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

Control of action potential afterdepolarizations in the inferior olive by inactivating A-type currents through KV4 channels

Neurons of the inferior olive (IO) fire action potentials with large, long-lasting afterdepolarizations (ADPs). Broader ADPs support more spikes in climbing fibre axons and evoke longer bursts of complex spikes in Purkinje cells, which affect the magnitude and sign of cerebellar synaptic plasticity. In the present study, we investigated the ionic mechanisms that regulate IO action potential waveforms by making whole-cell recordings in brainstem slices from C57BL6/J mice. IO spikes evoked from rest had ADPs of ∼30 ms. After 500-ms hyperpolarizations, however, evoked action potentials were brief (1-2 ms), lacking ADPs altogether. Because such preconditioning should maximally recruit depolarizing Ih and T-type currents and minimize repolarizing Ca-dependent currents known to shape the ADP, the rapid action potential downstroke suggested additional, dominant recovery of voltage-gated K currents at negative voltages. Under voltage clamp, outward currents evoked from -98 mV included large, voltage-gated, rapidly inactivating 'A-type' K currents. These currents had a steep availability curve with half-inactivation at -85 mV, suitable for recruitment by small hyperpolarizations. The fast decay time constant increased with depolarization, as is typical of KV4 channels. The KV4 channel blocker AmmTx3 almost eliminated inactivating currents and broadened action potentials evoked from strongly negative potentials by ∼8-fold. Optogenetic stimulation of inhibitory cerebellar nucleo-olivary terminals hyperpolarized IO cells sufficiently to abolish the ADP. The data support the idea that currents through KV4 channels control action potential waveforms in IO cells, shortening ADPs during synaptic inhibition or troughs of membrane potential oscillations, thereby controlling the number of climbing fibre action potentials that propagate to the cerebellum. KEY POINTS: Neurons in the mouse inferior olive (IO) express a large, inactivating, voltage-gated A-type K current carried by KV4 channels. IO action potentials evoked from rest have large, long afterdepolarizations that disappear with pre-spike hyperpolarizations of 5-15 mV. The steep voltage-sensitivity and rapid recovery of KV4 channels regulates the duration of the afterdepolarization over more than one order of magnitude. Factors such as synaptic inhibition are sufficient to recruit KV4 channels and eliminate afterdepolarization (ADP). By controlling the ADP, KV4 channels can set the number of climbing fibre action potentials relayed to the cerebellum and regulate plasticity implicated in motor learning.

Branch-specific clustered parallel fiber input controls dendritic computation in Purkinje cells

Most central neurons have intricately branched dendritic trees that integrate massive numbers of synaptic inputs. Intrinsic active mechanisms in dendrites can be heterogeneous and be modulated in a branch-specific way. However, it remains poorly understood how heterogeneous intrinsic properties contribute to processing of synaptic input. We propose the first computational model of the cerebellar Purkinje cell with dendritic heterogeneity, in which each branch is an individual unit and is characterized by its own set of ion channel conductance densities. When simultaneously activating a cluster of parallel fiber synapses, we measure the peak amplitude of a response and observe how changes in P-type calcium channel conductance density shift the dendritic responses from a linear one to a bimodal one including dendritic calcium spikes and vice-versa. These changes relate to the morphology of each branch. We show how dendritic calcium spikes propagate and how Kv4.3 channels block spreading depolarization to nearby branches.

NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brain regions

Scalable electronic brain implants with long-term stability and low biological perturbation are crucial technologies for high-quality brain-machine interfaces that can seamlessly access delicate and hard-to-reach regions of the brain. Here, we created "NeuroRoots," a biomimetic multi-channel implant with similar dimensions (7 μm wide and 1.5 μm thick), mechanical compliance, and spatial distribution as axons in the brain. Unlike planar shank implants, these devices consist of a number of individual electrode "roots," each tendril independent from the other. A simple microscale delivery approach based on commercially available apparatus minimally perturbs existing neural architectures during surgery. NeuroRoots enables high density single unit recording from the cerebellum in vitro and in vivo. NeuroRoots also reliably recorded action potentials in various brain regions for at least 7 weeks during behavioral experiments in freely-moving rats, without adjustment of electrode position. This minimally invasive axon-like implant design is an important step toward improving the integration and stability of brain-machine interfacing.

