Cerebellar loops: a review of the nucleocortical pathway

Cerebellar Functions Beyond Movement and Learning

The cerebellum has a well-established role in controlling motor functions, including coordination, posture, and the learning of skilled movements. The mechanisms for how it carries out motor behavior remain under intense investigation. Interestingly though, in recent years the mechanisms of cerebellar function have faced additional scrutiny since nonmotor behaviors may also be controlled by the cerebellum. With such complexity arising, there is now a pressing need to better understand how cerebellar structure, function, and behavior intersect to influence behaviors that are dynamically called upon as an animal experiences its environment. Here, we discuss recent experimental work that frames possible neural mechanisms for how the cerebellum shapes disparate behaviors and why its dysfunction is catastrophic in hereditary and acquired conditions-both motor and nonmotor. For these reasons, the cerebellum might be the ideal therapeutic target.

Unifying biophysical consciousness theories with MaxCon: maximizing configurations of brain connectivity

There is such a vast proliferation of scientific theories of consciousness that it is worrying some scholars. There are even competitions to test different theories, and the results are inconclusive. Consciousness research, far from converging toward a unifying framework, is becoming more discordant than ever, especially with respect to theoretical elements that do not have a clear neurobiological basis. Rather than dueling theories, an integration across theories is needed to facilitate a comprehensive view on consciousness and on how normal nervous system dynamics can develop into pathological states. In dealing with what is considered an extremely complex matter, we try to adopt a perspective from which the subject appears in relative simplicity. Grounded in experimental and theoretical observations, we advance an encompassing biophysical theory, MaxCon, which incorporates aspects of several of the main existing neuroscientific consciousness theories, finding convergence points in an attempt to simplify and to understand how cellular collective activity is organized to fulfill the dynamic requirements of the diverse theories our proposal comprises. Moreover, a computable index indicating consciousness level is presented. Derived from the level of description of the interactions among cell networks, our proposal highlights the association of consciousness with maximization of the number of configurations of neural network connections -constrained by neuroanatomy, biophysics and the environment- that is common to all consciousness theories.

Decoding state-dependent cortical-cerebellar cellular functional connectivity in the mouse brain

The cortex and cerebellum form multi-synaptic reciprocal connections. We investigate the functional connectivity between single spiking cerebellar neurons and the population activity of the mouse dorsal cortex using mesoscale imaging. Cortical representations of individual cerebellar neurons vary significantly across different brain states but are drawn from a common set of cortical networks. These cortical-cerebellar connectivity features are observed in mossy fibers and Purkinje cells as well as neurons in different cerebellar lobules, albeit with variations across cell types and regions. Complex spikes of Purkinje cells preferably associate with the sensorimotor cortex, whereas simple spikes display more diverse cortical connectivity patterns. The spontaneous functional connectivity patterns align with cerebellar neurons' functional responses to external stimuli in a modality-specific manner. The tuning properties of subsets of cerebellar neurons differ between anesthesia and awake states, mirrored by state-dependent changes in their long-range functional connectivity patterns with mesoscale cortical activity.

Cerebellum Lecture: the Cerebellar Nuclei-Core of the Cerebellum

The cerebellum is a key player in many brain functions and a major topic of neuroscience research. However, the cerebellar nuclei (CN), the main output structures of the cerebellum, are often overlooked. This neglect is because research on the cerebellum typically focuses on the cortex and tends to treat the CN as relatively simple output nuclei conveying an inverted signal from the cerebellar cortex to the rest of the brain. In this review, by adopting a nucleocentric perspective we aim to rectify this impression. First, we describe CN anatomy and modularity and comprehensively integrate CN architecture with its highly organized but complex afferent and efferent connectivity. This is followed by a novel classification of the specific neuronal classes the CN comprise and speculate on the implications of CN structure and physiology for our understanding of adult cerebellar function. Based on this thorough review of the adult literature we provide a comprehensive overview of CN embryonic development and, by comparing cerebellar structures in various chordate clades, propose an interpretation of CN evolution. Despite their critical importance in cerebellar function, from a clinical perspective intriguingly few, if any, neurological disorders appear to primarily affect the CN. To highlight this curious anomaly, and encourage future nucleocentric interpretations, we build on our review to provide a brief overview of the various syndromes in which the CN are currently implicated. Finally, we summarize the specific perspectives that a nucleocentric view of the cerebellum brings, move major outstanding issues in CN biology to the limelight, and provide a roadmap to the key questions that need to be answered in order to create a comprehensive integrated model of CN structure, function, development, and evolution.

A Systematic Review of Direct Outputs from the Cerebellum to the Brainstem and Diencephalon in Mammals

The cerebellum is involved in many motor, autonomic and cognitive functions, and new tasks that have a cerebellar contribution are discovered on a regular basis. Simultaneously, our insight into the functional compartmentalization of the cerebellum has markedly improved. Additionally, studies on cerebellar output pathways have seen a renaissance due to the development of viral tracing techniques. To create an overview of the current state of our understanding of cerebellar efferents, we undertook a systematic review of all studies on monosynaptic projections from the cerebellum to the brainstem and the diencephalon in mammals. This revealed that important projections from the cerebellum, to the motor nuclei, cerebral cortex, and basal ganglia, are predominantly di- or polysynaptic, rather than monosynaptic. Strikingly, most target areas receive cerebellar input from all three cerebellar nuclei, showing a convergence of cerebellar information at the output level. Overall, there appeared to be a large level of agreement between studies on different species as well as on the use of different types of neural tracers, making the emerging picture of the cerebellar output areas a solid one. Finally, we discuss how this cerebellar output network is affected by a range of diseases and syndromes, with also non-cerebellar diseases having impact on cerebellar output areas.

