Excitatory Cerebellar Nucleocortical Circuit Provides Internal Amplification during Associative Conditioning

Synergistic excitability plasticity in cerebellar functioning

The cerebellum, a universal processor for sensory acquisition and internal models, and its association with synaptic and nonsynaptic plasticity have been envisioned as the biological correlates of learning, perception, and even thought. Indeed, the cerebellum is no longer considered merely as the locus of motor coordination and its learning. Here, we introduce the mechanisms underlying the induction of multiple types of plasticity in cerebellar circuit and give an overview focusing on the plasticity of nonsynaptic intrinsic excitability. The discovery of long-term potentiation of synaptic responsiveness in hippocampal neurons led investigations into changes of their intrinsic excitability. This activity-dependent potentiation of neuronal excitability is distinct from that of synaptic efficacy. Systematic examination of excitability plasticity has indicated that the modulation of various types of Ca²⁺ - and voltage-dependent K⁺ channels underlies the phenomenon, which is also triggered by immune activity. Intrinsic plasticity is expressed specifically on dendrites and modifies the integrative processing and filtering effect. In Purkinje cells, modulation of the discordance of synaptic current on soma and dendrite suggested a novel type of cellular learning mechanism. This property enables a plausible synergy between synaptic efficacy and intrinsic excitability, by amplifying electrical conductivity and influencing the polarity of bidirectional synaptic plasticity. Furthermore, the induction of intrinsic plasticity in the cerebellum correlates with motor performance and cognitive processes, through functional connections from the cerebellar nuclei to neocortex and associated regions: for example, thalamus and midbrain. Taken together, recent advances in neuroscience have begun to shed light on the complex functioning of nonsynaptic excitability and the synergy.

The Optogenetic Revolution in Cerebellar Investigations

The cerebellum is most renowned for its role in sensorimotor control and coordination, but a growing number of anatomical and physiological studies are demonstrating its deep involvement in cognitive and emotional functions. Recently, the development and refinement of optogenetic techniques boosted research in the cerebellar field and, impressively, revolutionized the methodological approach and endowed the investigations with entirely new capabilities. This translated into a significant improvement in the data acquired for sensorimotor tests, allowing one to correlate single-cell activity with motor behavior to the extent of determining the role of single neuronal types and single connection pathways in controlling precise aspects of movement kinematics. These levels of specificity in correlating neuronal activity to behavior could not be achieved in the past, when electrical and pharmacological stimulations were the only available experimental tools. The application of optogenetics to the investigation of the cerebellar role in higher-order and cognitive functions, which involves a high degree of connectivity with multiple brain areas, has been even more significant. It is possible that, in this field, optogenetics has changed the game, and the number of investigations using optogenetics to study the cerebellar role in non-sensorimotor functions in awake animals is growing. The main issues addressed by these studies are the cerebellar role in epilepsy (through connections to the hippocampus and the temporal lobe), schizophrenia and cognition, working memory for decision making, and social behavior. It is also worth noting that optogenetics opened a new perspective for cerebellar neurostimulation in patients (e.g., for epilepsy treatment and stroke rehabilitation), promising unprecedented specificity in the targeted pathways that could be either activated or inhibited.

Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum during passive whole-body self-motion

Theories of cerebellar functions posit that the cerebellum implements internal models for online correction of motor actions and sensory estimation. As an example of such computations, an internal model resolves a sensory ambiguity where the peripheral otolith organs in the inner ear sense both head tilts and translations. Here we exploit the response dynamics of two functionally coupled Purkinje cell types in the vestibular part of the caudal vermis (lobules IX and X) to understand their role in this computation. We find that one population encodes tilt velocity, whereas the other, translation-selective, population encodes linear acceleration. We predict that an intermediate neuronal type should temporally integrate the output of tilt-selective cells into a tilt position signal.

Gradients in the mammalian cerebellar cortex enable Fourier-like transformation and improve storing capacity

Cerebellar granule cells (GCs) make up the majority of all neurons in the vertebrate brain, but heterogeneities among GCs and potential functional consequences are poorly understood. Here, we identified unexpected gradients in the biophysical properties of GCs in mice. GCs closer to the white matter (inner-zone GCs) had higher firing thresholds and could sustain firing with larger current inputs than GCs closer to the Purkinje cell layer (outer-zone GCs). Dynamic Clamp experiments showed that inner- and outer-zone GCs preferentially respond to high- and low-frequency mossy fiber inputs, respectively, enabling dispersion of the mossy fiber input into its frequency components as performed by a Fourier transformation. Furthermore, inner-zone GCs have faster axonal conduction velocity and elicit faster synaptic potentials in Purkinje cells. Neuronal network modeling revealed that these gradients improve spike-timing precision of Purkinje cells and decrease the number of GCs required to learn spike-sequences. Thus, our study uncovers biophysical gradients in the cerebellar cortex enabling a Fourier-like transformation of mossy fiber inputs.

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.

Consensus Paper: Experimental Neurostimulation of the Cerebellum

The cerebellum is best known for its role in controlling motor behaviors. However, recent work supports the view that it also influences non-motor behaviors. The contribution of the cerebellum towards different brain functions is underscored by its involvement in a diverse and increasing number of neurological and neuropsychiatric conditions including ataxia, dystonia, essential tremor, Parkinson's disease (PD), epilepsy, stroke, multiple sclerosis, autism spectrum disorders, dyslexia, attention deficit hyperactivity disorder (ADHD), and schizophrenia. Although there are no cures for these conditions, cerebellar stimulation is quickly gaining attention for symptomatic alleviation, as cerebellar circuitry has arisen as a promising target for invasive and non-invasive neuromodulation. This consensus paper brings together experts from the fields of neurophysiology, neurology, and neurosurgery to discuss recent efforts in using the cerebellum as a therapeutic intervention. We report on the most advanced techniques for manipulating cerebellar circuits in humans and animal models and define key hurdles and questions for moving forward.

Diverse Neuron Properties and Complex Network Dynamics in the Cerebellar Cortical Inhibitory Circuit

Neuronal inhibition can be defined as a spatiotemporal restriction or suppression of local microcircuit activity. The importance of inhibition relies in its fundamental role in shaping signal processing in single neurons and neuronal circuits. In this context, the activity of inhibitory interneurons proved the key to endow networks with complex computational and dynamic properties. In the last 50 years, the prevailing view on the functional role of cerebellar cortical inhibitory circuits was that excitatory and inhibitory inputs sum spatially and temporally in order to determine the motor output through Purkinje cells (PCs). Consequently, cerebellar inhibition has traditionally been conceived in terms of restricting or blocking excitation. This assumption has been challenged, in particular in the cerebellar cortex where all neurons except granule cells (and unipolar brush cells in specific lobules) are inhibitory and fire spontaneously at high rates. Recently, a combination of electrophysiological recordings in vitro and in vivo, imaging, optogenetics and computational modeling, has revealed that inhibitory interneurons play a much more complex role in regulating cerebellar microcircuit functions: inhibition shapes neuronal response dynamics in the whole circuit and eventually regulate the PC output. This review elaborates current knowledge on cerebellar inhibitory interneurons [Golgi cells, Lugaro cells (LCs), basket cells (BCs) and stellate cells (SCs)], starting from their ontogenesis and moving up to their morphological, physiological and plastic properties, and integrates this knowledge with that on the more renown granule cells and PCs. We will focus on the circuit loops in which these interneurons are involved and on the way they generate feed-forward, feedback and lateral inhibition along with complex spatio-temporal response dynamics. In this perspective, inhibitory interneurons emerge as the real controllers of cerebellar functioning.

