Beyond "all-or-nothing" climbing fibers: graded representation of teaching signals in Purkinje cells

The Effect of Nucleo-Olivary Stimulation on Climbing Fiber EPSPs in Purkinje Cells

Climbing fibers, connecting the inferior olive and Purkinje cells, form the nervous system's strongest neural connection. These fibers activate after critical events like motor errors or anticipation of rewards, leading to bursts of excitatory postsynaptic potentials (EPSPs) in Purkinje cells. The number of EPSPs is a crucial variable when the brain is learning a new motor skill. Yet, we do not know what determines the number of EPSPs. Here, we measured the effect of nucleo-olivary stimulation on periorbital elicited climbing fiber responses through in-vivo intracellular Purkinje cell recordings in decerebrated ferrets. The results show that while nucleo-olivary stimulation decreased the probability of a response occurring at all, it did not reduce the number of EPSPs. The results suggest that nucleo-olivary stimulation does not influence the number of EPSPs in climbing fiber bursts.

Human Purkinje cells outperform mouse Purkinje cells in dendritic complexity and computational capacity

Purkinje cells in the cerebellum are among the largest neurons in the brain and have been extensively investigated in rodents. However, their morphological and physiological properties remain poorly understood in humans. In this study, we utilized high-resolution morphological reconstructions and unique electrophysiological recordings of human Purkinje cells ex vivo to generate computational models and estimate computational capacity. An inter-species comparison showed that human Purkinje cell had similar fractal structures but were larger than those of mouse Purkinje cells. Consequently, given a similar spine density (2/μm), human Purkinje cell hosted approximately 7.5 times more dendritic spines than those of mice. Moreover, human Purkinje cells had a higher dendritic complexity than mouse Purkinje cells and usually emitted 2-3 main dendritic trunks instead of one. Intrinsic electro-responsiveness was similar between the two species, but model simulations revealed that the dendrites could process ~6.5 times (n = 51 vs. n = 8) more input patterns in human Purkinje cells than in mouse Purkinje cells. Thus, while human Purkinje cells maintained spike discharge properties similar to those of rodents during evolution, they developed more complex dendrites, enhancing computational capacity.

Synaptic basis of a sub-second representation of time in a neural circuit model

Temporal sequences of neural activity are essential for driving well-timed behaviors, but the underlying cellular and circuit mechanisms remain elusive. We leveraged the well-defined architecture of the cerebellum, a brain region known to support temporally precise actions, to explore theoretically whether the experimentally observed diversity of short-term synaptic plasticity (STP) at the input layer could generate neural dynamics sufficient for sub-second temporal learning. A cerebellar circuit model equipped with dynamic synapses produced a diverse set of transient granule cell firing patterns that provided a temporal basis set for learning precisely timed pauses in Purkinje cell activity during simulated delay eyelid conditioning and Bayesian interval estimation. The learning performance across time intervals was influenced by the temporal bandwidth of the temporal basis, which was determined by the input layer synaptic properties. The ubiquity of STP throughout the brain positions it as a general, tunable cellular mechanism for sculpting neural dynamics and fine-tuning behavior.

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

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

Computational epidemiology study of homeostatic compensation during sensorimotor aging

The vestibulo-ocular reflex (VOR) stabilizes vision during head motion. Age-related changes of vestibular neuroanatomical properties predict a linear decay of VOR function. Nonetheless, human epidemiological data show a stable VOR function across the life span. In this study, we model cerebellum-dependent VOR adaptation to relate structural and functional changes throughout aging. We consider three neurosynaptic factors that may codetermine VOR adaptation during aging: the electrical coupling of inferior olive neurons, the long-term spike timing-dependent plasticity at parallel fiber - Purkinje cell synapses and mossy fiber - medial vestibular nuclei synapses, and the intrinsic plasticity of Purkinje cell synapses Our cross-sectional aging analyses suggest that long-term plasticity acts as a global homeostatic mechanism that underpins the stable temporal profile of VOR function. The results also suggest that the intrinsic plasticity of Purkinje cell synapses operates as a local homeostatic mechanism that further sustains the VOR at older ages. Importantly, the computational epidemiology approach presented in this study allows discrepancies among human cross-sectional studies to be understood in terms of interindividual variability in older individuals. Finally, our longitudinal aging simulations show that the amount of residual fibers coding for the peak and trough of the VOR cycle constitutes a predictive hallmark of VOR trajectories over a lifetime.

The Shape of Data: a Theory of the Representation of Information in the Cerebellar Cortex

This paper presents a model of rate coding in the cerebellar cortex. The pathway of input to output of the cerebellum forms an anatomically repeating, functionally modular network, whose basic wiring is preserved across vertebrate taxa. Each network is bisected centrally by a functionally defined cell group, a microzone, which forms part of the cerebellar circuit. Input to a network may be from tens of thousands of concurrently active mossy fibres. The model claims to quantify the conversion of input rates into the code received by a microzone. Recoding on entry converts input rates into an internal code which is homogenised in the functional equivalent of an imaginary plane, occupied by the centrally positioned microzone. Homogenised means the code exists in any random sample of parallel fibre signals over a minimum number. The nature of the code and the regimented architecture of the cerebellar cortex mean that the threshold can be represented by space so that the threshold can be met by the physical dimensions of the Purkinje cell dendritic arbour and planar interneuron networks. As a result, the whole population of a microzone receives the same code. This is part of a mechanism which orchestrates functionally indivisible behaviour of the cerebellar circuit and is necessary for coordinated control of the output cells of the circuit. In this model, fine control of Purkinje cells is by input rates to the system and not by learning so that it is in conflict with the for-years-dominant supervised learning model.

