Climbing Fibers Provide Graded Error Signals in Cerebellar Learning

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

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

Climbing Fiber Activation Induced by Footshock in the Cerebellar Vermis Lobule IV/V of Freely Moving Mice

Parallel fibers (PFs) in the cerebellar cortex are involved in a series of coordinated responses in the fear conditioning paradigm induced by footshock. However, whether footshock can activate cerebellar climbing fibers (CFs) remains unclear. In this study, we recorded calcium (Ca2+) activity in CFs by optical fiber photometry in the cerebellar vermis lobule IV/V of freely moving mice with footshock stimulation. We found that the activation of CFs in the lobule IV/V was highly correlated with footshock stimulation but not with the sound stimulation used as a control. This result suggests that afferent information from CFs might be associated with the motor initiation of fear-related behaviors or fear emotion itself. Thus, our results suggest that a characteristic CF signal in the cerebellar cortex might be related to fear processing or footshock-related behaviors (such as startle responses or pain sensation).

Systemic pharmacological suppression of neural activity reverses learning impairment in a mouse model of Fragile X syndrome

The enhancement of associative synaptic plasticity often results in impaired rather than enhanced learning. Previously, we proposed that such learning impairments can result from saturation of the plasticity mechanism (Nguyen-Vu et al., 2017), or, more generally, from a history-dependent change in the threshold for plasticity. This hypothesis was based on experimental results from mice lacking two class I major histocompatibility molecules, MHCI H2-Kb and H2-Db (MHCI KbDb-/-), which have enhanced associative long-term depression at the parallel fiber-Purkinje cell synapses in the cerebellum (PF-Purkinje cell LTD). Here, we extend this work by testing predictions of the threshold metaplasticity hypothesis in a second mouse line with enhanced PF-Purkinje cell LTD, the Fmr1 knockout mouse model of Fragile X syndrome (FXS). Mice lacking Fmr1 gene expression in cerebellar Purkinje cells (L7-Fmr1 KO) were selectively impaired on two oculomotor learning tasks in which PF-Purkinje cell LTD has been implicated, with no impairment on LTD-independent oculomotor learning tasks. Consistent with the threshold metaplasticity hypothesis, behavioral pre-training designed to reverse LTD at the PF-Purkinje cell synapses eliminated the oculomotor learning deficit in the L7-Fmr1 KO mice, as previously reported in MHCI KbDb-/-mice. In addition, diazepam treatment to suppress neural activity and thereby limit the induction of associative LTD during the pre-training period also eliminated the learning deficits in L7-Fmr1 KO mice. These results support the hypothesis that cerebellar LTD-dependent learning is governed by an experience-dependent sliding threshold for plasticity. An increased threshold for LTD in response to elevated neural activity would tend to oppose firing rate stability, but could serve to stabilize synaptic weights and recently acquired memories. The metaplasticity perspective could inform the development of new clinical approaches for addressing learning impairments in autism and other disorders of the nervous system.

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

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

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Recent data on the cerebellum require new models and theories

The cerebellum has been a popular topic for theoretical studies because its structure was thought to be simple. Since David Marr and James Albus related its function to motor skill learning and proposed the Marr-Albus cerebellar learning model, this theory has guided and inspired cerebellar research. In this review, we summarize the theoretical progress that has been made within this framework of error-based supervised learning. We discuss the experimental progress that demonstrates more complicated molecular and cellular mechanisms in the cerebellum as well as new cell types and recurrent connections. We also cover its involvement in diverse non-motor functions and evidence of other forms of learning. Finally, we highlight the need to explain these new experimental findings into an integrated cerebellar model that can unify its diverse computational functions.

The study of plasticity has always been about gradients

The experimental study of learning and plasticity has always been driven by an implicit question: how can physiological changes be adaptive and improve performance? For example, in Hebbian plasticity only synapses from presynaptic neurons that were active are changed, avoiding useless changes. Similarly, in dopamine-gated learning synapse changes depend on reward or lack thereof and do not change when everything is predictable. Within machine learning we can make the question of which changes are adaptive concrete: performance improves when changes correlate with the gradient of an objective function quantifying performance. This result is general for any system that improves through small changes. As such, physiology has always implicitly been seeking mechanisms that allow the brain to approximate gradients. Coming from this perspective we review the existing literature on plasticity-related mechanisms, and we show how these mechanisms relate to gradient estimation. We argue that gradients are a unifying idea to explain the many facets of neuronal plasticity.

