Sensorimotor Representations in Cerebellar Granule Cells in Larval Zebrafish Are Dense, Spatially Organized, and Non-temporally Patterned

Increased understanding of complex neuronal circuits in the cerebellar cortex

The prevailing belief has been that the fundamental structures of cerebellar neuronal circuits, consisting of a few major neuron types, are simple and well understood. Given that the cerebellum has long been known to be crucial for motor behaviors, these simple yet organized circuit structures seemed beneficial for theoretical studies proposing neural mechanisms underlying cerebellar motor functions and learning. On the other hand, experimental studies using advanced techniques have revealed numerous structural properties that were not traditionally defined. These include subdivided neuronal types and their circuit structures, feedback pathways from output Purkinje cells, and the multidimensional organization of neuronal interactions. With the recent recognition of the cerebellar involvement in non-motor functions, it is possible that these newly identified structural properties, which are potentially capable of generating greater complexity than previously recognized, are associated with increased information capacity. This, in turn, could contribute to the wide range of cerebellar functions. However, it remains largely unknown how such structural properties contribute to cerebellar neural computations through the regulation of neuronal activity or synaptic transmissions. To promote further research into cerebellar circuit structures and their functional significance, we aim to summarize the newly identified structural properties of the cerebellar cortex and discuss future research directions concerning cerebellar circuit structures and their potential functions.

Brain-wide circuitry underlying altered auditory habituation in zebrafish models of autism

Auditory processing is widely understood to occur differently in autism, though the patterns of brain activity underlying these differences are not well understood. The diversity of autism also means brain-wide networks may change in various ways to produce similar behavioral outputs. We used larval zebrafish to investigate auditory habituation in four genetic lines relevant to autism: fmr1, mecp2, scn1lab and cntnap2. In free-swimming behavioral tests, we found each line had a unique profile of auditory hypersensitivity and/or delayed habituation. Combining the optical transparency of larval zebrafish with genetically encoded calcium indicators and light-sheet microscopy, we then observed brain-wide activity at cellular resolution during auditory habituation. As with behavior, each line showed unique alterations in brain-wide spontaneous activity, auditory processing, and adaptation in response to repetitive acoustic stimuli. We also observed commonalities in activity across our genetic lines that indicate shared circuit changes underlying certain aspects of their behavioral phenotypes. These were predominantly in regions involved in sensory integration and sensorimotor gating rather than primary auditory areas. Overlapping phenotypes include differences in the activity and functional connectivity of the telencephalon, thalamus, dopaminergic regions, and the locus coeruleus, and excitatory/inhibitory imbalance in the cerebellum. Unique phenotypes include loss of activity in the habenula in scn1lab, increased activity in auditory regions in fmr1, and differences in network activity over time in mecp2 and cntnap2. Comparing these distinct but overlapping brain-wide auditory networks furthers our understanding of how diverse genetic factors can produce similar behavioral effects through a range of circuit- and network-scale mechanisms.

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.

Comparing the Representation of a Simple Visual Stimulus across the Cerebellar Network

The cerebellum is a conserved structure of the vertebrate brain involved in the timing and calibration of movements. Its function is supported by the convergence of fibers from granule cells (GCs) and inferior olive neurons (IONs) onto Purkinje cells (PCs). Theories of cerebellar function postulate that IONs convey error signals to PCs that, paired with the contextual information provided by GCs, can instruct motor learning. Here, we use the larval zebrafish to investigate (1) how sensory representations of the same stimulus vary across GCs and IONs and (2) how PC activity reflects these two different input streams. We use population calcium imaging to measure ION and GC responses to flashes of diverse luminance and duration. First, we observe that GCs show tonic and graded responses, as opposed to IONs, whose activity peaks mostly at luminance transitions, consistently with the notion that GCs and IONs encode context and error information, respectively. Second, we show that GC activity is patterned over time: some neurons exhibit sustained responses for the entire duration of the stimulus, while in others activity ramps up with slow time constants. This activity could provide a substrate for time representation in the cerebellum. Together, our observations give support to the notion of an error signal coming from IONs and provide the first experimental evidence for a temporal patterning of GC activity over many seconds.

Case report: Isolated brainstem-cerebellar symptoms in a patient with anti-NMDA receptor encephalitis

Cerebellar ataxia is an uncommon and atypical manifestation of anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis, often accompanied by seizures, psychiatric symptoms, and cognitive deficits. Previous cases of isolated brainstem-cerebellar symptoms in patients with anti-NMDAR encephalitis have not been documented. This report presents a case of anti-NMDAR encephalitis in which the patient exhibited cerebellar ataxia, nystagmus, diplopia, positive bilateral pathological signs, and hemiparesthesia with no other accompanying symptoms or signs. The presence of positive CSF anti-NMDAR antibodies further supports the diagnosis. Other autoantibodies were excluded through the use of cell-based assays. Immunotherapy was subsequently administered, leading to a gradual recovery of the patient.

Local synaptic inhibition mediates cerebellar granule cell pattern separation and enables learned sensorimotor associations

The cerebellar cortex has a key role in generating predictive sensorimotor associations. To do so, the granule cell layer is thought to establish unique sensorimotor representations for learning. However, how this is achieved and how granule cell population responses contribute to behavior have remained unclear. To address these questions, we have used in vivo calcium imaging and granule cell-specific pharmacological manipulation of synaptic inhibition in awake, behaving mice. These experiments indicate that inhibition sparsens and thresholds sensory responses, limiting overlap between sensory ensembles and preventing spiking in many granule cells that receive excitatory input. Moreover, inhibition can be recruited in a stimulus-specific manner to powerfully decorrelate multisensory ensembles. Consistent with these results, granule cell inhibition is required for accurate cerebellum-dependent sensorimotor behavior. These data thus reveal key mechanisms for granule cell layer pattern separation beyond those envisioned by classical models.