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

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

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.

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

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

The Cerebellar Cortex

The cerebellar cortex is an important system for relating neural circuits and learning. Its promise reflects the longstanding idea that it contains simple, repeated circuit modules with only a few cell types and a single plasticity mechanism that mediates learning according to classical Marr-Albus models. However, emerging data have revealed surprising diversity in neuron types, synaptic connections, and plasticity mechanisms, both locally and regionally within the cerebellar cortex. In light of these findings, it is not surprising that attempts to generate a holistic model of cerebellar learning across different behaviors have not been successful. While the cerebellum remains an ideal system for linking neuronal function with behavior, it is necessary to update the cerebellar circuit framework to achieve its great promise. In this review, we highlight recent advances in our understanding of cerebellar-cortical cell types, synaptic connections, signaling mechanisms, and forms of plasticity that enrich cerebellar processing.

VTA-projecting cerebellar neurons mediate stress-dependent depression-like behaviors

Although cerebellar alterations have been implicated in stress symptoms, the exact contribution of the cerebellum to stress symptoms remains to be elucidated. Here, we demonstrated the crucial role of cerebellar neurons projecting to the ventral tegmental area (VTA) in the development of chronic stress-induced behavioral alterations in mice. Chronic chemogenetic activation of inhibitory Purkinje cells in crus I suppressed c-Fos expression in the DN and an increase in immobility in the tail suspension test or forced swimming test, which were triggered by chronic stress application. The combination of adeno-associated virus-based circuit mapping and electrophysiological recording identified network connections from crus I to the VTA via the dentate nucleus (DN) of the deep cerebellar nuclei. Furthermore, chronic inhibition of specific neurons in the DN that project to the VTA prevented stressed mice from showing such depression-like behavior, whereas chronic activation of these neurons alone triggered behavioral changes that were comparable with the depression-like behaviors triggered by chronic stress application. Our results indicate that the VTA-projecting cerebellar neurons proactively regulate the development of depression-like behavior, raising the possibility that cerebellum may be an effective target for the prevention of depressive disorders in human.

Olivocerebellar control of movement symmetry

Coordination of bilateral movements is essential for a large variety of animal behaviors. The olivocerebellar system is critical for the control of movement, but its role in bilateral coordination has yet to be elucidated. Here, we examined whether Purkinje cells encode and influence synchronicity of left-right whisker movements. We found that complex spike activity is correlated with a prominent left-right symmetry of spontaneous whisker movements within parts, but not all, of Crus1 and Crus2. Optogenetic stimulation of climbing fibers in the areas with high and low correlations resulted in symmetric and asymmetric whisker movements, respectively. Moreover, when simple spike frequency prior to the complex spike was higher, the complex spike-related symmetric whisker protractions were larger. This finding alludes to a role for rebound activity in the cerebellar nuclei, which indeed turned out to be enhanced during symmetric protractions. Tracer injections suggest that regions associated with symmetric whisker movements are anatomically connected to the contralateral cerebellar hemisphere. Together, these data point toward the existence of modules on both sides of the cerebellar cortex that can differentially promote or reduce the symmetry of left and right movements in a context-dependent fashion.

When the front fails, the rear wins. Cerebellar correlates of prefrontal dysfunction in cocaine-induced memory in male rats

Reciprocal pathways connecting the cerebellum to the prefrontal cortex provide a biological and functional substrate to modulate cognitive functions. Dysfunction of both medial prefrontal cortex (mPFC) and cerebellum underlie the phenotypes of several neuropsychiatric disorders that exhibit comorbidity with substance use disorder (SUD). In people with SUD, cue-action-reward associations appears to be particularly strong and salient, acting as powerful motivational triggers for craving and relapse. Studies of cue reactivity in human with SUD have shown cerebellar activations when drug-related cues are presented. Our preclinical research showed that cocaine-induced conditioned preference increases neural activity and upregulates perineuronal nets (PNNs) around Golgi interneurons in the posterior cerebellar cortex. In the present investigation, we aimed at evaluating cerebellar signatures of conditioned preference for cocaine when drug learning is established under mPFC impairment. We used lidocaine to temporarily inactivate in male rats either the Prelimbic (PL) or the Infralimbic (IL) cortices during cocaine-induced conditioning. The inactivation of the IL, but not the PL, encouraged the acquisition of preference for cocaine-related cues, increased posterior cerebellar cortex activity, and upregulated the expression of PNNs around Golgi interneurons. Moreover, IL impairment not only increased vGluT2- and vGAT-related activity around Golgi cells but also regulated PNNs differently on subpopulations of Golgi cells, increasing the number of neurogranin+ PNN-expressing Golgi cells. Our findings suggest that IL dysfunction may facilitate the acquisition of cocaine-induced memory and cerebellar drug-related learning hallmarks. Overall, IL perturbation during cocaine-induced Pavlovian learning increased cerebellar activity and drug effects. Importantly, cerebellum involvement requires a contingent experience with the drug, and it is not the effect of a mere inactivation of IL cortex.

