Characteristics of responses of Golgi cells and mossy fibers to eye saccades and saccadic adaptation recorded from the posterior vermis of the cerebellum

A deep-learning strategy to identify cell types across species from high-density extracellular recordings

High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but don't reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals, revealing the computational roles of neurons with distinct functional, molecular, and anatomical properties. We combine optogenetic activation and pharmacology using the cerebellum as a testbed to generate a curated ground-truth library of electrophysiological properties for Purkinje cells, molecular layer interneurons, Golgi cells, and mossy fibers. We train a semi-supervised deep-learning classifier that predicts cell types with greater than 95% accuracy based on waveform, discharge statistics, and layer of the recorded neuron. The classifier's predictions agree with expert classification on recordings using different probes, in different laboratories, from functionally distinct cerebellar regions, and across animal species. Our classifier extends the power of modern dynamical systems analyses by revealing the unique contributions of simultaneously-recorded cell types during behavior.

Organization of reward and movement signals in the basal ganglia and cerebellum

The basal ganglia and the cerebellum are major subcortical structures in the motor system. The basal ganglia have been cast as the reward center of the motor system, whereas the cerebellum is thought to be involved in adjusting sensorimotor parameters. Recent findings of reward signals in the cerebellum have challenged this dichotomous view. To compare the basal ganglia and the cerebellum directly, we recorded from oculomotor regions in both structures from the same monkeys. We partitioned the trial-by-trial variability of the neurons into reward and eye-movement signals to compare the coding across structures. Reward expectation and movement signals were the most pronounced in the output structure of the basal ganglia, intermediate in the cerebellum, and the smallest in the input structure of the basal ganglia. These findings suggest that reward and movement information is sharpened through the basal ganglia, resulting in a higher signal-to-noise ratio than in the cerebellum.

Closed-Loop Optogenetic Perturbation of Macaque Oculomotor Cerebellum: Evidence for an Internal Saccade Model

Internal models are essential for the production of accurate movements. The accuracy of saccadic eye movements is thought to be mediated by an internal model of oculomotor mechanics encoded in the cerebellum. The cerebellum may also be part of a feedback loop that predicts the displacement of the eyes and compares it to the desired displacement in real time to ensure that saccades land on target. To investigate the role of the cerebellum in these two aspects of saccade production, we delivered saccade-triggered light pulses to channelrhodopsin-2-expressing Purkinje cells in the oculomotor vermis (OMV) of two male macaque monkeys. Light pulses delivered during the acceleration phase of ipsiversive saccades slowed the deceleration phase. The long latency of these effects and their scaling with light pulse duration are consistent with an integration of neural signals at or downstream of the stimulation site. In contrast, light pulses delivered during contraversive saccades reduced saccade velocity at short latency and were followed by a compensatory reacceleration which caused gaze to land on or near the target. We conclude that the contribution of the OMV to saccade production depends on saccade direction; the ipsilateral OMV is part of a forward model that predicts eye displacement, whereas the contralateral OMV is part of an inverse model that creates the force required to move the eyes with optimal peak velocity for the intended displacement.

Closed-loop optogenetic perturbation of macaque oculomotor cerebellum: evidence for an internal saccade model

Internal models are essential for the production of accurate movements. The accuracy of saccadic eye movements is thought to be mediated by an internal model of oculomotor mechanics encoded in the cerebellum. The cerebellum may also be part of a feedback loop that predicts the displacement of the eyes and compares it to the desired displacement in real time to ensure that saccades land on target. To investigate the role of the cerebellum in these two aspects of saccade production, we delivered saccade-triggered light pulses to channelrhodopsin-2-expressing Purkinje cells in the oculomotor vermis (OMV) of two macaque monkeys. Light pulses delivered during the acceleration phase of ipsiversive saccades slowed the deceleration phase. The long latency of these effects and their scaling with light pulse duration are consistent with an integration of neural signals at or downstream of the stimulation site. In contrast, light pulses delivered during contraversive saccades reduced saccade velocity at short latency and were followed by a compensatory reacceleration which caused gaze to land near or on the target. We conclude that the contribution of the OMV to saccade production depends on saccade direction; the ipsilateral OMV is part of a forward model that predicts eye displacement, whereas the contralateral OMV is part of an inverse model that creates the force required to move the eyes with optimal peak velocity for the intended displacement.

Reduced Cerebellar BDNF Availability Affects Postnatal Differentiation and Maturation of Granule Cells in a Mouse Model of Cholesterol Dyshomeostasis

Niemann-Pick type C1 (NPC1) disease is a lysosomal lipid storage disorder due to mutations in the NPC1 gene resulting in the accumulation of cholesterol within the endosomal/lysosomal compartments. The prominent feature of the disorder is the progressive Purkinje cell degeneration leading to ataxia.In a mouse model of NPC1 disease, we have previously demonstrated that impaired Sonic hedgehog signaling causes defective proliferation of granule cells (GCs) and abnormal cerebellar morphogenesis. Studies conducted on cortical and hippocampal neurons indicate a functional interaction between Sonic hedgehog and brain-derived neurotrophic factor (BDNF) expression, leading us to hypothesize that BDNF signaling may be altered in Npc1 mutant mice, contributing to the onset of cerebellar alterations present in NPC1 disease before the appearance of signs of ataxia.We characterized the expression/localization patterns of the BDNF and its receptor, tropomyosin-related kinase B (TrkB), in the early postnatal and young adult cerebellum of the Npc1nmf164 mutant mouse strain.In Npc1nmf164 mice, our results show (i) a reduced expression of cerebellar BDNF and pTrkB in the first 2 weeks postpartum, phases in which most GCs complete the proliferative/migrative program and begin differentiation; (ii) an altered subcellular localization of the pTrkB receptor in GCs, both in vivo and in vitro; (iii) reduced chemotactic response to BDNF in GCs cultured in vitro, associated with impaired internalization of the activated TrkB receptor; (iv) an overall increase in dendritic branching in mature GCs, resulting in impaired differentiation of the cerebellar glomeruli, the major synaptic complex between GCs and mossy fibers.

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.

Multiple step saccades are generated by internal real-time saccadic error correction

Objectives

Multiple step saccades (MSSs) are an atypical form of saccade that consists of a series of small-amplitude saccades. It has been argued that the mechanism for generating MSS is due to the automatic saccadic plan. This argument was based on the observation that trials with MSS had shorter saccadic latency than trials without MSS in the reactive saccades. However, the validity of this argument has never been verified by other saccadic tasks. Alternatively, we and other researchers have speculated that the function of MSS is the same as that of the corrective saccade (CS), i.e., to correct saccadic errors. Thus, we propose that the function of the MSS is also to rectify saccadic errors and generated by forward internal models. The objective of the present study is to examine whether the automatic theory is universally applicable for the generation of MSSs in various saccadic tasks and to seek other possible mechanisms, such as error correction by forward internal models.

Methods

Fifty young healthy subjects (YHSs) and fifty elderly healthy subjects (EHSs) were recruited in the present study. The task paradigms were prosaccade (PS), anti-saccade (AS) and memory-guided saccade (MGS) tasks.

