errors, and updating its internal representation to minimize errors. In this regard, we studied cerebellar interpositus nucleus (IPn) functional capabilities by recording its unitary activity in behaving rabbits during an associative learning task: the classical conditioning of eyelid responses. We recorded IPn neurons in rabbits during classical eyeblink conditioning using a delay paradigm. We found that IPn neurons reduce error signals across conditioning sessions, simultaneously increasing and transmitting spikes before the onset of the unconditioned stimulus. Thus, IPn neurons generate predictions that optimize in time and shape the conditioned eyeblink response. Our results are consistent with the idea that the cerebellum works under Bayesian rules updating the weights using the previous history.

Mild Deficits in Fear Learning: Evidence from Humans and Mice with Cerebellar Cortical Degeneration

Functional brain imaging studies in humans suggest involvement of the cerebellum in fear conditioning but do not allow conclusions about the functional significance. The main aim of the present study was to examine whether patients with cerebellar degeneration show impaired fear conditioning and whether this is accompanied by alterations in cerebellar cortical activations. To this end, a 2 d differential fear conditioning study was conducted in 20 cerebellar patients and 21 control subjects using a 7 tesla (7 T) MRI system. Fear acquisition and extinction training were performed on day 1, followed by recall on day 2. Cerebellar patients learned to differentiate between the CS+ and CS-. Acquisition and consolidation of learned fear, however, was slowed. Additionally, extinction learning appeared to be delayed. The fMRI signal was reduced in relation to the prediction of the aversive stimulus and altered in relation to its unexpected omission. Similarly, mice with cerebellar cortical degeneration (spinocerebellar ataxia type 6, SCA6) were able to learn the fear association, but retrieval of fear memory was reduced. In sum, cerebellar cortical degeneration led to mild abnormalities in the acquisition of learned fear responses in both humans and mice, particularly manifesting postacquisition training. Future research is warranted to investigate the basis of altered fMRI signals related to fear learning.

Emergence of syntax and word prediction in an artificial neural circuit of the cerebellum

The cerebellum, interconnected with the cerebral neocortex, plays a vital role in human-characteristic cognition such as language processing, however, knowledge about the underlying circuit computation of the cerebellum remains very limited. To gain a better understanding of the computation underlying cerebellar language processing, we developed a biologically constrained cerebellar artificial neural network (cANN) model, which implements the recently identified cerebello-cerebellar recurrent pathway. We found that while cANN acquires prediction of future words, another function of syntactic recognition emerges in the middle layer of the prediction circuit. The recurrent pathway of the cANN was essential for the two language functions, whereas cANN variants with further biological constraints preserved these functions. Considering the uniform structure of cerebellar circuitry across all functional domains, the single-circuit computation, which is the common basis of the two language functions, can be generalized to fundamental cerebellar functions of prediction and grammar-like rule extraction from sequences, that underpin a wide range of cerebellar motor and cognitive functions. This is a pioneering study to understand the circuit computation of human-characteristic cognition using biologically-constrained ANNs.

Predictive neural computations in the cerebellum contribute to motor planning and faster behavioral responses in larval zebrafish

The ability to predict the future based on past experience lies at the core of the brain's ability to adapt behavior. However, the neural mechanisms that participate in generating and updating predictions are not clearly understood. Further, the evolutionary antecedents and the prevalence of predictive processing among vertebrates are even less explored. Here, we show evidence of predictive processing via the involvement of cerebellar circuits in larval zebrafish. We presented stereotyped optic flow stimuli to larval zebrafish to evoke swims and discovered that lesioning the cerebellum abolished prediction-dependent modulation of swim latency. When expectations of optic flow direction did not match with reality, error signals arrive at Purkinje cells via the olivary climbing fibers, whereas granule cells and Purkinje cells encode signals of expectation. Strong neural representations of expectation correlate with faster swim responses and vice versa. In sum, our results show evidence for predictive processing in nonmammalian vertebrates with the involvement of cerebellum, an evolutionarily conserved brain structure.

