Neural circuits of the cerebellum: hypothesis for function

Human Purkinje cells outperform mouse Purkinje cells in dendritic complexity and computational capacity

Purkinje cells in the cerebellum are among the largest neurons in the brain and have been extensively investigated in rodents. However, their morphological and physiological properties remain poorly understood in humans. In this study, we utilized high-resolution morphological reconstructions and unique electrophysiological recordings of human Purkinje cells ex vivo to generate computational models and estimate computational capacity. An inter-species comparison showed that human Purkinje cell had similar fractal structures but were larger than those of mouse Purkinje cells. Consequently, given a similar spine density (2/μm), human Purkinje cell hosted approximately 7.5 times more dendritic spines than those of mice. Moreover, human Purkinje cells had a higher dendritic complexity than mouse Purkinje cells and usually emitted 2-3 main dendritic trunks instead of one. Intrinsic electro-responsiveness was similar between the two species, but model simulations revealed that the dendrites could process ~6.5 times (n = 51 vs. n = 8) more input patterns in human Purkinje cells than in mouse Purkinje cells. Thus, while human Purkinje cells maintained spike discharge properties similar to those of rodents during evolution, they developed more complex dendrites, enhancing computational capacity.

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.

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits. While MFs have been generated for the isocortex, they are still missing for other parts of the brain. Here we have designed and simulated a multi-layer MF of the cerebellar microcircuit (including Granule Cells, Golgi Cells, Molecular Layer Interneurons, and Purkinje Cells) and validated it against experimental data and the corresponding spiking neural network (SNN) microcircuit model. The cerebellar MF was built using a system of equations, where properties of neuronal populations and topological parameters are embedded in inter-dependent transfer functions. The model time constant was optimised using local field potentials recorded experimentally from acute mouse cerebellar slices as a template. The MF reproduced the average dynamics of different neuronal populations in response to various input patterns and predicted the modulation of the Purkinje Cells firing depending on cortical plasticity, which drives learning in associative tasks, and the level of feedforward inhibition. The cerebellar MF provides a computationally efficient tool for future investigations of the causal relationship between microscopic neuronal properties and ensemble brain activity in virtual brain models addressing both physiological and pathological conditions.

Neuronavigated Cerebellar 50 Hz tACS: Attenuation of Stimulation Effects by Motor Sequence Learning

Cerebellar transcranial alternating current stimulation (tACS) is an emerging non-invasive technique that induces electric fields to modulate cerebellar function. Although the effect of cortical tACS seems to be state-dependent, the impact of concurrent motor activation and the duration of stimulation on the effects of cerebellar tACS has not yet been examined. In our study, 20 healthy subjects received neuronavigated 50 Hz cerebellar tACS for 40 s or 20 min, each during performance using a motor sequence learning task (MSL) and at rest. We measured the motor evoked potential (MEP) before and at two time points after tACS application to assess corticospinal excitability. Additionally, we investigated the online effect of tACS on MSL. Individual electric field simulations were computed to evaluate the distribution of electric fields, showing a focal electric field in the right cerebellar hemisphere with the highest intensities in lobe VIIb, VIII and IX. Corticospinal excitability was only increased after tACS was applied for 40 s or 20 min at rest, and motor activation during tACS (MSL) cancelled this effect. In addition, performance was better (shorter reaction times) for the learned sequences after 20 min of tACS, indicating more pronounced learning under 20 min of tACS compared to tACS applied only in the first 40 s.

Variations on the theme: focus on cerebellum and emotional processing

The cerebellum operates exploiting a complex modular organization and a unified computational algorithm adapted to different behavioral contexts. Recent observations suggest that the cerebellum is involved not just in motor but also in emotional and cognitive processing. It is therefore critical to identify the specific regional connectivity and microcircuit properties of the emotional cerebellum. Recent studies are highlighting the differential regional localization of genes, molecules, and synaptic mechanisms and microcircuit wiring. However, the impact of these regional differences is not fully understood and will require experimental investigation and computational modeling. This review focuses on the cellular and circuit underpinnings of the cerebellar role in emotion. And since emotion involves an integration of cognitive, somatomotor, and autonomic activity, we elaborate on the tradeoff between segregation and distribution of these three main functions in the cerebellum.