Results

Saccadic latency in trials with MSS was shorter than without MSS in the PS task but similar in the AS and MGS tasks. The intersaccadic intervals (ISI) were similar among the three tasks in both YHSs and EHSs.

Conclusion

Our results indicate that the automatic theory is not a universal mechanism. Instead, the forward internal model for saccadic error correction might be an important mechanism.

Neuronal activity patterns in microcircuits of the cerebellar cortical C3 zone during reaching

The cerebellum is the largest sensorimotor structure in the brain. A fundamental organizational feature of its cortex is its division into a series of rostrocaudally elongated zones. These are defined by their inputs from specific parts of the inferior olive and Purkinje cell output to specific cerebellar and vestibular nuclei. However, little is known about how patterns of neuronal activity in zones, and their microcircuit subdivisions, microzones, are related to behaviour in awake animals. In the present study, we investigated the organization of microzones within the C3 zone and their activity during a skilled forelimb reaching task in cats. Neurons in different microzones of the C3 zone, functionally determined by receptive field characteristics, differed in their patterns of activity during movement. Groups of Purkinje cells belonging to different receptive field classes, and therefore belonging to different microzones, were found to collectively encode different aspects of the reach controlled by the C3 zone. Our results support the hypothesis that the cerebellar C3 zone is organized and operates within a microzonal frame of reference, with a specific relationship between the sensory input to each microzone and its motor output. KEY POINTS: A defining feature of cerebellar organization is its division into a series of zones and smaller subunits termed microzones. Much of how zones and microzones are organized has been determined in anaesthetized preparations, and little is known about their function in awake animals. We recorded from neurons in the forelimb part of the C3 zone 'in action' by recording from single cerebellar cortical neurons located in different microzones defined by their peripheral receptive field properties during a forelimb reach-retrieval task in cats. Neurons from individual microzones had characteristic patterns of activity during movement, indicating that function is organized in relation to microcomplexes.

Associative anticipatory learning and control of the cerebellar cortex based on the spike-timing-dependent plasticity of the parallel fiber-Purkinje cell synapses

Time delays are inevitable in the neural processing of sensorimotor systems; small delays can cause severe damage to movement accuracy and stability. It is strongly suggested that the cerebellum compensates for delays in neural signal processing and performs predictive control. Neural computational theories have explored concepts of the internal models of control objects-believed to avoid delays by providing internal feedback information-although there has been no clear relevance to neural processing. The timing-dependent plasticity of parallel fiber-Purkinje cell synapses is well known. The long-term depression of the synapse is observed when parallel fiber activation precedes climbing fiber activation within -50-300 ms, and is the greatest within 50-200 ms. This paper presents a theory that this temporal difference of 50-200 ms is the basis for an associative anticipation of as many milliseconds. Associative learning can theoretically connect an input signal to a desired signal; therefore, a 50-200 ms earlier input signal can be connected to a desired output signal through temporary asymmetric plasticity. After learning is completed, an input signal generates a desired output signal that appears 50-200 ms later. For the associative learning of temporally continuous signals, this study integrates the universal function approximation capability of the cerebellar cortex model and temporally asymmetric synaptic plasticity to create the theory of associative anticipatory learning of the cerebellum. The effective motor control of this learning is demonstrated by adaptively stabilizing an inverted pendulum with a delay similar to that done by humans.

Role of the Vermal Cerebellum in Visually Guided Eye Movements and Visual Motion Perception

The cerebellar cortex is a crystal-like structure consisting of an almost endless repetition of a canonical microcircuit that applies the same computational principle to different inputs. The output of this transformation is broadcasted to extracerebellar structures by way of the deep cerebellar nuclei. Visually guided eye movements are accommodated by different parts of the cerebellum. This review primarily discusses the role of the oculomotor part of the vermal cerebellum [the oculomotor vermis (OMV)] in the control of visually guided saccades and smooth-pursuit eye movements. Both types of eye movements require the mapping of retinal information onto motor vectors, a transformation that is optimized by the OMV, considering information on past performance. Unlike the role of the OMV in the guidance of eye movements, the contribution of the adjoining vermal cortex to visual motion perception is nonmotor and involves a cerebellar influence on information processing in the cerebral cortex.

Modeling the Encoding of Saccade Kinematic Metrics in the Purkinje Cell Layer of the Cerebellar Vermis

Recent electrophysiological observations related to saccadic eye movements in rhesus monkeys, suggest a prediction of the sensory consequences of movement in the Purkinje cell layer of the cerebellar oculomotor vermis (OMV). A definite encoding of real-time motion of the eye has been observed in simple-spike responses of the combined burst-pause Purkinje cell populations, organized based upon their complex-spike directional tuning. However, the underlying control mechanisms that could lead to such action encoding are still unclear. We propose a saccade control model, with emphasis on the structure of the OMV and its interaction with the extra-cerebellar components. In the simulated bilateral organization of the OMV, each caudal fastigial nucleus is arranged to receive incoming projections from combined burst-pause Purkinje cell populations. The OMV, through the caudal fastigial nuclei, interacts with the brainstem to provide adaptive saccade gain corrections that minimize the visual error in reaching a given target location. The simulation results corroborate the experimental Purkinje cell population activity patterns and their relation with saccade kinematic metrics. The Purkinje layer activity that emerges from the proposed organization, precisely predicted the speed of the eye at different target eccentricities. Simulated granular layer activity suggests no separate dynamics with respect to shaping the bilateral Purkine layer activity. We further examine the validity of the simulated OMV in maintaining the accuracy of saccadic eye movements in the presence of signal dependent variabilities, that can occur in extra-cerebellar pathways.

Encoding of locomotion kinematics in the mouse cerebellum

The cerebellum is involved in coordinating motor behaviour, but how the cerebellar network regulates locomotion is still not well understood. We characterised the activity of putative cerebellar Purkinje cells, Golgi cells and mossy fibres in awake mice engaged in an active locomotion task, using high-density silicon electrode arrays. Analysis of the activity of over 300 neurons in response to locomotion revealed that the majority of cells (53%) were significantly modulated by phase of the stepping cycle. However, in contrast to studies involving passive locomotion on a treadmill, we found that a high proportion of cells (45%) were tuned to the speed of locomotion, and 19% were tuned to yaw movements. The activity of neurons in the cerebellar vermis provided more information about future speed of locomotion than about past or present speed, suggesting a motor, rather than purely sensory, role. We were able to accurately decode the speed of locomotion with a simple linear algorithm, with only a relatively small number of well-chosen cells needed, irrespective of cell class. Our observations suggest that behavioural state modulates cerebellar sensorimotor integration, and advocate a role for the cerebellar vermis in control of high-level locomotor kinematic parameters such as speed and yaw.