Precision of Discrete and Rhythmic Forelimb Movements Requires a Distinct Neuronal Subpopulation in the Interposed Anterior Nucleus

The deep cerebellar nuclei (DCN) represent output channels of the cerebellum, and they transmit integrated sensorimotor signals to modulate limb movements. But the functional relevance of identifiable neuronal subpopulations within the DCN remains unclear. Here, we examine a genetically tractable population of neurons in the mouse interposed anterior nucleus (IntA). We show that these neurons represent a subset of glutamatergic neurons in the IntA and constitute a specific element of an internal feedback circuit within the cerebellar cortex and cerebello-thalamo-cortical pathway associated with limb control. Ablation and optogenetic stimulation of these neurons disrupt efficacy of skilled reach and locomotor movement and reveal that they control positioning and timing of the forelimb and hindlimb. Together, our findings uncover the function of a distinct neuronal subpopulation in the deep cerebellum and delineate the anatomical substrates and kinematic parameters through which it modulates precision of discrete and rhythmic limb movements.

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.

Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network

Reconstructing neuronal microcircuits through computational models is fundamental to simulate local neuronal dynamics. Here a scaffold model of the cerebellum has been developed in order to flexibly place neurons in space, connect them synaptically, and endow neurons and synapses with biologically-grounded mechanisms. The scaffold model can keep neuronal morphology separated from network connectivity, which can in turn be obtained from convergence/divergence ratios and axonal/dendritic field 3D geometries. We first tested the scaffold on the cerebellar microcircuit, which presents a challenging 3D organization, at the same time providing appropriate datasets to validate emerging network behaviors. The scaffold was designed to integrate the cerebellar cortex with deep cerebellar nuclei (DCN), including different neuronal types: Golgi cells, granule cells, Purkinje cells, stellate cells, basket cells, and DCN principal cells. Mossy fiber inputs were conveyed through the glomeruli. An anisotropic volume (0.077 mm³) of mouse cerebellum was reconstructed, in which point-neuron models were tuned toward the specific discharge properties of neurons and were connected by exponentially decaying excitatory and inhibitory synapses. Simulations using both pyNEST and pyNEURON showed the emergence of organized spatio-temporal patterns of neuronal activity similar to those revealed experimentally in response to background noise and burst stimulation of mossy fiber bundles. Different configurations of granular and molecular layer connectivity consistently modified neuronal activation patterns, revealing the importance of structural constraints for cerebellar network functioning. The scaffold provided thus an effective workflow accounting for the complex architecture of the cerebellar network. In principle, the scaffold can incorporate cellular mechanisms at multiple levels of detail and be tuned to test different structural and functional hypotheses. A future implementation using detailed 3D multi-compartment neuron models and dynamic synapses will be needed to investigate the impact of single neuron properties on network computation.

Memristor in a Reservoir System-Experimental Evidence for High-Level Computing and Neuromorphic Behavior of PbI2

Lead halides in an asymmetric layered structure form memristive devices which are controlled by the electronic structure of the PbX₂|metal interface. In this paper, we explain the mechanism that stands behind the I- V pinched hysteresis loop of the device and shortly present its synaptic-like plasticity (spike-timing-dependent plasticity and spike-rate-dependent plasticity) and nonvolatile memory effects. This memristive element was incorporated into a reservoir system, in particular, the echo-state network with delayed feedback, which exhibits brain-like recurrent behavior and demonstrates metaplasticity as one of the available learning mechanisms. It can serve as a classification system that classifies input signals according to their amplitude.

A Working Hypothesis for the Role of the Cerebellum in Impulsivity and Compulsivity

Growing evidence associates cerebellar abnormalities with several neuropsychiatric disorders in which compulsive symptomatology and impulsivity are part of the disease pattern. Symptomatology of autism, addiction, obsessive-compulsive (OCD), and attention deficit/hyperactivity (ADHD) disorders transcends the sphere of motor dysfunction and essentially entails integrative processes under control of prefrontal-thalamic-cerebellar loops. Patients with brain lesions affecting the cortico-striatum thalamic circuitry and the cerebellum indeed exhibit compulsive symptoms. Specifically, lesions of the posterior cerebellar vermis cause affective dysregulation and deficits in executive function. These deficits may be due to impairment of one of the main functions of the cerebellum, implementation of forward internal models of the environment. Actions that are independent of internal models may not be guided by predictive relationships or a mental representation of the goal. In this review article, we explain how this deficit might affect executive functions. Additionally, regionalized cerebellar lesions have been demonstrated to impair other brain functions such as the emergence of habits and behavioral inhibition, which are also altered in compulsive disorders. Similar to the infralimbic cortex, clinical studies and research in animal models suggest that the cerebellum is not required for learning goal-directed behaviors, but it is critical for habit formation. Despite this accumulating data, the role of the cerebellum in compulsive symptomatology and impulsivity is still a matter of discussion. Overall, findings point to a modulatory function of the cerebellum in terminating or initiating actions through regulation of the prefrontal cortices. Specifically, the cerebellum may be crucial for restraining ongoing actions when environmental conditions change by adjusting prefrontal activity in response to the new external and internal stimuli, thereby promoting flexible behavioral control. We elaborate on this explanatory framework and propose a working hypothesis for the involvement of the cerebellum in compulsive and impulsive endophenotypes.

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.

Shared Cortex-Cerebellum Dynamics in the Execution and Learning of a Motor Task

Throughout mammalian neocortex, layer 5 pyramidal (L5) cells project via the pons to a vast number of cerebellar granule cells (GrCs), forming a fundamental pathway. Yet, it is unknown how neuronal dynamics are transformed through the L5→GrC pathway. Here, by directly comparing premotor L5 and GrC activity during a forelimb movement task using dual-site two-photon Ca2+ imaging, we found that in expert mice, L5 and GrC dynamics were highly similar. L5 cells and GrCs shared a common set of task-encoding activity patterns, possessed similar diversity of responses, and exhibited high correlations comparable to local correlations among L5 cells. Chronic imaging revealed that these dynamics co-emerged in cortex and cerebellum over learning: as behavioral performance improved, initially dissimilar L5 cells and GrCs converged onto a shared, low-dimensional, task-encoding set of neural activity patterns. Thus, a key function of cortico-cerebellar communication is the propagation of shared dynamics that emerge during learning.

