The Cerebellum: Adaptive Prediction for Movement and Cognition

Coincidence detection between apical and basal dendrites drives STDP in cerebellar Golgi cells

Cerebellar Golgi cells (GoCs), segregate parallel fiber (pf), and mossy fiber (mf) inputs on apical and basal dendrites. Computational modeling predicted that this anatomical arrangement, coupled with a specific ionic channel localization, could be instrumental to drive STDP at mf-GoC synapses. Here, we test this hypothesis with GoC patch-clamp recordings in acute mouse cerebellar slices. Repeated mf-pf pairing on the theta-band within a ± 50 ms time window induces anti-symmetric Hebbian-STDP, with spike-timing long-term potentiation or depression (st-LTP or st-LTD) occurring when action potentials (APs) elicited by pf stimulation follow or precede the activation of mf synapses, respectively. Mf-GoC STDP induction requires AP backpropagation from apical to basal dendrites, NMDA receptor activation at mf-GoC synapses, and intracellular calcium changes. Importantly, STDP is inverted by inhibitory control. Thus, experimental evidence confirms and extends model predictions suggesting that GoC STDP can bind molecular layer to granular layer activity, regulating cerebellar computation and learning.

Learning performance of cerebellar circuit depends on diversity and chaoticity of spiking patterns in granule cells: A simulation study

The cerebellum, composed of numerous neurons, plays various roles in motor control. Although it is functionally subdivided, the cerebellar cortex has a canonical structural pattern in neuronal circuits including a recurrent circuit pattern formed by granule cells (GrCs) and Golgi cells (GoCs). The canonical circuital pattern suggests the existence of a fundamental computational algorithm, although it remains unclear. Modeling and simulation studies are useful for verifying hypotheses about complex systems. Previous models have shown that they could reproduced the neurophysiological data of the cerebellum; however, the dynamic characteristics of the system have not been fully elucidated. Understanding the dynamic characteristics of the circuital pattern is necessary to reveal the computational algorithm embedded in the circuit. This study conducted numerical simulations using the cerebellar circuit model to investigate dynamic characteristics in a simplified model of cerebellar microcircuits. First, the diversity and chaoticity of the patterns of spike trains generated from GrCs depending on the synaptic strength between the GrCs and GoCs were investigated based on cluster analysis and the Lyapunov exponent, respectively. Then the effect of synaptic strength on learning tasks was investigated based on the convergence properties of the output signals from Purkinje cells. The synaptic strength for high learning performance was almost consistent with that for the high diversity of the generated patterns and the edge of chaos. These results suggest that the learning performance of the cerebellar circuit depends on the diversity and the chaoticity of the spiking patterns from the GrC-GoC recurrent circuit.

The cerebellum in frontotemporal dementia: From neglected bystander to potential neuromodulatory target. A narrative review

BACKGROUND

Though cortical changes in frontotemporal dementia (FTD) are well-documented, the cerebellum's role, closely linked to these areas, remains unclear.

OBJECTIVES

To provide evidence on cerebellar involvement in FTD across clinical, genetic, imaging, neuropathological, and neurophysiological perspectives. Additionally, we sought evidence supporting the application of cerebellar non-invasive brain stimulation (NIBS) in FTD for both diagnostic and therapeutic purposes.

METHODS

We performed a literature review using MEDLINE (via PubMed), Scopus, and Web of Science databases.

RESULTS

We emphasized the involvement of specific cerebellar regions which differentiate each FTD subtypes and may account for some of the characteristic symptoms. Furthermore, we highlighted peculiarities in FTD genetic alterations. Finally, we outlined neurophysiological evidence supporting a role for the cerebellum in FTD pathogenesis.

CONCLUSION

The cerebellum is critically involved in the FTD spectrum. Moreover, it can be speculated that cerebellar modulation, as already shown in other neurodegenerative disorders, could restore the interneuronal intracortical circuits typically impaired in FTD patients, providing clinical improvements and fundamental outcome measures in clinical trials.

Motor markers of congenital cerebellar hypoplasia

The Reach-to-Grasp (RtG) movement is a fundamental feature of human competence and a widely adopted model for the study of functional movements in both healthy and disease-affected individuals. In particular, 3-D kinematic analysis of RtG allows the study of fine hand movements and submovements, described as secondary fluctuations of the main movement. The aim of this study was to use a RtG movement to test upper limb motor performance in a patient with ataxic syndrome due to cerebellar hypoplasia. 3-D kinematical recording and MRI-based structural measures were combined to provide a comprehensive characterization of the movement and its neural underpinnings at the baseline and after a 2 years follow-up. In terms of kinematics, a dissociation between reaching and grasping performance was observed over time: while grasping appeared to be characterized by an improvement at the 2 years follow-up, reaching showed a significant increase of jerk submovements, suggesting a loss of functionality in feedback mechanisms allowing for smoothness of the movement. At the neural level, an increase of gray matter volume of the anterior right cerebellar hemisphere, alongside with an increased structural connectivity within the sensorimotor network were observed at the 2 years follow up, presumably mirroring the improvement observed for the grasping component. These results highlight the potential of the jerk submovements as a motor biomarker in contexts where feedback mechanisms may be compromised, such as in the case of cerebellar dysfunctions, contributing to the development of new methods for the motor assessment of patients in clinical settings.

Predictive coding and attention in developmental cognitive neuroscience and perspectives for neurodevelopmental disorders

Sensory prediction and repetition suppression are closely related cognitive mechanisms that allow the brain to form predictions about the environment, and guide perception in synergy with attention. Predictive coding is a theory of the fundamental role of predictive mechanisms in brain functions. Authors have proposed a central role of predictive impairments in autism and possibly other neurodevelopmental disorders. However, little is known about predictive mechanisms in typical development, and how they co-develop with attention. Here we review experimental support for predictive coding and its links with attention in healthy adults' brains, the first experimental works performed in typically developing children and infants, and theoretical accounts of neurodevelopmental disorders using a predictive coding framework. We propose future directions for predictive coding research in development. Finally, we describe the first predictive coding experiments in neonates and provide research perspectives for using this framework in searching for early markers of atypical neurodevelopment.

Beyond motor learning: Insights from infant magnetic resonance imaging on the critical role of the cerebellum in behavioral development

Although the cerebellum is now recognized for its crucial role in non-motor functions such as language, perceptual processes, social communication, and executive function in adults, it is often overlooked in studies of non-motor behavioral development in infancy. Recent magnetic resonance imaging (MRI) research increasingly shows the cerebellum is key to understanding the emergence of complex human behaviors and neurodevelopmental conditions. This review summarizes studies from diverse MRI modalities that link early cerebellar development from birth to age two with emerging non-motor behaviors and psychiatric symptomatology. Our focus centered on both term and preterm infants, excluding studies of perinatal injury and cerebellar pathology. We conclude that the cerebellum is implicated in many non-motor behaviors and implicit learning mechanisms in infancy. The field's current limitations include inconsistencies in study design, a paucity of gold-standard infant neuroimaging tools, and treatment of the cerebellum as a uniform structure. Moving forward, the cerebellum should be considered a structure of greater interest to the developmental neuroimaging community. Studies should test developmental hypotheses about the behavioral roles of specific cerebro-cerebellar circuits, and theoretical frameworks such as Olson's "model switch" hypothesis of cerebellar learning. Large-scale, longitudinal, well-powered neuroimaging studies of typical and preterm development will be key.