Population calcium responses of Purkinje cells in the oculomotor cerebellum driven by non-visual input

The climbing fiber input to the cerebellum conveys instructive signals that can induce synaptic plasticity and learning by triggering complex spikes accompanied by large calcium transients in Purkinje cells. In the cerebellar flocculus, which supports oculomotor learning, complex spikes are driven by image motion on the retina, which could indicate an oculomotor error. In the same neurons, complex spikes also can be driven by non-visual signals. It has been shown that the calcium transients accompanying each complex spike can vary in amplitude, even within a given cell, therefore, we compared the calcium responses associated with the visual and non-visual inputs to floccular Purkinje cells. The calcium indicator GCaMP6f was selectively expressed in Purkinje cells, and fiber photometry was used to record the calcium responses from a population of Purkinje cells in the flocculus of awake behaving mice. During visual (optokinetic) stimuli and pairing of vestibular and visual stimuli, the calcium level increased during contraversive retinal image motion. During performance of the vestibulo-ocular reflex in the dark, calcium increased during contraversive head rotation and the associated ipsiverse eye movements. The amplitude of this non-visual calcium response was comparable to that during conditions with retinal image motion present that induce oculomotor learning. Thus, population calcium responses of Purkinje cells in the cerebellar flocculus to visual and non-visual input are similar to what has been reported previously for complex spikes, suggesting that multimodal instructive signals control the synaptic plasticity supporting oculomotor learning.

Behavioral Tests for Mouse Models of Autism: An Argument for the Inclusion of Cerebellum-Controlled Motor Behaviors

Mouse models of Autism Spectrum Disorder (ASD) have been interrogated using a variety of behavioral tests in order to understand the symptoms of ASD. However, the hallmark behaviors that are classically affected in ASD - deficits in social interaction and communication as well as the occurrence of repetitive behaviors - do not have direct murine equivalents. Thus, it is critical to identify the caveats that come with modeling a human disorder in mice. The most commonly used behavioral tests represent complex cognitive processes based on largely unknown brain circuitry. Motor impairments provide an alternative, scientifically rigorous approach to understanding ASD symptoms. Difficulties with motor coordination and learning - seen in both patients and mice - point to an involvement of the cerebellum in ASD pathology. This brain area supports types of motor learning that are conserved throughout vertebrate evolution, allowing for direct comparisons of functional abnormalities between humans with autism and ASD mouse models. Studying simple motor behaviors provides researchers with clearly interpretable results. We describe and evaluate methods used on mouse behavioral assays designed to test for social, communicative, perseverative, anxious, nociceptive, and motor learning abnormalities. We comment on the effectiveness and validity of each test based on how much information its results give, as well as its relevance to ASD, and will argue for an inclusion of cerebellum-supported motor behaviors in the phenotypic description of ASD mouse models. LAY SUMMARY: Mouse models of Autism Spectrum Disorder help us gain insight about ASD symptoms in human patients. However, there are many differences between mice and humans, which makes interpreting behaviors challenging. Here, we discuss a battery of behavioral tests for specific mouse behaviors to explore whether each test does indeed evaluate the intended measure, and whether these tests are useful in learning about ASD.

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.

Gating by Functionally Indivisible Cerebellar Circuits: a Hypothesis

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

Dendritic coincidence detection in Purkinje neurons of awake mice

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

A cerebello-olivary signal for negative prediction error is sufficient to cause extinction of associative motor learning

The brain generates negative prediction error (NPE) signals to trigger extinction, a type of inhibitory learning that is responsible for suppressing learned behaviors when they are no longer useful. Neurons encoding NPE have been reported in multiple brain regions. Here, we use an optogenetic approach to demonstrate that GABAergic cerebello-olivary neurons can generate a powerful NPE signal, capable of causing extinction of conditioned motor responses on its own.

Direct translation of climbing fiber burst-mediated sensory coding into post-synaptic Purkinje cell dendritic calcium

Climbing fibers (CFs) generate complex spikes (CS) and Ca²⁺ transients in cerebellar Purkinje cells (PCs), serving as instructive signals. The so-called 'all-or-none' character of CSs has been questioned since the CF burst was described. Although recent studies have indicated a sensory-driven enhancement of PC Ca²⁺ signals, how CF responds to sensory events and contributes to PC dendritic Ca²⁺ and CS remains unexplored. Here, single or simultaneous Ca²⁺ imaging of CFs and PCs in awake mice revealed the presynaptic CF Ca²⁺ amplitude encoded the sensory input's strength and directly influenced post-synaptic PC dendritic Ca²⁺ amplitude. The sensory-driven variability in CF Ca²⁺ amplitude depended on the number of spikes in the CF burst. Finally, the spike number of the CF burst determined the PC Ca²⁺ influx and CS properties. These results reveal the direct translation of sensory information-coding CF inputs into PC Ca²⁺, suggesting the sophisticated role of CFs as error signals.

Principles of operation of a cerebellar learning circuit

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

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.

Intrinsic Excitability Increase in Cerebellar Purkinje Cells after Delay Eye-Blink Conditioning in Mice

Cerebellar-based learning is thought to rely on synaptic plasticity, particularly at synaptic inputs to Purkinje cells. Recently, however, other complementary mechanisms have been identified. Intrinsic plasticity is one such mechanism, and depends in part on the downregulation of calcium-dependent SK-type K+ channels, which contribute to a medium-slow afterhyperpolarization (AHP) after spike bursts, regulating membrane excitability. In the hippocampus, intrinsic plasticity plays a role in trace eye-blink conditioning; however, corresponding excitability changes in the cerebellum in associative learning, such as in trace or delay eye-blink conditioning, are less well studied. Whole-cell patch-clamp recordings were obtained from Purkinje cells in cerebellar slices prepared from male mice ∼48 h after they learned a delay eye-blink conditioning task. Over a period of repeated training sessions, mice received either paired trials of a tone coterminating with a periorbital shock (conditioning) or trials in which these stimuli were randomly presented in an unpaired manner (pseudoconditioning). Purkinje cells from conditioned mice show a significantly reduced AHP after trains of parallel fiber stimuli and after climbing fiber evoked complex spikes. The number of spikelets in the complex spike waveform is increased after conditioning. Moreover, we find that SK-dependent intrinsic plasticity is occluded in conditioned, but not pseudoconditioned mice. These findings show that excitability is enhanced in Purkinje cells after delay eye-blink conditioning, and point toward a downregulation of SK channels as a potential underlying mechanism. The observation that this learning effect lasts at least up to 2 d after training shows that intrinsic plasticity regulates excitability in the long term.SIGNIFICANCE STATEMENT Plasticity of membrane excitability ("intrinsic plasticity") has been observed in invertebrate and vertebrate neurons, coinduced with synaptic plasticity or in isolation. Although the cellular phenomenon per se is well established, it remains unclear what role intrinsic plasticity plays in learning and if it even persists long enough to serve functions in engram physiology beyond aiding synaptic plasticity. Here, we demonstrate that cerebellar Purkinje cells upregulate excitability in delay eye-blink conditioning, a form of motor learning. This plasticity is observed 48 h after training and alters synaptically evoked spike firing and integrative properties of these neurons. These findings show that intrinsic plasticity enhances the spike firing output of Purkinje cells and persists over the course of days.