Cerebellar transcranial current stimulation – An intraindividual comparison of different techniques

Transcranial current stimulation (tCS) techniques have been shown to induce cortical plasticity. As an important relay in the motor system, the cerebellum is an interesting target for plasticity induction using tCS, aiming to modulate its excitability and connectivity. However, until now it remains unclear, which is the most effective tCS method for inducing plasticity in the cerebellum. Thus, in this study, the effects of anodal transcranial direct current stimulation (tDCS), 50 Hz transcranial alternating current stimulation (50 Hz tACS), and high frequency transcranial random noise stimulation (tRNS) were compared with sham stimulation in 20 healthy subjects in a within-subject design. tCS was applied targeting the cerebellar lobe VIIIA using neuronavigation. We measured corticospinal excitability, short-interval intracortical inhibition (SICI), short-latency afferent inhibition (SAI), and cerebellar brain inhibition (CBI) and performed a sensor-based movement analysis at baseline and three times after the intervention (post1 = 15 min; post2 = 55 min; post3 = 95 min). Corticospinal excitability increased following cerebellar tACS and tRNS compared to sham stimulation. This effect was most pronounced directly after stimulation but lasted for at least 55 min after tACS. Cortico-cortical and cerebello-cortical conditioning protocols, as well as sensor-based movement analyses, did not change. Our findings suggest that cerebellar 50 Hz tACS is the most effective protocol to change corticospinal excitability.

Discovering Microcircuit Secrets With Multi-Spot Imaging and Electrophysiological Recordings: The Example of Cerebellar Network Dynamics

The cerebellar cortex microcircuit is characterized by a highly ordered neuronal architecture having a relatively simple and stereotyped connectivity pattern. For a long time, this structural simplicity has incorrectly led to the idea that anatomical considerations would be sufficient to understand the dynamics of the underlying circuitry. However, recent experimental evidence indicates that cerebellar operations are much more complex than solely predicted by anatomy, due to the crucial role played by neuronal and synaptic properties. To be able to explore neuronal and microcircuit dynamics, advanced imaging, electrophysiological techniques and computational models have been combined, allowing us to investigate neuronal ensembles activity and to connect microscale to mesoscale phenomena. Here, we review what is known about cerebellar network organization, neural dynamics and synaptic plasticity and point out what is still missing and would require experimental assessments. We consider the available experimental techniques that allow a comprehensive assessment of circuit dynamics, including voltage and calcium imaging and extracellular electrophysiological recordings with multi-electrode arrays (MEAs). These techniques are proving essential to investigate the spatiotemporal pattern of activity and plasticity in the cerebellar network, providing new clues on how circuit dynamics contribute to motor control and higher cognitive functions.

Exploring the Genomic Patterns in Human and Mouse Cerebellums Via Single-Cell Sequencing and Machine Learning Method

In mammals, the cerebellum plays an important role in movement control. Cellular research reveals that the cerebellum involves a variety of sub-cell types, including Golgi, granule, interneuron, and unipolar brush cells. The functional characteristics of cerebellar cells exhibit considerable differences among diverse mammalian species, reflecting a potential development and evolution of nervous system. In this study, we aimed to recognize the transcriptional differences between human and mouse cerebellum in four cerebellar sub-cell types by using single-cell sequencing data and machine learning methods. A total of 321,387 single-cell sequencing data were used. The 321,387 cells included 4 cell types, i.e., Golgi (5,048, 1.57%), granule (250,307, 77.88%), interneuron (60,526, 18.83%), and unipolar brush (5,506, 1.72%) cells. Our results showed that by using gene expression profiles as features, the optimal classification model could achieve very high even perfect performance for Golgi, granule, interneuron, and unipolar brush cells, respectively, suggesting a remarkable difference between the genomic profiles of human and mouse. Furthermore, a group of related genes and rules contributing to the classification was identified, which might provide helpful information for deepening the understanding of cerebellar cell heterogeneity and evolution.