Errors of attention adaptively warp spatial cognition

Adaptation is the process by which we adjust internal models of the body, world and mind in response to sensory feedback. Although adaptation is studied extensively in the context of motor control, there is limited evidence that cognitive functions such as working memory are subject to the same error-driven adaptive control mechanism. To examine the possibility that internal spatial representations undergo adaptation, we had participants perform a task that interleaved a perceptual discrimination task and a spatial working memory task. Perceptual discrimination trials (85% of trials) presented an initial peripheral cue to exogenously capture attention, immediately followed by a displaced target stimulus. This sequence of events served to repeatedly induce a covert attentional allocation error. Interleaved spatial working memory trials (15% of trials) presented a stimulus at a pseudorandom peripheral location followed by a delay interval. On half of the working memory trials, the stimulus was surreptitiously presented at the same location as the initial attentional cue. We found that as attentional errors accumulated over the course of the experiment, participants' spatial recall shifted to counteract the attentional error. The magnitude of this shift was proportional to the number of induced errors. Recall performance recovered rapidly following the offset of error trials. Multiple control experiments ruled out alternative explanations for these results, such as oculomotor confounds and attentional biases unrelated to error. These findings indicate that the computational mechanisms governing the adaptation of motor commands appear to similarly serve to adjust and calibrate spatial cognition.

Ignoring the cerebellum is hindering progress in neuroscience

Traditionally considered a motor structure, the cerebellum has been shown to play a key role in several cognitive functions. However, for decades, the cerebellum has been largely overlooked and even deliberately excluded from 'whole-brain' neuroimaging studies. Here, we propose that the continued exclusion of the cerebellum has limited our understanding of whole-brain function. We describe reasons - both warranted and unwarranted - behind its historical exclusion from the neuroimaging literature, review literature describing the importance of the cerebellum and its unique role in brain function, and outline the potential unintended negative consequences of exclusion of the cerebellum for our comprehensive understanding of brain function and clinical disorders.

The cerebellum contributes to prediction error coding in reinforcement learning in humans

Recent rodent data suggest that the cerebellum - a region typically associated with processing sensory prediction errors (PEs) - also processes PEs in reinforcement learning (RL-PEs; i.e., learning from action outcomes). We tested whether cerebellar output is necessary for RL-PE processing in regions more traditionally associated with action-outcome processing, such as striatum and anterior cingulate cortex. The feedback-related negativity (FRN) was measured as a proxy of cerebral RL-PE processing in a probabilistic feedback learning task using electroencephalography. Two complementary experiments were performed in humans. First, patients with chronic cerebellar stroke (20 male, 6 female) and matched healthy controls (19 male, 7 female) were tested. Second, single-pulse cerebellar transcranial magnetic stimulation (TMS) was applied in healthy participants (7 male, 17 female), thus implementing a virtual lesion approach. Consistent with previous studies, learning of action-outcome associations was intact with only minor changes in behavioural flexibility. Importantly, no significant RL-PE processing was observed in the FRN in patients with cerebellar stroke, and in participants receiving cerebellar TMS. Findings in both experiments show that RL-PE processing in the forebrain depends on cerebellar output in humans, complementing and extending previous findings in rodents.Significance statement While processing of prediction errors in reinforcement learning (RL-PEs) is usually attributed to midbrain and forebrain, recent rodent studies have recorded RL-PE signals in the cerebellum. It is not yet clear whether these cerebellar RL-PE signals contribute to RL-PE processing in the forebrain/midbrain. In the current study, we could show that forebrain RL-PE coding is blunted when the cerebellum is affected across two complementary lesion models (patients with cerebellar stroke, cerebellar TMS). Our results support direct involvement of the cerebellum in RL-PE processing. We can further show that the cerebellum is necessary for RL-PE coding in the forebrain.

The role of cerebellar-cortical connectivity in modulating attentional abilities: insight from football athletes

Neuroplasticity, a phenomenon present throughout the lifespan, is thought to be influenced by physical training. However, the relationship between neuroplastic differences and attentional abilities remains unclear. This study explored the differences in brain function and attentional abilities between professional football athletes and novices, and further investigated the relationship between the two. To address this question, we included 49 football athletes and 63 novices in our study, collecting data on resting-state functional connectivity and Attention Network Test (ANT). Behavioral results from the ANT indicated that football experts had superior orienting attention but weaker alerting functions compared to novices, with no difference in executive control attention. fMRI results revealed that football experts exhibited higher fractional Amplitude of Low-Frequency Fluctuations (fALFF) values in the bilateral anterior cerebellar lobes, bilateral insula, and left superior temporal gyrus. Functional connectivity analysis showed increased connectivity between the left anterior cerebellar lobe and various cortical regions, including the right supramarginal gyrus, left precuneus, left superior frontal gyrus, bilateral posterior cerebellar lobes, and bilateral precentral gyri in experts compared to novices. More importantly, in the expert group but not in novice group, functional connectivity differences significantly predicted attentional orienting scores. Graph theoretical analysis showed that experts exhibited higher betweenness centrality and node efficiency in the right cerebellar lobule III (Cerebelum_3_R) node. Our findings demonstrate that long-term professional football training may significantly affect neuroplasticity and attentional functions. Importantly, our analysis reveals a substantive connection between these two aspects, suggesting that the integration of neuroplastic and attentional changes is likely mediated by cerebellar-cortical connectivity.

Insights on the Shared Genetic Landscape of Neurodevelopmental and Movement Disorders

PURPOSE OF REVIEW

Large-scale studies using hypothesis-free exome sequencing have revealed the strong heritability of neurodevelopmental disorders (NDDs) and their molecular overlap with later-onset, progressive, movement disorders phenotypes. In this review, we focus on the shared genetic landscape of NDDs and movement disorders.

RECENT FINDINGS

Cumulative research has shown that up to 30% of cases labelled as "cerebral palsy" have a monogenic etiology. Causal pathogenic variants are particularly enriched in genes previously associated with adult-onset progressive movement disorders, such as spastic paraplegias, dystonias, and cerebellar ataxias. Biological pathways that have emerged as common culprits are transcriptional regulation, neuritogenesis, and synaptic function. Defects in the same genes can cause neurological dysfunction both during early development and later in life. We highlight the implications of the increasing number of NDD gene etiologies for genetic testing in movement disorders. Finally, we discuss gaps and opportunities in the translation of this knowledge to the bedside.

Cerebellar output shapes cortical preparatory activity during motor adaptation

The cerebellum plays a key role in motor adaptation by driving trial-to-trial recalibration of movements based on previous errors. In primates, cortical correlates of adaptation are encoded already in the pre-movement motor plan, but these early cortical signals could be driven by a cerebellar-to-cortical information flow or evolve independently through intracortical mechanisms. To address this question, we trained female macaque monkeys to reach against a viscous force field (FF) while blocking cerebellar outflow. The cerebellar block led to impaired FF adaptation and a compensatory, re-aiming-like shift in motor cortical preparatory activity. In the null-field conditions, the cerebellar block altered neural preparatory activity by increasing task-representation dimensionality and impeding generalization. A computational model indicated that low-dimensional (cerebellar-like) feedback is sufficient to replicate these findings. We conclude that cerebellar signals carry task structure information that constrains the dimensionality of the cortical preparatory manifold and promotes generalization. In the absence of these signals, cortical mechanisms are harnessed to partially restore adaptation.

Crus control: effective cerebello-cerebral connectivity during social action prediction using dynamic causal modelling

This dynamic causal modeling (DCM) analysis, comprising 99 participants from 4 studies, investigated effective neuronal connectivity during social action sequence prediction. The analysis focused on mentalizing areas within the cerebellum, specifically the bilateral Crus 1, Crus 2, and lobule IX, as well as cerebral mentalizing areas within the precuneus, temporo-parietal junction (TPJ), and dorsal medial prefrontal cortex (dmPFC). Consistent with previous research, we found robust bidirectional closed loop connections between the posterior cerebellar Crus and cerebral mentalizing areas. We also found previously unexplored unidirectional connections originating from cerebellar lobule IX to the dmPFC and left TPJ and from the right TPJ to lobule IX. Furthermore, we uncovered many bidirectional closed loops within the cerebellum between the left and right Crus 1, and between Crus 1 and Crus 2, and for the first time, between the bilateral Crus 2 and lobule IX. Our findings illuminate the distinct role of cerebellar Crus and lobule IX, and cerebral mentalizing areas in predicting social action sequences.