Learning from the past: A reverberation of past errors in the cerebellar climbing fiber signal

The cerebellum allows us to rapidly adjust motor behavior to the needs of the situation. It is commonly assumed that cerebellum-based motor learning is guided by the difference between the desired and the actual behavior, i.e., by error information. Not only immediate but also future behavior will benefit from an error because it induces lasting changes of parallel fiber synapses on Purkinje cells (PCs), whose output mediates the behavioral adjustments. Olivary climbing fibers, likewise connecting with PCs, are thought to transport information on instant errors needed for the synaptic modification yet not to contribute to error memory. Here, we report work on monkeys tested in a saccadic learning paradigm that challenges this concept. We demonstrate not only a clear complex spikes (CS) signature of the error at the time of its occurrence but also a reverberation of this signature much later, before a new manifestation of the behavior, suitable to improve it.

Population-scale organization of cerebellar granule neuron signaling during a visuomotor behavior

Granule cells at the input layer of the cerebellum comprise over half the neurons in the human brain and are thought to be critical for learning. However, little is known about granule neuron signaling at the population scale during behavior. We used calcium imaging in awake zebrafish during optokinetic behavior to record transgenically identified granule neurons throughout a cerebellar population. A significant fraction of the population was responsive at any given time. In contrast to core precerebellar populations, granule neuron responses were relatively heterogeneous, with variation in the degree of rectification and the balance of positive versus negative changes in activity. Functional correlations were strongest for nearby cells, with weak spatial gradients in the degree of rectification and the average sign of response. These data open a new window upon cerebellar function and suggest granule layer signals represent elementary building blocks under-represented in core sensorimotor pathways, thereby enabling the construction of novel patterns of activity for learning.

Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer

The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. Patterned mossy fiber activity induces rhythmic Golgi cell activity that is synchronized by shared parallel fiber input and by gap junctions. This leads to long distance synchrony of Golgi cells along the transverse axis, powerfully regulating granule cell firing by imposing inhibition during a specific time window. The essential network mechanisms, including tunable Golgi cell oscillations, on-beam inhibition and NMDA receptors causing first winner keeps winning of granule cells, illustrate how fundamental properties of the granule layer operate in tandem to produce (1) well timed and spatially bound output, (2) a wide dynamic range of granule cell firing and (3) transient and coherent gating oscillations. These results substantially enrich our understanding of granule cell layer processing, which seems to promote spatial group selection of granule cell activity as a function of timing of mossy fiber input.

The cerebellum is an organ of peculiar geometrical properties, and has been attributed the function of applying spatiotemporal transforms to sensorimotor data since Eccles. In this work we have analyzed the spatiotemporal response properties of the first part of the cerebellar circuit, the granule layer. On the basis of a biophysically plausible and large-scale model of the cerebellum, constrained by a wealth of anatomical data, we study the network dynamics and firing properties of individual cell populations in response to 'realistic' input patterns. We make specific predictions about the spatiotemporal features of granule layer processing regarding the effects of the gap junction coupled network of Golgi cells on a spatially restricted input, in an effect we denominate first-takes-all. Furthermore, we calculate that the granule cell layer has a wide dynamic range, indicating that this is a system that can transmit large variations of input intensities.

Selective Optogenetic Control of Purkinje Cells in Monkey Cerebellum

Purkinje cells of the primate cerebellum play critical but poorly understood roles in the execution of coordinated, accurate movements. Elucidating these roles has been hampered by a lack of techniques for manipulating spiking activity in these cells selectively-a problem common to most cell types in non-transgenic animals. To overcome this obstacle, we constructed AAV vectors carrying the channelrhodopsin-2 (ChR2) gene under the control of a 1 kb L7/Pcp2 promoter. We injected these vectors into the cerebellar cortex of rhesus macaques and tested vector efficacy in three ways. Immunohistochemical analyses confirmed selective ChR2 expression in Purkinje cells. Neurophysiological recordings confirmed robust optogenetic activation. Optical stimulation of the oculomotor vermis caused saccade dysmetria. Our results demonstrate the utility of AAV-L7-ChR2 for revealing the contributions of Purkinje cells to circuit function and behavior, and they attest to the feasibility of promoter-based, targeted, genetic manipulations in primates.

Robust transmission of rate coding in the inhibitory Purkinje cell to cerebellar nuclei pathway in awake mice

Neural coding through inhibitory projection pathways remains poorly understood. We analyze the transmission properties of the Purkinje cell (PC) to cerebellar nucleus (CN) pathway in a modeling study using a data set recorded in awake mice containing respiratory rate modulation. We find that inhibitory transmission from tonically active PCs can transmit a behavioral rate code with high fidelity. We parameterized the required population code in PC activity and determined that 20% of PC inputs to a full compartmental CN neuron model need to be rate-comodulated for transmission of a rate code. Rate covariance in PC inputs also accounts for the high coefficient of variation in CN spike trains, while the balance between excitation and inhibition determines spike rate and local spike train variability. Overall, our modeling study can fully account for observed spike train properties of cerebellar output in awake mice, and strongly supports rate coding in the cerebellum.

Detailed computer simulations of biological neurons can make an important contribution to our understanding of how the brain works. In this paper we use such a model of a neuron that represents the output from the cerebellum. We can show that the inhibition this neuron type receives from Purkinje cells in the cerebellar cortex is well suited to pass a detailed time course of movement control to the output of the cerebellum. Importantly we find that this type of coding requires a population of Purkinje cells that pass the same temporal coding of spike rate to the output neurons in the cerebellar nuclei.

Cerebellar Synaptic Plasticity and the Credit Assignment Problem

The mechanism by which a learnt synaptic weight change can contribute to learning or adaptation of brain function is a type of credit assignment problem, which is a key issue for many parts of the brain. In the cerebellum, detailed knowledge not only of the local circuitry connectivity but also of the topography of different sources of afferent/external information makes this problem particularly tractable. In addition, multiple forms of synaptic plasticity and their general rules of induction have been identified. In this review, we will discuss the possible roles of synaptic and cellular plasticity at specific locations in contributing to behavioral changes. Focus will be on the parts of the cerebellum that are devoted to limb control, which constitute a large proportion of the cortex and where the knowledge of the external connectivity is particularly well known. From this perspective, a number of sites of synaptic plasticity appear to primarily have the function of balancing the overall level of activity in the cerebellar circuitry, whereas the locations at which synaptic plasticity leads to functional changes in terms of limb control are more limited. Specifically, the postsynaptic forms of long-term potentiation (LTP) and long-term depression (LTD) at the parallel fiber synapses made on interneurons and Purkinje cells, respectively, are the types of plasticity that mediate the widest associative capacity and the tightest link between the synaptic change and the external functions that are to be controlled.

Cerebellar physiology: links between microcircuitry properties and sensorimotor functions

Existing knowledge of the cerebellar microcircuitry structure and physiology allows a rather detailed description of what it in itself can and cannot do. Combined with a known mapping of different cerebellar regions to afferent systems and motor output target structures, there are several constraints that can be used to describe how specific components of the cerebellar microcircuitry may work during sensorimotor control. In fact, as described in this review, the major factor that hampers further progress in understanding cerebellar function is the limited insights into the circuitry-level function of the targeted motor output systems and the nature of the information in the mossy fiber afferents. The cerebellar circuitry in itself is here summarized as a gigantic associative memory element, primarily consisting of the parallel fiber synapses, whereas most other circuitry components, including the climbing fiber system, primarily has the role of maintaining activity balance in the intracerebellar and extracerebellar circuitry. The review explores the consistency of this novel interpretational framework with multiple diverse observations at the synaptic and microcircuitry level within the cerebellum.