Selective targeting of unipolar brush cell subtypes by cerebellar mossy fibers

In vestibular cerebellum, primary afferents carry signals from single vestibular end organs, whereas secondary afferents from vestibular nucleus carry integrated signals. Selective targeting of distinct mossy fibers determines how the cerebellum processes vestibular signals. We focused on vestibular projections to ON and OFF classes of unipolar brush cells (UBCs), which transform single mossy fiber signals into long-lasting excitation or inhibition respectively, and impact the activity of ensembles of granule cells. To determine whether these contacts are indeed selective, connectivity was traced back from UBC to specific ganglion cell, hair cell and vestibular organ subtypes in mice. We show that a specialized subset of primary afferents contacts ON UBCs, but not OFF UBCs, while secondary afferents contact both subtypes. Striking anatomical differences were observed between primary and secondary afferents, their synapses, and the UBCs they contact. Thus, each class of UBC functions to transform specific signals through distinct anatomical pathways.

While out jogging, you have no trouble keeping your eyes fixed on objects in the distance even though your head and eyes are moving with every step. Humans owe this stability of the visual world partly to a region of the brain called the vestibular cerebellum. From its position underneath the rest of the brain, the vestibular cerebellum detects head motion and then triggers compensatory movements to stabilize the head, body and eyes.

The vestibular cerebellum receives sensory input from the body via direct and indirect routes. The direct input comes from five structures within the inner ear, each of which detects movement of the head in one particular direction. The indirect input travels to the cerebellum via the brainstem, which connects the brain with the spinal cord. The indirect input contains information on head movements in multiple directions combined with input from other senses such as vision.

By studying the mouse brain, Balmer and Trussell have now mapped the direct and indirect circuits that carry sensory information to the vestibular cerebellum. Both types of input activate cells within the vestibular cerebellum called unipolar brush cells (UBCs). There are two types of UBCs: ON and OFF. Direct sensory input from the inner ear activates only ON UBCs. These cells respond to the arrival of sensory input by increasing their activity. Indirect input from the brainstem activates both ON UBCs and OFF UBCs. The latter respond to the input by decreasing their activity.

The vestibular cerebellum thus processes direct and indirect inputs via segregated pathways containing different types of UBCs. The next step in understanding how the cerebellum maintains a stable visual world is to identify the circuitry beyond the UBCs. Understanding these circuits will ultimately provide insights into balance disorders, such as vertigo.

Reevaluating the ability of cerebellum in associative motor learning

It has been well established that the cerebellum and its associated circuitry constitute the essential neuronal system for both delay and trace classical eyeblink conditioning (DEC and TEC). However, whether the cerebellum is sufficient to independently modulate the DEC, and TEC with a shorter trace interval remained controversial. Here, we used direct optogenetic stimulation of mossy fibers in the middle cerebellar peduncle (MCP) as a conditioned stimulus (CS) replacement for the peripheral CS (eg, a tone CS or a light CS) paired with a periorbital shock unconditioned stimulus (US) to examine the ability of the cerebellum to learn the DEC and the TEC with various trace intervals. Moreover, neural inputs to the pontine nucleus (PN) were pharmacological blocked to limit the associative motor learning inside the cerebellum. We show that all rats quickly acquired the DEC, indicating that direct optogenetic stimulation of mossy fibers in the left MCP is a very effective and sufficient CS to establish DEC and to limit the motor learning process inside the cerebellum. However, only five out of seven rats acquired the TEC with a 150-ms trace interval, three out of nine rats acquired the TEC with a 350-ms trace interval, and none of the rats acquired the TEC with a 500-ms trace interval. Moreover, pharmacological blocking glutamatergic and GABAergic inputs to the PN from the extra-cerebellar and cerebellar regions has no significant effect on the DEC and TEC learning with the optogenetic CS. These results indicate that the cerebellum has the ability to independently support both the simple DEC, and the TEC with a trace interval of 150 or 350 ms, but not the TEC with a trace interval of 500 ms. The present results are of great importance in our understanding of the mechanisms and ability of the cerebellum in associative motor learning and memory.

Long-Lasting Response Changes in Deep Cerebellar Nuclei in vivo Correlate With Low-Frequency Oscillations

The deep cerebellar nuclei (DCN) have been suggested to play a critical role in sensorimotor learning and some forms of long-term synaptic plasticity observed in vitro have been proposed as a possible substrate. However, till now it was not clear whether and how DCN neuron responses manifest long-lasting changes in vivo. Here, we have characterized DCN unit responses to tactile stimulation of the facial area in anesthetized mice and evaluated the changes induced by theta-sensory stimulation (TSS), a 4 Hz stimulation pattern that is known to induce plasticity in the cerebellar cortex in vivo. DCN units responded to tactile stimulation generating bursts and pauses, which reflected combinations of excitatory inputs most likely relayed by mossy fiber collaterals, inhibitory inputs relayed by Purkinje cells, and intrinsic rebound firing. Interestingly, initial bursts and pauses were often followed by stimulus-induced oscillations in the peri-stimulus time histograms (PSTH). TSS induced long-lasting changes in DCN unit responses. Spike-related potentiation and suppression (SR-P and SR-S), either in units initiating the response with bursts or pauses, were correlated with stimulus-induced oscillations. Fitting with resonant functions suggested the existence of peaks in the theta-band (burst SR-P at 9 Hz, pause SR-S at 5 Hz). Optogenetic stimulation of the cerebellar cortex altered stimulus-induced oscillations suggesting that Purkinje cells play a critical role in the circuits controlling DCN oscillations and plasticity. This observation complements those reported before on the granular and molecular layers supporting the generation of multiple distributed plasticities in the cerebellum following naturally patterned sensory entrainment. The unique dependency of DCN plasticity on circuit oscillations discloses a potential relationship between cerebellar learning and activity patterns generated in the cerebellar network.

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.

A method for combining multiple-units readout of optogenetic control with natural stimulation-evoked eyeblink conditioning in freely-moving mice

A growing pool of transgenic mice expressing Cre-recombinases, together with Cre-dependent opsin viruses, provide good tools to manipulate specific neural circuits related to eyeblink conditioning (EBC). However, currently available methods do not enable to get fast and precise readout of optogenetic control when the freely-moving mice are receiving EBC training. In the current study, we describe a laser diode (LD)-optical fiber (OF)-Tetrode assembly that allows for simultaneous multiple units recording and optical stimulation. Since the numbers of various cables that require to be connected are minimized, the LD-OF-Tetrode assembly can be combined with CS-US delivery apparatus for revealing the effects of optical stimulation on EBC in freely- moving mice. Moreover, this combination of techniques can be utilized to optogenetically intervene in hippocampal neuronal activities during the post-conditioning sleep in a closed-loop manner. This novel device thus enhances our ability to explore how specific neuronal assembly contributes to associative motor memory in vivo.