Association between urban upbringing and functional brain connectivity in schizophrenia

Background

Environmental factors considerably influence the development of the human cortex during the perinatal period, early childhood, and adolescence. Urban upbringing in the first 15 years of life is a known risk factor for schizophrenia (SCZ). Though the risk of urban birth and upbringing is well-examined from an epidemiological perspective, the biological mechanisms underlying urban upbringing remain unknown. The effect of urban birth and upbringing on functional brain connectivity in SCZ patients is not yet examined.

Methods

This is a secondary data analysis of three studies that included 87 patients with SCZ and 70 healthy volunteers (HV) aged 18 to 50 years. We calculated the developmental urbanicity index using a validated method in earlier studies. Following standard pre-processing of resting functional magnetic resonance imaging (fMRI) scans, seed-return on investment (ROI) functional connectivity analysis was performed.

Results

The results showed a significant association between urban birth and upbringing on functional connectivity in SCZ patients and HV (P < 0.05). In SCZ patients, connections from the right caudate, anterior cingulate cortex, left and right intracalcarine cortices, left and right lingual gyri, left posterior parahippocampal cortex to the cerebellum, fusiform gyri, lateral occipital cortex, and amygdala were significantly associated with the urbanicity index (P < 0.05).

Conclusions

These study findings suggest a significant association between urban birth and upbringing on functional brain connectivity in regions involved in reward processing and social cognition in SCZ. Assessment of social cognition could have implications in developing an in-depth understanding of this impairment in persons with SCZ.

Cerebellar contribution to autism-relevant behaviors in fragile X syndrome models

Cerebellar dysfunction has been linked to autism spectrum disorders (ASDs). Although cerebellar pathology has been observed in individuals with fragile X syndrome (FXS) and in mouse models of the disorder, a cerebellar functional contribution to ASD-relevant behaviors in FXS has yet to be fully characterized. In this study, we demonstrate a critical cerebellar role for Fmr1 (fragile X messenger ribonucleoprotein 1) in ASD-relevant behaviors. First, we identify reduced social behaviors, sensory hypersensitivity, and cerebellar dysfunction, with loss of cerebellar Fmr1. We then demonstrate that cerebellar-specific expression of Fmr1 is sufficient to impact social, sensory, cerebellar dysfunction, and cerebro-cortical hyperexcitability phenotypes observed in global Fmr1 mutants. Moreover, we demonstrate that targeting the ASD-implicated cerebellar region Crus1 ameliorates behaviors in both cerebellar-specific and global Fmr1 mutants. Together, these results demonstrate a critical role for the cerebellar contribution to FXS-related behaviors, with implications for future therapeutic strategies.

Cerebellar Degeneration Impairs Strategy Discovery but Not Strategy Recall

The cerebellum is recognized to play a critical role in the automatic and implicit process by which movement errors are used to keep the sensorimotor system precisely calibrated. However, its role in other learning processes frequently engaged during sensorimotor adaptation tasks remains unclear. In the present study, we tested the performance of individuals with cerebellar degeneration on a variant of a visuomotor adaptation task in which learning requires the use of strategic re-aiming, a process that can nullify movement errors in a rapid and volitional manner. Our design allowed us to assess two components of this learning process, the discovery of an appropriate strategy and the recall of a learned strategy. Participants were exposed to a 60° visuomotor rotation twice, with the initial exposure block assessing strategy discovery and the re-exposure block assessing strategy recall. Compared to age-matched controls, individuals with cerebellar degeneration were slower to derive an appropriate aiming strategy in the initial Discovery block but exhibited similar recall of the aiming strategy during the Recall block. This dissociation underscores the multi-faceted contributions of the cerebellum to sensorimotor learning, highlighting one way in which this subcortical structure facilitates volitional action selection.