Evaluating the efficacy of hearing aids for tinnitus therapy - A Positron emission tomography study

Brain imaging studies have revealed neural changes in chronic tinnitus patients that are not restricted to auditory brain areas; rather, the engagement of limbic system structures, attention and memory networks are has been noted. Hearing aids (HA) provide compensation for comorbid hearing loss and may decrease tinnitus-related perception and annoyance. Using resting state positron emission tomography our goal was to analyze metabolic and functional brain changes after six months of effective HA use by patients with chronic tinnitus and associated sensorineural hearing loss. 33 age and hearing loss matched participants with mild/moderate hearing loss were enrolled in this study: 19 with tinnitus, and 14 without tinnitus. Participants with tinnitus of more than 6 months with moderate/severe Tinnitus Handicap Inventory (THI) and Visual Analogue Scale (VAS) scores composed the tinnitus group. A full factorial 2X2 ANOVA was conducted for imaging analysis, with group (tinnitus and controls) and time point (pre-intervention and post-intervention) as factors. Six months after HA fitting, tinnitus scores reduced statistically and clinically. Analysis revealed increased glycolytic metabolism in the left orbitofrontal cortex, right temporal lobe and right hippocampus, and reduced glycolytic metabolism in the left cerebellum and inferior parietal lobe within the tinnitus group. The hearing loss control group showed no significant metabolic changes in the analysis. Parsing out the contribution of tinnitus independent of hearing loss, allowed us to identify areas implicated in declines in tinnitus handicap as a result of the intervention. Brain regions implicated in the present study may be part of chronic tinnitus-specific network.

Deficiency of TRIM32 Impairs Motor Function and Purkinje Cells in Mid-Aged Mice

Proper functioning of the cerebellum is crucial to motor balance and coordination in adult mammals. Purkinje cells (PCs), the sole output neurons of the cerebellar cortex, play essential roles in cerebellar motor function. Tripartite motif-containing protein 32 (TRIM32) is an E3 ubiquitin ligase that is involved in balance activities of neurogenesis in the subventricular zone of the mammalian brain and in the development of many nervous system diseases, such as Alzheimer's disease, autism spectrum disorder, attention deficit hyperactivity disorder. However, the role of TRIM32 in cerebellar motor function has never been examined. In this study we found that motor balance and coordination of mid-aged TRIM32 deficient mice were poorer than those of wild-type littermates. Immunohistochemical staining was performed to assess cerebella morphology and TRIM32 expression in PCs. Golgi staining showed that the extent of dendritic arborization and dendritic spine density of PCs were decreased in the absence of TRIM32. The loss of TRIM32 was also associated with a decrease in the number of synapses between parallel fibers and PCs, and in synapses between climbing fibers and PCs. In addition, deficiency of TRIM32 decreased Type I inositol 1,4,5-trisphosphate 5-phosphatase (INPP5A) levels in cerebellum. Overall, this study is the first to elucidate a role of TRIM32 in cerebellar motor function and a possible mechanism, thereby highlighting the importance of TRIM32 in the cerebellum.

Frequency-dependent modulation of cerebellar excitability during the application of non-invasive alternating current stimulation

Background

it is well-known that the cerebellum is critical for the integrity of motor and cognitive actions. Applying non-invasive brain stimulation techniques over this region results in neurophysiological and behavioural changes, which have been associated with the modulation of cerebellar-cerebral cortex connectivity. Here, we investigated whether online application of cerebellar transcranial alternating current stimulation (tACS) results in changes to this pathway.

Methods

thirteen healthy individuals participated in two sessions of cerebellar tACS delivered at different frequencies (5Hz and 50Hz). We used transcranial magnetic stimulation to measure cerebellar-motor cortex (M1) inhibition (CBI), short-intracortical inhibition (SICI) and short-afferent inhibition (SAI) before, during and after the application of tACS.

Results

we found that CBI was specifically strengthened during the application of 5Hz cerebellar tACS. No changes were detected immediately following the application of 5Hz stimulation, nor at any time point with 50Hz stimulation. We also found no changes to M1 intracortical circuits (i.e. SICI) or sensorimotor interaction (i.e. SAI), indicating that the effects of 5Hz tACS over the cerebellum are site-specific.