Regulation of early cerebellar development

The study of cerebellar development has been at the forefront of neuroscience since the pioneering work of Wilhelm His Sr., Santiago Ramón y Cajal and many others since the 19th century. They laid the foundation to identify the circuitry of the cerebellum, already revealing its stereotypic three-layered cortex and discerning several of its neuronal components. Their work was fundamental in the acceptance of the neuron doctrine, which acknowledges the key role of individual neurons in forming the basic units of the nervous system. Increasing evidence shows that the cerebellum performs a variety of homeostatic and higher order neuronal functions beyond the mere control of motor behaviour. Over the last three decades, many studies have revealed the molecular machinery that regulates distinct aspects of cerebellar development, from the establishment of a cerebellar anlage in the posterior brain to the identification of cerebellar neuron diversity at the single cell level. In this review, we focus on summarizing our current knowledge on early cerebellar development with a particular emphasis on the molecular determinants that secure neuron specification and contribute to the diversity of cerebellar neurons.

Diverse role of NMDA receptors for dendritic integration of neural dynamics

Neurons, represented as a tree structure of morphology, have various distinguished branches of dendrites. Different types of synaptic receptors distributed over dendrites are responsible for receiving inputs from other neurons. NMDA receptors (NMDARs) are expressed as excitatory units, and play a key physiological role in synaptic function. Although NMDARs are widely expressed in most types of neurons, they play a different role in the cerebellar Purkinje cells (PCs). Utilizing a computational PC model with detailed dendritic morphology, we explored the role of NMDARs at different parts of dendritic branches and regions. We found somatic responses can switch from silent, to simple spikes and complex spikes, depending on specific dendritic branches. Detailed examination of the dendrites regarding their diameters and distance to soma revealed diverse response patterns, yet explain two firing modes, simple and complex spike. Taken together, these results suggest that NMDARs play an important role in controlling excitability sensitivity while taking into account the factor of dendritic properties. Given the complexity of neural morphology varying in cell types, our work suggests that the functional role of NMDARs is not stereotyped but highly interwoven with local properties of neuronal structure.

Neuronal morphology enhances robustness to perturbations of channel densities

Biological neurons show significant cell-to-cell variability but have the striking ability to maintain their key firing properties in the face of unpredictable perturbations and stochastic noise. Using a population of multi-compartment models consisting of soma, neurites, and axon for the lateral pyloric neuron in the crab stomatogastric ganglion, we explore how rebound bursting is preserved when the 14 channel conductances in each model are all randomly varied. The coupling between the axon and other compartments is critical for the ability of the axon to spike during bursts and consequently determines the set of successful solutions. When the coupling deviates from a biologically realistic range, the neuronal tolerance of conductance variations is lessened. Thus, the gross morphological features of these neurons enhance their robustness to perturbations of channel densities and expand the space of individual variability that can maintain a desired output pattern.

Optogenetic activation of mGluR1 signaling in the cerebellum induces synaptic plasticity

Neuronal plasticity underlying cerebellar learning behavior is strongly associated with type 1 metabotropic glutamate receptor (mGluR1) signaling. Activation of mGluR1 leads to activation of the G_q/11 pathway, which is involved in inducing synaptic plasticity at the parallel fiber-Purkinje cell synapse (PF-PC) in form of long-term depression (LTD). To optogenetically modulate mGluR1 signaling we fused mouse melanopsin (OPN4) that activates the G_q/11 pathway to the C-termini of mGluR1 splice variants (OPN4-mGluR1a and OPN4-mGluR1b). Activation of both OPN4-mGluR1 variants showed robust Ca²⁺ increase in HEK cells and PCs of cerebellar slices. We provide the prove-of-concept approach to modulate synaptic plasticity via optogenetic activation of OPN4-mGluR1a inducing LTD at the PF-PC synapse in vitro. Moreover, we demonstrate that light activation of mGluR1a signaling pathway by OPN4-mGluR1a in PCs leads to an increase in intrinsic activity of PCs in vivo and improved cerebellum driven learning behavior.