Effect of Ethanol on Brain Electrical Tissue Conductivity in Social Drinkers

BACKGROUND

How the biophysics of electrical conductivity measures relate to brain activity is poorly understood. The sedative, ethanol, reduces metabolic activity but its impact on brain electrical conductivity is unknown.

PURPOSE

To investigate whether ethanol reduces brain electrical tissue conductivity.

STUDY TYPE

Prospective.

SUBJECTS

Fifty-two healthy volunteers (aged 18-37 years, 22 females, 30 males).

FIELD STRENGTH/SEQUENCE

3 T, T1-weighted, multi-shot, turbo-field echo (TFE); 3D balanced fast-field echo (bFFE).

ASSESSMENT

Brain gray and white matter tissue conductivity measured with phase-based magnetic resonance electrical properties tomography (MREPT) compared before and 20 minutes after ethanol consumption (0.7 g/kg body weight). Differential conductivity whole brain maps were generated for three subgroups: those with strong ( ∆ σ max  > 0.1 S/m; N = 33), weak (0.02 S/m ≤  ∆ σ max  ≤ 0.1 S/m; N = 9) conductivity decrease, and no significant response ( ∆ σ max  < 0.02 S/m, N = 10). Maps were compared in the strong response group where breath alcohol rose between scans, vs. those where it fell.

STATISTICAL TESTS

Average breath alcohol levels were compared to the differential conductivity maps using linear regression. T-maps were generated (threshold P < 0.05 and P < 0.001; minimum cluster 48 mm3). Differential conductivity maps were compared with ANOVA.

RESULTS

Whole-group analysis showed decreased conductivity that did not survive statistical thresholding. Strong responders (N = 33) showed a consistent pattern of significantly decreased conductivity ( ∆ σ max  > 0.1 S/m) in frontal/occipital and cerebellar white matter. The weak response group (N = 9) showed a similar pattern of conductivity decrease (0.02 S/m ≤  ∆ σ max  ≤ 0.1 S/m). There was no significant relationship with breath alcohol levels, alcohol use, age, ethnicity, or sex. The strong responders' regional response was different between ascending (N = 12) or descending (N = 20) alcohol during the scan.

DATA CONCLUSION

Ethanol reduces brain tissue conductivity in a participant-dependent and spatially dependent fashion.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Cerebellar output shapes cortical preparatory activity during motor adaptation

The cerebellum plays a key role in motor adaptation by driving trial-to-trial recalibration of movements based on previous errors. In primates, cortical correlates of adaptation are encoded already in the pre-movement motor plan, but these early cortical signals could be driven by a cerebellar-to-cortical information flow or evolve independently through intracortical mechanisms. To address this question, we trained female macaque monkeys to reach against a viscous force field (FF) while blocking cerebellar outflow. The cerebellar block led to impaired FF adaptation and a compensatory, re-aiming-like shift in motor cortical preparatory activity. In the null-field conditions, the cerebellar block altered neural preparatory activity by increasing task-representation dimensionality and impeding generalization. A computational model indicated that low-dimensional (cerebellar-like) feedback is sufficient to replicate these findings. We conclude that cerebellar signals carry task structure information that constrains the dimensionality of the cortical preparatory manifold and promotes generalization. In the absence of these signals, cortical mechanisms are harnessed to partially restore adaptation.

Predictive coding in neuropsychiatric disorders: A systematic transdiagnostic review

The predictive coding framework postulates that the human brain continuously generates predictions about the environment, maximizing successes and minimizing failures based on prior experiences and beliefs. This PRISMA-compliant systematic review aims to comprehensively and transdiagnostically examine the differences in predictive coding between individuals with neuropsychiatric disorders and healthy controls. We included 72 articles including case-control studies investigating predictive coding as the primary outcome and reporting behavioral, neuroimaging, or electrophysiological findings. Thirty-three studies investigated predictive coding in the schizophrenia spectrum, 33 in neurodevelopmental disorders, 5 in mood disorders, 4 in neurocognitive disorders, 1 in post-traumatic stress disorder, and 1 in substance use disorders. Oddball and oddball-like paradigms were most frequently used to quantify predictive coding performance. Evidence showed heterogeneous impairments in the predictive coding abilities of the brain across neuropsychiatric disorders, particularly in schizophrenia and autism. Patients within the schizophrenia spectrum showed a consistent pattern of impaired non-social predictive coding. Conversely, predictive coding deficits were more selective for social cues in the autism spectrum. Predictive coding impairments were correlated with clinical symptom severity. These findings underscore the potential utility of predictive coding as a framework for understanding cognitive dysfunctions in the neuropsychiatric population, even though more evidence is needed on underexplored conditions, also considering potential confounders such as medication use and sex/gender. The potential role of predictive coding as a determinant of treatment response may also be considered to tailor personalized interventions.

Enhancing automatic sleep stage classification with cerebellar EEG and machine learning techniques

Sleep disorders have become a significant health concern in modern society. To investigate and diagnose sleep disorders, sleep analysis has emerged as the primary research method. Conventional polysomnography primarily relies on cerebral electroencephalography (EEG) and electromyography (EMG) for sleep stage scoring, but manual scoring is time-consuming and subjective. This study investigated the potential application of cerebellar EEG combined with machine learning in automatic sleep stage classification. Twenty-five male mice underwent 24-h cerebral EEG/cerebellar EEG/EMG recording, and manual sleep staging was performed. Various machine learning models, including Light Gradient Boosting (LGBoost), Extreme Gradient Boosting, Categorical Boosting, Support Vector Machine, Logistic Regression, Random Forest, Long Short-Term Memory and Convolutional Neural Network, were applied for automatic sleep stage classification. The performance of different models and the efficacy of cerebellar EEG, cerebral EEG, and EMG were compared under different training:test set ratios. Cerebellar EEG exhibited significant differences in power spectral density across wakefulness, non-rapid eye movement sleep stages, and rapid eye movement sleep stages, particularly at frequencies >7 Hz. LGBoost, Extreme Gradient Boosting, and Categorical Boosting models showed comparable performance, with LGBoost being selected for further analyses due to its shorter computation time. Cerebral EEG consistently demonstrated the highest precision, recall/sensitivity, and specificity in classifying sleep stages across all training:test set ratios, followed by cerebellar EEG, which outperformed EMG. Combining the top 5 cerebellar EEG features with cerebral EEG features yielded better classification performance than combining EMG features with cerebral EEG features. Using the top 20 features, the model achieved mean area under the receiver operating characteristic curve values of 0.98 ± 0.08, 0.98 ± 0.10, and 0.99 ± 0.07 for wakefulness, non-rapid eye movement sleep stages, and rapid eye movement sleep stages, respectively. The cerebellum may play a unique and important role in sleep-wake regulation. Incorporating cerebellar EEG into polysomnography has the potential to enhance the accuracy and efficiency of sleep stage classification.

Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population

Children's brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9~11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state with the most within-network synchrony and the anticorrelations between networks, especially between the sensory networks and between the cerebellum and other networks, was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a DFC state showing integration of sensory networks and antagonism between default-mode and sensorimotor networks but weak segregation of the cerebellum. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.

Cerebellar-cerebral circuits functional connectivity in patients with cognitive impairment after basal ganglia stroke: a pilot study

Introduction

This study aims to assess the pattern of functional connectivity (FC) between cerebellar subregions, the basal ganglia (BG), and the cortex, and explore the relationship between FC patterns and cognitive function after stroke with BG infarcts.