Conclusions

cerebellar tACS can modulate cerebellar excitability in a time- and frequency-dependent manner. Additionally, cerebellar tACS does not appear to induce any long-lasting effects (i.e. plasticity), suggesting that stimulation enhances oscillations within the cerebellum only throughout the stimulation period. As such, cerebellar tACS may have significant implications for diseases manifesting with abnormal cerebellar oscillatory activity and also for future behavioural studies.

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Cerebellar tACS increases the inhibitory tone that the cerebellum exerts over M1 (CBI).

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CBI changes were found only during the online application of 5Hz tACS and not immediately following stimulation.

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The effects are specific to the cerebellum, as no changes were found in intracortical measures (e.g. SICI and SAI).

Temporal constrained objects for modelling neuronal dynamics

BACKGROUND

Several new programming languages and technologies have emerged in the past few decades in order to ease the task of modelling complex systems. Modelling the dynamics of complex systems requires various levels of abstractions and reductive measures in representing the underlying behaviour. This also often requires making a trade-off between how realistic a model should be in order to address the scientific questions of interest and the computational tractability of the model.

METHODS

In this paper, we propose a novel programming paradigm, called temporal constrained objects, which facilitates a principled approach to modelling complex dynamical systems. Temporal constrained objects are an extension of constrained objects with a focus on the analysis and prediction of the dynamic behaviour of a system. The structural aspects of a neuronal system are represented using objects, as in object-oriented languages, while the dynamic behaviour of neurons and synapses are modelled using declarative temporal constraints. Computation in this paradigm is a process of constraint satisfaction within a time-based simulation.

RESULTS

We identified the feasibility and practicality in automatically mapping different kinds of neuron and synapse models to the constraints of temporal constrained objects. Simple neuronal networks were modelled by composing circuit components, implicitly satisfying the internal constraints of each component and interface constraints of the composition. Simulations show that temporal constrained objects provide significant conciseness in the formulation of these models. The underlying computational engine employed here automatically finds the solutions to the problems stated, reducing the code for modelling and simulation control. All examples reported in this paper have been programmed and successfully tested using the prototype language called TCOB. The code along with the programming environment are available at http://github.com/compneuro/TCOB_Neuron.

DISCUSSION

Temporal constrained objects provide powerful capabilities for modelling the structural and dynamic aspects of neural systems. Capabilities of the constraint programming paradigm, such as declarative specification, the ability to express partial information and non-directionality, and capabilities of the object-oriented paradigm especially aggregation and inheritance, make this paradigm the right candidate for complex systems and computational modelling studies. With the advent of multi-core parallel computer architectures and techniques or parallel constraint-solving, the paradigm of temporal constrained objects lends itself to highly efficient execution which is necessary for modelling and simulation of large brain circuits.

Increased Resting-State Cerebellar-Cerebral Functional Connectivity Underlying Chronic Tinnitus

Purpose: Chronic subjective tinnitus may arise from aberrant functional coupling between the cerebellum and the cerebral cortex. To explore this hypothesis, we used resting-state functional magnetic resonance imaging (fMRI) to illuminate the functional connectivity network of the cerebellar regions in chronic tinnitus patients and controls.

Methods: Resting-state fMRI scans were obtained from 28 chronic tinnitus patients and 29 healthy controls (well matched for age, sex and education) in this study. Cerebellar-cerebral functional connectivity was characterized using a seed-based whole-brain correlation method. The resulting cerebellar functional connectivity measures were correlated with each clinical tinnitus characteristic.

Results: Chronic tinnitus patients demonstrated increased functional connectivity between the cerebellum and several cerebral regions, including the superior temporal gyrus (STG), parahippocampal gyrus (PHG), inferior occipital gyrus (IOG), and precentral gyrus. The enhanced functional connectivity between the left cerebellar Lobule VIIb and the right STG was positively correlated with the Tinnitus Handicap Questionnaires (THQ) score (r = 0.577, p = 0.004). Furthermore, the increased functional connectivity between the cerebellar vermis and the right STG was also associated with the THQ score (r = 0.432, p = 0.039).

Conclusions: Chronic tinnitus patients have greater cerebellar functional connectivity to certain cerebral brain regions which is associated with specific tinnitus characteristics. Resting-state cerebellar-cerebral functional connectivity disturbances may play a pivotal role in neuropathological features of tinnitus.