Motor adaptation does not differ when a perturbation is introduced abruptly or gradually

People continuously adapt their movements to ever-changing circumstances, and particularly in skills training and rehabilitation, it is crucial that we understand how to optimize implicit adaptation in order for these processes to require as little conscious effort as possible. Although it is generally assumed that the way to do this is by introducing perturbations gradually, the literature is ambivalent on the effectiveness of this approach. Here, we tested whether there are differences in motor performance when adapting to an abrupt compared to a ramped visuomotor rotation. Using a within-subjects design, we tested this question under 3 different rotation sizes: 30-degrees, 45-degrees, and 60-degrees, as well as in 3 different populations: younger adults, older adults, and patients with mild cerebellar ataxia. We find no significant differences in either the behavioural outcomes, or model fits, between abrupt and gradual learning across any of the different conditions. Neither age, nor cerebellar ataxia had any significant effect on error-sensitivity either. These findings together indicate that error-sensitivity is not modulated by introducing a perturbation abruptly compared to gradually, and is also unaffected by age or mild cerebellar ataxia.

Hands off, brain off? A meta-analysis of neuroimaging data during active and passive driving

BACKGROUND

Car driving is more and more automated, to such an extent that driving without active steering control is becoming a reality. Although active driving requires the use of visual information to guide actions (i.e., steering the vehicle), passive driving only requires looking at the driving scene without any need to act (i.e., the human is passively driven).

MATERIALS & METHODS

After a careful search of the scientific literature, 11 different studies, providing 17 contrasts, were used to run a comprehensive meta-analysis contrasting active driving with passive driving.

RESULTS

Two brain regions were recruited more consistently for active driving compared to passive driving, the left precentral gyrus (BA3 and BA4) and the left postcentral gyrus (BA4 and BA3/40), whereas a set of brain regions was recruited more consistently in passive driving compared to active driving: the left middle frontal gyrus (BA6), the right anterior lobe and the left posterior lobe of the cerebellum, the right sub-lobar thalamus, the right anterior prefrontal cortex (BA10), the right inferior occipital gyrus (BA17/18/19), the right inferior temporal gyrus (BA37), and the left cuneus (BA17).

DISCUSSION

From a theoretical perspective, these findings support the idea that the output requirement of the visual scanning process engaged for the same activity can trigger different cerebral pathways, associated with different cognitive processes. A dorsal stream dominance was found during active driving, whereas a ventral stream dominance was obtained during passive driving. From a practical perspective, and contrary to the dominant position in the Human Factors community, our findings support the idea that a transition from passive to active driving would remain challenging as passive and active driving engage distinct neural networks.

Heterogeneous encoding of temporal stimuli in the cerebellar cortex

Local feedforward and recurrent connectivity are rife in the frontal areas of the cerebral cortex, which gives rise to rich heterogeneous dynamics observed in such areas. Recently, similar local connectivity motifs have been discovered among Purkinje and molecular layer interneurons of the cerebellar cortex, however, task-related activity in these neurons has often been associated with relatively simple facilitation and suppression dynamics. Here, we show that the rodent cerebellar cortex supports heterogeneity in task-related neuronal activity at a scale similar to the cerebral cortex. We provide a computational model that inculcates recent anatomical insights into local microcircuit motifs to show the putative basis for such heterogeneity. We also use cell-type specific chronic viral lesions to establish the involvement of cerebellar lobules in associative learning behaviors. Functional heterogeneity in neuronal profiles may not merely be the remit of the associative cerebral cortex, similar principles may be at play in subcortical areas, even those with seemingly crystalline and homogenous cytoarchitectures like the cerebellum.

Cognitive-Affective Functions of the Cerebellum

The cerebellum, traditionally associated with motor coordination and balance, also plays a crucial role in various aspects of higher-order function and dysfunction. Emerging research has shed light on the cerebellum's broader contributions to cognitive, emotional, and reward processes. The cerebellum's influence on autonomic function further highlights its significance in regulating motivational and emotional states. Perturbations in cerebellar development and function have been implicated in various neurodevelopmental disorders, including autism spectrum disorder and attention deficit hyperactivity disorder. An increasing appreciation for neuropsychiatric symptoms that arise from cerebellar dysfunction underscores the importance of elucidating the circuit mechanisms that underlie complex interactions between the cerebellum and other brain regions for a comprehensive understanding of complex behavior. By briefly discussing new advances in mapping cerebellar function in affective, cognitive, autonomic, and social processing and reviewing the role of the cerebellum in neuropathology beyond the motor domain, this Mini-Symposium review aims to provide a broad perspective of cerebellar intersections with the limbic brain in health and disease.