Diversity of cellular physiology and morphology of Purkinje cells in the adult zebrafish cerebellum

This study was designed to explore the functional circuitry of the adult zebrafish cerebellum, focusing on its Purkinje cells and using whole-cell patch recordings and single cell labeling in slice preparations. Following physiological characterizations, the recorded single cells were labeled for morphological identification. It was found that the zebrafish Purkinje cells are surprisingly diverse. Based on their physiology and morphology, they can be classified into at least three subtypes: Type I, a narrow spike cell, which fires only narrow Na⁺ spikes (<3 ms in duration), and has a single primary dendrite with an arbor restricted to the distal molecular layer; Type II, a broad spike cell, which fires broad Ca²⁺ spikes (5-7 ms in duration) and has a primary dendrite with limited branching in the inner molecular layer and then further radiates throughout the molecular layer; and Type III, a very broad spike cell, which fires very broad Ca²⁺ spikes (≥10 ms in duration) and has a dense proximal dendritic arbor that is either restricted to the inner molecular layer (Type IIIa), or radiates throughout the entire molecular layer (Type IIIb). The graded paired-pulse facilitation of these Purkinje cells' responses to parallel fiber activations and the all-or-none, paired-pulse depression of climbing fiber activation are largely similar to those reported for mammals. The labeled axon terminals of these Purkinje cells end locally, as reported for larval zebrafish. The present study provides evidence that the corresponding functional circuitry and information processing differ from what has been well-established in the mammalian cerebellum.

Potential Interactions Between Cerebellar Dysfunction and Sleep Disturbances in Dystonia

Dystonia is the third most common movement disorder. It causes debilitating twisting postures that are accompanied by repetitive and sometimes intermittent co- or over-contractions of agonist and antagonist muscles. Historically diagnosed as a basal ganglia disorder, dystonia is increasingly considered a network disorder involving various brain regions including the cerebellum. In certain etiologies of dystonia, aberrant motor activity is generated in the cerebellum and the abnormal signals then propagate through a “dystonia circuit” that includes the thalamus, basal ganglia, and cerebral cortex. Importantly, it has been reported that non-motor defects can accompany the motor symptoms; while their severity is not always correlated, it is hypothesized that common pathways may nevertheless be disrupted. In particular, circadian dysfunction and disordered sleep are common non-motor patient complaints in dystonia. Given recent evidence suggesting that the cerebellum contains a circadian oscillator, displays sleep-stage-specific neuronal activity, and sends robust long-range projections to several subcortical regions involved in circadian rhythm regulation, disordered sleep in dystonia may result from cerebellum-mediated dysfunction of the dystonia circuit. Here, we review the evidence linking dystonia, cerebellar network dysfunction, and cerebellar involvement in sleep. Together, these ideas may form the basis for the development of improved pharmacological and surgical interventions that could take advantage of cerebellar circuitry to restore normal motor function as well as non-motor (sleep) behaviors in dystonia.

Opposing actions of CRF-R1 and CB1 receptor on facial stimulation-induced MLI-PC plasticity in mouse cerebellar cortex

BACKGROUND

Corticotropin-releasing factor (CRF) is the major neuromodulator orchestrating the stress response, and is secreted by neurons in various regions of the brain. Cerebellar CRF is released by afferents from inferior olivary neurons and other brainstem nuclei in response to stressful challenges, and contributes to modulation of synaptic plasticity and motor learning behavior via its receptors. We recently found that CRF modulates facial stimulation-evoked molecular layer interneuron-Purkinje cell (MLI-PC) synaptic transmission via CRF type 1 receptor (CRF-R1) in vivo in mice, suggesting that CRF modulates sensory stimulation-evoked MLI-PC synaptic plasticity. However, the mechanism of how CRF modulates MLI-PC synaptic plasticity is unclear. We investigated the effect of CRF on facial stimulation-evoked MLI-PC long-term depression (LTD) in urethane-anesthetized mice by cell-attached recording technique and pharmacological methods.