Methods

A total of 39 stroke patients and 29 healthy controls were recruited. Four cerebellar seed points were selected, and the FC of each seed point with other voxels in the whole brain was calculated. FC and cognitive performance were compared between the two groups, and their correlations were analyzed.

Results

Stroke patients exhibited increased FC between the bilateral cerebellum IX and BG (particularly the head of the caudate nucleus), which was positively correlated with episodic memory, visuospatial ability, and attention. Increased FC was also observed between the right cerebellum Crus I/II and BG, as well as the bilateral cerebellum VI and BG, correlating positively with episodic memory. Conversely, decreased FC was identified between the bilateral cerebellum IX and the right caudal cuneus, which negatively correlated with episodic memory, language, and attention but positively correlated with executive function. Additionally, increased FC between the bilateral cerebellum VI and the bilateral inferior parietal lobule was associated with improvements in episodic memory, language, and attention. Decreased FC was observed between the right cerebellum VI and the left insula, as well as between the right cerebellum Crus I/II and the left insula, which negatively correlated with episodic memory.

Discussion

The enhanced FC between the cerebellum and BG, along with the reorganization of new neural circuits involving the cerebellar cortex, may contribute to cognitive recovery following stroke. These changes may represent compensatory mechanisms of the cerebellum in response to stroke injury.

The effect of 3-di-o-tolylguanidine on the level of neurotransmitters in the cerebellum and related disorders of social behavior

It is common knowledge that the cerebellum is a structure of the central nervous system that influences the processes of balance and motor coordination. Recently its influence on social interactions has also been emphasized. The sigma receptor agonist: 3-di-o-tolylguanidine (DTG) is characterized by high affinity for sigma 1 and sigma 2 receptors, widely distributed in the cerebellum. In the experiment we assessed the effect of long term administration of DTG to adult male Sprague Dawley rats on social behavior and the concentration of neurotransmitters in the cerebellum. DTG was administered orally at a dose of 3 mg/kg body weight (bw) (DTG3), 10 mg/kg bw (DTG10) and 30 mg/kg bw (DTG30) for 9 weeks before the behavioral test. After the experiment, the concentration of catecholamines and amino acids in the cerebellum was assessed using high performance liquid chromatography (HPLC). Treatment groups showed reductions in social interactions such as grooming, sniffing and total time spent interacting. At the same time, it was shown that in the group receiving the lowest dose of the drug, a decrease in the concentration of dopamine and serotonin in the cerebellum was observed. Furthermore, changes in the concentration of taurine, alanine, glutamic acid and gamma-aminobutyric acid were observed in the treated groups. We found that long term administration of DTG disturbs animals' social interactions and the concentration of neurotransmitters in the cerebellum.

Causally Mapping the Cerebellum in Children and Young Adults: from Motor to Cognition

While the cerebellum's role in orchestrating motor execution and routines is well established, its functional role in supporting cognition is less clear. Previous studies claim that motricity and cognition are mapped in different areas of the cerebellar cortex, with an anterior/posterior dichotomy. However, most of the studies supporting this claim either use correlational methods (neuroimaging) or are lesion studies that did not consider central covariates (such as age, gender, treatment presence, and deep nuclei impairment) known to influence motor and cognitive recoveries in patients. Here, we used voxel-based lesion-symptom mapping (VLSM) on children and young adults having undergone cerebellar tumor resection. This approach allows to control for these covariates and evaluate causal relationships between brain anatomy and behavioral performances to disentangle the anatomic substrate of motor and cognitive functions. VLSM analyses showed that both motor and cognitive impairments were greater in children and young adults with lesions of the posterior cerebellum. These results highlight distinct and overlapping structural correlates of motor and cognitive performance in the cerebellum and are consistent with structural and functional hypotheses of integration of the cerebellum in motor and cognitive functions.

Unstable functional brain states and reduced cerebro-cerebellar modularity in elderly individuals with subjective cognitive decline

The preclinical stage of Alzheimer's Disease (AD) holds great potential for intervention, therefore, it is crucial to elucidate the neural mechanisms underlying the progression of subjective cognitive decline (SCD). Previous studies have predominantly focused on the neural changes in the cerebrum associated with SCD, but have relatively neglected the cerebellum, and its functional relationship with the cerebrum. In the current study, we employed dynamic functional connectivity and large-scale brain network approaches to investigate the pathological characteristics of dynamic brain states and cerebro-cerebellar collaboration between SCD (n = 32) and the healthy elderly (n = 29) using resting-state fMRI. Two-way repeated measures ANOVA and permutation t-tests revealed significant group differences, with individuals with SCD exhibiting shorter state duration and more frequent transitions between states compared to the healthy elderly individuals. Additionally, individuals with SCD showed lower levels of intracerebellar functional connectivity, but higher levels of cerebellar-cerebral functional integration. Furthermore, the hub nodes of the functional networks in SCD shifted between the cerebellum and cerebrum across different brain states. These findings indicate that SCD exhibits greater state instability but may compensate for the negative effects of early disease by integrating cerebellar and cerebral networks, thereby maintaining cognitive performance. This study enhances our theoretical understanding of cerebellar-cerebral relationship changes in the early stages of AD and provides evidence for early interventions targeting the cerebellum.

Patterns of Cerebellar-Cortical Structural Covariance Mirror Anatomical Connectivity of Sensorimotor and Cognitive Networks

The cortex and cerebellum are densely connected through reciprocal input/output projections that form segregated circuits. These circuits are shown to differentially connect anterior lobules of the cerebellum to sensorimotor regions, and lobules Crus I and II to prefrontal regions. This differential connectivity pattern leads to the hypothesis that individual differences in structure should be related, especially for connected regions. To test this hypothesis, we examined covariation between the volumes of anterior sensorimotor and lateral cognitive lobules of the cerebellum and measures of cortical thickness (CT) and surface area (SA) across the whole brain in a sample of 270 young adults drawn from the HCP dataset. We observed that patterns of cerebellar-cortical covariance differed between sensorimotor and cognitive networks. Anterior motor lobules of the cerebellum showed greater covariance with sensorimotor regions of the cortex, while lobules Crus I and Crus II showed greater covariance with frontal and temporal regions. Interestingly, cerebellar volume showed predominantly negative relationships with CT and predominantly positive relationships with SA. Individual differences in SA are thought to be largely under genetic control while CT is thought to be more malleable by experience. This suggests that cerebellar-cortical covariation for SA may be a more stable feature, whereas covariation for CT may be more affected by development. Additionally, similarity metrics revealed that the pattern of covariance showed a gradual transition between sensorimotor and cognitive lobules, consistent with evidence of functional gradients within the cerebellum. Taken together, these findings are consistent with known patterns of structural and functional connectivity between the cerebellum and cortex. They also shed new light on possibly differing relationships between cerebellar volume and cortical thickness and surface area. Finally, our findings are consistent with the interactive specialization framework which proposes that structurally and functionally connected brain regions develop in concert.