Parvalbumin-expressing basal forebrain neurons mediate learning from negative experience

Parvalbumin (PV)-expressing GABAergic neurons of the basal forebrain (BFPVNs) were proposed to serve as a rapid and transient arousal system, yet their exact role in awake behaviors remains unclear. We performed bulk calcium measurements and electrophysiology with optogenetic tagging from the horizontal limb of the diagonal band of Broca (HDB) while male mice were performing an associative learning task. BFPVNs responded with a distinctive, phasic activation to punishment, but showed slower and delayed responses to reward and outcome-predicting stimuli. Optogenetic inhibition during punishment impaired the formation of cue-outcome associations, suggesting a causal role of BFPVNs in associative learning. BFPVNs received strong inputs from the hypothalamus, the septal complex and the median raphe region, while they synapsed on diverse cell types in key limbic structures, where they broadcasted information about aversive stimuli. We propose that the arousing effect of BFPVNs is recruited by aversive stimuli to serve crucial associative learning functions.

Intrinsic and synaptic determinants of receptive field plasticity in Purkinje cells of the mouse cerebellum

Non-synaptic (intrinsic) plasticity of membrane excitability contributes to aspects of memory formation, but it remains unclear whether it merely facilitates synaptic long-term potentiation or plays a permissive role in determining the impact of synaptic weight increase. We use tactile stimulation and electrical activation of parallel fibers to probe intrinsic and synaptic contributions to receptive field plasticity in awake mice during two-photon calcium imaging of cerebellar Purkinje cells. Repetitive activation of both stimuli induced response potentiation that is impaired in mice with selective deficits in either synaptic or intrinsic plasticity. Spatial analysis of calcium signals demonstrated that intrinsic, but not synaptic plasticity, enhances the spread of dendritic parallel fiber response potentiation. Simultaneous dendrite and axon initial segment recordings confirm these dendritic events affect axonal output. Our findings support the hypothesis that intrinsic plasticity provides an amplification mechanism that exerts a permissive control over the impact of long-term potentiation on neuronal responsiveness.

The olivary input to the cerebellum dissociates sensory events from movement plans

Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules, but what is computed by each module? Here, we designed a saccade task in marmosets that dissociated sensory events from motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset, it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if the subject experienced an error but chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group, the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still.

Nitric oxide modulates NMDA receptor through a negative feedback mechanism and regulates the dynamical behavior of neuronal postsynaptic components

Nitric oxide (NO) is known to be an important regulator of neurological processes in the central nervous system which acts directly on the presynaptic neuron and enhances the release of neurotransmitters like glutamate into the synaptic cleft. Calcium influx activates a cascade of biochemical reactions to influence the production of nitric oxide in the postsynaptic neuron. This has been modeled in the present work as a system of ordinary differential equations, to explore the dynamics of the interacting components and predict the dynamical behavior of the postsynaptic neuron. It has been hypothesized that nitric oxide modulates the NMDA receptor via a feedback mechanism and regulates the dynamic behavior of postsynaptic components. Results obtained by numerical analyses indicate that the biochemical system is stimulus-dependent and shows oscillations of calcium and other components within a limited range of concentration. Some of the parameters such as stimulus strength, extracellular calcium concentration, and rate of nitric oxide feedback are crucial for the dynamics of the components in the postsynaptic neuron.