Cerebellar Purkinje Cells Control Posture in Larval Zebrafish (Danio rerio)

Cerebellar dysfunction leads to postural instability. Recent work in freely moving rodents has transformed investigations of cerebellar contributions to posture. However, the combined complexity of terrestrial locomotion and the rodent cerebellum motivate development of new approaches to perturb cerebellar function in simpler vertebrates. Here, we used a powerful chemogenetic tool (TRPV1/capsaicin) to define the role of Purkinje cells - the output neurons of the cerebellar cortex - as larval zebrafish swam freely in depth. We achieved both bidirectional control (activation and ablation) of Purkinje cells while performing quantitative high-throughput assessment of posture and locomotion. Activation disrupted postural control in the pitch (nose-up/nose-down) axis. Similarly, ablations disrupted pitch-axis posture and fin-body coordination responsible for climbs. Postural disruption was more widespread in older larvae, offering a window into emergent roles for the developing cerebellum in the control of posture. Finally, we found that activity in Purkinje cells could individually and collectively encode tilt direction, a key feature of postural control neurons. Our findings delineate an expected role for the cerebellum in postural control and vestibular sensation in larval zebrafish, establishing the validity of TRPV1/capsaicin-mediated perturbations in a simple, genetically-tractable vertebrate. Moreover, by comparing the contributions of Purkinje cell ablations to posture in time, we uncover signatures of emerging cerebellar control of posture across early development. This work takes a major step towards understanding an ancestral role of the cerebellum in regulating postural maturation.

Predictive neural computations in the cerebellum contribute to motor planning and faster behavioral responses in larval zebrafish

The ability to predict the future based on past experience lies at the core of the brain's ability to adapt behavior. However, the neural mechanisms that participate in generating and updating predictions are not clearly understood. Further, the evolutionary antecedents and the prevalence of predictive processing among vertebrates are even less explored. Here, we show evidence of predictive processing via the involvement of cerebellar circuits in larval zebrafish. We presented stereotyped optic flow stimuli to larval zebrafish to evoke swims and discovered that lesioning the cerebellum abolished prediction-dependent modulation of swim latency. When expectations of optic flow direction did not match with reality, error signals arrive at Purkinje cells via the olivary climbing fibers, whereas granule cells and Purkinje cells encode signals of expectation. Strong neural representations of expectation correlate with faster swim responses and vice versa. In sum, our results show evidence for predictive processing in nonmammalian vertebrates with the involvement of cerebellum, an evolutionarily conserved brain structure.

Cognitive-Affective Functions of the Cerebellum

The cerebellum, traditionally associated with motor coordination and balance, also plays a crucial role in various aspects of higher-order function and dysfunction. Emerging research has shed light on the cerebellum's broader contributions to cognitive, emotional, and reward processes. The cerebellum's influence on autonomic function further highlights its significance in regulating motivational and emotional states. Perturbations in cerebellar development and function have been implicated in various neurodevelopmental disorders, including autism spectrum disorder and attention deficit hyperactivity disorder. An increasing appreciation for neuropsychiatric symptoms that arise from cerebellar dysfunction underscores the importance of elucidating the circuit mechanisms that underlie complex interactions between the cerebellum and other brain regions for a comprehensive understanding of complex behavior. By briefly discussing new advances in mapping cerebellar function in affective, cognitive, autonomic, and social processing and reviewing the role of the cerebellum in neuropathology beyond the motor domain, this Mini-Symposium review aims to provide a broad perspective of cerebellar intersections with the limbic brain in health and disease.

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.

Task-dependent optimal representations for cerebellar learning

The cerebellar granule cell layer has inspired numerous theoretical models of neural representations that support learned behaviors, beginning with the work of Marr and Albus. In these models, granule cells form a sparse, combinatorial encoding of diverse sensorimotor inputs. Such sparse representations are optimal for learning to discriminate random stimuli. However, recent observations of dense, low-dimensional activity across granule cells have called into question the role of sparse coding in these neurons. Here, we generalize theories of cerebellar learning to determine the optimal granule cell representation for tasks beyond random stimulus discrimination, including continuous input-output transformations as required for smooth motor control. We show that for such tasks, the optimal granule cell representation is substantially denser than predicted by classical theories. Our results provide a general theory of learning in cerebellum-like systems and suggest that optimal cerebellar representations are task-dependent.

Synaptic variance and action potential firing of cerebellar output neurons during motor learning in larval zebrafish

The cerebellum regulates both reflexive and acquired movements. Here, by recording voltage-clamped synaptic currents and spiking in cerebellar output (eurydendroid) neurons in immobilized larval zebrafish, we investigated synaptic integration during reflexive movements and throughout associative motor learning. Spiking coincides with the onset of reflexive fictive swimming but precedes learned swimming, suggesting that eurydendroid signals may facilitate the initiation of acquired movements. Although firing rates increase during swimming, mean synaptic inhibition greatly exceeds mean excitation, indicating that learned responses cannot result solely from changes in synaptic weight or upstream excitability that favor excitation. Estimates of spike threshold crossings based on measurements of intrinsic properties and the time course of synaptic currents demonstrate that noisy excitation can transiently outweigh noisy inhibition enough to increase firing rates at swimming onset. Thus, the millisecond-scale variance of synaptic currents can regulate cerebellar output, and the emergence of learned cerebellar behaviors may involve a time-based code.