Relationship Between Orthostatic Hypotension and Cognitive Functions in Multiple System Atrophy: A Longitudinal Study

Introduction: The aim of this study is to investigate the impact of orthostatic hypotension (OH) on cognitive functions in patients with multiple system atrophy (MSA) followed over time. Methods: Thirty-two MSA patients were enrolled and underwent a comprehensive neuropsychological battery; at baseline (T₀) 15 out of 32 patients presented OH, assessed by means of orthostatic standing test. All patients underwent a follow-up (T₁) evaluation 12 months after baseline. Thirteen out of 32 patients also underwent a second follow-up (T₂) evaluation at 24 months. Changes over time on different neuropsychological tasks were compared between patients with and without OH by means of Mann-Whitney's U-test. Moreover, clinical categories of normal cognition, mild cognitive impairment, and dementia were determined, and changes at T₁ and T₂ in global cognitive status were compared between patients with and without OH. Results: At T₀, patients with OH had better performance on words/non-words repetition task (p = 0.02) compared to patients without OH. Compared to patients without OH, patients with OH performed worse on semantic association task (p < 0.01) at T₁ and on Stroop test-error effect (p = 0.04) at T₂. The percentage of patients with worsened cognitive status at T₁ was higher among patients with OH than among patients without OH (93 vs. 59%, p = 0.03). OH (β = -4.67, p = 0.01), education (β = 0.45, p = 0.02), age (β = 0.19, p = 0.03), and Montreal Cognitive Assessment battery (MOCA) score at T₀ (β = -0.26, p = 0.04) were significant predictors of global cognitive status worsening at T₁. Discussion: We found that global cognitive status worsened at 1-year follow-up in 93% of patients with OH, and OH, along with age, education, and MOCA score, predicted cognitive worsening over time. To clarify the relationship between OH and cognitive dysfunction in MSA, we suggest the use of clinical categories of normal cognition, mild cognitive impairment, and dementia in further longitudinal studies on MSA patients with and without OH.

Incorporation of 5-Bromo-2'-deoxyuridine into DNA and Proliferative Behavior of Cerebellar Neuroblasts: All That Glitters Is Not Gold

The synthetic halogenated pyrimidine analog, 5-bromo-2'-deoxyuridine (BrdU), is a marker of DNA synthesis. This exogenous nucleoside has generated important insights into the cellular mechanisms of the central nervous system development in a variety of animals including insects, birds, and mammals. Despite this, the detrimental effects of the incorporation of BrdU into DNA on proliferation and viability of different types of cells has been frequently neglected. This review will summarize and present the effects of a pulse of BrdU, at doses ranging from 25 to 300 µg/g, or repeated injections. The latter, following the method of the progressively delayed labeling comprehensive procedure. The prenatal and perinatal development of the cerebellum are studied. These current data have implications for the interpretation of the results obtained by this marker as an index of the generation, migration, and settled pattern of neurons in the developing central nervous system. Caution should be exercised when interpreting the results obtained using BrdU. This is particularly important when high or repeated doses of this agent are injected. I hope that this review sheds light on the effects of this toxic maker. It may be used as a reference for toxicologists and neurobiologists given the broad use of 5-bromo-2'-deoxyuridine to label dividing cells.

Developmental timetables and gradients of neurogenesis in cerebellar Purkinje cells and deep glutamatergic neurons: A comparative study between the mouse and the rat

The aim of this report is to determine whether the times of neuron origin and neurogenetic gradients of PCs and Deep cerebellar nucli (DCN) glutamatergic neurons are different between mice and rats. Purkinje cells (PCs) were analyzed in each compartment of the cerebellar cortex (vermis, paravermis, medial, and lateral hemispheres), and deep glutamatergic neurons at the level of the medialis, interpositus, and lateralis nuclei. Tritiated thymidine ([³ H]TdR) autoradiography was applied on sections. The experimental rodents were the offspring of pregnant dams injected with [³ H]TdR on embryonic days (E) 11-12, E12-13, E13-14, E14-15, E15-16, and E16-17. Our results indicate that systematic differences exist in the pattern of neurogenesis and the spatial location of cerebellar PCs and deep glutamatergic neurons between mice and rats. In mice, PCs and deep glutamatergic neurons neurogenesis extend from E10 to E14, with a predominance of neurogenesis on E12 for PCs, and on E12, E11, and E10 for the medialis, interpositus, and lateralis neurons, respectively. When neurogenesis in rats was considered, the data reveal that PCs and deep glutamatergic neurons production extends from E12 to E16, with a peak of production on E14 for PCs, and on E14, E13, and E12 for the medialis, interpositus, and lateralis neurons, respectively. Current data also indicate that, both in mice and rats, both types of macroneurons are generated according to a lateral-to-medial gradient. Thus, the lateral hemisphere and the lateralis nucleus present more early-generated neurons than the vermis and the medialis nucleus, which in their turn have more late-produced neurons.