RESULTS

Facial stimulation at 1 Hz induced LTD of MLI-PC synaptic transmission under control conditions, but not in the presence of CRF (100 nM). The CRF-abolished MLI-PC LTD was restored by application of a selective CRF-R1 antagonist, BMS-763,534 (200 nM), but it was not restored by application of a selective CRF-R2 antagonist, antisauvagine-30 (200 nM). Blocking cannabinoid type 1 (CB1) receptor abolished the facial stimulation-induced MLI-PC LTD, and revealed a CRF-triggered MLI-PC long-term potentiation (LTP) via CRF-R1. Notably, either inhibition of protein kinase C (PKC) with chelerythrine (5 µM) or depletion of intracellular Ca²⁺ with cyclopiazonic acid (100 µM), completely prevented CRF-triggered MLI-PC LTP in mouse cerebellar cortex in vivo.

CONCLUSIONS

The present results indicated that CRF blocked sensory stimulation-induced opioid-dependent MLI-PC LTD by triggering MLI-PC LTP through CRF-R1/PKC and intracellular Ca²⁺ signaling pathway in mouse cerebellar cortex. These results suggest that activation of CRF-R1 opposes opioid-mediated cerebellar MLI-PC plasticity in vivo in mice.

Optical Fiber-Based Recording of Climbing Fiber Ca2+ Signals in Freely Behaving Mice

Simple Summary

In this study, we established a robust and accessible method to chronically record calcium signals from climbing fiber (CF) projections to the cerebellar cortex in freely behaving mice. This technique was demonstrated with optical fiber photometry in lobule IV/V of the cerebellar vermis during open field exploration, where various movement-evoked CF Ca²⁺ signals were observed, and the onset of exploratory-like behaviors was highly synchronous with the recorded CF activity.

Abstract

The olivocerebellar circuitry is important to convey both motor and non-motor information from the inferior olive (IO) to the cerebellar cortex. Several methods are currently established to observe the dynamics of the olivocerebellar circuitry, largely by recording the complex spike activity of cerebellar Purkinje cells; however, these techniques can be technically challenging to apply in vivo and are not always possible in freely behaving animals. Here, we developed a method for the direct, accessible, and robust recording of climbing fiber (CF) Ca²⁺ signals based on optical fiber photometry. We first verified the IO stereotactic coordinates and the organization of contralateral CF projections using tracing techniques and then injected Ca²⁺ indicators optimized for axonal labeling, followed by optical fiber-based recordings. We demonstrated this method by recording CF Ca²⁺ signals in lobule IV/V of the cerebellar vermis, comparing the resulting signals in freely moving mice. We found various movement-evoked CF Ca²⁺ signals, but the onset of exploratory-like behaviors, including rearing and tiptoe standing, was highly synchronous with recorded CF activity. Thus, we have successfully established a robust and accessible method to record the CF Ca²⁺ signals in freely behaving mice, which will extend the toolbox for studying cerebellar function and related disorders.

A review of motor neural system robotic modeling approaches and instruments

In this review, we are considering an actively developing tool in neuroscience-robotic modeling. The new perspective and existing application fields, tools, and methods are discussed. We try to determine starting positions and approaches that are useful at the beginning of new research in this field. Among multiple directions of the research is robotic modeling on the level of muscles fibers and their afferents, skin surface sensors, muscles, and joints proprioceptors. Some examples of technical implementation for physical modeling are reviewed. They are software and hardware tools like event-related modeling algorithms, reduced neuron models, robotic drives constructions. We observe existing drives technologies and prospective electric motor types: switched reluctance and transverse flux motors. Next, we look at the existing examples and approaches for robotic modeling of the cerebellum and spinal cord neural networks. These examples show practical methods for the model neural network architecture and adaptation. Those methods allow the use of cortical and spinal cord reflexes for the network training and apply additional artificial blocks for data processing in other brain structures that transmit and receive data from biologically realistic models.

Structure, Function, and Genetics of the Cerebellum in Autism

Autism spectrum disorders are common neurodevelopmental disorders that are defined by core behavioral symptoms but have diverse genetic and environmental risk factors. Despite its etiological heterogeneity, several unifying theories of autism have been proposed, including a central role for cerebellar dysfunction. The cerebellum follows a protracted course of development that culminates in an exquisitely crafted brain structure containing over half of the neurons in the entire brain densely packed into a highly organized structure. Through its complex network of connections with cortical and subcortical brain regions, the cerebellum acts as a sensorimotor regulator and affects changes in executive and limbic processing. In this review, we summarize the structural, functional, and genetic contributions of the cerebellum to autism.