Molecular layer interneurons shape the spike activity of cerebellar Purkinje cells

Purkinje cells receive synaptic input from several classes of interneurons. Here, we address the roles of inhibitory molecular layer interneurons in establishing Purkinje cell function in vivo. Using conditional genetics approaches in mice, we compare how the lack of stellate cell versus basket cell GABAergic neurotransmission sculpts the firing properties of Purkinje cells. We take advantage of an inducible Ascl1CreER allele to spatially and temporally target the deletion of the vesicular GABA transporter, Vgat, in developing neurons. Selective depletion of basket cell GABAergic neurotransmission increases the frequency of Purkinje cell simple spike firing and decreases the frequency of complex spike firing in adult behaving mice. In contrast, lack of stellate cell communication increases the regularity of Purkinje cell simple spike firing while increasing the frequency of complex spike firing. Our data uncover complementary roles for molecular layer interneurons in shaping the rate and pattern of Purkinje cell activity in vivo.

Resistance, vulnerability and resilience: A review of the cognitive cerebellum in aging and neurodegenerative diseases

In the context of neurodegeneration and aging, the cerebellum is an enigma. Genetic markers of cellular aging in cerebellum accumulate more slowly than in the rest of the brain, and it generates unknown factors that may slow or even reverse neurodegenerative pathology in animal models of Alzheimer's Disease (AD). Cerebellum shows increased activity in early AD and Parkinson's disease (PD), suggesting a compensatory function that may mitigate early symptoms of neurodegenerative pathophysiology. Perhaps most notably, different parts of the brain accumulate neuropathological markers of AD in a recognized progression and generally, cerebellum is the last brain region to do so. Taken together, these data suggest that cerebellum may be resistant to certain neurodegenerative mechanisms. On the other hand, in some contexts of accelerated neurodegeneration, such as that seen in chronic traumatic encephalopathy (CTE) following repeated traumatic brain injury (TBI), the cerebellum appears to be one of the most susceptible brain regions to injury and one of the first to exhibit signs of pathology. Cerebellar pathology in neurodegenerative disorders is strongly associated with cognitive dysfunction. In neurodegenerative or neurological disorders associated with cerebellar pathology, such as spinocerebellar ataxia, cerebellar cortical atrophy, and essential tremor, rates of cognitive dysfunction, dementia and neuropsychiatric symptoms increase. When the cerebellum shows AD pathology, such as in familial AD, it is associated with earlier onset and greater severity of disease. These data suggest that when neurodegenerative processes are active in the cerebellum, it may contribute to pathological behavioral outcomes. The cerebellum is well known for comparing internal representations of information with observed outcomes and providing real-time feedback to cortical regions, a critical function that is disturbed in neuropsychiatric disorders such as intellectual disability, schizophrenia, dementia, and autism, and required for cognitive domains such as working memory. While cerebellum has reciprocal connections with non-motor brain regions and likely plays a role in complex, goal-directed behaviors, it has proven difficult to establish what it does mechanistically to modulate these behaviors. Due to this lack of understanding, it's not surprising to see the cerebellum reflexively dismissed or even ignored in basic and translational neuropsychiatric literature. The overarching goals of this review are to answer the following questions from primary literature: When the cerebellum is affected by pathology, is it associated with decreased cognitive function? When it is intact, does it play a compensatory or protective role in maintaining cognitive function? Are there theoretical frameworks for understanding the role of cerebellum in cognition, and perhaps, illnesses characterized by cognitive dysfunction? Understanding the role of the cognitive cerebellum in neurodegenerative diseases has the potential to offer insight into origins of cognitive deficits in other neuropsychiatric disorders, which are often underappreciated, poorly understood, and not often treated.

Pathway-Specific Drive of Cerebellar Golgi Cells Reveals Integrative Rules of Cortical Inhibition

Cerebellar granule cells (GrCs) constitute over half of all neurons in the vertebrate brain and are proposed to decorrelate convergent mossy fiber (MF) inputs in service of learning. Interneurons within the GrC layer, Golgi cells (GoCs), are the primary inhibitors of this vast population and therefore play a major role in influencing the computations performed within the layer. Despite this central function for GoCs, few studies have directly examined how GoCs integrate inputs from specific afferents, which vary in density to regulate GrC population activity. We used a variety of methods in mice of either sex to study feedforward inhibition recruited by identified MFs, focusing on features that would influence integration by GrCs. Comprehensive 3D reconstruction and quantification of GoC axonal boutons revealed tightly clustered boutons that focus feedforward inhibition in the neighborhood of GoC somata. Acute whole-cell patch-clamp recordings from GrCs in brain slices showed that, despite high GoC bouton density, fast phasic inhibition was very sparse relative to slow spillover mediated inhibition. Dynamic-clamp simulating inhibition combined with optogenetic MF activation at moderate rates supported a predominant role of slow spillover mediated inhibition in reducing GrC activity. Whole-cell recordings from GoCs revealed a role for the density of active MFs in preferentially driving them. Thus, our data provide empirical confirmation of predicted rules by which MFs activate GoCs to regulate GrC activity levels.SIGNIFICANCE STATEMENT A unifying framework in neural circuit analysis is identifying circuit motifs that subserve common computations. Wide-field inhibitory interneurons globally inhibit neighbors and have been studied extensively in the insect olfactory system and proposed to serve pattern separation functions. Cerebellar Golgi cells (GoCs), a type of mammalian wide-field inhibitory interneuron observed in the granule cell layer, are well suited to perform normalization or pattern separation functions, but the relationship between spatial characteristics of input patterns to GoC-mediated inhibition has received limited attention. This study provides unprecedented quantitative structural details of GoCs and identifies a role for population input activity levels in recruiting inhibition using in vitro electrophysiology and optogenetics.