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

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

Evidence for Hierarchical Cognitive Control in the Human Cerebellum

In non-habitual situations, cognitive control aligns actions with both short- and long-term goals. The capacity for cognitive control is tightly tied to the prefrontal cortex, whose expansion in humans relative to other species is thought to support our superior cognitive control. However, the posterolateral cerebellum has also expanded greatly relative to non-human primates and has an organizational structure that mirrors the prefrontal cortex. Nevertheless, cerebellar contributions to cognitive control are poorly understood. Here, we sought to explore whether a functional hierarchical processing framework, applied to the cerebellum, could elucidate cerebellar contributions to cognitive control. Using functional magnetic resonance imaging, we show that a gradient within the posterolateral cerebellum supports cognitive control with motor-adjacent cerebellar sub-regions supporting control of concrete, proximal actions and motor-distal, cerebellar sub-regions supporting abstract, future processing. This gradient was functionally hierarchical, with regions higher in the hierarchy influencing the relationship between regions lower in the hierarchy. This functional hierarchy provides the infrastructure by which context can inform current actions and prepare for future goals. Crucially, this mirrors the hierarchical organization of cognitive control within the prefrontal cortex. Based on these findings, we propose that the cerebellum contains within itself a parallel but separate hierarchical organization that, along with the prefrontal cortex, supports complex cognition.

Principles of operation of a cerebellar learning circuit

We provide behavioral evidence using monkey smooth pursuit eye movements for four principles of cerebellar learning. Using a circuit-level model of the cerebellum, we link behavioral data to learning's neural implementation. The four principles are: (1) early, fast, acquisition driven by climbing fiber inputs to the cerebellar cortex, with poor retention; (2) learned responses of Purkinje cells guide transfer of learning from the cerebellar cortex to the deep cerebellar nucleus, with excellent retention; (3) functionally different neural signals are subject to learning in the cerebellar cortex versus the deep cerebellar nuclei; and (4) negative feedback from the cerebellum to the inferior olive reduces the magnitude of the teaching signal in climbing fibers and limits learning. Our circuit-level model, based on these four principles, explains behavioral data obtained by strategically manipulating the signals responsible for acquisition and recall of direction learning in smooth pursuit eye movements across multiple timescales.

Neural Evidence of the Cerebellum as a State Predictor

We here provide neural evidence that the cerebellar circuit can predict future inputs from present outputs, a hallmark of an internal forward model. Recent computational studies hypothesize that the cerebellum performs state prediction known as a forward model. To test the forward-model hypothesis, we analyzed activities of 94 mossy fibers (inputs to the cerebellar cortex), 83 Purkinje cells (output from the cerebellar cortex to dentate nucleus), and 73 dentate nucleus cells (cerebellar output) in the cerebro-cerebellum, all recorded from a monkey performing step-tracking movements of the right wrist. We found that the firing rates of one population could be reconstructed as a weighted linear sum of those of preceding populations. We then went on to investigate if the current outputs of the cerebellum (dentate cells) could predict the future inputs of the cerebellum (mossy fibers). The firing rates of mossy fibers at time t + t₁ could be well reconstructed from as a weighted sum of firing rates of dentate cells at time t, thereby proving that the dentate activities contained predictive information about the future inputs. The average goodness-of-fit (R²) decreased moderately from 0.89 to 0.86 when t₁ was increased from 20 to 100 ms, hence indicating that the prediction is able to compensate the latency of sensory feedback. The linear equations derived from the firing rates resembled those of a predictor known as Kalman filter composed of prediction and filtering steps. In summary, our analysis of cerebellar activities supports the forward-model hypothesis of the cerebellum.

Computational Principles of Supervised Learning in the Cerebellum

Supervised learning plays a key role in the operation of many biological and artificial neural networks. Analysis of the computations underlying supervised learning is facilitated by the relatively simple and uniform architecture of the cerebellum, a brain area that supports numerous motor, sensory, and cognitive functions. We highlight recent discoveries indicating that the cerebellum implements supervised learning using the following organizational principles: ( a) extensive preprocessing of input representations (i.e., feature engineering), ( b) massively recurrent circuit architecture, ( c) linear input-output computations, ( d) sophisticated instructive signals that can be regulated and are predictive, ( e) adaptive mechanisms of plasticity with multiple timescales, and ( f) task-specific hardware specializations. The principles emerging from studies of the cerebellum have striking parallels with those in other brain areas and in artificial neural networks, as well as some notable differences, which can inform future research on supervised learning and inspire next-generation machine-based algorithms.

Corollary Discharge Signals in the Cerebellum

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

Localization of AMPA, kainate, and NMDA receptor mRNAs in the pigeon cerebellum

In the present study, we investigated the location of mRNAs for three types of ionotropic glutamate receptors (iGluRs) in the pigeon cerebellum and then compared the results with those of mammals. The following nine iGluRs subunits were analyzed by in situ hybridization: AMPA receptors (GluA1, GluA2, GluA3, and GluA4), kainate receptors (GluK1, GluK2, and GluK4), and NMDA receptors (GluN1 and GluN2A). Subunit hybridization revealed expression in different cell types of the cerebellar cortex: Purkinje cells expressed most subunits, including AMPA receptors (GluA1, GluA2, and GluA3), kainate receptors (GluK1 and GluK4), and NMDA receptors (GluN1); granule cells expressed four subunits of kainate (GluK1 and GluK2) and NMDA receptors (GluN1 and GluN2A); stellate and basket cells expressed GluK1, GluK2, and GluN1; Golgi cells expressed GluA1, GluA3, and GluN1; and Bergmann glial cells expressed only AMPA receptors (GluA2 and GluA4). Cerebellar nuclei showed no AMPA subunit signals, whereas kainate and NMDA receptors were observed in the five cerebellar nuclei divisions (CbL, CbMic, CbMim, CbMin, and CbMvm). The five divisions showed weak expression of GluK1, GluK2, and GluN2A; moderate to intense expression of GluK4; and intense expression of GluN1. These results demonstrate that in pigeons the cerebellar cortex expresses AMPA, kainate, and NMDA receptors, while the cerebellar nuclei express kainate and NMDA receptors. Taken together, these findings provide anatomical data for further analysis of the functions of iGluR-expressing neurons in glutamatergic circuits of the avian cerebellum.