Bidirectional short-term plasticity during single-trial learning of cerebellar-driven eyelid movements in mice

The brain is constantly monitoring its own performance, using error signals to trigger mechanisms of plasticity that help improve future behavior. Indeed, adaptive changes in behavior have been observed after a single error trial in many learning tasks, including cerebellum-dependent eyeblink conditioning. Here, we demonstrate that the plasticity underlying single-trial learning during eyeblink conditioning in mice is bidirectionally regulated by positive and negative prediction errors, has an ephemeral effect on behavior (decays in <1 min), and can be triggered in the absence of errors in performance. We suggest that these three properties of single-trial learning may be particularly useful for driving mechanisms of motor adaptation that can achieve optimal performance in the face of environmental disturbances with a fast timescale.

Climbing Fibers Provide Graded Error Signals in Cerebellar Learning

The cerebellum plays a critical role in coordinating and learning complex movements. Although its importance has been well recognized, the mechanisms of learning remain hotly debated. According to the classical cerebellar learning theory, depression of parallel fiber synapses instructed by error signals from climbing fibers, drives cerebellar learning. The uniqueness of long-term depression (LTD) in cerebellar learning has been challenged by evidence showing multi-site synaptic plasticity. In Purkinje cells, long-term potentiation (LTP) of parallel fiber synapses is now well established and it can be achieved with or without climbing fiber signals, making the role of climbing fiber input more puzzling. The central question is how individual Purkinje cells extract global errors based on climbing fiber input. Previous data seemed to demonstrate that climbing fibers are inefficient instructors, because they were thought to carry “binary” error signals to individual Purkinje cells, which significantly constrains the efficiency of cerebellar learning in several regards. In recent years, new evidence has challenged the traditional view of “binary” climbing fiber responses, suggesting that climbing fibers can provide graded information to efficiently instruct individual Purkinje cells to learn. Here we review recent experimental and theoretical progress regarding modulated climbing fiber responses in Purkinje cells. Analog error signals are generated by the interaction of varying climbing fibers inputs with simultaneous other synaptic input and with firing states of targeted Purkinje cells. Accordingly, the calcium signals which trigger synaptic plasticity can be graded in both amplitude and spatial range to affect the learning rate and even learning direction. We briefly discuss how these new findings complement the learning theory and help to further our understanding of how the cerebellum works.

Using extracellular low frequency signals to improve the spike sorting of cerebellar complex spikes

BACKGROUND

The challenge of spike sorting has been addressed by numerous electrophysiological studies. These methods tend to focus on the information conveyed by the high frequencies, but ignore the potentially informative signals at lower frequencies. Activation of Purkinje cells in the cerebellum by input from the climbing fibers results in a large amplitude dendritic spike concurrent with a high-frequency burst known as a complex spike. Due to the variability in the high-frequency component of complex spikes, previous methods have struggled to sort these complex spikes in an accurate and reliable way. However, complex spikes have a prominent extracellular low-frequency signal generated by the input from the climbing fibers, which can be exploited for complex spike sorting.

NEW METHOD

We exploited the low-frequency signal (20-400 Hz) to improve complex spike sorting by applying Principal Component Analysis (PCA).

RESULTS AND COMPARISONS

The low-frequency first PC achieves a better separation of the complex spikes from noise. The low-frequency data facilitate the detection of events entering into the analysis, and therefore can be harnessed to analyze the data with a larger signal to noise ratio. These advantages make this method more effective for complex spike sorting than methods restricted to the high-frequency signal (> 600 Hz).

CONCLUSIONS

Gathering low frequency data can improve spike sorting. This is illustrated for the case of complex spikes in the cerebellum. Our characterization of the dendritic low-frequency components of complex spikes can be applied elsewhere to gain insights into processing in the cerebellum.

Computational Principles of Supervised Learning in the Cerebellum

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

Consensus paper: Decoding the Contributions of the Cerebellum as a Time Machine. From Neurons to Clinical Applications

Time perception is an essential element of conscious and subconscious experience, coordinating our perception and interaction with the surrounding environment. In recent years, major technological advances in the field of neuroscience have helped foster new insights into the processing of temporal information, including extending our knowledge of the role of the cerebellum as one of the key nodes in the brain for this function. This consensus paper provides a state-of-the-art picture from the experts in the field of the cerebellar research on a variety of crucial issues related to temporal processing, drawing on recent anatomical, neurophysiological, behavioral, and clinical research.The cerebellar granular layer appears especially well-suited for timing operations required to confer millisecond precision for cerebellar computations. This may be most evident in the manner the cerebellum controls the duration of the timing of agonist-antagonist EMG bursts associated with fast goal-directed voluntary movements. In concert with adaptive processes, interactions within the cerebellar cortex are sufficient to support sub-second timing. However, supra-second timing seems to require cortical and basal ganglia networks, perhaps operating in concert with cerebellum. Additionally, sensory information such as an unexpected stimulus can be forwarded to the cerebellum via the climbing fiber system, providing a temporally constrained mechanism to adjust ongoing behavior and modify future processing. Patients with cerebellar disorders exhibit impairments on a range of tasks that require precise timing, and recent evidence suggest that timing problems observed in other neurological conditions such as Parkinson's disease, essential tremor, and dystonia may reflect disrupted interactions between the basal ganglia and cerebellum.The complex concepts emerging from this consensus paper should provide a foundation for further discussion, helping identify basic research questions required to understand how the brain represents and utilizes time, as well as delineating ways in which this knowledge can help improve the lives of those with neurological conditions that disrupt this most elemental sense. The panel of experts agrees that timing control in the brain is a complex concept in whom cerebellar circuitry is deeply involved. The concept of a timing machine has now expanded to clinical disorders.