An Integrated Neurorobotics Model of the Cerebellar-Basal Ganglia Circuitry

This work presents a neurorobotics model of the brain that integrates the cerebellum and the basal ganglia regions to coordinate movements in a humanoid robot. This cerebellar-basal ganglia circuitry is well known for its relevance to the motor control used by most mammals. Other computational models have been designed for similar applications in the robotics field. However, most of them completely ignore the interplay between neurons from the basal ganglia and cerebellum. Recently, neuroscientists indicated that neurons from both regions communicate not only at the level of the cerebral cortex but also at the subcortical level. In this work, we built an integrated neurorobotics model to assess the capacity of the network to predict and adjust the motion of the hands of a robot in real time. Our model was capable of performing different movements in a humanoid robot by respecting the sensorimotor loop of the robot and the biophysical features of the neuronal circuitry. The experiments were executed in simulation and the real world. We believe that our proposed neurorobotics model can be an important tool for new studies on the brain and a reference toward new robot motor controllers.

The role of the cerebellum in internet gaming disorder-A systematic review

Recent studies increasingly highlight involvement of the cerebellum in drug craving and addiction. However, its exact role, that is, whether the cerebellum is a critical component of a brain network underlying addictive behaviour, or whether it rather is a facilitator or mediator, is still unclear. Findings concerning the newly recognized internet gaming disorder (IGD) suggest that changes in cerebellar connectivity and functioning are associated with behavioural/non-substance addiction. Here, we systematically review the literature on IGD and cerebellar involvement following the PRISMA guidelines. A total of 13 neuroimaging studies met the inclusion criteria. Studies utilized a broad range of diagnostic instruments and resulting cut-off criteria, rendering it difficult to compare findings. Results on altered cerebro-cerebellar connectivity in patients with IGD are mixed; most studies report altered or increased functional connectivity. Moreover, decreased cerebellar grey matter volume is reported. Studies have further indicated that differential activation patterns in the cerebellum may enable discrimination between healthy subjects and subjects with IGD, even allowing for prediction of treatment outcomes. Given the strong connectivity between the cerebellum and cerebral regions, the cerebellum may act as an intermediary between regions involved in craving and addiction and consequently affect symptoms of IGD. Results suggest differential involvement of the cerebellar lobes, emphasizing a need for high-resolution parcellation of the cerebellum in future studies. However, the studies included in the present review have small sample sizes and include mostly male participants. Thus, results may have limited generalizability yet highlight a crucial role of the cerebellum in IGD that needs further investigation.

Cerebellar Prediction and Feeding Behaviour

Given the importance of the cerebellum in controlling movements, it might be expected that its main role in eating would be the control of motor elements such as chewing and swallowing. Whilst such functions are clearly important, there is more to eating than these actions, and more to the cerebellum than motor control. This review will present evidence that the cerebellum contributes to homeostatic, motor, rewarding and affective aspects of food consumption.Prediction and feedback underlie many elements of eating, as food consumption is influenced by expectation. For example, circadian clocks cause hunger in anticipation of a meal, and food consumption causes feedback signals which induce satiety. Similarly, the sight and smell of food generate an expectation of what that food will taste like, and its actual taste will generate an internal reward value which will be compared to that expectation. Cerebellar learning is widely thought to involve feed-forward predictions to compare expected outcomes to sensory feedback. We therefore propose that the overarching role of the cerebellum in eating is to respond to prediction errors arising across the homeostatic, motor, cognitive, and affective domains.