Consensus Paper: Novel Directions and Next Steps of Non-invasive Brain Stimulation of the Cerebellum in Health and Disease

The cerebellum is involved in multiple closed-loops circuitry which connect the cerebellar modules with the motor cortex, prefrontal, temporal, and parietal cortical areas, and contribute to motor control, cognitive processes, emotional processing, and behavior. Among them, the cerebello-thalamo-cortical pathway represents the anatomical substratum of cerebellum-motor cortex inhibition (CBI). However, the cerebellum is also connected with basal ganglia by disynaptic pathways, and cerebellar involvement in disorders commonly associated with basal ganglia dysfunction (e.g., Parkinson's disease and dystonia) has been suggested. Lately, cerebellar activity has been targeted by non-invasive brain stimulation (NIBS) techniques including transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) to indirectly affect and tune dysfunctional circuitry in the brain. Although the results are promising, several questions remain still unsolved. Here, a panel of experts from different specialties (neurophysiology, neurology, neurosurgery, neuropsychology) reviews the current results on cerebellar NIBS with the aim to derive the future steps and directions needed. We discuss the effects of TMS in the field of cerebellar neurophysiology, the potentials of cerebellar tDCS, the role of animal models in cerebellar NIBS applications, and the possible application of cerebellar NIBS in motor learning, stroke recovery, speech and language functions, neuropsychiatric and movement disorders.

Gating by Memory: a Theory of Learning in the Cerebellum

This paper presents a model of learning by the cerebellar circuit. In the traditional and dominant learning model, training teaches finely graded parallel fibre synaptic weights which modify transmission to Purkinje cells and to interneurons that inhibit Purkinje cells. Following training, input in a learned pattern drives a training-modified response. The function is that the naive response to input rates is displaced by a learned one, trained under external supervision. In the proposed model, there is no weight-controlled graduated balance of excitation and inhibition of Purkinje cells. Instead, the balance has two functional states-a switch-at synaptic, whole cell and microzone level. The paper is in two parts. The first is a detailed physiological argument for the synaptic learning function. The second uses the function in a computational simulation of pattern memory. Against expectation, this generates a predictable outcome from input chaos (real-world variables). Training always forces synaptic weights away from the middle and towards the limits of the range, causing them to polarise, so that transmission is either robust or blocked. All conditions teach the same outcome, such that all learned patterns receive the same, rather than a bespoke, effect on transmission. In this model, the function of learning is gating-that is, to select patterns that trigger output merely, and not to modify output. The outcome is memory-operated gate activation which operates a two-state balance of weight-controlled transmission. Group activity of parallel fibres also simultaneously contains a second code contained in collective rates, which varies independently of the pattern code. A two-state response to the pattern code allows faithful, and graduated, control of Purkinje cell firing by the rate code, at gated times.

Celsr3 is required for Purkinje cell maturation and regulates cerebellar postsynaptic plasticity

Atypical cadherin Celsr3 is critical for brain embryonic development, and its role in the postnatal cerebellum remains unknown. Using Celsr3-GFP mice, Celsr3 shows high expression in postnatal Purkinje cells (PCs). Mice with conditional knockout (cKO) of Celsr3 in postnatal PCs exhibit deficit in motor coordination and learning, atrophic PC dendrites, and decreased synapses. Whole-PC recording in cerebellar slices discloses a reduction frequency of mEPSC and defective postsynaptic plasticity (LTP and LTD) in Celsr3 cKO mutants. Wnt5a perfusion enhances LTP formation, which could be occluded by cAMP agonist and diminished by cAMP antagonist in control, but not in Celsr3 cKO or Fzd3 cKO cerebellar slices. Celsr3 cKO resulted in the failure of mGluR1 agonist-induced LTD and paired stimulation-induced PKCα overexpression in PC dendrites, and downregulation of mGluR1 expression compvared to controls. In conclusion, Celsr3 is required for PCs maturation and regulates postsynaptic LTP and LTD through Wnt5a/cAMP and mGluR1/PKCα signaling respectively.