Development, circuitry, and function of the zebrafish cerebellum

The cerebellum represents a brain compartment that first appeared in gnathostomes (jawed vertebrates). Besides the addition of cell numbers, its development, cytoarchitecture, circuitry, physiology, and function have been highly conserved throughout avian and mammalian species. While cerebellar research in avian and mammals is extensive, systematic investigations on this brain compartment in zebrafish as a teleostian model organism started only about two decades ago, but has provided considerable insight into cerebellar development, physiology, and function since then. Zebrafish are genetically tractable with nearly transparent small-sized embryos, in which cerebellar development occurs within a few days. Therefore, genetic investigations accompanied with non-invasive high-resolution in vivo time-lapse imaging represents a powerful combination for interrogating the behavior and function of cerebellar cells in their complex native environment.

Effective and efficient neural networks for spike inference from in vivo calcium imaging

Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a supervised data-driven approach to extract spike information from calcium signals. We propose the ENS2 (effective and efficient neural networks for spike inference from calcium signals) system for spike-rate and spike-event predictions using ΔF/F0 calcium inputs based on a U-Net deep neural network. When testing on a large, ground-truth public database, it consistently outperformed state-of-the-art algorithms in both spike-rate and spike-event predictions with reduced computational load. We further demonstrated that ENS2 can be applied to analyses of orientation selectivity in primary visual cortex neurons. We conclude that it would be a versatile inference system that may benefit diverse neuroscience studies.

Multidimensional cerebellar computations for flexible kinematic control of movements

Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional computations for the flexible control of different movement parameters depending on the prevailing context. This conclusion is based on the identification of a manifold-like activity in both mossy fibers (MFs, network input) and Purkinje cells (PCs, output), recorded from monkeys performing a saccade task. Unlike MFs, the PC manifolds developed selective representations of individual movement parameters. Error feedback-driven climbing fiber input modulated the PC manifolds to predict specific, error type-dependent changes in subsequent actions. Furthermore, a feed-forward network model that simulated MF-to-PC transformations revealed that amplification and restructuring of the lesser variability in the MF activity is a pivotal circuit mechanism. Therefore, the flexible control of movements by the cerebellum crucially depends on its capacity for multi-dimensional computations.

Delay eyeblink conditioning performance and brain-wide c-Fos expression in male and female mice

Delay eyeblink conditioning has been extensively used to study associative learning and the cerebellar circuits underlying this task have been largely identified. However, there is a little knowledge on how factors such as strain, sex and innate behaviour influence performance during this type of learning. In this study, we used male and female mice of C57BL/6J (B6) and B6CBAF1 strains to investigate the effect of sex, strain and locomotion in delay eyeblink conditioning. We performed a short and a long delay eyeblink conditioning paradigm and used a c-Fos immunostaining approach to explore the involvement of different brain areas in this task. We found that both B6 and B6CBAF1 females reach higher learning scores compared to males in the initial stages of learning. This sex-dependent difference was no longer present as the learning progressed. Moreover, we found a strong positive correlation between learning scores and voluntary locomotion irrespective of the training duration. c-Fos immunostainings after the short paradigm showed positive correlations between c-Fos expression and learning scores in the cerebellar cortex and brainstem, as well as previously unreported areas. By contrast, after the long paradigm, c-Fos expression was only significantly elevated in the brainstem. Taken together, we show that differences in voluntary locomotion and activity across brain areas correlate with performance in delay eyeblink conditioning across strains and sexes.

Developmental timing-dependent organization of synaptic connections between mossy fibers and granule cells in the cerebellum

The long-standing hypothesis that synapses between mossy fibers (MFs) and cerebellar granule cells (GCs) are organized according to the origins of MFs and locations of GC axons, parallel fibers (PFs), is supported by recent findings. However, the mechanisms of such organized synaptic connections remain unknown. Here, using our technique that enabled PF location-dependent labeling of GCs in mice, we confirmed that synaptic connections of GCs with specific MFs originating from the pontine nucleus (PN-MFs) and dorsal column nuclei (DCoN-MFs) were gently but differentially organized according to their PF locations. We then found that overall MF-GC synaptic connectivity was biased in a way that dendrites of GCs having nearby PFs tended to connect with the same MF terminals, implying that the MF origin- and PF location-dependent organization is associated with the overall biased MF-GC synaptic connectivity. Furthermore, the development of PN-MFs preceded that of DCoN-MFs, which matches the developmental sequence of GCs that preferentially connect with each type of these MFs. Thus, our results revealed that overall MF-GC synaptic connectivity is biased in terms of PF locations, and suggested that such connectivity is likely the result of synaptic formation between developmental timing-matched partners.