Conditional Spike Transmission Mediated by Electrical Coupling Ensures Millisecond Precision-Correlated Activity among Interneurons In Vivo

Many GABAergic interneurons are electrically coupled and in vitro can display correlated activity with millisecond precision. However, the mechanisms underlying correlated activity between interneurons in vivo are unknown. Using dual patch-clamp recordings in vivo, we reveal that in the presence of spontaneous background synaptic activity, electrically coupled cerebellar Golgi cells exhibit robust millisecond precision-correlated activity which is enhanced by sensory stimulation. This precisely correlated activity results from the cooperative action of two mechanisms. First, electrical coupling ensures slow subthreshold membrane potential correlations by equalizing membrane potential fluctuations, such that coupled neurons tend to approach action potential threshold together. Second, fast spike-triggered spikelets transmitted through gap junctions conditionally trigger postjunctional spikes, depending on both neurons being close to threshold. Electrical coupling therefore controls the temporal precision and degree of both spontaneous and sensory-evoked correlated activity between interneurons, by the cooperative effects of shared synaptic depolarization and spikelet transmission.

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Double patch-clamp recordings from Golgi cells reveal millisecond synchrony in vivo

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Millisecond synchrony requires gap junctions and is enhanced by sensory stimuli

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Gap junctions drive synchrony via slow V_m equalization and fast spikelet transmission

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Modeling shows these findings can be generalized to any electrically coupled neurons

Encoding of action by the Purkinje cells of the cerebellum

Execution of accurate eye movements depends critically on the cerebellum^1,2,3, suggesting that Purkinje cells (P-cells) may predict motion of the eye. Yet, this encoding has remained a long-standing puzzle: P-cells show little consistent modulation with respect to saccade amplitude^4,5 or direction⁴, and critically, their discharge lasts longer than duration of a saccade^6,7. Here, we analyzed P-cell discharge in the oculomotor vermis of behaving monkeys^8,9 and found neurons that increased or decreased their activity during saccades. We estimated the combined effect of these two populations via their projections on the caudal fastigial nucleus (cFN) and uncovered a simple-spike population response that precisely predicted the real-time motion of the eye. When we organized the P-cells according to each cell's complex-spike directional tuning, the simple-spike population response predicted both the real-time speed and direction of saccade multiplicatively via a gain-field. This suggests that the cerebellum predicts the real-time motion of the eye during saccades via the combined inputs of P-cells onto individual nucleus neurons. A gain-field encoding of simple spikes emerges if the P-cells that project onto a nucleus neuron are not selected at random, but share a common complex-spike property.

Information processing in the hemisphere of the cerebellar cortex for control of wrist movement

A region of cerebellar lobules V and VI makes strong loop connections with the primary motor (M1) and premotor (PM) cortical areas and is assumed to play essential roles in limb motor control. To examine its functional role, we compared the activities of its input, intermediate, and output elements, i.e., mossy fibers (MFs), Golgi cells (GoCs), and Purkinje cells (PCs), in three monkeys performing wrist movements in two different forearm postures. The results revealed distinct steps of information processing. First, MF activities displayed temporal and directional properties that were remarkably similar to those of M1/PM neurons, suggesting that MFs relay near copies of outputs from these motor areas. Second, all GoCs had a stereotyped pattern of activity independent of movement direction or forearm posture. Instead, GoC activity resembled an average of all MF activities. Therefore, inhibitory GoCs appear to provide a filtering function that passes only prominently modulated MF inputs to granule cells. Third, PCs displayed highly complex spatiotemporal patterns of activity, with coordinate frames distinct from those of MF inputs and directional tuning that changed abruptly before movement onset. The complexity of PC activities may reflect rapidly changing properties of the peripheral motor apparatus during movement. Overall, the cerebellar cortex appears to transform a representation of outputs from M1/PM into different movement representations in a posture-dependent manner and could work as part of a forward model that predicts the state of the peripheral motor apparatus.

Questioning the role of sparse coding in the brain

Coding principles are central to understanding the organization of brain circuitry. Sparse coding offers several advantages, but a near-consensus has developed that it only has beneficial properties, and these are partially unique to sparse coding. We find that these advantages come at the cost of several trade-offs, with the lower capacity for generalization being especially problematic, and the value of sparse coding as a measure and its experimental support are both questionable. Furthermore, silent synapses and inhibitory interneurons can permit learning speed and memory capacity that was previously ascribed to sparse coding only. Combining these properties without exaggerated sparse coding improves the capacity for generalization and facilitates learning of models of a complex and high-dimensional reality.

Single granule cells excite Golgi cells and evoke feedback inhibition in the cochlear nucleus

In cerebellum-like circuits, synapses from thousands of granule cells converge onto principal cells. This fact, combined with theoretical considerations, has led to the concept that granule cells encode afferent input as a population and that spiking in individual granule cells is relatively unimportant. However, granule cells also provide excitatory input to Golgi cells, each of which provide inhibition to hundreds of granule cells. We investigated whether spiking in individual granule cells could recruit Golgi cells and thereby trigger widespread inhibition in slices of mouse cochlear nucleus. Using paired whole-cell patch-clamp recordings, trains of action potentials at 100 Hz in single granule cells was sufficient to evoke spikes in Golgi cells in ∼40% of paired granule-to-Golgi cell recordings. High-frequency spiking in single granule cells evoked IPSCs in ∼5% of neighboring granule cells, indicating that bursts of activity in single granule cells can recruit feedback inhibition from Golgi cells. Moreover, IPSPs mediated by single Golgi cell action potentials paused granule cell firing, suggesting that inhibitory events recruited by activity in single granule cells were able to control granule cell firing. These results suggest a previously unappreciated relationship between population coding and bursting in single granule cells by which spiking in a small number of granule cells may have an impact on the activity of a much larger number of granule cells.

Duration of Purkinje cell complex spikes increases with their firing frequency

Climbing fiber (CF) triggered complex spikes (CS) are massive depolarization bursts in the cerebellar Purkinje cell (PC), showing several high frequency spikelet components (±600 Hz). Since its early observations, the CS is known to vary in shape. In this study we describe CS waveforms, extracellularly recorded in awake primates (Macaca mulatta) performing saccades. Every PC analyzed showed a range of CS shapes with profoundly different duration and number of spikelets. The initial part of the CS was rather constant but the later part differed greatly, with a pronounced jitter of the last spikelets causing a large variation in total CS duration. Waveforms did not effect the following pause duration in the simple spike (SS) train, nor were SS firing rates predictive of the waveform shapes or vice versa. The waveforms did not differ between experimental conditions nor was there a preferred sequential order of CS shapes throughout the recordings. Instead, part of their variability, the timing jitter of the CS’s last spikelets, strongly correlated with interval length to the preceding CS: shorter CS intervals resulted in later appearance of the last spikelets in the CS burst, and vice versa. A similar phenomenon was observed in rat PCs recorded in vitro upon repeated extracellular stimulation of CFs at different frequencies in slice experiments. All together these results strongly suggest that the variability in the timing of the last spikelet is due to CS frequency dependent changes in PC excitability.