Cerebellar climbing fibers multiplex movement and reward signals during a voluntary movement task in mice

Cerebellar climbing fibers convey sensorimotor information and their errors, which are used for motor control and learning. Furthermore, they represent reward-related information. Despite such functional diversity of climbing fiber signals, it is still unclear whether each climbing fiber conveys the information of single or multiple modalities and how the climbing fibers conveying different information are distributed over the cerebellar cortex. Here we perform two-photon calcium imaging from cerebellar Purkinje cells in mice engaged in a voluntary forelimb lever-pull task and demonstrate that climbing fiber responses in 68% of Purkinje cells can be explained by the combination of multiple behavioral variables such as lever movement, licking, and reward delivery. Neighboring Purkinje cells exhibit similar climbing fiber response properties, form functional clusters, and share noise fluctuations of responses. Taken together, individual climbing fibers convey behavioral information on multiplex variables and are spatially organized into the functional modules of the cerebellar cortex.

Intrinsic and synaptic determinants of receptive field plasticity in Purkinje cells of the mouse cerebellum

Non-synaptic ('intrinsic') plasticity of membrane excitability contributes to aspects of memory formation, but it remains unclear whether it merely facilitates synaptic long-term potentiation (LTP), or whether it plays a permissive role in determining the impact of synaptic weight increase. We use tactile stimulation and electrical activation of parallel fibers to probe intrinsic and synaptic contributions to receptive field (RF) plasticity in awake mice during two-photon calcium imaging of cerebellar Purkinje cells. Repetitive activation of both stimuli induced response potentiation that is impaired in mice with selective deficits in either intrinsic plasticity (SK2 KO) or LTP (CaMKII TT305/6VA). Intrinsic, but not synaptic, plasticity expands the local, dendritic RF representation. Simultaneous dendrite and axon initial segment recordings confirm that these dendritic events affect axonal output. Our findings support the hypothesis that intrinsic plasticity provides an amplification mechanism that exerts a permissive control over the impact of LTP on neuronal responsiveness.

Climbing fiber multi-innervation of mouse Purkinje dendrites with arborization common to human

Canonically, each Purkinje cell (PC) in the adult cerebellum receives only one climbing fiber (CF) from the inferior olive. Underlying current theories of cerebellar function is the notion that this highly conserved one-to-one relationship renders Purkinje dendrites into a single computational compartment. However, we discovered that multiple primary dendrites are a near-universal morphological feature in humans. Using tract tracing, immunolabeling, and in vitro electrophysiology, we found that in mice ~25% of mature multibranched cells receive more than one CF input. Two-photon calcium imaging in vivo revealed that separate dendrites can exhibit distinct response properties to sensory stimulation, indicating that some multibranched cells integrate functionally independent CF-receptive fields. These findings indicate that PCs are morphologically and functionally more diverse than previously thought.

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

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

Cholinergic activity reflects reward expectations and predicts behavioral responses

Basal forebrain cholinergic neurons (BFCNs) play an important role in associative learning, suggesting that BFCNs may participate in processing stimuli that predict future outcomes. However, the impact of outcome probabilities on BFCN activity remained elusive. Therefore, we performed bulk calcium imaging and recorded spiking of identified cholinergic neurons from the basal forebrain of mice performing a probabilistic Pavlovian cued outcome task. BFCNs responded more to sensory cues that were often paired with reward. Reward delivery also activated BFCNs, with surprising rewards eliciting a stronger response, whereas punishments evoked uniform positive-going responses. We propose that BFCNs differentially weigh predictions of positive and negative reinforcement, reflecting divergent relative salience of forecasting appetitive and aversive outcomes, partially explained by a simple reinforcement learning model of a valence-weighed unsigned prediction error. Finally, the extent of cue-driven cholinergic activation predicted subsequent decision speed, suggesting that the expectation-gated cholinergic firing is instructive to reward-seeking behaviors.

Sensory Over-responsivity and Aberrant Plasticity in Cerebellar Cortex in a Mouse Model of Syndromic Autism

Background

Patients with autism spectrum disorder often show altered responses to sensory stimuli as well as motor deficits, including an impairment of delay eyeblink conditioning, which involves integration of sensory signals in the cerebellum. Here, we identify abnormalities in parallel fiber (PF) and climbing fiber (CF) signaling in the mouse cerebellar cortex that may contribute to these pathologies.