Structured cerebellar connectivity supports resilient pattern separation

The cerebellum is thought to help detect and correct errors between intended and executed commands1,2 and is critical for social behaviours, cognition and emotion3-6. Computations for motor control must be performed quickly to correct errors in real time and should be sensitive to small differences between patterns for fine error correction while being resilient to noise7. Influential theories of cerebellar information processing have largely assumed random network connectivity, which increases the encoding capacity of the network's first layer8-13. However, maximizing encoding capacity reduces the resilience to noise7. To understand how neuronal circuits address this fundamental trade-off, we mapped the feedforward connectivity in the mouse cerebellar cortex using automated large-scale transmission electron microscopy and convolutional neural network-based image segmentation. We found that both the input and output layers of the circuit exhibit redundant and selective connectivity motifs, which contrast with prevailing models. Numerical simulations suggest that these redundant, non-random connectivity motifs increase the resilience to noise at a negligible cost to the overall encoding capacity. This work reveals how neuronal network structure can support a trade-off between encoding capacity and redundancy, unveiling principles of biological network architecture with implications for the design of artificial neural networks.

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

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

Cerebellum as a kernel machine: A novel perspective on expansion recoding in granule cell layer

Sensorimotor information provided by mossy fibers (MF) is mapped to high-dimensional space by a huge number of granule cells (GrC) in the cerebellar cortex's input layer. Significant studies have demonstrated the computational advantages and primary contributor of this expansion recoding. Here, we propose a novel perspective on the expansion recoding where each GrC serve as a kernel basis function, thereby the cerebellum can operate like a kernel machine that implicitly use high dimensional (even infinite) feature spaces. We highlight that the generation of kernel basis function is indeed biologically plausible scenario, considering that the key idea of kernel machine is to memorize important input patterns. We present potential regimes for developing kernels under constrained resources and discuss the advantages and disadvantages of each regime using various simulation settings.

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.

A Direct Interaction between Cyclodextrins and TASK Channels Decreases the Leak Current in Cerebellar Granule Neurons

Simple Summary

Cyclodextrins are cyclic oligosaccharides used to deplete cholesterol from cellular membranes. The effects of methyl-β-cyclodextrin (MβCD) on cellular functions originate principally from reductions in cholesterol levels. In this study, using immunocytochemistry, heterologous expression of K2P channels, and cholesterol-depleting maneuvers, we provide evidence of expression in cultured rat cerebellar granule neurons (CGNs) of TWIK-1 (K2P1), TASK-1 (K2P3), TASK-3 (K2P9), and TRESK (K2P18) channels and their association with lipid rafts using the specific lipids raft markers. In addition, we show a direct blocking with MβCD of TASK-1 and TASK-3 channels as well as for the covalently concatenated heterodimer TASK-1/TASK-3.

Abstract

Two pore domain potassium channels (K2P) are strongly expressed in the nervous system (CNS), where they play a central role in excitability. These channels give rise to background K⁺ currents, also known as IK_SO (standing-outward potassium current). We detected the expression in primary cultured cerebellar granule neurons (CGNs) of TWIK-1 (K2P1), TASK-1 (K2P3), TASK-3 (K2P9), and TRESK (K2P18) channels by immunocytochemistry and their association with lipid rafts using the specific lipids raft markers flotillin-2 and caveolin-1. At the functional level, methyl-β-cyclodextrin (MβCD, 5 mM) reduced IK_SO currents by ~40% in CGN cells. To dissect out this effect, we heterologously expressed the human TWIK-1, TASK-1, TASK-3, and TRESK channels in HEK-293 cells. MβCD directly blocked TASK-1 and TASK-3 channels and the covalently concatenated heterodimer TASK-1/TASK-3 currents. Conversely, MβCD did not affect TWIK-1- and TRESK-mediated K+ currents. On the other hand, the cholesterol-depleting agent filipin III did not affect TASK-1/TASK-3 channels. Together, the results suggest that neuronal background K⁺ channels are associated to lipid raft environments whilst the functional activity is independent of the cholesterol membrane organization.

The Cerebellar Cortex

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

Transduction of Brain Neurons in Juvenile Chum Salmon (Oncorhynchus keta) with Recombinant Adeno-Associated Hippocampal Virus Injected into the Cerebellum during Long-Term Monitoring

Corpus cerebelli in juvenile chum salmon is a multiprojective region of the brain connected via afferent and efferent projections with the higher regions of the brainstem and synencephalon, as well as with multiprojection regions of the medulla oblongata and spinal cord. During the postembryonic development of the cerebellum in chum salmon, Oncorhynchus keta, the lateral part of the juvenile cerebellum gives rise to the caudomedial part of the definitive cerebellum, which is consistent with the data reported for zebrafish and mouse cerebellum. Thus, the topographic organization of the cerebellum and its efferents are similar between fish (chum salmon and zebrafish) and mammals, including mice and humans. The distributions of recombinant adeno-associated viral vectors (rAAVs) after an injection of the base vector into the cerebellum have shown highly specific patterns of transgene expression in bipolar neurons in the latero-caudal lobe of the juvenile chum tectum opticum. The distribution of rAAVs in the dorsal thalamus, epithalamus, nucleus rotundus, and pretectal complex indicates the targeted distribution of the transgene via the thalamo-cerebellar projections. The detection of GFP expression in the cells of the epiphysis and posterior tubercle of juvenile chum salmon is associated with the transgene’s distribution and with the cerebrospinal fluid flow, the brain ventricles and its outer surface. The direct delivery of the rAAV into the central nervous system by intracerebroventricular administration allows it to spread widely in the brain. Thus, the presence of special projection areas in the juvenile chum salmon cerebellum, as well as outside it, and the identification of the transgene’s expression in them confirm the potential ability of rAAVs to distribute in both intracerebellar and afferent and efferent extracerebellar projections of the cerebellum.