Spontaneous activity does not predict morphological type in cerebellar interneurons

The effort to determine morphological and anatomically defined neuronal characteristics from extracellularly recorded physiological signatures has been attempted with varying success in different brain areas. Recent studies have attempted such classification of cerebellar interneurons (CINs) based on statistical measures of spontaneous activity. Previously, such efforts in different brain areas have used supervised clustering methods based on standard parameterizations of spontaneous interspike interval (ISI) histograms. We worried that this might bias researchers toward positive identification results and decided to take a different approach. We recorded CINs from anesthetized cats. We used unsupervised clustering methods applied to a nonparametric representation of the ISI histograms to identify groups of CINs with similar spontaneous activity and then asked how these groups map onto different cell types. Our approach was a fuzzy C-means clustering algorithm applied to the Kullbach-Leibler distances between ISI histograms. We found that there is, in fact, a natural clustering of the spontaneous activity of CINs into six groups but that there was no relationship between this clustering and the standard morphologically defined cell types. These results proved robust when generalization was tested to completely new datasets, including datasets recorded under different anesthesia conditions and in different laboratories and different species (rats). Our results suggest the importance of an unsupervised approach in categorizing neurons according to their extracellular activity. Indeed, a reexamination of such categorization efforts throughout the brain may be necessary. One important open question is that of functional differences of our six spontaneously defined clusters during actual behavior.

Synaptic diversity enables temporal coding of coincident multisensory inputs in single neurons

The ability of the brain to rapidly process information from multiple pathways is critical for reliable execution of complex sensory-motor behaviors, yet the cellular mechanisms underlying a neuronal representation of multimodal stimuli are poorly understood. Here we explored the possibility that the physiological diversity of mossy fiber (MF) to granule cell (GC) synapses within the mouse vestibulocerebellum may contribute to the processing of coincident multisensory information at the level of individual GCs. We found that the strength and short-term dynamics of individual MF-GC synapses can act as biophysical signatures for primary vestibular, secondary vestibular and visual input pathways. The majority of GCs receive inputs from different modalities, which when co-activated, produced enhanced GC firing rates and distinct first spike latencies. Thus, pathway-specific synaptic response properties permit temporal coding of correlated multisensory input by single GCs, thereby enriching sensory representation and facilitating pattern separation.

In vivo properties of cerebellar interneurons in the macaque caudal vestibular vermis

KEY POINTS

We quantify both spontaneous and stimulus-driven responses of interneurons in lobules X (nodulus) and IXc,d (ventral uvula) of the caudal vermis during vestibular stimulation. Based on baseline firing, at least three types of neuronal populations could be distinguished. First, there was a group of very regular firing neurons with high mean discharge rates. Second, there was a group of low firing neurons with a range of discharge regularity. Third, we also encountered putative interneurons with discharge regularity and mean firing rates that were indistinguishable from those of physiologically identified Purkinje cells. The vestibular responses of putative interneurons were generally similar to those of Purkinje cells, thus encoding tilt, translation or mixtures of these signals. Mossy fibres showed unprocessed, otolith afferent-like properties. The cerebellar cortex is among the brain's most well-studied circuits and includes distinct classes of excitatory and inhibitory interneurons. Several studies have attempted to characterize the in vivo properties of cerebellar interneurons, yet little is currently known about their stimulus-driven properties. Here we quantify both spontaneous and stimulus-driven responses of interneurons in lobules X (nodulus) and IXc,d (ventral uvula) of the macaque caudal vermis during vestibular stimulation. Interneurons were identified as cells located >100 μm from the Purkinje cell layer that did not exhibit complex spikes. Based on baseline firing, three types of interneurons could be distinguished. First, there was a group of very regular firing interneurons with high mean discharge rates, which consistently encoded tilt, rather than translational head movements. Second, there was a group of low firing interneurons with a range of discharge regularity. This group had more diverse vestibular properties, where most were translation-selective and a few tilt- or gravitoinertial acceleration-selective. Third, we also encountered interneurons that were similar to Purkinje cells in terms of discharge regularity and mean firing rate. This group also encoded mixtures of tilt and translation signals. A few mossy fibres showed unprocessed, otolith afferent-like properties, encoding the gravitoinertial acceleration. We conclude that tilt- and translation-selective signals, which reflect neural computations transforming vestibular afferent information, are not only encountered in Purkinje cell responses. Instead, upstream interneurons within the cerebellar cortex are also characterized by similar properties, thus implying a widespread network computation.

Cerebellum-dependent motor learning: lessons from adaptation of eye movements in primates

In order to ameliorate the consequences of ego motion for vision, human and nonhuman observers generate reflexive, compensatory eye movements based on visual as well as vestibular information, helping to stabilize the images of visual scenes on the retina despite ego motion. And in order to fully exploit the advantages of foveal vision, they make saccades to shift the image of an object onto the fovea and smooth pursuit eye movements to stabilize it there despite continuing object movement relative to the observer. With the exception of slow visually driven eye movements, which can be understood as manifestations of relatively straightforward feedback systems, most eye movements require a direct conversion of sensory input into appropriate motor responses in the absence of immediate sensory feedback. Hence, in order to generate appropriate oculomotor responses, the parameters linking input and output must be chosen suitably. Moreover, as the parameters may change from one manifestation of a movement to the next, for instance because of oculomotor fatigue, the choices should also be quickly modifiable. This chapter will present evidence showing that this fast parametric optimization, understood as a functionally distinct example of motor learning, is an accomplishment of specific parts of the cerebellum devoted to the control of eye movements. It will also discuss recent electrophysiological results suggesting how this specific form of motor learning may emerge from information processing in cerebellar circuits.

Cerebellar cortex granular layer interneurons in the macaque monkey are functionally driven by mossy fiber pathways through net excitation or inhibition

The granular layer is the input layer of the cerebellar cortex. It receives information through mossy fibers, which contact local granular layer interneurons (GLIs) and granular layer output neurons (granule cells). GLIs provide one of the first signal processing stages in the cerebellar cortex by exciting or inhibiting granule cells. Despite the importance of this early processing stage for later cerebellar computations, the responses of GLIs and the functional connections of mossy fibers with GLIs in awake animals are poorly understood. Here, we recorded GLIs and mossy fibers in the macaque ventral-paraflocculus (VPFL) during oculomotor tasks, providing the first full inventory of GLI responses in the VPFL of awake primates. We found that while mossy fiber responses are characterized by a linear monotonic relationship between firing rate and eye position, GLIs show complex response profiles characterized by “eye position fields” and single or double directional tunings. For the majority of GLIs, prominent features of their responses can be explained by assuming that a single GLI receives inputs from mossy fibers with similar or opposite directional preferences, and that these mossy fiber inputs influence GLI discharge through net excitatory or inhibitory pathways. Importantly, GLIs receiving mossy fiber inputs through these putative excitatory and inhibitory pathways show different firing properties, suggesting that they indeed correspond to two distinct classes of interneurons. We propose a new interpretation of the information flow through the cerebellar cortex granular layer, in which mossy fiber input patterns drive the responses of GLIs not only through excitatory but also through net inhibitory pathways, and that excited and inhibited GLIs can be identified based on their responses and their intrinsic properties.