Methods

We used a mouse model for the human 15q11-13 duplication (patDp/+) and studied responses to sensory stimuli in Purkinje cells from awake mice using two-photon imaging of GCaMP6f signals. Moreover, we examined synaptic transmission and plasticity using in vitro electrophysiological, immunohistochemical, and confocal microscopic techniques.

Results

We found that spontaneous and sensory-evoked CF-calcium transients are enhanced in patDp/+ Purkinje cells, and aversive movements are more severe across sensory modalities. We observed increased expression of the synaptic organizer NRXN1 at CF synapses and ectopic spread of these synapses to fine dendrites. CF-excitatory postsynaptic currents recorded from Purkinje cells are enlarged in patDp/+ mice, while responses to PF stimulation are reduced. Confocal measurements show reduced PF+CF-evoked spine calcium transients, a key trigger for PF long-term depression, one of several plasticity types required for eyeblink conditioning learning. Long-term depression is impaired in patDp/+ mice but is rescued on pharmacological enhancement of calcium signaling.

Conclusions

Our findings suggest that this genetic abnormality causes a pathological inflation of CF signaling, possibly resulting from enhanced NRXN1 expression, with consequences for the representation of sensory stimuli by the CF input and for PF synaptic organization and plasticity.

Computational Methods for Neuron Segmentation in Two-Photon Calcium Imaging Data: A Survey

Calcium imaging has rapidly become a methodology of choice for real-time in vivo neuron analysis. Its application to large sets of data requires automated tools to annotate and segment cells, allowing scalable image segmentation under reproducible criteria. In this paper, we review and summarize the most recent methods for computational segmentation of calcium imaging. The contributions of the paper are three-fold: we provide an overview of the main algorithms taxonomized in three categories (signal processing, matrix factorization and machine learning-based approaches), we highlight the main advantages and disadvantages of each category and we provide a summary of the performance of the methods that have been tested on public benchmarks (with links to the public code when available).

Designing AAV Vectors for Monitoring the Subtle Calcium Fluctuations of Inferior Olive Network in vivo

Adeno-associated viral (AAV) vectors, used as vehicles for gene transfer into the brain, are a versatile and powerful tool of modern neuroscience that allow identifying specific neuronal populations, monitoring and modulating their activity. For consistent and reproducible results, the AAV vectors must be engineered so that they reliably and accurately target cell populations. Furthermore, transgene expression must be adjusted to sufficient and safe levels compatible with the physiology of studied cells. We undertook the effort to identify and validate an AAV vector that could be utilized for researching the inferior olivary (IO) nucleus, a structure gating critical timing-related signals to the cerebellum. By means of systematic construct generation and quantitative expression profiling, we succeeded in creating a viral tool for specific and strong transfection of the IO neurons without adverse effects on their physiology. The potential of these tools is demonstrated by expressing the calcium sensor GCaMP6s in adult mouse IO neurons. We could monitor subtle calcium fluctuations underlying two signatures of intrinsic IO activity: the subthreshold oscillations (STOs) and the variable-duration action potential waveforms both in-vitro and in-vivo. Further, we show that the expression levels of GCaMP6s allowing such recordings are compatible with the delicate calcium-based dynamics of IO neurons, inviting future work into the network dynamics of the olivo-cerebellar system in behaving animals.

Reward signals in the cerebellum: origins, targets, and functional implications

The cerebellum has long been proposed to play a role in cognitive function, although this has remained controversial. This idea has received renewed support with the recent discovery that signals associated with reward can be observed in the cerebellar circuitry, particularly in goal-directed learning tasks involving an interplay between the cerebellar cortex, basal ganglia, and cerebral cortex. Remarkably, a wide range of reward contingencies-including reward expectation, delivery, size, and omission-can be encoded by specific circuit elements in a manner that reflects the microzonal organization of the cerebellar cortex. The facts that reward signals have been observed in both the mossy fiber and climbing fiber input pathways to the cerebellar cortex and that their convergence may trigger plasticity in Purkinje cells suggest that these interactions may be crucial for the role of the cerebellar cortex in learned behavior. These findings strengthen the emerging consensus that the cerebellum plays a pivotal role in shaping cognitive processing and suggest that the cerebellum may combine both supervised learning and reinforcement learning to optimize goal-directed action. We make specific predictions about how cerebellar circuits can work in concert with the basal ganglia to guide different stages of learning.