Distinct representations of body and head motion are dynamically encoded by Purkinje cell populations in the macaque cerebellum

The ability to accurately control our posture and perceive our spatial orientation during self-motion requires knowledge of the motion of both the head and body. However, while the vestibular sensors and nuclei directly encode head motion, no sensors directly encode body motion. Instead, the integration of vestibular and neck proprioceptive inputs is necessary to transform vestibular information into the body-centric reference frame required for postural control. The anterior vermis of the cerebellum is thought to play a key role in this transformation, yet how its Purkinje cells transform multiple streams of sensory information into an estimate of body motion remains unknown. Here, we recorded the activity of individual anterior vermis Purkinje cells in alert monkeys during passively applied whole-body, body-under-head, and head-on-body rotations. Most Purkinje cells dynamically encoded an intermediate representation of self-motion between head and body motion. Notably, Purkinje cells responded to both vestibular and neck proprioceptive stimulation with considerable heterogeneity in their response dynamics. Furthermore, their vestibular responses were tuned to head-on-body position. In contrast, targeted neurons in the deep cerebellar nuclei are known to unambiguously encode either head or body motion across conditions. Using a simple population model, we established that combining responses of~40-50 Purkinje cells could explain the responses of these deep cerebellar nuclei neurons across all self-motion conditions. We propose that the observed heterogeneity in Purkinje cell response dynamics underlies the cerebellum’s capacity to compute the dynamic representation of body motion required to ensure accurate postural control and perceptual stability in our daily lives.

What Can We Learn from Synaptic Connectivity Maps about Cerebellar Internal Models?

The cerebellum is classically associated with fine motor control, motor learning, and timing of actions. However, while its anatomy is well described and many synaptic plasticity have been identified, the computation performed by the cerebellar cortex is still debated. We, here, review recent advances on how the description of the functional synaptic connectivity between granule cells and Purkinje cells support the hypothesis that the cerebellum stores internal models of the body coordinates. We propose that internal models are specific of the task and of the locomotor context of each individual.

Two-Photon Laser Ablation and In Vivo Wide-Field Imaging of Inferior Olive Neurons Revealed the Recovery of Olivocerebellar Circuits in Zebrafish

The cerebellum, a brain region with a high degree of plasticity, is pivotal in motor control, learning, and cognition. The cerebellar reserve is the capacity of the cerebellum to respond and adapt to various disorders via resilience and reversibility. Although structural and functional recovery has been reported in mammals and has attracted attention regarding treatments for cerebellar dysfunction, such as spinocerebellar degeneration, the regulatory mechanisms of the cerebellar reserve are largely unidentified, particularly at the circuit level. Herein, we established an optical approach using zebrafish, an ideal vertebrate model in optical techniques, neuroscience, and developmental biology. By combining two-photon laser ablation of the inferior olive (IO) and long-term non-invasive imaging of "the whole brain" at a single-cell resolution, we succeeded in visualization of the morphological changes occurring in the IO neuron population and showed at a single-cell level that structural remodeling of the olivocerebellar circuit occurred in a relatively short period. This system, in combination with various functional analyses, represents a novel and powerful approach for uncovering the mechanisms of the cerebellar reserve, and highlights the potential of the zebrafish model to elucidate the organizing principles of neuronal circuits and their homeostasis in health and disease.

Cerebellar granule cell axons support high-dimensional representations

In classical theories of cerebellar cortex, high-dimensional sensorimotor representations are used to separate neuronal activity patterns, improving associative learning and motor performance. Recent experimental studies suggest that cerebellar granule cell (GrC) population activity is low-dimensional. To examine sensorimotor representations from the point of view of downstream Purkinje cell 'decoders', we used three-dimensional acousto-optic lens two-photon microscopy to record from hundreds of GrC axons. Here we show that GrC axon population activity is high dimensional and distributed with little fine-scale spatial structure during spontaneous behaviors. Moreover, distinct behavioral states are represented along orthogonal dimensions in neuronal activity space. These results suggest that the cerebellar cortex supports high-dimensional representations and segregates behavioral state-dependent computations into orthogonal subspaces, as reported in the neocortex. Our findings match the predictions of cerebellar pattern separation theories and suggest that the cerebellum and neocortex use population codes with common features, despite their vastly different circuit structures.

Circuit Organization Underlying Optic Flow Processing in Zebrafish

Animals’ self-motion generates a drifting movement of the visual scene in the entire field of view called optic flow. Animals use the sensation of optic flow to estimate their own movements and accordingly adjust their body posture and position and stabilize the direction of gaze. In zebrafish and other vertebrates, optic flow typically drives the optokinetic response (OKR) and optomotor response (OMR). Recent functional imaging studies in larval zebrafish have identified the pretectum as a primary center for optic flow processing. In contrast to the view that the pretectum acts as a relay station of direction-selective retinal inputs, pretectal neurons respond to much more complex visual features relevant to behavior, such as spatially and temporally integrated optic flow information. Furthermore, optic flow signals, as well as motor signals, are represented in the cerebellum in a region-specific manner. Here we review recent findings on the circuit organization that underlies the optic flow processing driving OKR and OMR.