Physiology of the cerebellum

The cerebellum is a central brain structure deeply integrated into major loops with the cerebral cortex, brainstem, and spinal cord. The cerebellum shows a complex regional organization consisting of modules with sagittal orientation. The cerebellum takes part in motor control and its lesions cause a movement incoordination syndrome called ataxia. Recent observations also imply involvement of the cerebellum in cognition and executive control, with an impact on pathologies like dyslexia and autism. The cerebellum operates as a forward controller learning to predict the precise timing of correlated events. The physiologic mechanisms of cerebellar functioning are still the object of intense research. The signals entering the cerebellum through the mossy fibers are processed in the granular layer and transmitted to Purkinje cells, while a collateral pathway activates the deep cerebellar nuclei (DCN). Purkinje cells in turn inhibit DCN, so that the cerebellar cortex operates as a side loop controlling the DCN. Learning is now known to occur through synaptic plasticity at multiple synapses in the granular layer, molecular layer, and DCN, extending the original concept of the Motor Learning Theory that predicted a single form of plasticity at the synapse between parallel fibers and Purkinje cells under the supervision of climbing fibers deriving from the inferior olive. Coordination derives from the precise regulation of timing and gain in the different cerebellar modules. The investigation of cerebellar dynamics using advanced physiologic recordings and computational models is now providing new clues on how the cerebellar network performs its internal computations.

Distribution of CGRP and CGRP receptor components in the rat brain

BACKGROUND

Calcitonin gene-related peptide and its receptor, consisting of receptor activity-modifying protein 1 and calcitonin receptor-like receptor, are of considerable interest because of the role they play in migraine and recently developed migraine therapies.

METHODS

To better understand the function of this neuropeptide, we used immunohistochemistry to determine a detailed distribution of calcitonin gene-related peptide, receptor activity-modifying protein 1 and calcitonin receptor-like receptor in the rat brain in a region of 0.5-1.5 mm lateral to the midline. We found calcitonin gene-related peptide immunoreactivity in most of the neurons of the cerebral cortex, hippocampus, cerebellum, thalamic nuclei, hypothalamic nuclei and brainstem nuclei. In contrast, receptor activity-modifying protein 1 and calcitonin receptor-like receptor immunoreactivity were found almost exclusively in the neuronal processes in the investigated regions.

CONCLUSION

Overall, the degree of expression of calcitonin gene-related peptide and calcitonin gene-related peptide receptor components in the central nervous system is astonishingly complex and suggestive of many different brain functions, including a possible role in migraine. However, currently, the presence of calcitonin gene-related peptide and the nature of its receptors throughout the brain is an enigma yet to be solved.

Distributed Circuit Plasticity: New Clues for the Cerebellar Mechanisms of Learning

The cerebellum is involved in learning and memory of sensory motor skills. However, the way this process takes place in local microcircuits is still unclear. The initial proposal, casted into the Motor Learning Theory, suggested that learning had to occur at the parallel fiber-Purkinje cell synapse under supervision of climbing fibers. However, the uniqueness of this mechanism has been questioned, and multiple forms of long-term plasticity have been revealed at various locations in the cerebellar circuit, including synapses and neurons in the granular layer, molecular layer and deep-cerebellar nuclei. At present, more than 15 forms of plasticity have been reported. There has been a long debate on which plasticity is more relevant to specific aspects of learning, but this question turned out to be hard to answer using physiological analysis alone. Recent experiments and models making use of closed-loop robotic simulations are revealing a radically new view: one single form of plasticity is insufficient, while altogether, the different forms of plasticity can explain the multiplicity of properties characterizing cerebellar learning. These include multi-rate acquisition and extinction, reversibility, self-scalability, and generalization. Moreover, when the circuit embeds multiple forms of plasticity, it can easily cope with multiple behaviors endowing therefore the cerebellum with the properties needed to operate as an effective generalized forward controller.