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.

The Cellular Electrophysiological Properties Underlying Multiplexed Coding in Purkinje Cells

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

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

Purkinje Cell Activity Determines the Timing of Sensory-Evoked Motor Initiation

Cerebellar neurons can signal sensory and motor events, but their role in active sensorimotor processing remains unclear. We record and manipulate Purkinje cell activity during a task that requires mice to rapidly discriminate between multisensory and unisensory stimuli before motor initiation. Neuropixels recordings show that both sensory stimuli and motor initiation are represented by short-latency simple spikes. Optogenetic manipulation of short-latency simple spikes abolishes or delays motor initiation in a rate-dependent manner, indicating a role in motor initiation and its timing. Two-photon calcium imaging reveals task-related coherence of complex spikes organized into conserved alternating parasagittal stripes. The coherence of sensory-evoked complex spikes increases with learning and correlates with enhanced temporal precision of motor initiation. These results suggest that both simple spikes and complex spikes govern sensory-driven motor initiation: simple spikes modulate its latency, and complex spikes refine its temporal precision, providing specific cellular substrates for cerebellar sensorimotor control.

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 FN-MdV pathway and its role in cerebellar multimodular control of sensorimotor behavior

The cerebellum is crucial for various associative sensorimotor behaviors. Delay eyeblink conditioning (DEC) depends on the simplex lobule-interposed nucleus (IN) pathway, yet it is unclear how other cerebellar modules cooperate during this task. Here, we demonstrate the contribution of the vermis-fastigial nucleus (FN) pathway in controlling DEC. We found that task-related modulations in vermal Purkinje cells and FN neurons predict conditioned responses (CRs). Coactivation of the FN and the IN allows for the generation of proper motor commands for CRs, but only FN output fine-tunes unconditioned responses. The vermis-FN pathway launches its signal via the contralateral ventral medullary reticular nucleus, which converges with the command from the simplex-IN pathway onto facial motor neurons. We propose that the IN pathway specifically drives CRs, whereas the FN pathway modulates the amplitudes of eyelid closure during DEC. Thus, associative sensorimotor task optimization requires synergistic modulation of different olivocerebellar modules each provide unique contributions.

Delay eyeblink conditioning depends on the simplex lobule-interposed nucleus pathway in the cerebellum. Here, the authors show that the vermis-fastigial nucleus-medullary reticular nucleus pathway modulates the conditioned and unconditioned eyelid closure during delay eyeblink conditioning.

Population coding in the cerebellum: a machine learning perspective

The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron is a prediction that is compared with the actual observation, resulting in an error signal that originates in the inferior olive. Efficient learning requires that the error signal reach the DCN neurons, as well as the P-cells that project onto them. However, this basic rule of learning is violated in the cerebellum: the olivary projections to the DCN are weak, particularly in adulthood. Instead, an extraordinarily strong signal is sent from the olive to the P-cells, producing complex spikes. Curiously, P-cells are grouped into small populations that converge onto single DCN neurons. Why are the P-cells organized in this way, and what is the membership criterion of each population? Here, I apply elementary mathematics from machine learning and consider the fact that P-cells that form a population exhibit a special property: they can synchronize their complex spikes, which in turn suppress activity of DCN neuron they project to. Thus complex spikes cannot only act as a teaching signal for a P-cell, but through complex spike synchrony, a P-cell population may act as a surrogate teacher for the DCN neuron that produced the erroneous output. It appears that grouping of P-cells into small populations that share a preference for error satisfies a critical requirement of efficient learning: providing error information to the output layer neuron (DCN) that was responsible for the error, as well as the hidden layer neurons (P-cells) that contributed to it. This population coding may account for several remarkable features of behavior during learning, including multiple timescales, protection from erasure, and spontaneous recovery of memory.