Reorganization of Dynamic Network in Stroke Patients and Its Potential for Predicting Motor Recovery

Objective: The investigation of brain functional network dynamics offers a promising approach to understanding network reorganization poststroke. This study aims to explore the dynamic network configurations associated with motor recovery in stroke patients and assess their predictive potential using multilayer network analysis. Methods: Resting-state functional magnetic resonance imaging data were collected from patients with subacute stroke within 2 weeks of onset and from matched healthy controls (HCs). Group-independent component analysis and a sliding window approach were utilized to construct dynamic functional networks. A multilayer network model was applied to quantify the switching rates of individual nodes, subnetworks, and the global network across the dynamic network. Correlation analyses assessed the relationship between switching rates and motor function recovery, while linear regression models evaluated the predictive potential of global network switching rate on motor recovery outcomes. Results: Stroke patients exhibited a significant increase in the switching rates of specific brain regions, including the medial frontal gyrus, precentral gyrus, inferior parietal lobule, anterior cingulate, superior frontal gyrus, and postcentral gyrus, compared to HCs. Additionally, elevated switching rates were observed in the frontoparietal network, default mode network, cerebellar network, and in the global network. These increased switching rates were positively correlated with baseline Fugl-Meyer assessment (FMA) scores and changes in FMA scores at 90 days poststroke. Importantly, the global network's switching rate emerged as a significant predictor of motor recovery in stroke patients. Conclusions: The reorganization of dynamic network configurations in stroke patients reveals crucial insights into the mechanisms of motor recovery. These findings suggest that metrics of dynamic network reorganization, particularly global network switching rate, may offer a robust predictor of motor recovery.

Functional neural substrates of Parkinson's disease and potential underpinnings of acute responses to acupuncture stimulation

Parkinson's disease is a heterogenous neurodegenerative disorder with a wide variety of motor and non-motor symptoms. This study used resting-state fMRI to identify the neural substrates of PD and explore the acute neural response to acupuncture stimulation in 74 participants (50 patients with PD and 24 healthy controls). All participants with PD were evaluated for the severity of symptoms using the Unified Parkinson's Disease Rating Scale and Balance Master. The z-transformed fractional amplitude of low-frequency fluctuation analysis showed significant differences between the PD and healthy controls in the cerebellar regions, which are thought to play a crucial role in PD pathology. Subsequently, seed-based functional connectivity of the cerebellum with the frontal, parietal, and limbic regions was identified as a potential diagnostic marker for PD. In addition, spontaneous neural activity in the precentral gyrus and thalamus was significantly associated with the severity of PD symptoms. Neural activity in the precentral gyrus, precuneus, and superior temporal gyrus showed a significant correlation with Balance Master indicators. Finally, acupuncture stimulation at GB34 significantly reduced the activity of the occipital regions in patients with PD, but this effect was not observed in healthy controls. The mixed-effects analysis revealed an interaction effects between group and acupuncture stimulation, suggesting that the modulatory effects of acupuncture could differ depending on disease status. Therefore, this study suggests the neural substrates of PD and potential underpinnings of acute neural response to acupuncture stimulation.

Multisensory approach in Mental Imagery: ALE meta-analyses comparing Motor, Visual and Auditory Imagery

Mental Imagery is a topic of longstanding and widespread scientific interest. Individual studies have typically focused on a single modality (e.g. Motor, Visual, Auditory) of Mental Imagery. Relatively little work has considered directly comparing and contrasting the brain networks associated with these different modalities of Imagery. The present study integrates data from 439 neuroimaging experiments to identify both modality-specific and shared neural networks involved in Mental Imagery. Comparing the networks involved in Motor, Visual, and Auditory Imagery identified a pattern whereby each form of Imagery preferentially recruited 'higher level' associative brain regions involved in the associated 'real' experience. Results also indicate significant overlap in a left-lateralized network including the pre-supplementary motor area, ventral premotor cortex and inferior parietal lobule. This pattern of results supports the existence of a 'core' network that supports the attentional, spatial, and decision-making demands of Mental Imagery. Together these results offer new insights into the brain networks underlying human imagination.

Abnormal stability of dynamic functional architecture in drug-naïve children with attention-deficit/hyperactivity disorder

BACKGROUND AND AIMS

Attention-deficit/hyperactivity disorder (ADHD) is most commonly diagnosed neurodevelopmental disorder in childhood, characterized by developmentally inappropriate inattention and/or hyperactivity/impulsivity symptoms. Static and dynamic functional connectivity (FC) studies have revealed brain dysfunction in ADHD. However, few studies have estimated the stability of dynamic functional architecture of children with ADHD. The present study attempted to identify the functional stability (FS) abnormalities associated with ADHD in drug-naïve children.

MATERIALS AND METHODS

The resting-state fMRI of 42 children with ADHD and 30 healthy controls (HCs) were collected. Using the sliding window approach, FS of each voxel was obtained by measuring the concordance of dynamic FC over time. Further, the seed based dynamic FC (dFC) was conducted to explore the specific brain regions with dFC alteration related to these brain regions with altered FS. Then, the inter-group comparison and correlation analysis were performed.

RESULTS

We found that children with ADHD exhibited (1) decreased FS in the bilateral superior frontal gyrus (SFG) and increased FS in the right middle temporal gyrus (MTG), which both belong to the default mode network (DMN); (2) increased dFC between the bilateral SFG of DMN and the left insula of salience networks (SN) (GRF, voxel-wise p < 0.001, cluster-wise p < 0.05); (3) decreased dFC between the right MTG and the left cerebellum posterior lobe, and (3) worse performance in the Stroop test that significantly correlate with decreased FS in the bilateral SFG (p = 0.043, FDR corrected).

CONCLUSIONS

Our findings showed that the abnormal functional architecture involved the DMN (the bilateral SFG and right MTG) and SN (left insula) regions in children with ADHD. This preliminary study provides novel insight into the dynamic brain functional networks in ADHD.

Within-individual organization of the human cognitive cerebellum: Evidence for closely juxtaposed, functionally specialized regions

Specific regions in the cognitive cerebellum are connected to distinct cerebral association networks. Do these cerebellar regions exhibit functional specialization similar to the cerebral cortex? Here, we mapped the cerebellum within intensively studied participants (N = 15) first using connectivity to estimate regions linked to specific networks and then prospectively testing functional response properties in task data within each individual's own idiosyncratic anatomy. A large megacluster extending across Crus I/II was consistently found with subregions linked to five higher-order association networks. A more variable smaller association cluster was found in lobule IX. Within the Crus I/II megacluster, specific cerebellar regions responded to domain-flexible cognitive control, while juxtaposed regions differentially responded to language, social, and spatial/episodic task demands. Similarly organized clusters also exist in the caudate consistent with the presence of multiple basal ganglia-cerebellar-cerebral cortical circuits that maintain functional specialization across their entire distributed extents.

The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder

Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression, defined in this context by a state of persistently low valence, may arise from various factors-including inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. Integrating algorithmic, dynamical systems, and neurobiological concepts, we map the agent model to brain circuits and functional networks, framing potential etiological routes and linking with depression biotypes. Finally, we explore how brain stimulation, psychotherapy, and plasticity-enhancing compounds such as psychedelics can synergistically repair neural circuits and optimize therapies using personalized computational models.

Intellectual Disability in Episodic Ataxia Type 2: Beyond Paroxysmal Vertigo and Ataxia

BACKGROUND AND PURPOSE

Episodic ataxia type 2 (EA2) is characterized by recurrent vertigo and ataxia due to mutations in CACNA1A that encodes the α1A-subunit of the P/Q-type voltage-gated calcium channel. This study aimed to determine intellectual function in EA2.

METHODS

During 2019-2023, 13 patients (6 males, age range=10-52 years, median age=29 years) with a genetically confirmed diagnosis of EA2 had their intellectual function evaluated using the Korean versions of the Wechsler Intelligence Scales (version IV) for adults or children in 3 referral-based university hospitals in South Korea.

RESULTS

The full-scale intelligence quotients (FSIQs) among the 13 patients were below the average (90-109) in 11, low average (80-89) in 5 (38.5%), borderline (70-79) in 1 (7.7%), and indicated intellectual disability (≤69) in 5 (38.5%). These patterns of cognitive impairments were observed in all four of the following subtests: verbal comprehension, perceptual reasoning, working memory, and processing speed. The FSIQ was not correlated with the ages at onset for vertigo and ataxia (Pearson correlation: p=0.40).