Repetitive TMS on Left Cerebellum Affects Impulsivity in Borderline Personality Disorder: A Pilot Study

The borderline personality disorder (BPD) is characterized by a severe pattern of instability in emotional regulation, interpersonal relationships, identity and impulse control. These functions are related to the prefrontal cortex (PFC), and since PFC shows a rich anatomical connectivity with the cerebellum, the functionality of the cerebellar-PFC axis may impact on BPD. In this study, we investigated the potential involvement of cerebello-thalamo-cortical connections in impulsive reactions through a pre/post stimulation design. BPD patients (n = 8) and healthy controls (HC; n = 9) performed an Affective Go/No-Go task (AGN) assessing information processing biases for positive and negative stimuli before and after repetitive transcranial magnetic stimulation (rTMS; 1 Hz/10 min, 80% resting motor threshold (RMT) over the left lateral cerebellum. The AGN task consisted of four blocks requiring associative capacities of increasing complexity. BPD patients performed significantly worse than the HC, especially when cognitive demands were high (third and fourth block), but their performance approached that of HC after rTMS (rTMS was almost ineffective in HC). The more evident effect of rTMS in complex associative tasks might have occurred since the cerebellum is deeply involved in integration and coordination of different stimuli. We hypothesize that in BPD patients, cerebello-thalamo-cortical communication is altered, resulting in emotional dysregulation and disturbed impulse control. The rTMS over the left cerebellum might have interfered with existing functional connections exerting a facilitating effect on PFC control.

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate “realistic” models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems.

Toll-Like Receptor 4 Deficiency Impairs Motor Coordination

The cerebellum plays an essential role in balance and motor coordination. Purkinje cells (PCs) are the sole output neurons of the cerebellar cortex and are critical for the execution of its functions, including motor coordination. Toll-like receptor (TLR) 4 is involved in the innate immune response and is abundantly expressed in the central nervous system; however, little is known about its role in cerebellum-related motor functions. To address this question, we evaluated motor behavior in TLR4 deficient mice. We found that TLR4(-∕-) mice showed impaired motor coordination. Morphological analyses revealed that TLR4 deficiency was associated with a reduction in the thickness of the molecular layer of the cerebellum. TLR4 was highly expressed in PCs but not in Bergmann glia or cerebellar granule cells; however, loss of TLR4 decreased the number of PCs. These findings suggest a novel role for TLR4 in cerebellum-related motor coordination through maintenance of the PC population.

Neural correlates underlying micrographia in Parkinson's disease

Micrographia is a common symptom in Parkinson's disease, which manifests as either a consistent or progressive reduction in the size of handwriting or both. Neural correlates underlying micrographia remain unclear. We used functional magnetic resonance imaging to investigate micrographia-related neural activity and connectivity modulations. In addition, the effect of attention and dopaminergic administration on micrographia was examined. We found that consistent micrographia was associated with decreased activity and connectivity in the basal ganglia motor circuit; while progressive micrographia was related to the dysfunction of basal ganglia motor circuit together with disconnections between the rostral supplementary motor area, rostral cingulate motor area and cerebellum. Attention significantly improved both consistent and progressive micrographia, accompanied by recruitment of anterior putamen and dorsolateral prefrontal cortex. Levodopa improved consistent micrographia accompanied by increased activity and connectivity in the basal ganglia motor circuit, but had no effect on progressive micrographia. Our findings suggest that consistent micrographia is related to dysfunction of the basal ganglia motor circuit; while dysfunction of the basal ganglia motor circuit and disconnection between the rostral supplementary motor area, rostral cingulate motor area and cerebellum likely contributes to progressive micrographia. Attention improves both types of micrographia by recruiting additional brain networks. Levodopa improves consistent micrographia by restoring the function of the basal ganglia motor circuit, but does not improve progressive micrographia, probably because of failure to repair the disconnected networks.

Cerebellar abnormalities in Huntington's disease: a role in motor and psychiatric impairment?