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Celsr3 cKO in postnatal PCs impairs mouse motor coordination and learning

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Celsr3 inactivation affects the maturation of PC dendrites and synapses

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Celsr3 is required for the cerebellar LTP induction via the Wnt5a/cAMP signaling

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Celsr3 regulates the cerebellar LTD induction through the mGluR1/PKCα pathway

Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways

The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented through various types of neural pathways interactively routing excitation and inhibition converged to PCs. Such tuning of excitation and inhibition, coming from the gating of specific pathways as well as short-term plasticity (STP) of the synapses, plays a dominant role in controlling the PC dynamics in terms of firing rate and spike timing. PCs receive cascade feedforward inputs from two major neural pathways: the first one is the feedforward excitatory pathway from granule cells (GCs) to PCs; the second one is the feedforward inhibition pathway from GCs, via molecular layer interneurons (MLIs), to PCs. The GC-PC pathway, together with short-term dynamics of excitatory synapses, has been a focus over past decades, whereas recent experimental evidence shows that MLIs also greatly contribute to controlling PC activity. Therefore, it is expected that the diversity of excitation gated by STP of GC-PC synapses, modulated by strong inhibition from MLI-PC synapses, can promote the computation performed by PCs. However, it remains unclear how these two neural pathways are interacted to modulate PC dynamics. Here using a computational model of PC network installed with these two neural pathways, we addressed this question to investigate the change of PC firing dynamics at the level of single cell and network. We show that the nonlinear characteristics of excitatory STP dynamics can significantly modulate PC spiking dynamics mediated by inhibition. The changes in PC firing rate, firing phase, and temporal spike pattern, are strongly modulated by these two factors in different ways. MLIs mainly contribute to variable delays in the postsynaptic action potentials of PCs while modulated by excitation STP. Notably, the diversity of synchronization and pause response in the PC network is governed not only by the balance of excitation and inhibition, but also by the synaptic STP, depending on input burst patterns. Especially, the pause response shown in the PC network can only emerge with the interaction of both pathways. Together with other recent findings, our results show that the interaction of feedforward pathways of excitation and inhibition, incorporated with synaptic short-term dynamics, can dramatically regulate the PC activities that consequently change the network dynamics of the cerebellar circuit.

It is well known that the dynamics of neuronal networks are controlled by various types of neural pathways that are interactively routing excitation and inhibition converged to postsynaptic neurons. In addition, gating of a specific neural pathway is enhanced by short-term plasticity of the synapses between neurons. However, it remains unclear how a combination of these factors, the strengths of excitation and inhibition, and their short-term dynamics respectively, contributes to the dynamics of single cells and neuronal networks. Using a network model of cerebellar Purkinje cells embedded with the feedforward excitatory pathway from granule cells and feedforward inhibition pathway of molecular layer interneurons. We show that the dynamics of firing rate, firing phase, and temporal spike pattern are notably yet differently modulated by these two pathways. At the single cell level, excitatory short-term plasticity nonlinearly modulates the input-output relationship of firing activity. At the network level, the diversity of synchronization and pause response is governed not only by the balance of excitation and inhibition, but also by synaptic short-term dynamics. Only when both neural pathways are incorporated, there is a strong pause response shown in the network. Our results, together with recent in vivo experimental observations in the cerebellum, show that the interaction of feedforward pathways of excitation and inhibition, together with synaptic short-term dynamics, can dramatically change the network dynamics of Purkinje cells.

Gating by Functionally Indivisible Cerebellar Circuits: a Hypothesis

The attempt to understand the cerebellum has been dominated for years by supervised learning models. The central idea is that a learning algorithm modifies transmission strength at repeatedly co-active synapses, creating memories stored as finely calibrated synaptic weights. As a result, Purkinje cells, usually the de facto output cells of these models, acquire a modified response to input in a remembered pattern. This paper proposes an alternative model of pattern memory in which the function of a match is permissive, allowing but not driving output, and accordingly controlling the timing of output but not the rate of firing by Purkinje cells. Learning does not result in graded synaptic weights. There is no supervised learning algorithm or memory of individual patterns, which, like graded weights, are unnecessary to explain the evidence. Instead, patterns are classed as simply either known or not, at the level of input to a functional population of 100s of Purkinje cells (a microzone). The standard is strict. If only a handful of Purkinje cells receive a mismatch output of the whole circuit is blocked. Only if there is a full and accurate match are projection neurons in deep nuclei, which carry the output of most circuits, released from default inhibitory restraint. Purkinje cell firing at those times is a linear function of input rates. There is no effect of modification of synaptic transmission except to either allow or block output.