Re-evaluating Circuit Mechanisms Underlying Pattern Separation

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

Sox14 Is Required for a Specific Subset of Cerebello-Olivary Projections

We identify Sox14 as an exclusive marker of inhibitory projection neurons in the lateral and interposed, but not the medial, cerebellar nuclei. Sox14⁺ neurons make up ∼80% of Gad1⁺ neurons in these nuclei and are indistinguishable by soma size from other inhibitory neurons. All Sox14⁺ neurons of the lateral and interposed cerebellar nuclei are generated at approximately E10/10.5 and extend long-range, predominantly contralateral projections to the inferior olive. A small Sox14⁺ population in the adjacent vestibular nucleus "Y" sends an ipsilateral projection to the oculomotor nucleus. Cerebellar Sox14⁺ and glutamatergic projection neurons assemble in non-overlapping populations at the nuclear transition zone, and their integration into a coherent nucleus depends on Sox14 function. Targeted ablation of Sox14⁺ cells by conditional viral expression of diphtheria toxin leads to significantly impaired motor learning. Contrary to expectations, associative learning is unaffected by unilateral Sox14⁺ neuron elimination in the interposed and lateral nuclei.SIGNIFICANCE STATEMENT The cerebellar nuclei are central to cerebellar function, yet how they modulate and process cerebellar inputs and outputs is still primarily unknown. Our study gives a direct insight into how nucleo-olivary projection neurons are generated, their projections, and their function in an intact behaving mouse. These neurons play a critical conceptual role in all models of cerebellar function, and this study represents the first specific analysis of their molecular identity and function and offers a powerful model for future investigation of cerebellar function in motor control and learning.

Morphological Constraints on Cerebellar Granule Cell Combinatorial Diversity

Combinatorial expansion by the cerebellar granule cell layer (GCL) is fundamental to theories of cerebellar contributions to motor control and learning. Granule cells (GrCs) sample approximately four mossy fiber inputs and are thought to form a combinatorial code useful for pattern separation and learning. We constructed a spatially realistic model of the cerebellar GCL and examined how GCL architecture contributes to GrC combinatorial diversity. We found that GrC combinatorial diversity saturates quickly as mossy fiber input diversity increases, and that this saturation is in part a consequence of short dendrites, which limit access to diverse inputs and favor dense sampling of local inputs. This local sampling also produced GrCs that were combinatorially redundant, even when input diversity was extremely high. In addition, we found that mossy fiber clustering, which is a common anatomical pattern, also led to increased redundancy of GrC input combinations. We related this redundancy to hypothesized roles of temporal expansion of GrC information encoding in service of learned timing, and we show that GCL architecture produces GrC populations that support both temporal and combinatorial expansion. Finally, we used novel anatomical measurements from mice of either sex to inform modeling of sparse and filopodia-bearing mossy fibers, finding that these circuit features uniquely contribute to enhancing GrC diversification and redundancy. Our results complement information theoretic studies of granule layer structure and provide insight into the contributions of granule layer anatomical features to afferent mixing.SIGNIFICANCE STATEMENT Cerebellar granule cells are among the simplest neurons, with tiny somata and, on average, just four dendrites. These characteristics, along with their dense organization, inspired influential theoretical work on the granule cell layer as a combinatorial expander, where each granule cell represents a unique combination of inputs. Despite the centrality of these theories to cerebellar physiology, the degree of expansion supported by anatomically realistic patterns of inputs is unknown. Using modeling and anatomy, we show that realistic input patterns constrain combinatorial diversity by producing redundant combinations, which nevertheless could support temporal diversification of like combinations, suitable for learned timing. Our study suggests a neural substrate for producing high levels of both combinatorial and temporal diversity in the granule cell layer.

Motor Imagery-Based Rehabilitation: Potential Neural Correlates and Clinical Application for Functional Recovery of Motor Deficits after Stroke

Motor imagery (MI), defined as the mental implementation of an action in the absence of movement or muscle activation, is a rehabilitation technique that offers a means to replace or restore lost motor function in stroke patients when used in conjunction with conventional physiotherapy procedures. This article briefly reviews the concepts and neural correlates of MI in order to promote improved understanding, as well as to enhance the clinical utility of MI-based rehabilitation regimens. We specifically highlight the role of the cerebellum and basal ganglia, premotor, supplementary motor, and prefrontal areas, primary motor cortex, and parietal cortex. Additionally, we examine the recent literature related to MI and its potential as a therapeutic technique in both upper and lower limb stroke rehabilitation.