Conversion of Graded Presynaptic Climbing Fiber Activity into Graded Postsynaptic Ca2+ Signals by Purkinje Cell Dendrites

The brain must make sense of external stimuli to generate relevant behavior. We used a combination of in vivo approaches to investigate how the cerebellum processes sensory-related information. We found that the inferior olive encodes contexts of sensory-associated external cues in a graded manner, apparent in the presynaptic activity of their axonal projections (climbing fibers) in the cerebellar cortex. Individual climbing fibers were broadly responsive to different sensory modalities but relayed sensory-related information to the cortex in a lobule-dependent manner. Purkinje cell dendrites faithfully transformed this climbing fiber activity into dendrite-wide Ca²⁺ signals without a direct contribution from the mossy fiber pathway. These results demonstrate that the size of climbing-fiber-evoked Ca²⁺ signals in Purkinje cell dendrites is largely determined by the firing level of climbing fibers. This coding scheme emphasizes the overwhelming role of the inferior olive in generating salient signals useful for instructing plasticity and learning.

Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation

Cerebellar Purkinje cells mediate accurate eye movement coordination. However, it remains unclear how oculomotor adaptation depends on the interplay between the characteristic Purkinje cell response patterns, namely tonic, bursting, and spike pauses. Here, a spiking cerebellar model assesses the role of Purkinje cell firing patterns in vestibular ocular reflex (VOR) adaptation. The model captures the cerebellar microcircuit properties and it incorporates spike-based synaptic plasticity at multiple cerebellar sites. A detailed Purkinje cell model reproduces the three spike-firing patterns that are shown to regulate the cerebellar output. Our results suggest that pauses following Purkinje complex spikes (bursts) encode transient disinhibition of target medial vestibular nuclei, critically gating the vestibular signals conveyed by mossy fibres. This gating mechanism accounts for early and coarse VOR acquisition, prior to the late reflex consolidation. In addition, properly timed and sized Purkinje cell bursts allow the ratio between long-term depression and potentiation (LTD/LTP) to be finely shaped at mossy fibre-medial vestibular nuclei synapses, which optimises VOR consolidation. Tonic Purkinje cell firing maintains the consolidated VOR through time. Importantly, pauses are crucial to facilitate VOR phase-reversal learning, by reshaping previously learnt synaptic weight distributions. Altogether, these results predict that Purkinje spike burst-pause dynamics are instrumental to VOR learning and reversal adaptation.

Cerebellar Purkinje cells regulate accurate eye movement coordination. However, it remains unclear how cerebellar-dependent oculomotor adaptation depends on the interplay between Purkinje cell characteristic response patterns: tonic, high frequency bursting, and post-complex spike pauses. We explore the role of Purkinje spike burst-pause dynamics in VOR adaptation. A biophysical model of Purkinje cell is at the core of a spiking network model, which captures the cerebellar microcircuit properties and incorporates spike-based synaptic plasticity mechanisms at different cerebellar sites. We show that Purkinje spike burst-pause dynamics are critical for (1) gating the vestibular-motor response association during VOR acquisition; (2) mediating the LTD/LTP balance for VOR consolidation; (3) reshaping synaptic efficacy distributions for VOR phase-reversal adaptation; (4) explaining the reversal VOR gain discontinuities during sleeping.

Complex Spike Wars: a New Hope

The climbing fiber-Purkinje cell circuit is one of the most powerful and highly conserved in the central nervous system. Climbing fibers exert a powerful excitatory action that results in a complex spike in Purkinje cells and normal functioning of the cerebellum depends on the integrity of climbing fiber-Purkinje cell synapse. Over the last 50 years, multiple hypotheses have been put forward on the role of the climbing fibers and complex spikes in cerebellar information processing and motor control. Central to these theories is the nature of the interaction between the low-frequency complex spike discharge and the high-frequency simple spike firing of Purkinje cells. This review examines the major hypotheses surrounding the action of the climbing fiber-Purkinje cell projection, discussing both supporting and conflicting findings. The review describes newer findings establishing that climbing fibers and complex spikes provide predictive signals about movement parameters and that climbing fiber input controls the encoding of behavioral information in the simple spike firing of Purkinje cells. Finally, we propose the dynamic encoding hypothesis for complex spike function that strives to integrate established and newer findings.

Coordinated cerebellar climbing fiber activity signals learned sensorimotor predictions

The prevailing model of cerebellar learning states that climbing fibers (CFs) are both driven by, and serve to correct, erroneous motor output. However, this model is grounded largely in studies of behaviors that utilize hardwired neural pathways to link sensory input to motor output. To test whether this model applies to more flexible learning regimes that require arbitrary sensorimotor associations, we developed a cerebellar-dependent motor learning task that is compatible with both mesoscale and single-dendrite-resolution calcium imaging in mice. We found that CFs were preferentially driven by and more time-locked to correctly executed movements and other task parameters that predict reward outcome, exhibiting widespread correlated activity in parasagittal processing zones that was governed by these predictions. Together, our data suggest that such CF activity patterns are well-suited to drive learning by providing predictive instructional input that is consistent with an unsigned reinforcement learning signal but does not rely exclusively on motor errors.

Simultaneous dendritic voltage and calcium imaging and somatic recording from Purkinje neurons in awake mice

Spatiotemporal maps of dendritic signalling and their relationship with somatic output is fundamental to neuronal information processing, yet remain unexplored in awake animals. Here, we combine simultaneous sub-millisecond voltage and calcium two-photon imaging from distal spiny dendrites, with somatic electrical recording from spontaneously active cerebellar Purkinje neurons (PN) in awake mice. We detect discrete 1−2 ms suprathreshold voltage spikelets in the distal spiny dendrites during dendritic complex spikes. Spikelets and their calcium correlates are highly heterogeneous in number, timing and spatial distribution within and between complex spikes. Back-propagating simple spikes are highly attenuated. Highly variable 5–10 ms voltage hotspots are localized to fine dendritic processes and are reduced in size and frequency by lidocaine and CNQX. Hotspots correlated with somatic output but also, at high frequency, trigger purely dendritic calcium spikes. Summarizing, spatiotemporal signalling in PNs is far more complex, dynamic, and fine scaled than anticipated, even in resting animals.