CONCLUSIONS

Patients with EA2 may have hidden intellectual disabilities even without a history of epilepsy or administration of antiepileptic drugs, and should be considered for genetic counseling and therapeutic interventions. Given the availability of medication to control episodic vertigo and ataxia, early diagnosis and management are important in preventing irreversible brain dysfunction in EA2.

Nasal obstruction during development leads to defective synapse elimination, hypersynchrony, and impaired cerebellar function

Nasal respiratory disorders are linked to craniofacial anomalies and systemic dysfunctions. However, the implications of nasal respiratory disorders on brain development and their subsequent impact on brain functionalization remain largely unknown. Here, we describe that nasal obstruction from postnatal developmental stages in mice precipitates deficits in cerebellum-associated behaviors and compromised refinement and maturation of neural circuits in the cerebellum. We show that mice with nasal obstruction during developmental phases exhibit marked impairments in motor function and exhibit increased immobility time in forced swimming test. Additionally, we identified critical periods during which nasal respiration is essential for optimizing motor function and preserving mental health. Our study also reveals that nasal obstruction in mice disrupts the typical developmental process of synapse elimination in the cerebellum and hinders the normal transition of activity patterns in cerebellar Purkinje cell populations during development. Through comparing activity patterns in mouse models subjected to nasal obstruction at various stages, we suggest that the maturation of specific activity pattern among Purkinje cell populations is fundamental to the functional integrity of the cerebellum. Our findings highlight the indispensable role of adequate nasal respiration during development for the establishment and functional integrity of neural circuits, thereby significantly affecting brain function.

MRI radiomics combined with machine learning for diagnosing mild cognitive impairment: a focus on the cerebellar gray and white matter

Objective

Mild Cognitive Impairment (MCI) is a recognized precursor to Alzheimer's Disease (AD), presenting a significant risk of progression. Early detection and intervention in MCI can potentially slow disease advancement, offering substantial clinical benefits. This study employed radiomics and machine learning methodologies to distinguish between MCI and Normal Cognition (NC) groups.

Methods

The study included 172 MCI patients and 183 healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, all of whom had 3D-T1 weighted MRI structural images. The cerebellar gray and white matter were segmented automatically using volBrain software, and radiomic features were extracted and screened through Pyradiomics. The screened features were then input into various machine learning models, including Random Forest (RF), Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), K Nearest Neighbors (KNN), Extra Trees, Light Gradient Boosting Machine (LightGBM), and Multilayer Perceptron (MLP). Each model was optimized for penalty parameters through 5-fold cross-validation to construct radiomic models. The DeLong test was used to evaluate the performance of different models.

Results

The LightGBM model, which utilizes a combination of cerebellar gray and white matter features (comprising eight gray matter and eight white matter features), emerges as the most effective model for radiomics feature analysis. The model demonstrates an Area Under the Curve (AUC) of 0.863 for the training set and 0.776 for the test set.

Conclusion

Radiomic features based on the cerebellar gray and white matter, combined with machine learning, can objectively diagnose MCI, which provides significant clinical value for assisted diagnosis.

Challenges and Approaches in the Study of Neural Entrainment

When exposed to rhythmic stimulation, the human brain displays rhythmic activity across sensory modalities and regions. Given the ubiquity of this phenomenon, how sensory rhythms are transformed into neural rhythms remains surprisingly inconclusive. An influential model posits that endogenous oscillations entrain to external rhythms, thereby encoding environmental dynamics and shaping perception. However, research on neural entrainment faces multiple challenges, from ambiguous definitions to methodological difficulties when endogenous oscillations need to be identified and disentangled from other stimulus-related mechanisms that can lead to similar phase-locked responses. Yet, recent years have seen novel approaches to overcome these challenges, including computational modeling, insights from dynamical systems theory, sophisticated stimulus designs, and study of neuropsychological impairments. This review outlines key challenges in neural entrainment research, delineates state-of-the-art approaches, and integrates findings from human and animal neurophysiology to provide a broad perspective on the usefulness, validity, and constraints of oscillatory models in brain-environment interaction.

Dissociations in perceptual discrimination following selective damage to the dentate gyrus versus CA1 subfield of the hippocampus

The hippocampus (HPC) is well-known for its involvement in declarative (consciously accessible) memory, but there is evidence that it may also play a role in complex perceptual discrimination. Separate research has demonstrated separable contributions of HPC subregions to component memory processes, with the dentate gyrus (DG) required for mnemonic discrimination of similar inputs and the CA1 subfield required for retention and retrieval, but contributions of these subregions to perceptual processes is understudied. The current study examined the nature and extent of a double dissociation between the dentate gyrus (DG) to discrimination processes and CA1 subfield to retention/retrieval by testing two unique individuals with bilateral damage to the DG (case BL) and CA1 (case BR). We tested BL and BR on a wide range of standardized neuropsychological tests to assess information encoding and retention/retrieval and co-opted many measures to assess perceptual discrimination. Compared to normative data, BL exhibited performance below expectations on most measures requiring perceptual discrimination and on measures of encoding but demonstrated intact retention. Conversely, BR showed no difficulties with perceptual discrimination or verbal encoding but exhibited poor verbal retention, as well as poor encoding and retention of spatial/integrative tasks (e.g., object in a location). These results indicate that, despite its prominent role in memory, the DG is necessary for perceptual discrimination and encoding, whereas CA1 is necessary for retention/retrieval and encoding of spatial information. The pattern of results highlights the critical nature of individual case studies in the nuanced understanding of HPC subfield contributions to different memory processes, as well as the utility of repurposing neuropsychological measures to capture individual differences.

Neurostructural Consequences of Obstetric Brachial Plexus Palsy in Childhood

Background

Obstetric brachial plexus palsy (OBPP) is a condition impairing limb function caused by birth injury. In 20 to 30% of cases, severe OBPP can cause life constraints in feeding, grooming, and clothing tasks.

Objective

The present study, using voxel- and surface-based morphometry (VBM and SBM), examined the brain structure of pediatric OBPP patients to better understand the effects of this peripheral motor deficit on early brain development.

Methods

Thirty-six T1-weighted images of 18 patients (2-17 years old, mean age = 11.3, 8 females) and 18 healthy controls (2-17 years old, mean age = 10.1, 8 females) were collected for this study. MRI data were processed and analyzed using the Statistical Parametric Mapping 12 (SPM12) toolbox. The custom pediatric tissue probability map was created with the CerebroMatic (COM) toolbox. The results were considered significant if they survived whole-brain family-wise error correction (P < .05).

Results

We have found differences in grey matter volumes in the bilateral anterior hippocampus (left P < .001 and right P = .01) and left cerebellum exterior (Crus I) (P < .001). We have also found differences in cortical thickness in the bilateral parahippocampal gyri (left P = .001 and right P = .005) and right orbitofrontal cortex (OFC) (P < .001).

Conclusions

These structural differences might be linked to the altered environmental adaptation that children with OBPP face due to their primary motor deficit. Our findings hint at a complex interplay between motor capabilities, brain structure development, and cognitive functions. However, more research combining neuroimaging, behavioral, cognitive, and clinical data is needed to support stronger conclusions on this subject.