The role of the cerebellum in drug-cue associative memory: functional interactions with the medial prefrontal cortex

Drug-induced Pavlovian memories are thought to be crucial for drug addiction because they guide behaviour towards environments with drug availability. Drug-related memory depends on persistent changes in dopamine-glutamate interactions in the medial prefrontal cortex (mPFC), basolateral amygdala, nucleus accumbens core and hippocampus. Recent evidence from our laboratory indicated that the cerebellum is also a relevant node for drug-cue associations. In the present study, we tested the role that specific regions of the cerebellum and mPFC play in the acquisition of cocaine-induced preference conditioning. Quinolinic acid was used to manage a permanent deactivation of lobule VIII in the vermis prior to conditioning. Additionally, lidocaine was infused into the prelimbic and infralimbic (IL) cortices for reversible deactivation before every training session. The present findings show, for the first time, that the cerebellum and mPFC might act together in order to acquire drug-cue Pavlovian associations. Either a dorsal lesion in lobule VIII or an IL deactivation encouraged cocaine-induced preference conditioning. Moreover, simultaneous IL-cerebellar deactivation prevented the effect of either of the separate deactivations. Therefore, similar to the IL cortex, neural activity in the cerebellum may be crucial for ensuring inhibitory control of the expression of cocaine-related memories.

Cerebellar Modules and Their Role as Operational Cerebellar Processing Units: A Consensus paper [corrected]

The compartmentalization of the cerebellum into modules is often used to discuss its function. What, exactly, can be considered a module, how do they operate, can they be subdivided and do they act individually or in concert are only some of the key questions discussed in this consensus paper. Experts studying cerebellar compartmentalization give their insights on the structure and function of cerebellar modules, with the aim of providing an up-to-date review of the extensive literature on this subject. Starting with an historical perspective indicating that the basis of the modular organization is formed by matching olivocorticonuclear connectivity, this is followed by consideration of anatomical and chemical modular boundaries, revealing a relation between anatomical, chemical, and physiological borders. In addition, the question is asked what the smallest operational unit of the cerebellum might be. Furthermore, it has become clear that chemical diversity of Purkinje cells also results in diversity of information processing between cerebellar modules. An additional important consideration is the relation between modular compartmentalization and the organization of the mossy fiber system, resulting in the concept of modular plasticity. Finally, examination of cerebellar output patterns suggesting cooperation between modules and recent work on modular aspects of emotional behavior are discussed. Despite the general consensus that the cerebellum has a modular organization, many questions remain. The authors hope that this joint review will inspire future cerebellar research so that we are better able to understand how this brain structure makes its vital contribution to behavior in its most general form.

The basal interstitial nucleus (BIN) of the cerebellum provides diffuse ascending inhibitory input to the floccular granule cell layer

The basal interstitial nucleus (BIN) in the white matter of the vestibulocerebellum has been defined more than three decades ago, but has since been largely ignored. It is still unclear which neurotransmitters are being used by BIN neurons, how these neurons are connected to the rest of the brain and what their activity patterns look like. Here, we studied BIN neurons in a range of mammals, including macaque, human, rat, mouse, rabbit, and ferret, using tracing, immunohistological and electrophysiological approaches. We show that BIN neurons are GABAergic and glycinergic, that in primates they also express the marker for cholinergic neurons choline acetyl transferase (ChAT), that they project with beaded fibers to the glomeruli in the granular layer of the ipsilateral floccular complex, and that they are driven by excitation from the ipsilateral and contralateral medio-dorsal medullary gigantocellular reticular formation. Systematic analysis of codistribution of the inhibitory synapse marker VIAAT, BIN axons, and Golgi cell marker mGluR2 indicate that BIN axon terminals complement Golgi cell axon terminals in glomeruli, accounting for a considerable proportion ( > 20%) of the inhibitory terminals in the granule cell layer of the floccular complex. Together, these data show that BIN neurons represent a novel and relevant inhibitory input to the part of the vestibulocerebellum that controls compensatory and smooth pursuit eye movements.

Dopamine D1 Receptor-Positive Neurons in the Lateral Nucleus of the Cerebellum Contribute to Cognitive Behavior

BACKGROUND

Studies in humans and nonhuman primates have identified a region of the dentate nucleus of the cerebellum, or the lateral cerebellar nucleus (LCN) in rodents, activated during performance of cognitive tasks involving complex spatial and sequential planning. Whether such a subdivision exists in rodents is not known. Dopamine and its receptors, which are implicated in cognitive function, are present in the cerebellar nuclei, but their function is unknown.

METHODS

Using viral and genetic strategies in mice, we examined cellular phenotypes of dopamine D₁ receptor-positive (D1R+) cells in the LCN with whole-cell patch clamp recordings, messenger RNA profiling, and immunohistochemistry to examine D1R expression in mouse LCN and human dentate nucleus of the cerebellum. We used chemogenetics to inhibit D1R+ neurons and examined behaviors including spatial navigation, social recognition memory, prepulse inhibition of the acoustic startle reflex, response inhibition, and working memory to test the necessity of these neurons in these behaviors.

RESULTS

We identified a population of D1R+ neurons that are localized to an anatomically distinct region of the LCN. We also observed D1R+ neurons in human dentate nucleus of the cerebellum, which suggests an evolutionarily conserved population of dopamine-receptive neurons in this region. The genetic, electrophysiological, and anatomical profile of mouse D1R neurons is consistent with a heterogeneous population of gamma-aminobutyric acidergic, and to a lesser extent glutamatergic, cell types. Selective inhibition of D1R+ LCN neurons impairs spatial navigation memory, response inhibition, working memory, and prepulse inhibition of the acoustic startle reflex.

CONCLUSIONS

Collectively, these data demonstrate a functional link between genetically distinct neurons in the LCN and cognitive behaviors.

Cerebellar implementation of movement sequences through feedback

Most movements are not unitary, but are comprised of sequences. Although patients with cerebellar pathology display severe deficits in the execution and learning of sequences (Doyon et al., 1997; Shin and Ivry, 2003), most of our understanding of cerebellar mechanisms has come from analyses of single component movements. Eyelid conditioning is a cerebellar-mediated behavior that provides the ability to control and restrict inputs to the cerebellum through stimulation of mossy fibers. We utilized this advantage to test directly how the cerebellum can learn a sequence of inter-connected movement components in rabbits. We show that the feedback signals from one component are sufficient to serve as a cue for the next component in the sequence. In vivo recordings from Purkinje cells demonstrated that all components of the sequence were encoded similarly by cerebellar cortex. These results provide a simple yet general framework for how the cerebellum can use simple associate learning processes to chain together a sequence of appropriately timed responses.

Imagine a gymnastics competition in which participants take turns to cartwheel and somersault across the floor. The routines on display comprise sequences of precisely timed movements learned through practice. This is also true for many of the actions we perform every day, such as reaching for a cup of coffee. A region of the brain called the cerebellum helps us learn sequences of movements. But how does it do this?

To find out, Khilkevich et al. came up with a new version of an old experiment. Rabbits were first trained to blink their eye in response to a specific external cue. This type of learning, called associative learning, has been shown before in the cerebellum. But Khilkevich et al. wondered whether the cerebellum could also use internal feedback signals from the eyeblink as a cue to learn the next movement? If so, this might explain how the cerebellum can chain movements together in a sequence.