Dendritic integration is important for information processing in the brain. Here, in awake mice, authors combine simultaneous dendritic recording of voltage and calcium signals, with somatic recording from Purkinje neurons, enabling characterization of dendritic spiking, action potential backpropagation, and ‘hotspots’ in spiny dendrites.

Inhibition gates supralinear Ca2+ signaling in Purkinje cell dendrites during practiced movements

Motor learning involves neural circuit modifications in the cerebellar cortex, likely through re-weighting of parallel fiber inputs onto Purkinje cells (PCs). Climbing fibers instruct these synaptic modifications when they excite PCs in conjunction with parallel fiber activity, a pairing that enhances climbing fiber-evoked Ca²⁺ signaling in PC dendrites. In vivo, climbing fibers spike continuously, including during movements when parallel fibers are simultaneously conveying sensorimotor information to PCs. Whether parallel fiber activity enhances climbing fiber Ca²⁺ signaling during motor behaviors is unknown. In mice, we found that inhibitory molecular layer interneurons (MLIs), activated by parallel fibers during practiced movements, suppressed parallel fiber enhancement of climbing fiber Ca²⁺ signaling in PCs. Similar results were obtained in acute slices for brief parallel fiber stimuli. Interestingly, more prolonged parallel fiber excitation revealed latent supralinear Ca²⁺ signaling. Therefore, the balance of parallel fiber and MLI input onto PCs regulates concomitant climbing fiber Ca²⁺ signaling.

Graded Control of Climbing-Fiber-Mediated Plasticity and Learning by Inhibition in the Cerebellum

Purkinje cell dendrites convert excitatory climbing fiber input into signals that instruct plasticity and motor learning. Modulation of instructive signaling may increase the range in which learning is encoded, yet the mechanisms that allow for this are poorly understood. We found that optogenetic activation of molecular layer interneurons (MLIs) that inhibit Purkinje cells suppressed climbing-fiber-evoked dendritic Ca²⁺ spiking. Inhibitory suppression of Ca²⁺ spiking depended on the level of MLI activation and influenced the induction of associative synaptic plasticity, converting climbing-fiber-mediated potentiation of parallel fiber-evoked responses into depression. In awake mice, optogenetic activation of floccular climbing fibers in association with head rotation produced an adaptive increase in the vestibulo-ocular reflex (VOR). However, when climbing fibers were co-activated with MLIs, adaptation occurred in the opposite direction, decreasing the VOR. Thus, MLIs can direct a continuous spectrum of plasticity and learning through their influence on Purkinje cell dendritic Ca²⁺ signaling.

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.

Purkinje Cell Representations of Behavior: Diary of a Busy Neuron

Fundamental for understanding cerebellar function is determining the representations in Purkinje cell activity, the sole output of the cerebellar cortex. Up to the present, the most accurate descriptions of the information encoded by Purkinje cells were obtained in the context of motor behavior and reveal a high degree of heterogeneity of kinematic and performance error signals encoded. The most productive framework for organizing Purkinje cell firing representations is provided by the forward internal model hypothesis. Direct tests of this hypothesis show that individual Purkinje cells encode two different forward models simultaneously, one for effector kinematics and one for task performance. Newer results demonstrate that the timing of simple spike encoding of motor parameters spans an extend interval of up to ±2 seconds. Furthermore, complex spike discharge is not limited to signaling errors, can be predictive, and dynamically controls the information in the simple spike firing to meet the demands of upcoming behavior. These rich, diverse, and changing representations highlight the integrative aspects of cerebellar function and offer the opportunity to generalize the cerebellar computational framework over both motor and non-motor domains.

Purkinje cell BKchannel ablation induces abnormal rhythm in deep cerebellar nuclei and prevents LTD

Purkinje cells (PC) control deep cerebellar nuclei (DCN), which in turn inhibit inferior olive nucleus, closing a positive feedback loop via climbing fibers. PC highly express potassium BK channels but their contribution to the olivo-cerebellar loop is not clear. Using multiple-unit recordings in alert mice we found in that selective deletion of BK channels in PC induces a decrease in their simple spike firing with a beta-range bursting pattern and fast intraburst frequency (~200 Hz). To determine the impact of this abnormal rhythm on the olivo-cerebellar loop we analyzed simultaneous rhythmicity in different cerebellar structures. We found that this abnormal PC rhythmicity is transmitted to DCN neurons with no effect on their mean firing frequency. Long term depression at the parallel-PC synapses was altered and the intra-burst complex spike spikelets frequency was increased without modification of the mean complex spike frequency in BK-PC^−/− mice. We argue that the ataxia present in these conditional knockout mice could be explained by rhythmic disruptions transmitted from mutant PC to DCN but not by rate code modification only. This suggests a neuronal mechanism for ataxia with possible implications for human disease.

Synaptic excitation by climbing fibre collaterals in the cerebellar nuclei of juvenile and adult mice

KEY POINTS

The inferior olive sends instructive motor signals to the cerebellum via the climbing fibre projection, which sends collaterals directly to large premotor neurons of the mouse cerebellar nuclei (CbN cells). Optogenetic activation of inferior olivary axons in vitro evokes EPSCs in CbN cells of several hundred pA to more than 1 nA. The inputs are three-fold larger at younger ages, 12 to 14 days old, than at 2 months old, suggesting a strong functional role for this pathway earlier in development. The EPSCs are multipeaked, owing to burst firing in several olivary afferents that fire asynchronously. The convergence of climbing fibre collaterals onto CbN cells decreases from ∼40 to ∼8, which is consistent with the formation of closed-loop circuits in which each CbN neuron receives input from 4-7 collaterals from inferior olivary neurons as well as from all 30-50 Purkinje cells that are innervated by those olivary neurons.