The Cellular Electrophysiological Properties Underlying Multiplexed Coding in Purkinje Cells

Neuronal firing patterns are crucial to underpin circuit level behaviors. In cerebellar Purkinje cells (PCs), both spike rates and pauses are used for behavioral coding, but the cellular mechanisms causing code transitions remain unknown. We use a well-validated PC model to explore the coding strategy that individual PCs use to process parallel fiber (PF) inputs. We find increasing input intensity shifts PCs from linear rate-coders to burst-pause timing-coders by triggering localized dendritic spikes. We validate dendritic spike properties with experimental data, elucidate spiking mechanisms, and predict spiking thresholds with and without inhibition. Both linear and burst-pause computations use individual branches as computational units, which challenges the traditional view of PCs as linear point neurons. Dendritic spike thresholds can be regulated by voltage state, compartmentalized channel modulation, between-branch interaction and synaptic inhibition to expand the dynamic range of linear computation or burst-pause computation. In addition, co-activated PF inputs between branches can modify somatic maximum spike rates and pause durations to make them carry analog signals. Our results provide new insights into the strategies used by individual neurons to expand their capacity of information processing.

SIGNIFICANCE STATEMENT Understanding how neurons process information is a fundamental question in neuroscience. Purkinje cells (PCs) were traditionally regarded as linear point neurons. We used computational modeling to unveil their electrophysiological properties underlying the multiplexed coding strategy that is observed during behaviors. We demonstrate that increasing input intensity triggers localized dendritic spikes, shifting PCs from linear rate-coders to burst-pause timing-coders. Both coding strategies work at the level of individual dendritic branches. Our work suggests that PCs have the ability to implement branch-specific multiplexed coding at the cellular level, thereby increasing the capacity of cerebellar coding and learning.

Dendritic coincidence detection in Purkinje neurons of awake mice

Dendritic coincidence detection is fundamental to neuronal processing yet remains largely unexplored in awake animals. Specifically, the underlying dendritic voltage–calcium relationship has not been directly addressed. Here, using simultaneous voltage and calcium two-photon imaging of Purkinje neuron spiny dendrites, we show how coincident synaptic inputs and resulting dendritic spikes modulate dendritic calcium signaling during sensory stimulation in awake mice. Sensory stimulation increased the rate of postsynaptic potentials and dendritic calcium spikes evoked by climbing fiber and parallel fiber synaptic input. These inputs are integrated in a time-dependent and nonlinear fashion to enhance the sensory-evoked dendritic calcium signal. Intrinsic supralinear dendritic mechanisms, including voltage-gated calcium channels and metabotropic glutamate receptors, are recruited cooperatively to expand the dynamic range of sensory-evoked dendritic calcium signals. This establishes how dendrites can use multiple interplaying mechanisms to perform coincidence detection, as a fundamental and ongoing feature of dendritic integration in behaving animals.

Is Purkinje Neuron Hyperpolarisation Important for Cerebellar Synaptic Plasticity? A Retrospective and Prospective Analysis

Two recent studies have demonstrated that the dendritic Ca²⁺ signal associated with a climbing fibre (CF) input to the cerebellar Purkinje neuron (PN) depends on the membrane potential (V_m). Specifically, when the cell is hyperpolarised, this signal is mediated by T-type voltage-gated Ca²⁺ channels; in contrast, when the cell is firing, the CF-PN signal is mediated by P/Q-type voltage-gated Ca²⁺ channels. When the CF input is paired with parallel fibre (PF) activity, the signal is locally amplified at the sites of PF-activated synapses according to the V_m at the time of the CF input, suggesting that the standing V_m is a critical parameter for the induction of PF synaptic plasticity. In this review, I analyse how the V_m can potentially play a role in cerebellar learning focussing, in particular, on the hyperpolarised state that appears to occur episodically, since PNs are mostly firing under physiological conditions. By revisiting the recent literature reporting in vivo recordings and synaptic plasticity studies, I speculate on how a putative role of the PN V_m can provide an interpretation for the results of these studies.