As predicted, Khilkevich et al. found that rabbits could learn to blink their eye in response to an initial signal, and then blink again in response to the first blink. Control experiments confirmed that the second eyeblink was coupled to the first, and not to the original cue. Moreover, on many trials the rabbits showed a third and even fourth eyeblink. This is because feedback signals from the first, second or third blink were the same. Thus, the feedback signals from the first blink triggered the second blink, feedback from the second triggered the third, and so forth. Rabbits could also learn to use a blink of the left eye as a cue for a blink of the right eye. Similar patterns of neuronal activity accompanied each blink, suggesting that the same mechanism generated them all.

The cerebellum can thus use feedback from one movement as a cue to learn the proper timing of the next movement in a sequence. A key question is whether this mechanism of sequence learning extends beyond movement. The cerebellum has extensive connections to the brain’s outer layer, the cortex, including many areas involved in cognition. Future experiments should test whether the cerebellum might help guide sequences of cortical activity during cognitive tasks.

Cerebellar Learning Properties Are Modulated by the CRF Receptor

Corticotropin-releasing factor (CRF) and its type 1 receptor (CRFR₁) play an important role in the responses to stressful challenges. Despite the well established expression of CRFR₁ in granular cells (GrCs), its role in procedural motor performance and memory formation remains elusive. To investigate the role of CRFR₁ expression in cerebellar GrCs, we used a mouse model depleted of CRFR₁ in these cells. We detected changes in the cellular learning mechanisms in GrCs depleted of CRFR₁ in that they showed changes in intrinsic excitability and long-term synaptic plasticity. Analysis of cerebella transcriptome obtained from KO and control mice detected prominent alterations in the expression of calcium signaling pathways components. Moreover, male mice depleted of CRFR₁ specifically in GrCs showed accelerated Pavlovian associative eye-blink conditioning, but no differences in baseline motor performance, locomotion, or fear and anxiety-related behaviors. Our findings shed light on the interplay between stress-related central mechanisms and cerebellar motor conditioning, highlighting the role of the CRF system in regulating particular forms of cerebellar learning.SIGNIFICANCE STATEMENT Although it is known that the corticotropin-releasing factor type 1 receptor (CRFR₁) is highly expressed in the cerebellum, little attention has been given to its role in cerebellar functions in the behaving animal. Moreover, most of the attention was directed at the effect of CRF on Purkinje cells at the cellular level and, to this date, almost no data exist on the role of this stress-related receptor in other cerebellar structures. Here, we explored the behavioral and cellular effect of granular cell-specific ablation of CRFR₁ We found a profound effect on learning both at the cellular and behavioral levels without an effect on baseline motor skills.

The Emerging Concept of Intrinsic Plasticity: Activity-dependent Modulation of Intrinsic Excitability in Cerebellar Purkinje Cells and Motor Learning

What is memory? How does the brain process the sensory information and modify an organism's behavior? Many neuroscientists have focused on the activity- and experience-dependent modifications of synaptic functions in order to solve these fundamental questions in neuroscience. Recently, the plasticity of intrinsic excitability (called intrinsic plasticity) has emerged as an important element for information processing and storage in the brain. As the cerebellar Purkinje cells are the sole output neurons in the cerebellar cortex and the information is conveyed from a neuron to its relay neurons by forms of action potential firing, the modulation of the intrinsic firing activity may play a critical role in the cerebellar learning. Many voltage-gated and/or Ca2+-activated ion channels are involved in shaping the spiking output as well as integrating synaptic inputs to finely tune the cerebellar output. Recent studies suggested that the modulation of the intrinsic excitability and its plasticity in the cerebellar Purkinje cells might function as an integrator for information processing and memory formation. Moreover, the intrinsic plasticity might also determine the strength of connectivity to the sub-cortical areas such as deep cerebellar nuclei and vestibular nuclei to trigger the consolidation of the cerebellar-dependent memory by transferring the information.

A cerebellar adaptation to uncertain inputs

Noise and variability are inherent and unavoidable features of neural processing. Despite this physiological challenge, brain systems function well, suggesting the existence of adaptations that cope with noise. We report a novel adaptation that the cerebellum implements to maintain correct responses in the face of ambiguous inputs. We found that under these conditions, the cerebellum used a probabilistic binary choice: Although the probability of behavioral response gradually increased or decreased depending on the degree of similarity between current and trained inputs, the size of response remained constant. That way the cerebellum kept responses adaptive to trained input corrupted by noise while minimizing false responses to novel stimuli. Recordings and analysis of Purkinje cells activity showed that the binary choice is made in the cerebellar cortex. Results from large-scale simulation suggest that internal feedback from cerebellar nucleus back to cerebellar cortex plays a critical role in implementation of binary choice.

Conditioned climbing fiber responses in cerebellar cortex and nuclei

The eyeblink conditioning paradigm captures an elementary form of associative learning in a neural circuitry that is understood to an extraordinary degree. Cerebellar cortical Purkinje cell simple spike suppression is widely regarded as the main process underlying conditioned responses (CRs), leading to disinhibition of neurons in the cerebellar nuclei that innervate eyelid muscles downstream. However, recent work highlights the addition of a conditioned Purkinje cell complex spike response, which at the level of the interposed nucleus seems to translate to a transient spike suppression that can be followed by a rapid spike facilitation. Here, we review the characteristics of these responses at the cerebellar cortical and nuclear level, and discuss possible origins and functions.

Locomotor activity modulates associative learning in mouse cerebellum

Changes in behavioral state can profoundly influence brain function. Here we show that behavioral state modulates performance in delay eyeblink conditioning, a cerebellum-dependent form of associative learning. Increased locomotor speed in head-fixed mice drove earlier onset of learning and trial-by-trial enhancement of learned responses that were dissociable from changes in arousal and independent of sensory modality. Eyelid responses evoked by optogenetic stimulation of mossy fiber inputs to the cerebellum, but not at sites downstream, were positively modulated by ongoing locomotion. Substituting prolonged, low-intensity optogenetic mossy fiber stimulation for locomotion was sufficient to enhance conditioned responses. Our results suggest that locomotor activity modulates delay eyeblink conditioning through increased activation of the mossy fiber pathway within the cerebellum. Taken together, these results provide evidence for a novel role for behavioral state modulation in associative learning and suggest a potential mechanism through which engaging in movement can improve an individual’s ability to learn.

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.

Motor learning induces plastic changes in Purkinje cell dendritic spines in the rat cerebellum

INTRODUCTION

The paramedian lobule of the cerebellum is involved in learning to correctly perform motor skills through practice. Dendritic spines are dynamic structures that regulate excitatory synaptic stimulation. We studied plastic changes occurring in the dendritic spines of Purkinje cells from the paramedian lobule of rats during motor learning.