ABSTRACT

The inferior olive conveys instructive signals to the cerebellum that drive sensorimotor learning. Inferior olivary neurons transmit their signals via climbing fibres, which powerfully excite Purkinje cells, evoking complex spikes and depressing parallel fibre synapses. Additionally, however, these climbing fibres send collaterals to the cerebellar nuclei (CbN). In vivo and in vitro data suggest that climbing fibre collateral excitation is weak in adult mice, raising the question of whether the primary role of this pathway may be developmental. We therefore examined climbing fibre collateral input to large premotor CbN cells over development by virally expressing channelrhodopsin in the inferior olive. In acute cerebellar slices from postnatal day (P)12-14 mice, light-evoked EPSCs were large (> 1 nA at -70 mV). The amplitude of these EPSCs decreased over development, reaching a plateau of ∼350 pA at P20-60. Trains of EPSCs (5 Hz) depressed strongly throughout development, whereas convergence estimates indicated that the total number of functional afferents decreased with age. EPSC waveforms consisted of multiple peaks, probably resulting from action potential bursts in single collaterals and variable times to spike threshold in converging afferents. Activating climbing fibre collaterals evoked well-timed increases in firing probability in CbN neurons, especially in younger mice. The initially strong input, followed by the decrement in synaptic strength coinciding with the pruning of climbing fibres in the cerebellar cortex, implicates the climbing fibre collateral pathway in early postnatal development. Additionally, the persistence of substantial synaptic input at least to P60 suggests that this pathway may function in cerebellar processing into adulthood.

Inferior Olivary TMEM16B Mediates Cerebellar Motor Learning

Ca²⁺-activated ion channels shape membrane excitability and Ca²⁺ dynamics in response to cytoplasmic Ca²⁺ elevation. Compared to the Ca²⁺-activated K⁺ channels, known as BK and SK channels, the physiological importance of Ca²⁺-activated Cl^- channels (CaCCs) in neurons has been largely overlooked. Here we report that CaCCs coexist with BK and SK channels in inferior olivary (IO) neurons that send climbing fibers to innervate cerebellar Purkinje cells for the control of motor learning and timing. Ca²⁺ influx through the dendritic high-threshold voltage-gated Ca²⁺ channels activates CaCCs, which contribute to membrane repolarization of IO neurons. Loss of TMEM16B expression resulted in the absence of CaCCs in IO neurons, leading to markedly diminished action potential firing of IO neurons in TMEM16B knockout mice. Moreover, these mutant mice exhibited severe cerebellar motor learning deficits. Our findings thus advance the understanding of the neurophysiology of CaCCs and the ionic basis of IO neuron excitability.

Modulation of Complex-Spike Duration and Probability during Cerebellar Motor Learning in Visually Guided Smooth-Pursuit Eye Movements of Monkeys

Activation of an inferior olivary neuron powerfully excites Purkinje cells via its climbing fiber input and triggers a characteristic high-frequency burst, known as the complex spike (CS). The theory of cerebellar learning postulates that the CS induces long-lasting depression of the strength of synapses from active parallel fibers onto Purkinje cells, and that synaptic depression leads to changes in behavior. Prior reports showed that a CS on one learning trial is linked to a properly timed depression of simple spikes on the subsequent trial, as well as a learned change in pursuit eye movement. Further, the duration of a CS is a graded instruction for single-trial plasticity and behavioral learning. We now show across multiple learning paradigms that both the probability and duration of CS responses are correlated with the magnitudes of neural and behavioral learning in awake behaving monkeys. When the direction of the instruction for learning repeatedly was in the same direction or alternated directions, the duration and probability of CS responses decreased over a learning block along with the magnitude of trial-over-trial neural learning. When the direction of the instruction was randomized, CS duration, CS probability, and neural and behavioral learning remained stable across time. In contrast to depression, potentiation of simple-spike firing rate for ON-direction learning instructions follows a longer time course and plays a larger role as depression wanes. Computational analysis provides a model that accounts fully for the detailed statistics of a complex set of data.

Heterogeneity of Purkinje cell simple spike-complex spike interactions: zebrin- and non-zebrin-related variations

KEY POINTS

Cerebellar Purkinje cells (PCs) generate two types of action potentials, simple and complex spikes. Although they are generated by distinct mechanisms, interactions between the two spike types exist. Zebrin staining produces alternating positive and negative stripes of PCs across most of the cerebellar cortex. Thus, here we compared simple spike-complex spike interactions both within and across zebrin populations. Simple spike activity undergoes a complex modulation preceding and following a complex spike. The amplitudes of the pre- and post-complex spike modulation phases were correlated across PCs. On average, the modulation was larger for PCs in zebrin positive regions. Correlations between aspects of the complex spike waveform and simple spike activity were found, some of which varied between zebrin positive and negative PCs. The implications of the results are discussed with regard to hypotheses that complex spikes are triggered by rises in simple spike activity for either motor learning or homeostatic functions.

ABSTRACT

Purkinje cells (PCs) generate two types of action potentials, called simple and complex spikes (SSs and CSs). We first investigated the CS-associated modulation of SS activity and its relationship to the zebrin status of the PC. The modulation pattern consisted of a pre-CS rise in SS activity, and then, following the CS, a pause, a rebound, and finally a late inhibition of SS activity for both zebrin positive (Z+) and negative (Z-) cells, though the amplitudes of the phases were larger in Z+ cells. Moreover, the amplitudes of the pre-CS rise with the late inhibitory phase of the modulation were correlated across PCs. In contrast, correlations between modulation phases across CSs of individual PCs were generally weak. Next, the relationship between CS spikelets and SS activity was investigated. The number of spikelets/CS correlated with the average SS firing rate only for Z+ cells. In contrast, correlations across CSs between spikelet numbers and the amplitudes of the SS modulation phases were generally weak. Division of spikelets into likely axonally propagated and non-propagated groups (based on their interspikelet interval) showed that the correlation of spikelet number with SS firing rate primarily reflected a relationship with non-propagated spikelets. In sum, the results show both zebrin-related and non-zebrin-related physiological heterogeneity in SS-CS interactions among PCs, which suggests that the cerebellar cortex is more functionally diverse than is assumed by standard theories of cerebellar function.