Organization of Purkinje cell development by neuronal MEGF11 in cerebellar granule cells

As cerebellar granule cells (GCs) coordinate the formation of regular cerebellar networks during postnatal development, molecules in GCs are expected to be involved. Here, we test the effects of the knockdown (KD) of multiple epidermal growth factor-like domains protein 11 (MEGF11), which is a homolog of proteins mediating astrocytic phagocytosis but is substantially increased at the later developmental stages of GCs on cerebellar development. MEGF11-KD in GCs of developing mice results in abnormal cerebellar structures, including extensively ectopic Purkinje cell (PC) somas, and in impaired motor functions. MEGF11-KD also causes abnormally asynchronous synaptic release from GC axons, parallel fibers, before the appearance of abnormal cerebellar structures. Interestingly, blockade of this abnormal synaptic release restores most of the cerebellar structures. Thus, apart from phagocytic functions of its related homologs in astrocytes, MEGF11 in GCs promotes proper PC development and cerebellar network formation by regulating immature synaptic transmission.

Cerebellar climbing fibers multiplex movement and reward signals during a voluntary movement task in mice

Cerebellar climbing fibers convey sensorimotor information and their errors, which are used for motor control and learning. Furthermore, they represent reward-related information. Despite such functional diversity of climbing fiber signals, it is still unclear whether each climbing fiber conveys the information of single or multiple modalities and how the climbing fibers conveying different information are distributed over the cerebellar cortex. Here we perform two-photon calcium imaging from cerebellar Purkinje cells in mice engaged in a voluntary forelimb lever-pull task and demonstrate that climbing fiber responses in 68% of Purkinje cells can be explained by the combination of multiple behavioral variables such as lever movement, licking, and reward delivery. Neighboring Purkinje cells exhibit similar climbing fiber response properties, form functional clusters, and share noise fluctuations of responses. Taken together, individual climbing fibers convey behavioral information on multiplex variables and are spatially organized into the functional modules of the cerebellar cortex.

Increased Cerebellar Gray Matter Volume in Athletes: A Voxel-Wise Coordinate-Based Meta-Analysis

Purpose: The purpose of this systematic review and meta-analysis study was to investigate distinct brain structural characteristics in athletes as compared with those in non-athletes by quantifying regional gray matter (GM) volume changes using voxel-based morphometry analysis based on a whole-brain approach. Methods: The systematic literature search was conducted from November 1, 2020 to October 18, 2021 via the two search engines including the PubMed and Web of Science. We included 13 studies that reported GM volume data in 229 athletes as compared 219 non-athletes based on the whole-brain analysis with specific three-dimensional coordinates in a standard stereotactic space. Thus, we performed a coordinate-based meta-analysis using the seed-based d mapping via permutation of subject images methods. Result: The coordinate-based meta-analysis reported that the athletes significantly reveal greater regional GM volume across right cerebellar lobules IV-V and Brodmann area 37 regions than those in the non-athletes with minimal levels of heterogeneity and publication bias between the included studies. The subgroup analyses show that greater GM volume for athletes in closed-skill sports appeared across the right cerebellar hemispheric lobules VIII and the right cingulum than those for non-athletes. Conclusion: These cumulative findings from multiple brain imaging studies suggest potential brain plasticity evidence in the athletes who experienced extensive motor training.

Study protocol: effects of treatment expectation toward repetitive transcranial magnetic stimulation (rTMS) in major depressive disorder-a randomized controlled clinical trial

BACKGROUND

Patients' expectations toward any given treatment are highly important for the effectiveness of such treatment, as has been demonstrated for several disorders. In particular, in major depressive disorder (MDD), one of the most frequent and most serious mental disorders with severe consequences for the affected, the augmentation of available treatment options could mean a ground-breaking success. Repetitive transcranial magnetic stimulation (rTMS), a new, non-invasive, and well-tolerated intervention with proven effects in the treatment of MDD, appears particularly suitable in this context as it is assumed to exert its effect via structures implicated in networks relevant for both expectation and depression.