METHODS

Adult male rats were trained over a 6-day period using an acrobatic motor learning paradigm; the density and type of dendritic spines were determined every day during the study period using a modified version of the Golgi method.

RESULTS

The learning curve reflected a considerable decrease in the number of errors made by rats as the training period progressed. We observed more dendritic spines on days 2 and 6, particularly more thin spines on days 1, 3, and 6, fewer mushroom spines on day 3, fewer stubby spines on day 1, and more thick spines on days 4 and 6.

CONCLUSION

The initial stage of motor learning may be associated with fast processing of the underlying synaptic information combined with an apparent "silencing" of memory consolidation processes, based on the regulation of the neuronal excitability.

Dynamic modulation of activity in cerebellar nuclei neurons during pavlovian eyeblink conditioning in mice

While research on the cerebellar cortex is crystallizing our understanding of its function in learning behavior, many questions surrounding its downstream targets remain. Here, we evaluate the dynamics of cerebellar interpositus nucleus (IpN) neurons over the course of Pavlovian eyeblink conditioning. A diverse range of learning-induced neuronal responses was observed, including increases and decreases in activity during the generation of conditioned blinks. Trial-by-trial correlational analysis and optogenetic manipulation demonstrate that facilitation in the IpN drives the eyelid movements. Adaptive facilitatory responses are often preceded by acquired transient inhibition of IpN activity that, based on latency and effect, appear to be driven by complex spikes in cerebellar cortical Purkinje cells. Likewise, during reflexive blinks to periocular stimulation, IpN cells show excitation-suppression patterns that suggest a contribution of climbing fibers and their collaterals. These findings highlight the integrative properties of subcortical neurons at the cerebellar output stage mediating conditioned behavior.

PRRT2-dependent dyskinesia: cerebellar, paroxysmal and persistent

In an elegant publication in Cell Research, Tan and colleagues showed that ablation of PRRT2 in cerebellar granule cells is sufficient to induce paroxysmal kinesigenic dyskinesia. PRRT2 turns out to downregulate the presynaptic SNARE complex in granule cell axons, which in turn controls the activity patterns of Purkinje cells, the sole output of the cerebellar cortex.

Cerebellar Granule Cells: Dense, Rich and Evolving Representations

For half a century it was assumed that granule cells use ultra-sparse encoding, but now in vivo calcium-imaging studies have shown that large ensembles of granule cells provide dense signals, which themselves evolve and adapt during training.

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.

Learned response sequences in cerebellar Purkinje cells

Associative learning in the cerebellum has previously focused on single movements. In eyeblink conditioning, for instance, a subject learns to blink at the right time in response to a conditional stimulus (CS), such as a tone that is repeatedly followed by an unconditional corneal stimulus (US). During conditioning, the CS and US are transmitted by mossy/parallel fibers and climbing fibers to cerebellar Purkinje cells that acquire a precisely timed pause response that drives the overt blink response. The timing of this conditional Purkinje cell response is determined by the CS-US interval and is independent of temporal patterns in the input signal. In addition to single movements, the cerebellum is also believed to be important for learning complex motor programs that require multiple precisely timed muscle contractions, such as, for example, playing the piano. In the present work, we studied Purkinje cells in decerebrate ferrets that were conditioned using electrical stimulation of mossy fiber and climbing fiber afferents as CS and US, while alternating between short and long interstimulus intervals. We found that Purkinje cells can learn double pause responses, separated by an intermediate excitation, where each pause corresponds to one interstimulus interval. The results show that individual cells can not only learn to time a single response but that they also learn an accurately timed sequential response pattern.

Modulation of 7 T fMRI Signal in the Cerebellar Cortex and Nuclei During Acquisition, Extinction, and Reacquisition of Conditioned Eyeblink Responses

Classical delay eyeblink conditioning is likely the most commonly used paradigm to study cerebellar learning. As yet, few studies have focused on extinction and savings of conditioned eyeblink responses (CRs). Saving effects, which are reflected in a reacquisition after extinction that is faster than the initial acquisition, suggest that learned associations are at least partly preserved during extinction. In this study, we tested the hypothesis that acquisition-related plasticity is nihilated during extinction in the cerebellar cortex, but retained in the cerebellar nuclei, allowing for faster reacquisition. Changes of 7 T functional magnetic resonance imaging (fMRI) signals were investigated in the cerebellar cortex and nuclei of young and healthy human subjects. Main effects of acquisition, extinction, and reacquisition against rest were calculated in conditioned stimulus-only trials. First-level β values were determined for a spherical region of interest (ROI) around the acquisition peak voxel in lobule VI, and dentate and interposed nuclei ipsilateral to the unconditioned stimulus. In the cerebellar cortex and nuclei, fMRI signals were significantly lower in extinction compared to acquisition and reacquisition, but not significantly different between acquisition and reacquisition. These findings are consistent with the theory of bidirectional learning in both the cerebellar cortex and nuclei. It cannot explain, however, why conditioned responses reappear almost immediately in reacquisition following extinction. Although the present data do not exclude that part of the initial memory remains in the cerebellum in extinction, future studies should also explore changes in extracerebellar regions as a potential substrate of saving effects. Hum Brain Mapp 38:3957-3974, 2017. © 2017 Wiley Periodicals, Inc.

The Sleeping Cerebellum

We sleep almost one-third of our lives and sleep plays an important role in critical brain functions like memory formation and consolidation. The role of sleep in cerebellar processing, however, constitutes an enigma in the field of neuroscience; we know little about cerebellar sleep-physiology, cerebro-cerebellar interactions during sleep, or the contributions of sleep to cerebellum-dependent memory consolidation. Likewise, we do not understand why cerebellar malfunction can lead to changes in the sleep-wake cycle and sleep disorders. In this review, we evaluate how sleep and cerebellar processing may influence one another and highlight which scientific routes and technical approaches could be taken to uncover the mechanisms underlying these interactions.

Genetic silencing of olivocerebellar synapses causes dystonia-like behaviour in mice

Theories of cerebellar function place the inferior olive to cerebellum connection at the centre of motor behaviour. One possible implication of this is that disruption of olivocerebellar signalling could play a major role in initiating motor disease. To test this, we devised a mouse genetics approach to silence glutamatergic signalling only at olivocerebellar synapses. The resulting mice had a severe neurological condition that mimicked the early-onset twisting, stiff limbs and tremor that is observed in dystonia, a debilitating movement disease. By blocking olivocerebellar excitatory neurotransmission, we eliminated Purkinje cell complex spikes and induced aberrant cerebellar nuclear activity. Pharmacologically inhibiting the erratic output of the cerebellar nuclei in the mutant mice improved movement. Furthermore, deep brain stimulation directed to the interposed cerebellar nuclei reduced dystonia-like postures in these mice. Collectively, our data uncover a neural mechanism by which olivocerebellar dysfunction promotes motor disease phenotypes and identify the cerebellar nuclei as a therapeutic target for surgical intervention.