GluA4 facilitates cerebellar expansion coding and enables associative memory formation

AMPA receptors (AMPARs) mediate excitatory neurotransmission in the central nervous system (CNS) and their subunit composition determines synaptic efficacy. Whereas AMPAR subunits GluA1–GluA3 have been linked to particular forms of synaptic plasticity and learning, the functional role of GluA4 remains elusive. Here, we demonstrate a crucial function of GluA4 for synaptic excitation and associative memory formation in the cerebellum. Notably, GluA4-knockout mice had ~80% reduced mossy fiber to granule cell synaptic transmission. The fidelity of granule cell spike output was markedly decreased despite attenuated tonic inhibition and increased NMDA receptor-mediated transmission. Computational network modeling incorporating these changes revealed that deletion of GluA4 impairs granule cell expansion coding, which is important for pattern separation and associative learning. On a behavioral level, while locomotor coordination was generally spared, GluA4-knockout mice failed to form associative memories during delay eyeblink conditioning. These results demonstrate an essential role for GluA4-containing AMPARs in cerebellar information processing and associative learning.

The relationship between birth timing, circuit wiring, and physiological response properties of cerebellar granule cells

Cerebellar granule cells (GrCs) are usually regarded as a uniform cell type that collectively expands the coding space of the cerebellum by integrating diverse combinations of mossy fiber inputs. Accordingly, stable molecularly or physiologically defined GrC subtypes within a single cerebellar region have not been reported. The only known cellular property that distinguishes otherwise homogeneous GrCs is the correspondence between GrC birth timing and the depth of the molecular layer to which their axons project. To determine the role birth timing plays in GrC wiring and function, we developed genetic strategies to access early- and late-born GrCs. We initiated retrograde monosynaptic rabies virus tracing from control (birth timing unrestricted), early-born, and late-born GrCs, revealing the different patterns of mossy fiber input to GrCs in vermis lobule 6 and simplex, as well as to early- and late-born GrCs of vermis lobule 6: sensory and motor nuclei provide more input to early-born GrCs, while basal pontine and cerebellar nuclei provide more input to late-born GrCs. In vivo multidepth two-photon Ca2+ imaging of axons of early- and late-born GrCs revealed representations of diverse task variables and stimuli by both populations, with modest differences in the proportions encoding movement, reward anticipation, and reward consumption. Our results suggest neither organized parallel processing nor completely random organization of mossy fiber→GrC circuitry but instead a moderate influence of birth timing on GrC wiring and encoding. Our imaging data also provide evidence that GrCs can represent generalized responses to aversive stimuli, in addition to recently described reward representations.

Projection-dependent heterogeneity of cerebellar granule cell calcium responses

Cerebellar granule cells (GCs) relay mossy fiber (MF) inputs to Purkinje cell dendrites via their axons, the parallel fibers (PFs), which are individually located at a given sublayer of the molecular layer (ML). Although a certain degree of heterogeneity among GCs has been recently reported, variability of GC responses to MF inputs has never been associated with their most notable structural variability, location of their projecting PFs in the ML. Here, we utilize an adeno-associated virus (AAV)-mediated labeling technique that enables us to categorize GCs according to the location of their PFs, and compare the Ca²⁺ responses to MF stimulations between three groups of GCs, consisting of either GCs having PFs at the deep (D-GCs), middle (M-GCs), or superficial (S-GCs) sublayer. Our structural analysis revealed that there was no correlation between position of GC soma in the GC layer and location of its PF in the ML, confirming that our AAV-mediated labeling was important to test the projection-dependent variability of the Ca²⁺ responses in GCs. We then found that the Ca²⁺ responses of D-GCs differed from those of M-GCs. Pharmacological experiments implied that the different Ca²⁺ responses were mainly attributable to varied distributions of GABA_A receptors (GABA_ARs) at the synaptic and extrasynaptic regions of GC dendrites. In addition to GABA_AR distributions, amounts of extrasynaptic NMDA receptors appear to be also varied, because Ca²⁺ responses were different between D-GCs and M-GCs when glutamate spillover was enhanced. Whereas the Ca²⁺ responses of S-GCs were mostly equivalent to those of D-GCs and M-GCs, the blockade of GABA uptake resulted in larger Ca²⁺ responses in S-GCs compared with D-GCs and M-GCs, implying existence of mechanisms leading to more excitability in S-GCs with increased GABA release. Thus, this study reveals MF stimulation-mediated non-uniform Ca²⁺ responses in the cerebellar GCs associated with the location of their PFs in the ML, and raises a possibility that combination of inherent functional variability of GCs and their specific axonal projection contributes to the information processing through the GCs.

Environmentally relevant concentrations of boscalid exposure affects the neurobehavioral response of zebrafish by disrupting visual and nervous systems

Boscalid is a persistent fungicide that is frequently detected in surface waters and may be neurotoxic to aquatic organisms. Herein, we evaluated the effects of environmentally relevant boscalid concentrations to zebrafish to explore its potentially neurotoxic mechanisms of effect. Behavioral responses (swimming, phototaxis, and predation), histopathology, transcriptomics, biochemical parameter analysis and gene expression of larval and adult zebrafish following boscalid treatment were assessed. We found that boscalid significantly inhibited the locomotor ability and phototactic response of larvae after an 8-d exposure, and altered the locomotor activity, predation trajectories and ability in adults after a 21-d exposure. It was noted that predation rates of zebrafish were significantly decreased by 30% and 100% after exposure to 0.1 and 1.0 mg/L boscalid, respectively. Adverse alterations in the cell differentiation of eyes and brain injury were also observed in both larvae and adults following boscalid exposure. The expression of genes related to neurodevelopment, neurotransmission, eye development, and visual function, in conjunction with RNA-Seq results, indicated that boscalid may impair visual phototransduction and nervous system processes in larval zebrafish. Conclusively, boscalid exposure may affect the neurobehavioral response of zebrafish by impairing proper visual and nervous system function.