Decomposition of a sensory prediction error signal for visuomotor adaptation

To accomplish effective motor control, the brain contains an internal forward model that predicts the expected sensory consequence of a motor command. When this prediction is inaccurate, a sensory prediction error is produced which adapts the forward model to make more accurate predictions of future movements. Other types of errors, such as task performance errors or reward, play less of a role in adapting a forward model. This raises the following question: What unique information is conveyed by the sensory prediction error that results in forward model adaptation? sensory prediction errors typically contain both the magnitude and direction of the error, but it is unclear if both components are necessary for adaptation or a single component is sufficient. In this article, we address this by having participants learn to counter a visuomotor rotation, which induces an angular mismatch between movements of the hand and visual feedback. We manipulated the information content of the visual feedback, in the form of a line, which accurately represented only the magnitude (distance), direction, or both magnitude and direction, of the virtual cursor relative to the target. We demonstrate that sensorimotor adaptation does not occur, or is minimal, when feedback is limited to information about the magnitude of an error. In contrast, sensorimotor adaptation is present when feedback is limited only to the direction of an error or when it contains combined direction and magnitude information. This result stands in contrast to current computational models of cerebellar-based sensorimotor adaptation that use error magnitude to drive adaptation. (PsycINFO Database Record

Distributed Circuit Plasticity: New Clues for the Cerebellar Mechanisms of Learning

The cerebellum is involved in learning and memory of sensory motor skills. However, the way this process takes place in local microcircuits is still unclear. The initial proposal, casted into the Motor Learning Theory, suggested that learning had to occur at the parallel fiber-Purkinje cell synapse under supervision of climbing fibers. However, the uniqueness of this mechanism has been questioned, and multiple forms of long-term plasticity have been revealed at various locations in the cerebellar circuit, including synapses and neurons in the granular layer, molecular layer and deep-cerebellar nuclei. At present, more than 15 forms of plasticity have been reported. There has been a long debate on which plasticity is more relevant to specific aspects of learning, but this question turned out to be hard to answer using physiological analysis alone. Recent experiments and models making use of closed-loop robotic simulations are revealing a radically new view: one single form of plasticity is insufficient, while altogether, the different forms of plasticity can explain the multiplicity of properties characterizing cerebellar learning. These include multi-rate acquisition and extinction, reversibility, self-scalability, and generalization. Moreover, when the circuit embeds multiple forms of plasticity, it can easily cope with multiple behaviors endowing therefore the cerebellum with the properties needed to operate as an effective generalized forward controller.

Climbing Fiber Regulation of Spontaneous Purkinje Cell Activity and Cerebellum-Dependent Blink Responses(1,2,3)

It has been known for a long time that GABAergic Purkinje cells in the cerebellar cortex, as well as their target neurons in the cerebellar nuclei, are spontaneously active. The cerebellar output will, therefore, depend on how input is integrated into this spontaneous activity. It has been shown that input from climbing fibers originating in the inferior olive controls the spontaneous activity in Purkinje cells. While blocking climbing fiber input to the Purkinje cells causes a dramatic increase in the firing rate, increased climbing fiber activity results in reduced Purkinje cell activity. However, the exact calibration of this regulation has not been examined systematically. Here we examine the relation between climbing fiber stimulation frequency and Purkinje cell activity in unanesthetized decerebrated ferrets. The results revealed a gradual suppression of Purkinje cell activity, starting at climbing fiber stimulation frequencies as low as 0.5 Hz. At 4 Hz, Purkinje cells were completely silenced. This effect lasted an average of 2 min after the stimulation rate was reduced to a lower level. We also examined the effect of sustained climbing fiber stimulation on overt behavior. Specifically, we analyzed conditioned blink responses, which are known to be dependent on the cerebellum, while stimulating the climbing fibers at different frequencies. In accordance with the neurophysiological data, the conditioned blink responses were suppressed at stimulation frequencies of ≥4 Hz.

Climbing fibers encode a temporal-difference prediction error during cerebellar learning in mice

Climbing fiber inputs to Purkinje cells are thought to play a teaching role by generating the instructive signals that drive cerebellar learning. To investigate how these instructive signals are encoded, we recorded the activity of individual climbing fibers during cerebellar-dependent eyeblink conditioning in mice. Our findings show that climbing fibers signal both the unexpected delivery and the unexpected omission of the periocular airpuff that serves as the instructive signal for eyeblink conditioning. In addition, we report the surprising discovery that climbing fibers activated by periocular airpuffs also respond to stimuli from other sensory modalities, if those stimuli are novel or if they predict that the periocular airpuff is about to be presented. This pattern of climbing fiber activity is strikingly similar to the responses of dopamine neurons during reinforcement learning, which have been shown to encode a particular type of instructive signal known as a temporal difference prediction error.

Purkinje cell activity during classical conditioning with different conditional stimuli explains central tenet of Rescorla–Wagner model [corrected]

A central tenet of Rescorla and Wagner's model of associative learning is that the reinforcement value of a paired trial diminishes as the associative strength between the presented stimuli increases. Despite its fundamental importance to behavioral sciences, the neural mechanisms underlying the model have not been fully explored. Here, we present findings that, taken together, can explain why a stronger association leads to a reduced reinforcement value, within the context of eyeblink conditioning. Specifically, we show that learned pause responses in Purkinje cells, which trigger adaptively timed conditioned eyeblinks, suppress the unconditional stimulus (US) signal in a graded manner. Furthermore, by examining how Purkinje cells respond to two distinct conditional stimuli and to a compound stimulus, we provide evidence that could potentially help explain the somewhat counterintuitive overexpectation phenomenon, which was derived from the Rescorla-Wagner model.

How the credit assignment problems in motor control could be solved after the cerebellum predicts increases in error

We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations.

Relative contribution of TARPs γ-2 and γ-7 to cerebellar excitatory synaptic transmission and motor behavior

Transmembrane AMPA receptor regulatory proteins (TARPs) play an essential role in excitatory synaptic transmission throughout the central nervous system (CNS) and exhibit subtype-specific effects on AMPA receptor (AMPAR) trafficking, gating, and pharmacology. The function of TARPs has largely been determined through work on canonical type I TARPs such as stargazin (TARP γ-2), absent in the ataxic stargazer mouse. Little is known about the function of atypical type II TARPs, such as TARP γ-7, which exhibits variable effects on AMPAR function. Because γ-2 and γ-7 are both strongly expressed in multiple cell types in the cerebellum, we examined the relative contribution of γ-2 and γ-7 to both synaptic transmission in the cerebellum and motor behavior by using both the stargazer mouse and a γ-7 knockout (KO) mouse. We found that the loss of γ-7 alone had little effect on climbing fiber (cf) responses in Purkinje neurons (PCs), yet the additional loss of γ-2 all but abolished cf responses. In contrast, γ-7 failed to make a significant contribution to excitatory transmission in stellate cells and granule cells. In addition, we generated a PC-specific deletion of γ-2, with and without γ-7 KO background, to examine the relative contribution of γ-2 and γ-7 to PC-dependent motor behavior. Selective deletion of γ-2 in PCs had little effect on motor behavior, yet the additional loss of γ-7 resulted in a severe disruption in motor behavior. Thus, γ-7 is capable of supporting a component of excitatory transmission in PCs, sufficient to maintain essentially normal motor behavior, in the absence of γ-2.