METHODS

All patients will receive rTMS according to its approval. Half of the patients will be randomized to a psychological intervention, which is a comprehensive medical consultation aiming to improve positive treatment expectations; the control group will receive a conventional informed consent discussion (in the sense of a treatment-as-usual condition). As outcome parameters, instruments for both self-assessment and external assessment of depression symptoms will be applied. Furthermore, psycho-immunological parameters such as inflammation markers and the cortisol awakening response in saliva will be investigated. Resting-state functional magnetic resonance imaging (rs fMRI) will be performed to analyze functional connectivity, including the cerebellum, and to identify neuronal predictors of expectation effects. In addition, possible cerebellar involvement will be assessed based on a cerebellar-dependent motor learning paradigm (i.e., eyeblink conditioning).

DISCUSSION

In this study, the effects of treatment expectations towards rTMS are investigated in patients with MDD. The aim of this study is to identify the mechanisms underlying the expectation effects and, beyond that, to expand the potential of non-invasive and well-tolerated treatments of MDD.

TRIAL REGISTRATION

German Registry of Clinical Studies (DRKS DRKS00028017. Registered on 2022/03/07. URL: https://www.drks.de/drks_web/ .

Excitatory nucleo-olivary pathway shapes cerebellar outputs for motor control

The brain generates predictive motor commands to control the spatiotemporal precision of high-velocity movements. Yet, how the brain organizes automated internal feedback to coordinate the kinematics of such fast movements is unclear. Here we unveil a unique nucleo-olivary loop in the cerebellum and its involvement in coordinating high-velocity movements. Activating the excitatory nucleo-olivary pathway induces well-timed internal feedback complex spike signals in Purkinje cells to shape cerebellar outputs. Anatomical tracing reveals extensive axonal collaterals from the excitatory nucleo-olivary neurons to downstream motor regions, supporting integration of motor output and internal feedback signals within the cerebellum. This pathway directly drives saccades and head movements with a converging direction, while curtailing their amplitude and velocity via the powerful internal feedback mechanism. Our finding challenges the long-standing dogma that the cerebellum inhibits the inferior olivary pathway and provides a new circuit mechanism for the cerebellar control of high-velocity movements.

Cerebellar contribution to the regulation of defensive states

Despite fine tuning voluntary movement as the most prominently studied function of the cerebellum, early human studies suggested cerebellar involvement emotion regulation. Since, the cerebellum has been associated with various mood and anxiety-related conditions. Research in animals provided evidence for cerebellar contributions to fear memory formation and extinction. Fear and anxiety can broadly be referred to as defensive states triggered by threat and characterized by multimodal adaptations such as behavioral and cardiac responses integrated into an intricately orchestrated defense reaction. This is mediated by an evolutionary conserved, highly interconnected network of defense-related structures with functional connections to the cerebellum. Projections from the deep cerebellar nucleus interpositus to the central amygdala interfere with retention of fear memory. Several studies uncovered tight functional connections between cerebellar deep nuclei and pyramis and the midbrain periaqueductal grey. Specifically, the fastigial nucleus sends direct projections to the ventrolateral PAG to mediate fear-evoked innate and learned freezing behavior. The cerebellum also regulates cardiovascular responses such as blood pressure and heart rate-effects dependent on connections with medullary cardiac regulatory structures. Because of the integrated, multimodal nature of defensive states, their adaptive regulation has to be highly dynamic to enable responding to a moving threatening stimulus. In this, predicting threat occurrence are crucial functions of calculating adequate responses. Based on its role in prediction error generation, its connectivity to limbic regions, and previous results on a role in fear learning, this review presents the cerebellum as a regulator of integrated cardio-behavioral defensive states.

Purkinje cell dopaminergic inputs to astrocytes regulate cerebellar-dependent behavior

Dopamine has a significant role in motor and cognitive function. The dopaminergic pathways originating from the midbrain have received the most attention; however, the relevance of the cerebellar dopaminergic system is largely undiscovered. Here, we show that the major cerebellar astrocyte type Bergmann glial cells express D1 receptors. Dopamine can be synthesized in Purkinje cells by cytochrome P450 and released in an activity-dependent fashion. We demonstrate that activation of D1 receptors induces membrane depolarization and Ca2+ release from the internal store. These astrocytic activities in turn modify Purkinje cell output by altering its excitatory and inhibitory synaptic input. Lastly, we show that conditional knockout of D1 receptors in Bergmann glial cells results in decreased locomotor activity and impaired social activity. These results contribute to the understanding of the molecular, cellular, and circuit mechanisms underlying dopamine function in the cerebellum, revealing a critical role for the cerebellar dopaminergic system in motor and social behavior.