Granule cell ascending axon excitatory synapses onto Golgi cells implement a potent feedback circuit in the cerebellar granular layer

The function of inhibitory interneurons within brain microcircuits depends critically on the nature and properties of their excitatory synaptic drive. Golgi cells (GoCs) of the cerebellum inhibit cerebellar granule cells (GrCs) and are driven both by feedforward mossy fiber (mf) and feedback GrC excitation. Here, we have characterized GrC inputs to GoCs in rats and mice. We show that, during sustained mf discharge, synapses from local GrCs contribute equivalent charge to GoCs as mf synapses, arguing for the importance of the feedback inhibition. Previous studies predicted that GrC-GoC synapses occur predominantly between parallel fibers (pfs) and apical GoC dendrites in the molecular layer (ML). By combining EM and Ca(2+) imaging, we now demonstrate the presence of functional synaptic contacts between ascending axons (aa) of GrCs and basolateral dendrites of GoCs in the granular layer (GL). Immunohistochemical quantification estimates these contacts to be ∼400 per GoC. Using Ca(2+) imaging to identify synaptic inputs, we show that EPSCs from aa and mf contacts in basolateral dendrites display similarly fast kinetics, whereas pf inputs in the ML exhibit markedly slower kinetics as they undergo strong filtering by apical dendrites. We estimate that approximately half of the local GrC contacts generate fast EPSCs, indicating their basolateral location in the GL. We conclude that GrCs, through their aa contacts onto proximal GoC dendrites, define a powerful feedback inhibitory circuit in the GL.

Golgi cell activity during eyeblink conditioning in decerebrate ferrets

Golgi cells have a central position in the cerebellar cortical network and are indirectly connected to Purkinje cells, which are important for the acquisition of learned responses in classical conditioning. In order to clarify the role of Golgi cells in classical conditioning, we made extracellular Golgi cell recordings during different stages of conditioning, using four different conditional stimuli. Our results show that forelimb and superior colliculus stimulation, but not mossy fiber stimulation, evokes a short latency increase in Golgi cell firing. These results suggest that Golgi cells are involved in modulating input to the cerebellar cortex. There were however no differences in Golgi cell activity between naïve and trained animals, which suggests that Golgi cells are not intimately involved in the plastic changes that occur during classical conditioning. The absence of long latency effects of the conditional stimulus also questions whether Golgi cells contribute to the generation of a temporal code in the granule cells.

The cerebellar Golgi cell and spatiotemporal organization of granular layer activity

The cerebellar granular layer has been suggested to perform a complex spatiotemporal reconfiguration of incoming mossy fiber signals. Central to this role is the inhibitory action exerted by Golgi cells over granule cells: Golgi cells inhibit granule cells through both feedforward and feedback inhibitory loops and generate a broad lateral inhibition that extends beyond the afferent synaptic field. This characteristic connectivity has recently been investigated in great detail and been correlated with specific functional properties of these neurons. These include theta-frequency pacemaking, network entrainment into coherent oscillations and phase resetting. Important advances have also been made in terms of determining the membrane and synaptic properties of the neuron, and clarifying the mechanisms of activation by input bursts. Moreover, voltage sensitive dye imaging and multi-electrode array (MEA) recordings, combined with mathematical simulations based on realistic computational models, have improved our understanding of the impact of Golgi cell activity on granular layer circuit computations. These investigations have highlighted the critical role of Golgi cells in: generating dense clusters of granule cell activity organized in center-surround structures, implementing combinatorial operations on multiple mossy fiber inputs, regulating transmission gain, and cut-off frequency, controlling spike timing and burst transmission, and determining the sign, intensity and duration of long-term synaptic plasticity at the mossy fiber-granule cell relay. This review considers recent advances in the field, highlighting the functional implications of Golgi cells for granular layer network computation and indicating new challenges for cerebellar research.

New supervised learning theory applied to cerebellar modeling for suppression of variability of saccade end points

A new supervised learning theory is proposed for a hierarchical neural network with a single hidden layer of threshold units, which can approximate any continuous transformation, and applied to a cerebellar function to suppress the end-point variability of saccades. In motor systems, feedback control can reduce noise effects if the noise is added in a pathway from a motor center to a peripheral effector; however, it cannot reduce noise effects if the noise is generated in the motor center itself: a new control scheme is necessary for such noise. The cerebellar cortex is well known as a supervised learning system, and a novel theory of cerebellar cortical function developed in this study can explain the capability of the cerebellum to feedforwardly reduce noise effects, such as end-point variability of saccades. This theory assumes that a Golgi-granule cell system can encode the strength of a mossy fiber input as the state of neuronal activity of parallel fibers. By combining these parallel fiber signals with appropriate connection weights to produce a Purkinje cell output, an arbitrary continuous input-output relationship can be obtained. By incorporating such flexible computation and learning ability in a process of saccadic gain adaptation, a new control scheme in which the cerebellar cortex feedforwardly suppresses the end-point variability when it detects a variation in saccadic commands can be devised. Computer simulation confirmed the efficiency of such learning and showed a reduction in the variability of saccadic end points, similar to results obtained from experimental data.

Processing of multi-dimensional sensorimotor information in the spinal and cerebellar neuronal circuitry: a new hypothesis

Why are sensory signals and motor command signals combined in the neurons of origin of the spinocerebellar pathways and why are the granule cells that receive this input thresholded with respect to their spike output? In this paper, we synthesize a number of findings into a new hypothesis for how the spinocerebellar systems and the cerebellar cortex can interact to support coordination of our multi-segmented limbs and bodies. A central idea is that recombination of the signals available to the spinocerebellar neurons can be used to approximate a wide array of functions including the spatial and temporal dependencies between limb segments, i.e. information that is necessary in order to achieve coordination. We find that random recombination of sensory and motor signals is not a good strategy since, surprisingly, the number of granule cells severely limits the number of recombinations that can be represented within the cerebellum. Instead, we propose that the spinal circuitry provides useful recombinations, which can be described as linear projections through aspects of the multi-dimensional sensorimotor input space. Granule cells, potentially with the aid of differentiated thresholding from Golgi cells, enhance the utility of these projections by allowing the Purkinje cell to establish piecewise-linear approximations of non-linear functions. Our hypothesis provides a novel view on the function of the spinal circuitry and cerebellar granule layer, illustrating how the coordinating functions of the cerebellum can be crucially supported by the recombinations performed by the neurons of the spinocerebellar systems.