The cerebellum has received limited attention in Huntington's disease (HD), despite signs of possible cerebellar dysfunction, including motor incoordination and impaired gait, which are currently attributed to basal ganglia atrophy and disrupted fronto-striatal circuits. This study is the first to investigate a potential contribution of macro- and microstructural cerebellar damage to clinical manifestations of HD. T1- and diffusion-weighted 3T magnetic resonance imaging (MRI) scans were obtained from 12 controls and 22 early-stage HD participants. Manual delineation and voxel-based morphometry were used to assess between-group differences in cerebellar volume, and diffusion metrics were compared between groups within the cerebellar gray and white matter. Associations between these imaging measures and clinical scores were examined within the HD group. Reduced paravermal volume was detected in HD compared with controls using voxel-based morphometry (P < 0.05), but no significant volumetric differences were found using manual delineation. Diffusion abnormalities were detected in both cerebellar gray matter and white matter. Smaller cerebellar volumes, although not significantly reduced, were significantly associated with impaired gait and psychiatric morbidity and of borderline significance with pronate/supinate-hand task performance. Abnormal cerebellar diffusion was associated with increased total motor score, impaired saccade initiation, tandem walking, and timed finger tapping. In conclusion, atrophy of the paravermis, possibly encompassing the cerebellar nuclei, and microstructural abnormalities within the cerebellum may contribute to HD neuropathology. Aberrant cerebellar diffusion and reduced cerebellar volume together associate with impaired motor function and increased psychiatric symptoms in stage I HD, potentially implicating the cerebellum more centrally in HD presentation than previously recognized.

Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation

The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior olive (IO), can only account for limited aspects of learning. Recently, the role of additional forms of plasticity in the granular layer, molecular layer and deep cerebellar nuclei (DCN) has been considered. In particular, learning at DCN synapses allows for generalization, but convergence to a stable state requires hundreds of repetitions. In this paper we have explored the putative role of the IO-DCN connection by endowing it with adaptable weights and exploring its implications in a closed-loop robotic manipulation task. Our results show that IO-DCN plasticity accelerates convergence of learning by up to two orders of magnitude without conflicting with the generalization properties conferred by DCN plasticity. Thus, this model suggests that multiple distributed learning mechanisms provide a key for explaining the complex properties of procedural learning and open up new experimental questions for synaptic plasticity in the cerebellar network.

The cerebellum for jocks and nerds alike

Historically the cerebellum has been implicated in the control of movement. However, the cerebellum's role in non-motor functions, including cognitive and emotional processes, has also received increasing attention. Starting from the premise that the uniform architecture of the cerebellum underlies a common mode of information processing, this review examines recent electrophysiological findings on the motor signals encoded in the cerebellar cortex and then relates these signals to observations in the non-motor domain. Simple spike firing of individual Purkinje cells encodes performance errors, both predicting upcoming errors as well as providing feedback about those errors. Further, this dual temporal encoding of prediction and feedback involves a change in the sign of the simple spike modulation. Therefore, Purkinje cell simple spike firing both predicts and responds to feedback about a specific parameter, consistent with computing sensory prediction errors in which the predictions about the consequences of a motor command are compared with the feedback resulting from the motor command execution. These new findings are in contrast with the historical view that complex spikes encode errors. Evaluation of the kinematic coding in the simple spike discharge shows the same dual temporal encoding, suggesting this is a common mode of signal processing in the cerebellar cortex. Decoding analyses show the considerable accuracy of the predictions provided by Purkinje cells across a range of times. Further, individual Purkinje cells encode linearly and independently a multitude of signals, both kinematic and performance errors. Therefore, the cerebellar cortex's capacity to make associations across different sensory, motor and non-motor signals is large. The results from studying how Purkinje cells encode movement signals suggest that the cerebellar cortex circuitry can support associative learning, sequencing, working memory, and forward internal models in non-motor domains.

Realistic modeling of neurons and networks: towards brain simulation

Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

Cutaneous and periodontal inputs to the cerebellum of the naked mole-rat (Heterocephalus glaber)