Dysplastic Cerebellar Epilepsy: Complete Seizure Control Following Resection of a Ganglioglioma

Subcortical epilepsy has been a controversial issue, partially settled by evidence showing seizure generation in hypothalamic hamartomas and also by reports of seizures caused by cerebellar lesions. We report 4-year-old girl with right hemifacial seizures and autonomic phenomena, in whom MRI showed an irregular mass in the right cerebellar peduncle. Despite several unremarkable video-EEG recordings, seizure origin in the lesion was hypothesized. Complete resection was feasible, histopathology showed a ganglioglioma, and she has been seizure free for 3 years. A fine line separates these developmental tumors from focal cortical dysplasia, and the homogeneous presentation of this entity led us to propose the terminology dysplastic cerebellar epilepsy.

Caveats in Transneuronal Tracing with Unmodified Rabies Virus: An Evaluation of Aberrant Results Using a Nearly Perfect Tracing Technique

Apart from the genetically engineered, modified, strains of rabies virus (RABV), unmodified ‘fixed’ virus strains of RABV, such as the ‘French’ subtype of CVS11, are used to examine synaptically connected networks in the brain. This technique has been shown to have all the prerequisite characteristics for ideal tracing as it does not metabolically affect infected neurons within the time span of the experiment, it is transferred transneuronally in one direction only and to all types of neurons presynaptic to the infected neuron, number of transneuronal steps can be precisely controlled by survival time and it is easily detectable with a sensitive technique. Here, using the ‘French’ CVS 11 subtype of RABV in Wistar rats, we show that some of these characteristics may not be as perfect as previously indicated. Using injection of RABV in hind limb muscles, we show that RABV-infected spinal motoneurons may already show lysis 1 or 2 days after infection. Using longer survival times we were able to establish that Purkinje cells may succumb approximately 3 days after infection. In addition, some neurons seem to resist infection, as we noted that the number of RABV-infected inferior olivary neurons did not progress in the same rate as other infected neurons. Furthermore, in our hands, we noted that infection of Purkinje cells did not result in expected transneuronal labeling of cell types that are presynaptic to Purkinje cells such as molecular layer interneurons and granule cells. However, these cell types were readily infected when RABV was injected directly in the cerebellar cortex. Conversely, neurons in the cerebellar nuclei that project to the inferior olive did not take up RABV when this was injected in the inferior olive, whereas these cells could be infected with RABV via a transneuronal route. These results suggest that viral entry from the extracellular space depends on other factors or mechanisms than those used for retrograde transneuronal transfer. We conclude that transneuronal tracing with RABV may result in unexpected results, as not all properties of RABV seem to be ubiquitously valid.

Recurrent Feedback Loops in Associative Learning

In this issue of Neuron, Gao et al. (2016) report on a little-studied feedback pathway from the cerebellar nuclei back to the cerebellar cortex. They find that it contributes to associative conditioning and execution of learned movements, highlighting a role for local feedback loops in the brain.

Tactile Stimulation Evokes Long-Lasting Potentiation of Purkinje Cell Discharge In Vivo

In the cerebellar network, a precise relationship between plasticity and neuronal discharge has been predicted. However, the potential generation of persistent changes in Purkinje cell (PC) spike discharge as a consequence of plasticity following natural stimulation patterns has not been clearly determined. Here, we show that facial tactile stimuli organized in theta-patterns can induce stereotyped N-methyl-D-aspartate (NMDA) and gamma-aminobutyric acid (GABA-A) receptor-dependent changes in PCs and molecular layer interneurons (MLIs) firing: invariably, all PCs showed a long-lasting increase (Spike-Related Potentiation or SR-P) and MLIs a long-lasting decrease (Spike-Related Suppression or SR-S) in baseline activity and spike response probability. These observations suggests that tactile sensory stimulation engages multiple long-term plastic changes that are distributed along the mossy fiber-parallel fiber (MF-PF) pathway and operate synergistically to potentiate spike generation in PCs. In contrast, theta-pattern electrical stimulation (ES) of PFs indistinctly induced SR-P and SR-S both in PCs and MLIs, suggesting that tactile sensory stimulation preordinates plasticity upstream of the PF-PC synapse. All these effects occurred in the absence of complex spike changes, supporting the theoretical prediction that PC activity is potentiated when the MF-PF system is activated in the absence of conjunctive climbing fiber (CF) activity.

Generation and vulnerability of deep cerebellar nuclei neurons in the weaver condition along the anteroposterior and mediolateral axes

Production and death of deep cerebellar nuclei (DCN) neurons were investigated in the weaver condition at appropriate anatomical levels throughout the mediolateral (medial, intermediate and lateral) and rostrocaudal (rostral, middle and caudal) axes of three DCN-cell groups: the fastigial, the interposed and the dentate nuclei. Current results have denoted that the deficit of DCN neurons is always more important in the homozygous weaver than in the heterozygous weaver mice. No loss of neurons was found in the dentate nucleus. In the mediolateral axis, an intranuclear gradient of depletion was observed in the mutant mice; in a given deep nucleus, neurodegeneration was more prominent in the medial pars than in lateral ones. In the rostrocaudal axis, on the other hand, when each deep nucleus was studied and compared as a whole, neuron loss was higher in the fastigial nucleus than in the interposed nucleus, which, in turn, was more important than in the dentate nucleus. These data suggest that, in the weaver condition, an internuclear gradient of neurodegeneration exists. Moreover, neurons located in rostral parts of a given nucleus appear to be more vulnerable than those settled in middle parts and these, in turn, are more than the caudal ones. These results seem to indicate the presence of an intranuclear gradient of depletion. Current autoradiographic results have revealed that, in the rostrocaudal axis, deep neurons are settled in the weaver cerebellum following three neurogenetic gradients. The first of these is internuclear; if each deep nucleus is analyzed and compared as a whole, the fastigial nucleus has more late-generated neurons than the interposed nucleus, and this, in turn, has more than the dentate nucleus. The second gradient is also internuclear; if the proportion of late-born neurons is compared throughout the rostral levels from each deep nucleus, it is observed that proportions increase from the fastigial to the dentate nucleus. A similar picture emerges when the middle and caudal regions are taken into account. The third gradient is intranuclear; in a given deep nucleus, the rostral region always presents more late-produced neurons than the middle region and these, in turn, more than in the caudal level.