A vermal Purkinje cell simple spike population response encodes the changes in eye movement kinematics due to smooth pursuit adaptation

Smooth pursuit adaptation (SPA) is an example of cerebellum-dependent motor learning that depends on the integrity of the oculomotor vermis (OMV). In an attempt to unveil the neuronal basis of the role of the OMV in SPA, we recorded Purkinje cell simple spikes (PC SS) of trained monkeys. Individual PC SS exhibited specific changes of their discharge patterns during the course of SPA. However, these individual changes did not provide a reliable explanation of the behavioral changes. On the other hand, the population response of PC SS perfectly reflected the changes resulting from adaptation. Population vector was calculated using all cells recorded independent of their location. A population code conveying the behavioral changes is in full accordance with the anatomical convergence of PC axons on target neurons in the cerebellar nuclei. Its computational advantage is the ease with which it can be adjusted to the needs of the behavior by changing the contribution of individual PC SS based on error feedback.

Probabilistic identification of cerebellar cortical neurones across species

Despite our fine-grain anatomical knowledge of the cerebellar cortex, electrophysiological studies of circuit information processing over the last fifty years have been hampered by the difficulty of reliably assigning signals to identified cell types. We approached this problem by assessing the spontaneous activity signatures of identified cerebellar cortical neurones. A range of statistics describing firing frequency and irregularity were then used, individually and in combination, to build Gaussian Process Classifiers (GPC) leading to a probabilistic classification of each neurone type and the computation of equi-probable decision boundaries between cell classes. Firing frequency statistics were useful for separating Purkinje cells from granular layer units, whilst firing irregularity measures proved most useful for distinguishing cells within granular layer cell classes. Considered as single statistics, we achieved classification accuracies of 72.5% and 92.7% for granular layer and molecular layer units respectively. Combining statistics to form twin-variate GPC models substantially improved classification accuracies with the combination of mean spike frequency and log-interval entropy offering classification accuracies of 92.7% and 99.2% for our molecular and granular layer models, respectively. A cross-species comparison was performed, using data drawn from anaesthetised mice and decerebrate cats, where our models offered 80% and 100% classification accuracy. We then used our models to assess non-identified data from awake monkeys and rabbits in order to highlight subsets of neurones with the greatest degree of similarity to identified cell classes. In this way, our GPC-based approach for tentatively identifying neurones from their spontaneous activity signatures, in the absence of an established ground-truth, nonetheless affords the experimenter a statistically robust means of grouping cells with properties matching known cell classes. Our approach therefore may have broad application to a variety of future cerebellar cortical investigations, particularly in awake animals where opportunities for definitive cell identification are limited.

Eye-hand synergy and intermittent behaviors during target-directed tracking with visual and non-visual information

Visual feedback and non-visual information play different roles in tracking of an external target. This study explored the respective roles of the visual and non-visual information in eleven healthy volunteers who coupled the manual cursor to a rhythmically moving target of 0.5 Hz under three sensorimotor conditions: eye-alone tracking (EA), eye-hand tracking with visual feedback of manual outputs (EH tracking), and the same tracking without such feedback (EHM tracking). Tracking error, kinematic variables, and movement intermittency (saccade and speed pulse) were contrasted among tracking conditions. The results showed that EHM tracking exhibited larger pursuit gain, less tracking error, and less movement intermittency for the ocular plant than EA tracking. With the vision of manual cursor, EH tracking achieved superior tracking congruency of the ocular and manual effectors with smaller movement intermittency than EHM tracking, except that the rate precision of manual action was similar for both types of tracking. The present study demonstrated that visibility of manual consequences altered mutual relationships between movement intermittency and tracking error. The speed pulse metrics of manual output were linked to ocular tracking error, and saccade events were time-locked to the positional error of manual tracking during EH tracking. In conclusion, peripheral non-visual information is critical to smooth pursuit characteristics and rate control of rhythmic manual tracking. Visual information adds to eye-hand synchrony, underlying improved amplitude control and elaborate error interpretation during oculo-manual tracking.

Event time representation in cerebellar mossy fibres arising from the lateral reticular nucleus

Time representation is an important element of cerebellar neural processing, but the mechanisms involved are poorly understood. We demonstrate that the major mossy fibre input system originating from the lateral reticular nucleus (LRN) can represent sensory event timing over hundreds of milliseconds. In vivo, cerebellar-projecting LRN neurons discharge extremely regularly with a clock-like rhythm. In response to stimulation of a wide peripheral receptive field, firing briefly pauses then resumes with precise timing. The precision of post-stimulus spikes and the regularity of firing mean that the stimulus timing is represented by LRN spike timing over hundreds of milliseconds. In an arithmetic progression model of LRN neuron firing, highly predictable post-stimulus spike timing is modulated by changing the variability of the first post-inhibitory spike and of the subsequent interspike intervals. From in vitro analysis we show that the Ca(2+)-activated small-conductance K(+) current (SK) contributes to interspike interval regularity and that the hyperpolarization-activated cation current (I(h)) contributes to short-latency, high-precision post-hyperpolarisation spike timing. Consistent with this, we demonstrate in vivo that resumption of firing becomes more sharply timed after longer stimulus-evoked pauses. Thus, I(h) is a potential conductance that could mediate the precisely timed resumption of firing after the pause. Through the widespread projections of LRN neurons, these properties may enable the LRN to provide precisely timed signals to the cerebellum over a prolonged period following a stimulus, which may also both activate and sustain oscillatory processes in the cerebellar cortex.

Distributed synergistic plasticity and cerebellar learning

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

Widespread state-dependent shifts in cerebellar activity in locomoting mice

Excitatory drive enters the cerebellum via mossy fibers, which activate granule cells, and climbing fibers, which activate Purkinje cell dendrites. Until now, the coordinated regulation of these pathways has gone unmonitored in spatially resolved neuronal ensembles, especially in awake animals. We imaged cerebellar activity using functional two-photon microscopy and extracellular recording in awake mice locomoting on an air-cushioned spherical treadmill. We recorded from putative granule cells, molecular layer interneurons, and Purkinje cell dendrites in zone A of lobule IV/V, representing sensation and movement from trunk and limbs. Locomotion was associated with widespread increased activity in granule cells and interneurons, consistent with an increase in mossy fiber drive. At the same time, dendrites of different Purkinje cells showed increased co-activation, reflecting increased synchrony of climbing fiber activity. In resting animals, aversive stimuli triggered increased activity in granule cells and interneurons, as well as increased Purkinje cell co-activation that was strongest for neighboring dendrites and decreased smoothly as a function of mediolateral distance. In contrast with anesthetized recordings, no 1–10 Hz oscillations in climbing fiber activity were evident. Once locomotion began, responses to external stimuli in all three cell types were strongly suppressed. Thus climbing and mossy fiber representations can shift together within a fraction of a second, reflecting in turn either movement-associated activity or external stimuli.