Diversity and dynamism in the cerebellum

The past several years have brought revelations and paradigm shifts in research on the cerebellum. Historically viewed as a simple sensorimotor controller with homogeneous architecture, the cerebellum is increasingly implicated in cognitive functions. It possesses an impressive diversity of molecular, cellular and circuit mechanisms, embedded in a dynamic, recurrent circuit architecture. Recent insights about the diversity and dynamism of the cerebellum provide a roadmap for the next decade of cerebellar research, challenging some old concepts, reinvigorating others and defining major new research directions.

Effect of diverse recoding of granule cells on optokinetic response in a cerebellar ring network with synaptic plasticity

We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varying the connection probability p_c from Golgi to GR cells. For an optimal value of p_c^∗(=0.06), individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of "effective" depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree L_g, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying p_c from p_c^∗, we find that a plot of saturated learning gain degree L_g^∗ versus p_c forms a bell-shaped curve with a peak at p_c^∗ (where the diversity degree in spiking patterns of GR cells is also maximum). Consequently, the more diverse in recoding of GR cells, the more effective in motor learning for the OKR adaptation.

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

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

Prediction signals in the cerebellum: beyond supervised motor learning

While classical views of cerebellar learning have suggested that this structure predominantly operates according to an error-based supervised learning rule to refine movements, emerging evidence suggests that the cerebellum may also harness a wider range of learning rules to contribute to a variety of behaviors, including cognitive processes. Together, such evidence points to a broad role for cerebellar circuits in generating and testing predictions about movement, reward, and other non-motor operations. However, this expanded view of cerebellar processing also raises many new questions about how such apparent diversity of function arises from a structure with striking homogeneity. Hence, this review will highlight both current evidence for predictive cerebellar circuit function that extends beyond the classical view of error-driven supervised learning, as well as open questions that must be addressed to unify our understanding cerebellar circuit function.

Cerebellar Neurodynamics Predict Decision Timing and Outcome on the Single-Trial Level

Goal-directed behavior requires the interaction of multiple brain regions. How these regions and their interactions with brain-wide activity drive action selection is less understood. We have investigated this question by combining whole-brain volumetric calcium imaging using light-field microscopy and an operant-conditioning task in larval zebrafish. We find global, recurring dynamics of brain states to exhibit pre-motor bifurcations toward mutually exclusive decision outcomes. These dynamics arise from a distributed network displaying trial-by-trial functional connectivity changes, especially between cerebellum and habenula, which correlate with decision outcome. Within this network the cerebellum shows particularly strong and predictive pre-motor activity (>10 s before movement initiation), mainly within the granule cells. Turn directions are determined by the difference neuroactivity between the ipsilateral and contralateral hemispheres, while the rate of bi-hemispheric population ramping quantitatively predicts decision time on the trial-by-trial level. Our results highlight a cognitive role of the cerebellum and its importance in motor planning.

Emerging connections between cerebellar development, behaviour and complex brain disorders

The human cerebellum has a protracted developmental timeline compared with the neocortex, expanding the window of vulnerability to neurological disorders. As the cerebellum is critical for motor behaviour, it is not surprising that most neurodevelopmental disorders share motor deficits as a common sequela. However, evidence gathered since the late 1980s suggests that the cerebellum is involved in motor and non-motor function, including cognition and emotion. More recently, evidence indicates that major neurodevelopmental disorders such as intellectual disability, autism spectrum disorder, attention-deficit hyperactivity disorder and Down syndrome have potential links to abnormal cerebellar development. Out of recent findings from clinical and preclinical studies, the concept of the 'cerebellar connectome' has emerged that can be used as a framework to link the role of cerebellar development to human behaviour, disease states and the design of better therapeutic strategies.

Neocortex-Cerebellum Circuits for Cognitive Processing

Although classically thought of as a motor circuit, the cerebellum is now understood to contribute to a wide variety of cognitive functions through its dense interconnections with the neocortex, the center of brain cognition. Recent investigations have shed light on the nature of cerebellar cognitive processing and information exchange with the neocortex. We review findings that demonstrate widespread reward-related cognitive input to the cerebellum, as well as new studies that have characterized the codependence of processing in the neocortex and cerebellum. Together, these data support a view of the neocortex-cerebellum circuit as a joint dynamic system both in classical sensorimotor contexts and reward-related, cognitive processing. These studies have also expanded classical theory on the computations performed by the cerebellar circuit.

The Zebrafish Visual System: From Circuits to Behavior

Visual stimuli can evoke complex behavioral responses, but the underlying streams of neural activity in mammalian brains are difficult to follow because of their size. Here, I review the visual system of zebrafish larvae, highlighting where recent experimental evidence has localized the functional steps of visuomotor transformations to specific brain areas. The retina of a larva encodes behaviorally relevant visual information in neural activity distributed across feature-selective ganglion cells such that signals representing distinct stimulus properties arrive in different areas or layers of the brain. Motor centers in the hindbrain encode motor variables that are precisely tuned to behavioral needs within a given stimulus setting. Owing to rapid technological progress, larval zebrafish provide unique opportunities for obtaining a comprehensive understanding of the intermediate processing steps occurring between visual and motor centers, revealing how visuomotor transformations are implemented in a vertebrate brain.