The Neural Code for Motor Control in the Cerebellum and Oculomotor Brainstem

Our paper evaluates the nature of the neural code under conditions where we can understand the details of trial-by-trial neural variation and its relationship to behavior. We demonstrate that a single extra spike in the activity of a neuron can predict impending motor behavior.

Spike trains are rich in information that can be extracted to guide behaviors at millisecond time resolution or across longer time intervals. In sensory systems, the information usually is defined with respect to the stimulus. Especially in motor systems, however, it is equally critical to understand how spike trains predict behavior. Thus, our goal was to compare systematically spike trains in the oculomotor system with eye movement behavior on single movements. We analyzed the discharge of Purkinje cells in the floccular complex of the cerebellum, floccular target neurons in the brainstem, other vestibular neurons, and abducens neurons. We find that an extra spike in a brief analysis window predicts a substantial fraction of the trial-by-trial variation in the initiation of smooth pursuit eye movements. For Purkinje cells, a single extra spike in a 40 ms analysis window predicts, on average, 0.5 SDs of the variation in behavior. An optimal linear estimator predicts behavioral variation slightly better than do spike counts in brief windows. Simulations reveal that the ability of single spikes to predict a fraction of behavior also emerges from model spike trains that have the same statistics as the real spike trains, as long as they are driven by shared sensory inputs. We think that the shared sensory estimates in their inputs create correlations in neural spiking across time and across each population. As a result, one or a small number of spikes in a brief time interval can predict a substantial fraction of behavioral variation.

Modulation of Purkinje cell complex spike waveform by synchrony levels in the olivocerebellar system

Purkinje cells (PCs) generate complex spikes (CSs) when activated by the olivocerebellar system. Unlike most spikes, the CS waveform is highly variable, with the number, amplitude, and timing of the spikelets that comprise it varying with each occurrence. This variability suggests that CS waveform could be an important control parameter of olivocerebellar activity. The origin of this variation is not well known. Thus, we obtained extracellular recordings of CSs to investigate the possibility that the electrical coupling state of the inferior olive (IO) affects the CS waveform. Using multielectrode recordings from arrays of PCs we showed that the variance in the recording signal during the period when the spikelets occur is correlated with CS synchrony levels in local groups of PCs. The correlation was demonstrated under both ketamine and urethane, indicating that it is robust. Moreover, climbing fiber reflex evoked CSs showed an analogous positive correlation between spikelet-related variance and the number of cells that responded to a stimulus. Intra-IO injections of GABA-A receptor antagonists or the gap junction blocker carbenoxolone produced correlated changes in the variance and synchrony levels, indicating the presence of a causal relationship. Control experiments showed that changes in variance with synchrony were primarily due to changes in the CS waveform, as opposed to changes in the strength of field potentials from surrounding cells. Direct counts of spikelets showed that their number increased with synchronization of CS activity. In sum, these results provide evidence of a causal link between two of the distinguishing characteristics of the olivocerebellar system, its ability to generate synchronous activity and the waveform of the CS.

Coding of stimulus strength via analog calcium signals in Purkinje cell dendrites of awake mice

The climbing fiber input to Purkinje cells acts as a teaching signal by triggering a massive influx of dendritic calcium that marks the occurrence of instructive stimuli during cerebellar learning. Here, we challenge the view that these calcium spikes are all-or-none and only signal whether the instructive stimulus has occurred, without providing parametric information about its features. We imaged ensembles of Purkinje cell dendrites in awake mice and measured their calcium responses to periocular airpuffs that serve as instructive stimuli during cerebellar-dependent eyeblink conditioning. Information about airpuff duration and pressure was encoded probabilistically across repeated trials, and in two additional signals in single trials: the synchrony of calcium spikes in the Purkinje cell population, and the amplitude of the calcium spikes, which was modulated by a non-climbing fiber pathway. These results indicate that calcium-based teaching signals in Purkinje cells contain analog information that encodes the strength of instructive stimuli trial-by-trial.

DOI:http://dx.doi.org/10.7554/eLife.03663.001

A region of the brain known as the cerebellum plays a key role in learning how to anticipate an event. For example, if you know that a puff of air is going to be directed at your eye, it's a good idea to close it in advance. However, how much you need to close it depends on how strong that puff of air is. A very strong puff might require closing the eye completely to protect it. In contrast, it is probably better to only partially close the eye if you know a lighter puff of air is coming, so that you can still see.

Extensive research has focused on how neurons in and around the cerebellum work together to achieve this goal. When an event—such as a puff of air—occurs, signals are sent to large neurons in the cerebellum, called Purkinje cells, by ‘climbing fibers’. However, climbing fibers were thought to be able to respond in only two ways: either they fire in a single burst to signal that an event has occurred, or they don't fire. It was therefore unclear how the finer details of the event (for example, the strength of the puff of air) are transmitted to the cerebellum.

Najafi et al. imaged the level of calcium in the cerebellum of mice, as this indicates how active the neurons are. When a puff of air was directed at the eyes of the mice, Najafi et al. saw that the size of the response of the Purkinje cells corresponded with how big the puff of air was. Najafi et al. show that the size of this response, which is based mostly on input from the climbing fibers, is also influenced by input from an additional unknown source.

These findings show that Purkinje cells of the cerebellum receive detailed information about the nature of an event, such as a puff of air. What remains to be seen is whether the cerebellum uses this information to learn the correct response, that is how hard to blink to avoid the expected puff.

DOI:http://dx.doi.org/10.7554/eLife.03663.002

A matter of trial and error for motor learning

Climbing fiber inputs to cerebellar Purkinje cells are thought to carry error signals that can trigger motor learning across multiple time scales. A new study by Kimpo et al. finds that the potency of climbing fibers as instructive signals for adaptation of the vestibulo-ocular reflex depends on task conditions.