At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters

Models of the cerebellar microcircuit often assume that input signals from the mossy-fibers are expanded and recoded to provide a foundation from which the Purkinje cells can synthesize output filters to implement specific input-signal transformations. Details of this process are however unclear. While previous work has shown that recurrent granule cell inhibition could in principle generate a wide variety of random outputs suitable for coding signal onsets, the more general application for temporally varying signals has yet to be demonstrated. Here we show for the first time that using a mechanism very similar to reservoir computing enables random neuronal networks in the granule cell layer to provide the necessary signal separation and extension from which Purkinje cells could construct basis filters of various time-constants. The main requirement for this is that the network operates in a state of criticality close to the edge of random chaotic behavior. We further show that the lack of recurrent excitation in the granular layer as commonly required in traditional reservoir networks can be circumvented by considering other inherent granular layer features such as inverted input signals or mGluR2 inhibition of Golgi cells. Other properties that facilitate filter construction are direct mossy fiber excitation of Golgi cells, variability of synaptic weights or input signals and output-feedback via the nucleocortical pathway. Our findings are well supported by previous experimental and theoretical work and will help to bridge the gap between system-level models and detailed models of the granular layer network.

The Global Cognition, Frontal Lobe Dysfunction and Behavior Changes in Chinese Patients with Multiple System Atrophy

BACKGROUND

Studies on cognition in multiple system atrophy (MSA) patients are limited.

METHODS

A total of 110 MSA patients were evaluated using Addenbrooke's Cognitive Examination-Revised (ACE-R), Frontal Assessment Battery (FAB), Frontal Behavioral Inventory (FBI), and Unified MSA Rating Scale (UMSARS) tests. Fifty-five age-, sex-, education- and domicile-matched healthy controls were recruited to perform the FAB and ACE-R scales.

RESULTS

Approximately 32.7% of the patients had global cognitive deficits with the most impaired domain being verbal fluency and visuospatial ability (26.4%), followed by memory (24.5%), language (20%) and orientation/attention (20%) based on a cut-off score of ACE-R ≤ 70. A total of 41.6% of the patients had frontal lobe dysfunction, with inhibitory control (60.9%) as the most impaired domain based on a cut-off score of FAB ≤14. Most patients (57.2%) showed moderate frontal behavior changes (FBI score 4-15), with incontinence (64.5%) as the most impaired domain. The binary logistic regression model revealed that an education level < 9 years (OR:13.312, 95% CI:2.931-60.469, P = 0.001) and UMSARS ≥ 40 (OR: 2.444, 95%CI: 1.002-5.962, P< 0.049) were potential determinants of abnormal ACE-R, while MSA-C (OR: 4.326, 95%CI: 1.631-11.477, P = 0.003), an education level < 9 years (OR:2.809 95% CI:1.060-7.444, P = 0.038) and UMSARS ≥ 40 (OR:5.396, 95%CI: 2.103-13.846, P < 0.0001) were potential determinants of abnormal FAB.

CONCLUSIONS

Cognitive impairment is common in Chinese MSA patients. MSA-C patients with low education levels and severe motor symptoms are likely to experience frontal lobe dysfunction, while MSA patients with low education levels and severe motor symptoms are likely to experience global cognitive deficits. These findings strongly suggest that cognitive impairment should not be an exclusion criterion for the diagnosis of MSA.

The neurobiology of pain perception in normal and persistent pain

SUMMARY 

Pain is a significant national burden in terms of patient suffering, expenditure and lost productivity. Understanding pain is fundamental to improving evaluation, treatment and innovation in the management of acute and persistent pain syndromes. Pain perception begins in the periphery, and then ascends in several tracts, relaying at different levels. Pain signals arrive in the thalamus and midbrain structures which form the pain neuromatrix, a constantly shifting set of networks and connections that determine conscious perception. Several cortical regions become active simultaneously during pain perception; activity in the cortical pain matrix evolves over time to produce a complex pain perception network. Dysfunction at any level has the potential to produce unregulated, persistent pain.

A novel inhibitory nucleo-cortical circuit controls cerebellar Golgi cell activity

The cerebellum, a crucial center for motor coordination, is composed of a cortex and several nuclei. The main mode of interaction between these two parts is considered to be formed by the inhibitory control of the nuclei by cortical Purkinje neurons. We now amend this view by showing that inhibitory GABA-glycinergic neurons of the cerebellar nuclei (CN) project profusely into the cerebellar cortex, where they make synaptic contacts on a GABAergic subpopulation of cerebellar Golgi cells. These spontaneously firing Golgi cells are inhibited by optogenetic activation of the inhibitory nucleo-cortical fibers both in vitro and in vivo. Our data suggest that the CN may contribute to the functional recruitment of the cerebellar cortex by decreasing Golgi cell inhibition onto granule cells.