The naked mole-rat (Heterocephalus glaber) is a small fossorial rodent with specialized dentition that is reflected by the large cortical area dedicated to representation of the prominent incisors. Due to naked mole-rats’ behavioral reliance on the incisors for digging and for manipulating objects, as well as their ability to move the lower incisors independently, we hypothesized that expanded somatosensory representations of the incisors would be present within the cerebellum in order to accommodate a greater degree of proprioceptive, cutaneous, and periodontal input. Multiunit electrophysiological recordings targeting the ansiform lobule were used to investigate tactile inputs from receptive fields on the entire body with a focus on the incisors. Similar to other rodents, a fractured somatotopy appeared to be present with discrete representations of the same receptive fields repeated within each folium of the cerebellum. These findings confirm the presence of somatosensory inputs to a large area of the naked mole-rat cerebellum with particularly extensive representations of the lower incisors and mystacial vibrissae. We speculate that these extensive inputs facilitate processing of tactile cues as part of a sensorimotor integration network that optimizes how sensory stimuli are acquired through active exploration and in turn adjusts motor outputs (such as independent movement of the lower incisors). These results highlight the diverse sensory specializations and corresponding brain organizational schemes that have evolved in different mammals to facilitate exploration of and interaction with their environment.

Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario.

An adaptive filter model of cerebellar zone C3 as a basis for safe limb control?

The review asks how the adaptive filter model of the cerebellum might be relevant to experimental work on zone C3, one of the most extensively studied regions of cerebellar cortex. As far as features of the cerebellar microcircuit are concerned, the model appears to fit very well with electrophysiological discoveries concerning the importance of molecular layer interneurons and their plasticity, the significance of long-term potentiation and the striking number of silent parallel fibre synapses. Regarding external connectivity and functionality, a key feature of the adaptive filter model is its use of the decorrelation algorithm, which renders it uniquely suited to problems of sensory noise cancellation. However, this capacity can be extended to the avoidance of sensory interference, by appropriate movements of, for example, the eyes in the vestibulo-ocular reflex. Avoidance becomes particularly important when painful signals are involved, and as the climbing fibre input to zone C3 is extremely responsive to nociceptive stimuli, it is proposed that one function of this zone is the avoidance of pain by, for example, adjusting movements of the body to avoid self-harm. This hypothesis appears consistent with evidence from humans and animals concerning the role of the intermediate cerebellum in classically conditioned withdrawal reflexes, but further experiments focusing on conditioned avoidance are required to test the hypothesis more stringently. The proposed architecture may also be useful for automatic self-adjusting damage avoidance in robots, an important consideration for next generation 'soft' robots designed to interact with people.

Seeking a unified framework for cerebellar function and dysfunction: from circuit operations to cognition

Following the fundamental recognition of its involvement in sensory-motor coordination and learning, the cerebellum is now also believed to take part in the processing of cognition and emotion. This hypothesis is recurrent in numerous papers reporting anatomical and functional observations, and it requires an explanation. We argue that a similar circuit structure in all cerebellar areas may carry out various operations using a common computational scheme. On the basis of a broad review of anatomical data, it is conceivable that the different roles of the cerebellum lie in the specific connectivity of the cerebellar modules, with motor, cognitive, and emotional functions (at least partially) segregated into different cerebro-cerebellar loops. We here develop a conceptual and operational framework based on multiple interconnected levels (a meta-levels hypothesis): from cellular/molecular to network mechanisms leading to generation of computational primitives, thence to high-level cognitive/emotional processing, and finally to the sphere of mental function and dysfunction. The main concept explored is that of intimate interplay between timing and learning (reminiscent of the “timing and learning machine” capabilities long attributed to the cerebellum), which reverberates from cellular to circuit mechanisms. Subsequently, integration within large-scale brain loops could generate the disparate cognitive/emotional and mental functions in which the cerebellum has been implicated. We propose, therefore, that the cerebellum operates as a general-purpose co-processor, whose effects depend on the specific brain centers to which individual modules are connected. Abnormal functioning in these loops could eventually contribute to the pathogenesis of major brain pathologies including not just ataxia but also dyslexia, autism, schizophrenia, and depression.

Distributed synergistic plasticity and cerebellar learning

Studies on synaptic plasticity in the context of learning have been dominated by the view that a single, particular type of plasticity forms the underlying mechanism for a particular type of learning. However, emerging evidence shows that many forms of synaptic and intrinsic plasticity at different sites are induced conjunctively during procedural memory formation in the cerebellum. Here, we review the main forms of long-term plasticity in the cerebellar cortex that underlie motor learning. We propose that the different forms of plasticity in the granular layer and the molecular layer operate synergistically in a temporally and spatially distributed manner, so as to ultimately create optimal output for behaviour.