Neural bases of reading fluency: A systematic review and meta-analysis

Reading fluency, the ability to read quickly and accurately, is a critical marker of successful reading and is notoriously difficult to improve in reading disabled populations. Despite its importance to functional literacy, fluency is a relatively under-studied aspect of reading, and the neural correlates of reading fluency are not well understood. Here, we review the literature of the neural correlates of reading fluency as well as rapid automatized naming (RAN), a task that is robustly related to reading fluency. In a qualitative review of the neuroimaging literature, we evaluated structural and functional MRI studies of reading fluency in readers from a range of skill levels. This was followed by a quantitative activation likelihood estimate (ALE) meta-analysis of fMRI studies of reading speed and RAN measures. We anticipated that reading speed, relative to untimed reading and reading-related tasks, would harness ventral reading pathways that are thought to enable the fast, visual recognition of words. The qualitative review showed that speeded reading taps the entire canonical reading network. The meta-analysis indicated a stronger role of the ventral reading pathway in rapid reading and rapid naming. Both reviews identified regions outside the canonical reading network that contribute to reading fluency, such as the bilateral insula and superior parietal lobule. We suggest that fluent reading engages both domain-specific reading pathways as well as domain-general regions that support overall task performance and discuss future avenues of research to expand our understanding of the neural bases of fluent reading.

The role of training variability for model-based and model-free learning of an arbitrary visuomotor mapping

A fundamental feature of the human brain is its capacity to learn novel motor skills. This capacity requires the formation of vastly different visuomotor mappings. Using a grid navigation task, we investigated whether training variability would enhance the flexible use of a visuomotor mapping (key-to-direction rule), leading to better generalization performance. Experiments 1 and 2 show that participants trained to move between multiple start-target pairs exhibited greater generalization to both distal and proximal targets compared to participants trained to move between a single pair. This finding suggests that limited variability can impair decisions even in simple tasks without planning. In addition, during the training phase, participants exposed to higher variability were more inclined to choose options that, counterintuitively, moved the cursor away from the target while minimizing its actual distance under the constrained mapping, suggesting a greater engagement in model-based computations. In Experiments 3 and 4, we showed that the limited generalization performance in participants trained with a single pair can be enhanced by a short period of variability introduced early in learning or by incorporating stochasticity into the visuomotor mapping. Our computational modeling analyses revealed that a hybrid model between model-free and model-based computations with different mixing weights for the training and generalization phases, best described participants' data. Importantly, the differences in the model-based weights between our experimental groups, paralleled the behavioral findings during training and generalization. Taken together, our results suggest that training variability enables the flexible use of the visuomotor mapping, potentially by preventing the consolidation of habits due to the continuous demand to change responses.

Motor imagery, forward models and the cerebellum: a commentary on Rieger et al., 2023

In this commentary on Rieger et al., Psychological Research Psychologische Forschung, 2023, I discuss possible ways to test the hypothesis that action imagery is achieved by simulations of actions through an internal forward model. These include brain imaging, perturbation through TMS, and psychophysical tests of adaptation of intended reach actions.

The cerebellum and the Mirror Neuron System: A matter of inhibition? From neurophysiological evidence to neuromodulatory implications. A narrative review

Mirror neurons show activity during both the execution (AE) and observation of actions (AO). The Mirror Neuron System (MNS) could be involved during motor imagery (MI) as well. Extensive research suggests that the cerebellum is interconnected with the MNS and may be critically involved in its activities. We gathered evidence on the cerebellum's role in MNS functions, both theoretically and experimentally. Evidence shows that the cerebellum plays a major role during AO and MI and that its lesions impair MNS functions likely because, by modulating the activity of cortical inhibitory interneurons with mirror properties, the cerebellum may contribute to visuomotor matching, which is fundamental for shaping mirror properties. Indeed, the cerebellum may strengthen sensory-motor patterns that minimise the discrepancy between predicted and actual outcome, both during AE and AO. Furthermore, through its connections with the hippocampus, the cerebellum might be involved in internal simulations of motor programs during MI. Finally, as cerebellar neuromodulation might improve its impact on MNS activity, we explored its potential neurophysiological and neurorehabilitation implications.

Isolation of Distinct Networks Driving Action and Cognition in Psychomotor Processes

BACKGROUND

Psychomotor disturbances are observed across psychiatric disorders and often manifest as psychomotor slowing, agitation, disorganized behavior, or catatonia. Psychomotor function includes both cognitive and motor components, but the neural circuits driving these subprocesses and how they relate to symptoms have remained elusive for centuries.

METHODS

We analyzed data from the HCP-EP (Human Connectome Project for Early Psychosis), a multisite study of 125 participants with early psychosis and 58 healthy participants with resting-state functional magnetic resonance imaging and clinical characterization. Psychomotor function was assessed using the 9-hole pegboard task, a timed motor task that engages mechanical and psychomotor components of action, and tasks assessing processing speed and task switching. We used multivariate pattern analysis of whole-connectome data to identify brain correlates of psychomotor function.

RESULTS

We identified discrete brain circuits driving the cognitive and motor components of psychomotor function. In our combined sample of participants with psychosis (n = 89) and healthy control participants (n = 52), the strongest correlates of psychomotor function (pegboard performance) (p < .005) were between a midline cerebellar region and left frontal region and presupplementary motor area. Psychomotor function was correlated with both cerebellar-frontal connectivity (r = 0.33) and cerebellar-presupplementary motor area connectivity (r = 0.27). However, the cognitive component of psychomotor performance (task switching) was correlated only with cerebellar-frontal connectivity (r = 0.19), whereas the motor component (processing speed) was correlated only with cerebellar-presupplementary motor area connectivity (r = 0.15), suggesting distinct circuits driving unique subprocesses of psychomotor function.

CONCLUSIONS

We identified cerebellar-cortical circuits that drive distinct subprocesses of psychomotor function. Future studies should probe relationships between cerebellar connectivity and psychomotor performance using neuromodulation.

Identification of schizophrenia by applying interpretable radiomics modeling with structural magnetic resonance imaging of the cerebellum

AIMS

The cerebellum is involved in higher-order mental processing as well as sensorimotor functions. Although structural abnormalities in the cerebellum have been demonstrated in schizophrenia, neuroimaging techniques are not yet applicable to identify them given the lack of biomarkers. We aimed to develop a robust diagnostic model for schizophrenia using radiomic features from T1-weighted magnetic resonance imaging (T1-MRI) of the cerebellum.

METHODS

A total of 336 participants (174 schizophrenia; 162 healthy controls [HCs]) were allocated to training (122 schizophrenia; 115 HCs) and test (52 schizophrenia; 47 HCs) cohorts. We obtained 2568 radiomic features from T1-MRI of the cerebellar subregions. After feature selection, a light gradient boosting machine classifier was trained. The discrimination and calibration of the model were evaluated. SHapley Additive exPlanations (SHAP) was applied to determine model interpretability.

RESULTS

We identified 17 radiomic features to differentiate participants with schizophrenia from HCs. In the test cohort, the radiomics model had an area under the curve, accuracy, sensitivity, and specificity of 0.89 (95% confidence interval: 0.82-0.95), 78.8%, 88.5%, and 75.4%, respectively. The model explanation by SHAP suggested that the second-order size zone non-uniformity feature from the right lobule IX and first-order energy feature from the right lobules V and VI were highly associated with the risk of schizophrenia.

CONCLUSION

The radiomics model focused on the cerebellum demonstrates robustness in diagnosing schizophrenia. Our results suggest that microcircuit disruption in the posterior cerebellum is a disease-defining feature of schizophrenia, and radiomics modeling has potential for supporting biomarker-based decision-making in clinical practice.

Activity of forkhead box P2-positive neurons is associated with tadpole begging behaviour

Motor function is a critical aspect of social behaviour in a wide range of taxa. The transcription factor forkhead box P2 (FoxP2) is well studied in the context of vocal communication in humans, mice and songbirds, but its role in regulating social behaviour in other vertebrate taxa is unclear. We examined the distribution and activity of FoxP2-positive neurons in tadpoles of the mimic poison frog (Ranitomeya imitator). In this species, tadpoles are reared in isolated plant nurseries and are aggressive to other tadpoles. Mothers provide unfertilized egg meals to tadpoles that perform a begging display by vigorously vibrating back and forth. We found that FoxP2 is widely distributed in the tadpole brain and parallels the brain distribution in mammals, birds and fishes. We then tested the hypothesis that FoxP2-positive neurons would have differential activity levels in begging or aggression contexts compared to non-social controls. We found that FoxP2-positive neurons showed increased activation in the striatum and cerebellum during begging and in the nucleus accumbens during aggression. Overall, these findings lay a foundation for testing the hypothesis that FoxP2 has a generalizable role in social behaviour beyond vocal communication across terrestrial vertebrates.