NMDA receptors with incomplete Mg²⁺ block enable low-frequency transmission through the cerebellar cortex

The cerebellar cortex coordinates movements and maintains balance by modifying motor commands as a function of sensory-motor context, which is encoded by mossy fiber (MF) activity. MFs exhibit a wide range of activity, from brief precisely timed high-frequency bursts, which encode discrete variables such as whisker stimulation, to low-frequency sustained rate-coded modulation, which encodes continuous variables such as head velocity. While high-frequency MF inputs have been shown to activate granule cells (GCs) effectively, much less is known about sustained low-frequency signaling through the GC layer, which is impeded by a hyperpolarized resting potential and strong GABA(A)-mediated tonic inhibition of GCs. Here we have exploited the intrinsic MF network of unipolar brush cells to activate GCs with sustained low-frequency asynchronous MF inputs in rat cerebellar slices. We find that low-frequency MF input modulates the intrinsic firing of Purkinje cells, and that this signal transmission through the GC layer requires synaptic activation of Mg²⁺-block-resistant NMDA receptors (NMDARs) that are likely to contain the GluN2C subunit. Slow NMDAR conductances sum temporally to contribute approximately half the MF-GC synaptic charge at hyperpolarized potentials. Simulations of synaptic integration in GCs show that the NMDAR and slow spillover-activated AMPA receptor (AMPAR) components depolarize GCs to a similar extent. Moreover, their combined depolarizing effect enables the fast quantal AMPAR component to trigger action potentials at low MF input frequencies. Our results suggest that the weak Mg²⁺ block of GluN2C-containing NMDARs enables transmission of low-frequency MF signals through the input layer of the cerebellar cortex.

Tetrode recordings in the cerebellar cortex

Multi-unit recordings with tetrodes have been used in brain studies for many years, but surprisingly, scarcely in the cerebellum. The cerebellum is subdivided in multiple small functional zones. Understanding the proper features of the cerebellar computations requires a characterization of neuronal activity within each area. By allowing simultaneous recordings of neighboring cells, tetrodes provide a helpful technique to study the dynamics of the cerebellar local networks. Here, we discuss experimental configurations to optimize such recordings and demonstrate their use in the different layers of the cerebellar cortex. We show that tetrodes can also be used to perform simultaneous recordings from neighboring units in freely moving rats using a custom-made drive, thus permitting studies of cerebellar network dynamics in a large variety of behavioral conditions.

The role of the cerebellum in saccadic adaptation as a window into neural mechanisms of motor learning

How does the nervous system guide the muscular periphery during the acquisition of a new motor skill? This is a fundamental question for researchers trying to understand the neural basis of motor learning. Recent advances in studying a valuable example of short-term motor learning, namely the adaptation of saccadic eye movements, have revealed neuronal processes in the cerebellum that underlie the unfolding of the learned behavior. In this review, we describe the latest findings from electrophysiology studies of saccadic adaptation and how they can generalize to more elaborate examples of cerebellum-dependent adaptation of movements. We focus our discussion on the plastic changes that are observed in the firing properties of Purkinje cells during the acquisition of the wanted motor response and describe how the altered activity of these neurons modifies the dynamics of the cerebellar microcircuitry. We finally demonstrate how such task-related modifications in the cerebellum are appropriate to fine-tune extracerebellar pre-motor structures and induce the learned behavior.

Encoding of smooth-pursuit eye movement initiation by a population of vermal Purkinje cells

Lesion studies suggest that the oculomotor vermis (OMV) is critical for the initiation of smooth-pursuit eye movements (SPEMs); yet, its specific role has remained elusive. In this study, we tested the hypothesis that vermal Purkinje cells (PCs) may be needed to fine-tune the kinematic description of SPEM initiation. Recording from identified PCs from the monkey OMV, we observed that SPEM-related PCs were characterized by a formidable diversity of response profiles with typically only modest reflection of eye movement kinematics. In contrast, the PC population discharge could be perfectly predicted based on a linear combination of eye acceleration, velocity, and position. This finding is in full accord with a role of the OMV in shaping eye movement kinematics. It, moreover, supports the notion that this shaping action is based on a population code, whose anatomic basis is the convergence of PCs on target neurons in the cerebellar nuclei.

Multiple extra-synaptic spillover mechanisms regulate prolonged activity in cerebellar Golgi cell-granule cell loops

Despite a wealth of in vitro and modelling studies it remains unclear how neuronal populations in the cerebellum interact in vivo. We address the issue of how the cerebellar input layer processes sensory information, with particular focus on the granule cells (input relays) and their counterpart inhibitory interneurones, Golgi cells. Based on the textbook view, granule cells excite Golgi cells via glutamate forming a negative feedback loop. However, Golgi cells express inhibitory mGluR2 receptors suggesting an inhibitory role for glutamate. We set out to test this glutamatergic paradox in Golgi cells. Here we show that granule cells and Golgi cells interact through extra-synaptic signalling mechanisms during sensory information processing, as well as synaptic mechanisms. We demonstrate that such interactions depend on granule cell-derived glutamate acting via inhibitory mGluR2 receptors leading causally to the suppression of Golgi cell activity for several hundreds of milliseconds. We further show that granule cell-derived inhibition of Golgi cell activity is regulated by GABA-dependent extra-synaptic Golgi cell inhibition of granule cells, identifying a regulatory loop in which glutamate and GABA may be critical regulators of Golgi cell–granule cell functional activity. Thus, granule cells may promote their own prolonged activity via paradoxical feed-forward inhibition of Golgi cells, thereby enabling information processing over long timescales.

Spontaneous activity signatures of morphologically identified interneurons in the vestibulocerebellum

Cerebellar cortical interneurons such as Golgi cells, basket cells, stellate cells, unipolar brush cells, and granule cells play an essential role in the operations of the cerebellum. However, detailed functional studies of the activity of these cells in both anesthetized and behaving animals have been hampered by problems in recognizing their physiological signatures. We have extracellularly recorded the spontaneous activity of vestibulocerebellar interneurons in ketamine/xylazine-anesthetized rats and subsequently labeled them with Neurobiotin using the juxtacellular technique. After recovery and morphological identification of these cells, they were related to statistical measures of their spontaneous activity. Golgi cells display a somewhat irregular firing pattern with relatively low average frequencies. Unipolar brush cells are characterized by more regular firing at higher rates. Basket and stellate cells are alike in their firing characteristics, which mainly stand out by their irregularity; some of them are set apart by their very slow average rate. The spontaneous activity of interneurons examined in the ketamine/xylazine rabbit fit within this general pattern. In the rabbit, granule cells were identified by the spontaneous occurrence of extremely high-frequency bursts of action potentials, which were also recognized in the rat. On the basis of these observations, we devised an algorithm that reliably determined the identity of 75% of the cells with only 2% incorrect classifications. The remaining cells were placed into border categories within which no classification was attempted. We propose that this algorithm can be used to help classify vestibulocerebellar interneurons recorded in awake, behaving animals.