Cerebellar Premotor Output Neurons Collateralize to Innervate the Cerebellar Cortex

Motor commands computed by the cerebellum are hypothesized to use corollary discharge, or copies of outgoing commands, to accelerate motor corrections. Identifying sources of corollary discharge, therefore, is critical for testing this hypothesis. Here we verified that the pathway from the cerebellar nuclei to the cerebellar cortex in mice includes collaterals of cerebellar premotor output neurons, mapped this collateral pathway, and identified its postsynaptic targets. Following bidirectional tracer injections into a distal target of the cerebellar nuclei, the ventrolateral thalamus, we observed retrogradely labeled somata in the cerebellar nuclei and mossy fiber terminals in the cerebellar granule layer, consistent with collateral branching. Corroborating these observations, bidirectional tracer injections into the cerebellar cortex retrogradely labeled somata in the cerebellar nuclei and boutons in the ventrolateral thalamus. To test whether nuclear output neurons projecting to the red nucleus also collateralize to the cerebellar cortex, we used a Cre-dependent viral approach, avoiding potential confounds of direct red nucleus-to-cerebellum projections. Injections of a Cre-dependent GFP-expressing virus into Ntsr1-Cre mice, which express Cre selectively in the cerebellar nuclei, retrogradely labeled somata in the interposed nucleus, and putative collateral branches terminating as mossy fibers in the cerebellar cortex. Postsynaptic targets of all labeled mossy fiber terminals were identified using immunohistochemical Golgi cell markers and electron microscopic profiles of granule cells, indicating that the collaterals of nuclear output neurons contact both Golgi and granule cells. These results clarify the organization of a subset of nucleocortical projections that constitute an experimentally accessible corollary discharge pathway within the cerebellum.

Integration of Purkinje cell inhibition by cerebellar nucleo-olivary neurons

Neurons in the cerebellar cortex, cerebellar nuclei, and inferior olive (IO) form a trisynaptic loop critical for motor learning. IO neurons excite Purkinje cells via climbing fibers and depress their parallel fiber inputs. Purkinje cells inhibit diverse cells in the cerebellar nuclei, including small GABAergic nucleo-olivary neurons that project to the IO. To investigate how these neurons integrate synaptic signals from Purkinje cells, we retrogradely labeled nucleo-olivary cells in the contralateral interpositus and lateral nuclei with cholera toxin subunit B-Alexa Fluor 488 and recorded their electrophysiological properties in cerebellar slices from weanling mice. Nucleo-olivary cells fired action potentials over a relatively narrow dynamic range (maximal rate, ∼ 70 spikes/s), unlike large cells that project to premotor areas (maximal rate, ∼ 400 spikes/s). GABA(A) receptor-mediated IPSCs evoked by electrical or optogenetic stimulation of Purkinje cells were more than 10-fold slower in nucleo-olivary cells (decay time, ∼ 25 ms) than in large cells (∼ 2 ms), and repetitive stimulation at 20-150 Hz evoked greatly summating IPSCs. Nucleo-olivary firing rates varied inversely with IPSP frequency, and the timing of Purkinje IPSPs and nucleo-olivary spikes was uncorrelated. These attributes contrast with large cells, whose brief IPSCs and rapid firing rates can permit well timed postinhibitory spiking. Thus, the intrinsic and synaptic properties of these two projection neurons from the cerebellar nuclei tailor them for differential integration and transmission of their Purkinje cell input.

Differential GABAergic and glycinergic inputs of inhibitory interneurons and Purkinje cells to principal cells of the cerebellar nuclei

The principal neurons of the cerebellar nuclei (CN), the sole output of the olivo-cerebellar system, receive a massive inhibitory input from Purkinje cells (PCs) of the cerebellar cortex. Morphological evidence suggests that CN principal cells are also contacted by inhibitory interneurons, but the properties of this connection are unknown. Using transgenic, tracing, and immunohistochemical approaches in mice, we show that CN interneurons form a large heterogeneous population with GABA/glycinergic phenotypes, distinct from GABAergic olive-projecting neurons. CN interneurons are found to contact principal output neurons, via glycine receptor (GlyR)-enriched synapses, virtually devoid of the main GABA receptor (GABAR) subunits α1 and γ2. Those clusters account for 5% of the total number of inhibitory receptor clusters on principal neurons. Brief optogenetic stimulations of CN interneurons, through selective expression of channelrhodopsin 2 after viral-mediated transfection of the flexed gene in GlyT2-Cre transgenic mice, evoked fast IPSCs in principal cells. GlyR activation accounted for 15% of interneuron IPSC amplitude, while the remaining current was mediated by activation of GABAR. Surprisingly, small GlyR clusters were also found at PC synapses onto principal CN neurons in addition to α1 and γ2 GABAR subunits. However, GlyR activation was found to account for <3% of the PC inhibitory synaptic currents evoked by electrical stimulation. This work establishes CN glycinergic neurons as a significant source of inhibition to CN principal cells, forming contacts molecularly distinct from, but functionally similar to, Purkinje cell synapses. Their impact on CN output, motor learning, and motor execution deserves further investigation.