Activity of FoxP2-positive neurons is associated with tadpole begging behavior

Motor function is a critical aspect of social behavior in a wide range of taxa. The transcription factor FoxP2 is well studied in the context of vocal communication in humans, mice, and songbirds, but its role in regulating social behavior in other vertebrate taxa is unclear. We examined the distribution and activity of FoxP2-positive neurons in tadpoles of the mimic poison frog (Ranitomeya imitator). In this species, tadpoles are reared in isolated plant nurseries and are aggressive to other tadpoles. Mothers provide unfertilized egg meals to tadpoles that perform a begging display by vigorously vibrating back and forth. We found that FoxP2 is widely distributed in the tadpole brain and parallels the brain distribution in mammals, birds, and fishes. We then tested the hypothesis that FoxP2-positive neurons would have differential activity levels in begging or aggression contexts compared to non-social controls. We found that FoxP2-positive neurons showed increased activation in the striatum and cerebellum during begging and in the nucleus accumbens during aggression. Overall, these findings lay a foundation for testing the hypothesis that FoxP2 has a generalizable role in social behavior beyond vocal communication across terrestrial vertebrates.

A novel paradigm for measuring prediction abilities in a rat model using a speech-sound discrimination task

The ability to predict and respond to upcoming stimuli is a critical skill for all animals, including humans. Prediction operates largely below conscious awareness to allow an individual to recall previously encountered stimuli and prepare an appropriate response, especially in language. The ability to predict upcoming words within typical speech patterns aids fluent comprehension, as conversational speech occurs quickly. Individuals with certain neurodevelopmental disorders such as autism and dyslexia have deficits in their ability to generate and use predictions. Rodent models are often used to investigate specific aspects of these disorders, but there is no existing behavioral paradigm that can assess prediction capabilities with complex stimuli like speech sounds. Thus, the present study modified an existing rapid speech sound discrimination paradigm to assess whether rats can form predictions of upcoming speech sound stimuli and utilize them to improve task performance. We replicated prior work showing that rats can discriminate between speech sounds presented at rapid rates. We also saw that rats responded exclusively to the target at slow speeds but began responding to the predictive cue in anticipation of the target as the speed increased, suggesting that they learned the predictive value of the cue and adjusted their behavior accordingly. This prediction task will be useful in assessing prediction deficits in rat models of various neurodevelopmental disorders through the manipulation of both genetic and environmental factors.

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.

Prediction-error signals in anterior cingulate cortex drive task-switching

Task-switching is a fundamental cognitive ability that allows animals to update their knowledge of current rules or contexts. Detecting discrepancies between predicted and observed events is essential for this process. However, little is known about how the brain computes cognitive prediction-errors and whether neural prediction-error signals are causally related to task-switching behaviours. Here we trained mice to use a prediction-error to switch, in a single trial, between responding to the same stimuli using two distinct rules. Optogenetic silencing and un-silencing, together with widefield and two-photon calcium imaging revealed that the anterior cingulate cortex (ACC) was specifically required for this rapid task-switching, but only when it exhibited neural prediction-error signals. These prediction-error signals were projection-target dependent and were larger preceding successful behavioural transitions. An all-optical approach revealed a disinhibitory interneuron circuit required for successful prediction-error computation. These results reveal a circuit mechanism for computing prediction-errors and transitioning between distinct cognitive states.

Cortico-Cerebellar Monitoring of Speech Sequence Production

In a functional magnetic resonance imaging study, we examined speech error monitoring in a cortico-cerebellar network for two contrasts: (a) correct trials with high versus low articulatory error probability and (b) overtly committed errors versus correct trials. Engagement of the cognitive cerebellar region Crus I in both contrasts suggests that this region is involved in overarching performance monitoring. The activation of cerebellar motor regions (superior medial cerebellum, lobules VI and VIII) indicates the additional presence of a sensorimotor driven implementation of control. The combined pattern of pre-supplementary motor area (active across contrasts) and anterior cingulate cortex (only active in the contrast involving overt errors) activations suggests sensorimotor driven feedback monitoring in the medial frontal cortex, making use of proprioception and auditory feedback through overt errors. Differential temporal and parietal cortex activation across contrasts indicates involvement beyond sensorimotor driven feedback in line with speech production models that link these regions to auditory target processing and internal modeling-like mechanisms. These results highlight the presence of multiple, possibly hierarchically interdependent, mechanisms that support the optimizing of speech production.

Cerebellar Neuromodulation Impacts Reading Fluency in Young Adults

The cerebellum is traditionally associated with the control of coordinated movement, but ample evidence suggests that the cerebellum also supports cognitive processing. Consistent with this, right-lateralized posterolateral cerebellar regions are engaged during a range of reading and reading-related tasks, but the specific role of the cerebellum during reading tasks is not clear. Based on the cerebellar contribution to automatizing movement, it has been hypothesized that the cerebellum is specifically involved in rapid, fluent reading. We aimed to determine whether the right posterolateral cerebellum is a specific modulator of reading fluency or whether cerebellar modulation is broader, also impacting reading accuracy, rapid automatized naming, and general processing speed. To do this, we examined the effect of transcranial direct current stimulation (tDCS) targeting the right posterolateral cerebellum (lobules VI/VII) on single-word reading fluency, reading accuracy, rapid automatized naming, and processing speed. Young adults with typical reading development (n = 25; 15 female sex assigned at birth, 10 male sex assigned at birth, aged 18-28 years [M = 19.92 ± 2.04 years]) completed the reading and cognitive measures after 20 min of 2 mA anodal (excitatory), cathodal (inhibitory), or sham tDCS in a within-subjects design. Linear mixed effects models indicated that cathodal tDCS decreased single-word reading fluency scores (d = -0.36, p < 0.05) but did not significantly affect single-word reading accuracy, rapid automatized naming, or general processing speed measures. Our results suggest that the right posterolateral cerebellum is involved in reading fluency, consistent with a broader role of the cerebellum in fast, fluent cognition.

No Evidence for Semantic Prediction Deficits in Individuals With Cerebellar Degeneration

Cerebellar involvement in language processing has received considerable attention in the neuroimaging and neuropsychology literatures. Building off the motor control literature, one account of this involvement centers on the idea of internal models. In the context of language, this hypothesis suggests that the cerebellum is essential for building semantic models that, in concert with the cerebral cortex, help anticipate or predict linguistic input. To date, supportive evidence has primarily come from neuroimaging studies showing that cerebellar activation increases in contexts in which semantic predictions are generated and violated. Taking a neuropsychological approach, we put the internal model hypothesis to the test, asking if individuals with cerebellar degeneration (n = 14) show reduced sensitivity to semantic prediction. Using a sentence verification task, we compare reaction time to sentences that vary in terms of cloze probability. We also evaluated a more constrained variant of the prediction hypothesis, asking if the cerebellum facilitates the generation of semantic predictions when the content of a sentence refers to a dynamic rather than static mental transformation. The results failed to support either hypothesis: Compared to matched control participants (n = 17), individuals with cerebellar degeneration showed a similar reduction in reaction time for sentences with high cloze probability and no selective impairment in predictions involving dynamic transformations. These results challenge current theorizing about the role of the cerebellum in language processing, pointing to a misalignment between neuroimaging and neuropsychology research on this topic.