Dystonia is thought to be driven by impairments in cerebellar signalling. The authors use a mouse genetic approach to silence excitatory transmission in the inferior olive to cerebellum pathway, resulting in dystonia-like signs in the animals which can be alleviated using DBS stimulation of the pathway.

Cerebellar granule cells acquire a widespread predictive feedback signal during motor learning

Cerebellar granule cells, which constitute half the brain's neurons, supply Purkinje cells with contextual information necessary for motor learning, but how they encode this information is unknown. Here we show, using two-photon microscopy to track neural activity over multiple days of cerebellum-dependent eyeblink conditioning in mice, that granule cell populations acquire a dense representation of the anticipatory eyelid movement. Initially, granule cells responded to neutral visual and somatosensory stimuli as well as periorbital airpuffs used for training. As learning progressed, two-thirds of monitored granule cells acquired a conditional response whose timing matched or preceded the learned eyelid movements. Granule cell activity covaried trial by trial to form a redundant code. Many granule cells were also active during movements of nearby body structures. Thus, a predictive signal about the upcoming movement is widely available at the input stage of the cerebellar cortex, as required by forward models of cerebellar control.

Optimal Degrees of Synaptic Connectivity

Synaptic connectivity varies widely across neuronal types. Cerebellar granule cells receive five orders of magnitude fewer inputs than the Purkinje cells they innervate, and cerebellum-like circuits, including the insect mushroom body, also exhibit large divergences in connectivity. In contrast, the number of inputs per neuron in cerebral cortex is more uniform and large. We investigate how the dimension of a representation formed by a population of neurons depends on how many inputs each neuron receives and what this implies for learning associations. Our theory predicts that the dimensions of the cerebellar granule-cell and Drosophila Kenyon-cell representations are maximized at degrees of synaptic connectivity that match those observed anatomically, showing that sparse connectivity is sometimes superior to dense connectivity. When input synapses are subject to supervised plasticity, however, dense wiring becomes advantageous, suggesting that the type of plasticity exhibited by a set of synapses is a major determinant of connection density.

Glycinergic transmission: glycine transporter GlyT2 in neuronal pathologies

Glycinergic neurons are major contributors to the regulation of neuronal excitability, mainly in caudal areas of the nervous system. These neurons control fluxes of sensory information between the periphery and the CNS and diverse motor activities like locomotion, respiration or vocalization. The phenotype of a glycinergic neuron is determined by the expression of at least two proteins: GlyT2, a plasma membrane transporter of glycine, and VIAAT, a vesicular transporter shared by glycine and GABA. In this article, we review recent advances in understanding the role of GlyT2 in the pathophysiology of inhibitory glycinergic neurotransmission. GlyT2 mutations are associated to decreased glycinergic function that results in a rare movement disease termed hyperekplexia (HPX) or startle disease. In addition, glycinergic neurons control pain transmission in the dorsal spinal cord and their function is reduced in chronic pain states. A moderate inhibition of GlyT2 may potentiate glycinergic inhibition and constitutes an attractive target for pharmacological intervention against these devastating conditions.

Whole-Cell Properties of Cerebellar Nuclei Neurons In Vivo

Cerebellar nuclei neurons integrate sensorimotor information and form the final output of the cerebellum, projecting to premotor brainstem targets. This implies that, in contrast to specialized neurons and interneurons in cortical regions, neurons within the nuclei encode and integrate complex information that is most likely reflected in a large variation of intrinsic membrane properties and integrative capacities of individual neurons. Yet, whether this large variation in properties is reflected in a heterogeneous physiological cell population of cerebellar nuclei neurons with well or poorly defined cell types remains to be determined. Indeed, the cell electrophysiological properties of cerebellar nuclei neurons have been identified in vitro in young rodents, but whether these properties are similar to the in vivo adult situation has not been shown. In this comprehensive study we present and compare the in vivo properties of 144 cerebellar nuclei neurons in adult ketamine-xylazine anesthetized mice. We found regularly firing (N = 88) and spontaneously bursting (N = 56) neurons. Membrane-resistance, capacitance, spike half-width and firing frequency all widely varied as a continuum, ranging from 9.63 to 3352.1 MΩ, from 6.7 to 772.57 pF, from 0.178 to 1.98 ms, and from 0 to 176.6 Hz, respectively. At the same time, several of these parameters were correlated with each other. Capacitance decreased with membrane resistance (R² = 0.12, P<0.001), intensity of rebound spiking increased with membrane resistance (for 100 ms duration R² = 0.1503, P = 0.0011), membrane resistance decreased with membrane time constant (R² = 0.045, P = 0.031) and increased with spike half-width (R² = 0.023, P<0.001), while capacitance increased with firing frequency (R² = 0.29, P<0.001). However, classes of neuron subtypes could not be identified using merely k-clustering of their intrinsic firing properties and/or integrative properties following activation of their Purkinje cell input. Instead, using whole-cell parameters in combination with morphological criteria revealed by intracellular labelling with Neurobiotin (N = 18) allowed for electrophysiological identification of larger (29.3–50 μm soma diameter) and smaller (< 21.2 μm) cerebellar nuclei neurons with significant differences in membrane properties. Larger cells had a lower membrane resistance and a shorter spike, with a tendency for higher capacitance. Thus, in general cerebellar nuclei neurons appear to offer a rich and wide continuum of physiological properties that stand in contrast to neurons in most cortical regions such as those of the cerebral and cerebellar cortex, in which different classes of neurons operate in a narrower territory of electrophysiological parameter space. The current dataset will help computational modelers of the cerebellar nuclei to update and improve their cerebellar motor learning and performance models by incorporating the large variation of the in vivo properties of cerebellar nuclei neurons. The cellular complexity of cerebellar nuclei neurons may endow the nuclei to perform the intricate computations required for sensorimotor coordination.

Purkinje Cells Directly Inhibit Granule Cells in Specialized Regions of the Cerebellar Cortex

Inhibition of granule cells plays a key role in gating the flow of signals into the cerebellum, and it is thought that Golgi cells are the only interneurons that inhibit granule cells. Here we show that Purkinje cells, the sole output neurons of the cerebellar cortex, also directly inhibit granule cells via their axon collaterals. Anatomical and optogenetic studies indicate that this non-canonical feedback is region specific: it is most prominent in lobules that regulate eye movement and process vestibular information. Collaterals provide fast, slow, and tonic inhibition to granule cells, and thus allow Purkinje cells to regulate granule cell excitability on multiple timescales. We propose that this feedback mechanism could regulate excitability of the input layer, contribute to sparse coding, and mediate temporal integration.