Sensorimotor Coding of Vermal Granule Neurons in the Developing Mammalian Cerebellum

The vermal cerebellum is a hub of sensorimotor integration critical for postural control and locomotion, but the nature and developmental organization of afferent information to this region have remained poorly understood in vivo Here, we use in vivo two-photon calcium imaging of the vermal cerebellum in awake behaving male and female mice to record granule neuron responses to diverse sensorimotor cues targeting visual, auditory, somatosensory, and motor domains. Use of an activity-independent marker revealed that approximately half (54%) of vermal granule neurons were activated during these recordings. A multikernel linear model distinguished the relative influences of external stimuli and co-occurring movements on neural responses, indicating that, among the subset of activated granule neurons, locomotion (44%-56%) and facial air puffs (50%) were more commonly and reliably encoded than visual (31%-32%) and auditory (19%-28%) stimuli. Strikingly, we also uncover populations of granule neurons that respond differentially to voluntary and forced locomotion, whereas other granule neurons in the same region respond similarly to locomotion in both conditions. Finally, by combining two-photon calcium imaging with birth date labeling of granule neurons via in vivo electroporation, we find that early- and late-born granule neurons convey similarly diverse sensorimotor information to spatially distinct regions of the molecular layer. Collectively, our findings elucidate the nature and developmental organization of sensorimotor information in vermal granule neurons of the developing mammalian brain.SIGNIFICANCE STATEMENT Cerebellar granule neurons comprise over half the neurons in the brain, and their coding properties have been the subject of theoretical and experimental interest for over a half-century. In this study, we directly test long-held theories about encoding of sensorimotor stimuli in the cerebellum and compare the in vivo coding properties of early- and late-born granule neurons. Strikingly, we identify populations of granule neurons that differentially encode voluntary and forced locomotion and find that, although the birth order of granule neurons specifies the positioning of their parallel fiber axons, both early- and late-born granule neurons convey a functionally diverse sensorimotor code. These findings constitute important conceptual advances in understanding the principles underlying cerebellar circuit development and function.

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.

Neuronal Architecture of a Visual Center that Processes Optic Flow

Animals use global image motion cues to actively stabilize their position by compensatory movements. Neurons in the zebrafish pretectum distinguish different optic flow patterns, e.g., rotation and translation, to drive appropriate behaviors. Combining functional imaging and morphological reconstruction of single cells, we revealed critical neuroanatomical features of this sensorimotor transformation. Terminals of direction-selective retinal ganglion cells (DS-RGCs) are located within the pretectal retinal arborization field 5 (AF5), where they meet dendrites of pretectal neurons with simple tuning to monocular optic flow. Translation-selective neurons, which respond selectively to optic flow in the same direction for both eyes, are intermingled with these simple cells but do not receive inputs from DS-RGCs. Mutually exclusive populations of pretectal projection neurons innervate either the reticular formation or the cerebellum, which in turn control motor responses. We posit that local computations in a defined pretectal circuit transform optic flow signals into neural commands driving optomotor behavior. VIDEO ABSTRACT.

Modeling Neurodegenerative Spinocerebellar Ataxia Type 13 in Zebrafish Using a Purkinje Neuron Specific Tunable Coexpression System

Purkinje cells (PCs) are primarily affected in neurodegenerative spinocerebellar ataxias (SCAs). For generating animal models for SCAs, genetic regulatory elements specifically targeting PCs are required, thereby linking pathological molecular effects with impaired function and organismic behavior. Because cerebellar anatomy and function are evolutionary conserved, zebrafish represent an excellent model to study SCAs in vivo We have isolated a 258 bp cross-species PC-specific enhancer element that can be used in a bidirectional manner for bioimaging of transgene-expressing PCs in zebrafish (both sexes) with variable copy numbers for tuning expression strength. Emerging ectopic expression at high copy numbers can be further eliminated by repurposing microRNA-mediated posttranslational mRNA regulation.Subsequently, we generated a transgenic SCA type 13 (SCA13) model, using a zebrafish-variant mimicking a human pathological SCA13R420H mutation, resulting in cell-autonomous progressive PC degeneration linked to cerebellum-driven eye-movement deficits as observed in SCA patients. This underscores that investigating PC-specific cerebellar neuropathologies in zebrafish allows for interconnecting bioimaging of disease mechanisms with behavioral analysis suitable for therapeutic compound testing.SIGNIFICANCE STATEMENT SCA13 patients carrying a KCNC3R420H allele have been shown to display mid-onset progressive cerebellar atrophy, but genetic modeling of SCA13 by expressing this pathogenic mutant in different animal models has not resulted in neuronal degeneration so far; likely because the transgene was expressed in heterologous cell types. We developed a genetic system for tunable PC-specific coexpression of several transgenes to manipulate and simultaneously monitor cerebellar PCs. We modeled a SCA13 zebrafish accessible for bioimaging to investigate disease progression, revealing robust PC degeneration, resulting in impaired eye movement. Our transgenic zebrafish mimicking both neuropathological and behavioral changes manifested in SCA-affected patients will be suitable for investigating causes of cerebellar diseases in vivo from the molecular to the behavioral level.