Toward a cerebello-thalamo-cortical computational model of spinocerebellar ataxia

Computational neural network modelling is an emerging approach for optimization of drug treatment of neurological disorders and fine-tuning of rehabilitation strategies. In the current study, we constructed a cerebello-thalamo-cortical computational neural network model to simulate a mouse model of cerebellar ataxia (pcd^5J mice) by manipulating cerebellar bursts through reduction of GABAergic inhibitory input. Cerebellar output neurons were projected to the thalamus and bidirectionally connected with the cortical network. Our results showed that reduction of inhibitory input in the cerebellum orchestrated the cortical local field potential (LFP) dynamics to generate specific motor outputs of oscillations of the theta, alpha, and beta bands in the computational model as well as in mouse motor cortical neurons. The therapeutic potential of deep brain stimulation (DBS) was tested in the computational model by increasing the sensory input to restore cortical output. Ataxia mice showed normalization of the motor cortex LFP after cerebellum DBS. We provide a novel approach to computational modelling to investigate the effect of DBS by mimicking cerebellar ataxia involving degeneration of Purkinje cells. Simulated neural activity coincides with findings from neural recordings of ataxia mice. Our computational model could thus represent cerebellar pathologies and provide insight into how to improve disease symptoms by restoring neuronal electrophysiological properties using DBS.

An emergent temporal basis set robustly supports cerebellar time-series learning

The cerebellum is considered a "learning machine" essential for time interval estimation underlying motor coordination and other behaviors. Theoretical work has proposed that the cerebellum's input recipient structure, the granule cell layer (GCL), performs pattern separation of inputs that facilitates learning in Purkinje cells (P-cells). However, the relationship between input reformatting and learning has remained debated, with roles emphasized for pattern separation features from sparsification to decorrelation. We took a novel approach by training a minimalist model of the cerebellar cortex to learn complex time-series data from time-varying inputs, typical during movements. The model robustly produced temporal basis sets from these inputs, and the resultant GCL output supported better learning of temporally complex target functions than mossy fibers alone. Learning was optimized at intermediate threshold levels, supporting relatively dense granule cell activity, yet the key statistical features in GCL population activity that drove learning differed from those seen previously for classification tasks. These findings advance testable hypotheses for mechanisms of temporal basis set formation and predict that moderately dense population activity optimizes learning.NEW & NOTEWORTHY During movement, mossy fiber inputs to the cerebellum relay time-varying information with strong intrinsic relationships to ongoing movement. Are such mossy fibers signals sufficient to support Purkinje signals and learning? In a model, we show how the GCL greatly improves Purkinje learning of complex, temporally dynamic signals relative to mossy fibers alone. Learning-optimized GCL population activity was moderately dense, which retained intrinsic input variance while also performing pattern separation.

Consider the pons: bridging the gap on sensory prediction abnormalities in schizophrenia

A shared mechanism across species heralds the arrival of self-generated sensations, helping the brain to anticipate, and therefore distinguish, self-generated from externally generated sensations. In mammals, this sensory prediction mechanism is supported by communication within a cortico-ponto-cerebellar-thalamo-cortical loop. Schizophrenia is associated with impaired sensory prediction as well as abnormal structural and functional connections between nodes in this circuit. Despite the pons' principal role in relaying and processing sensory information passed from the cortex to cerebellum, few studies have examined pons connectivity in schizophrenia. Here, we first briefly describe how the pons contributes to sensory prediction. We then summarize schizophrenia-related abnormalities in the cortico-ponto-cerebellar-thalamo-cortical loop, emphasizing the dearth of research on the pons relative to thalamic and cerebellar connections. We conclude with recommendations for advancing our understanding of how the pons relates to sensory prediction failures in schizophrenia.