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.

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.

Identification of a molecular locus for normalizing dysregulated GABA release from interneurons in the Fragile X brain

Principal neurons encode information by varying their firing rate and patterns precisely fine-tuned through GABAergic interneurons. Dysregulation of inhibition can lead to neuropsychiatric disorders, yet little is known about the molecular basis underlying inhibitory control. Here, we find that excessive GABA release from basket cells (BCs) attenuates the firing frequency of Purkinje neurons (PNs) in the cerebellum of Fragile X Mental Retardation 1 (Fmr1) knockout (KO) mice, a model of Fragile X Syndrome (FXS) with abrogated expression of the Fragile X Mental Retardation Protein (FMRP). This over-inhibition originates from increased excitability and Ca²⁺ transients in the presynaptic terminals, where Kv1.2 potassium channels are downregulated. By paired patch-clamp recordings, we further demonstrate that acutely introducing an N-terminal fragment of FMRP into BCs normalizes GABA release in the Fmr1-KO synapses. Conversely, direct injection of an inhibitory FMRP antibody into BCs, or membrane depolarization of BCs, enhances GABA release in the wild type synapses, leading to abnormal inhibitory transmission comparable to the Fmr1-KO neurons. We discover that the N-terminus of FMRP directly binds to a phosphorylated serine motif on the C-terminus of Kv1.2; and that loss of this interaction in BCs exaggerates GABA release, compromising the firing activity of PNs and thus the output from the cerebellar circuitry. An allosteric Kv1.2 agonist, docosahexaenoic acid, rectifies the dysregulated inhibition in vitro as well as acoustic startle reflex and social interaction in vivo of the Fmr1-KO mice. Our results unravel a novel molecular locus for targeted intervention of FXS and perhaps autism.

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.

Complex spike clusters and false-positive rejection in a cerebellar supervised learning rule

KEY POINTS

Spike doublets comprise ∼10% of in vivo complex spike events under spontaneous conditions and ∼20% (up to 50%) under evoked conditions. Under near-physiological slice conditions, single complex spikes do not induce parallel fibre long-term depression. Doublet stimulation is required to induce long-term depression with an optimal parallel-fibre to first-complex-spike timing interval of 150 ms.

ABSTRACT

The classic example of biological supervised learning occurs at cerebellar parallel fibre (PF) to Purkinje cell synapses, comprising the most abundant synapse in the mammalian brain. Long-term depression (LTD) at these synapses is driven by climbing fibres (CFs), which fire continuously about once per second and therefore generate potential false-positive events. We show that pairs of complex spikes are required to induce LTD. In vivo, sensory stimuli evoked complex-spike doublets with intervals ≤150 ms in up to 50% of events. Using realistic [Ca2+ ]o and [Mg2+ ]o concentrations in slices, we determined that complex-spike doublets delivered 100-150 ms after PF stimulus onset were required to trigger PF-LTD, which is consistent with the requirements for eyeblink conditioning. Inter-complex spike intervals of 50-150 ms provided optimal decoding. This stimulus pattern prolonged evoked spine calcium signals and promoted CaMKII activation. Doublet activity may provide a means for CF instructive signals to stand out from background firing.

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.

Neurons of the inferior olive respond to broad classes of sensory input while subject to homeostatic control

KEY POINTS

Purkinje cells in the cerebellum integrate input from sensory organs with that from premotor centres. Purkinje cells use a variety of sensory inputs relaying information from the environment to modify motor control. Here we investigated to what extent the climbing fibre inputs to Purkinje cells signal mono- or multi-sensory information, and to what extent this signalling is subject to recent history of activity. We show that individual climbing fibres convey multiple types of sensory information, together providing a rich mosaic projection pattern of sensory signals across the cerebellar cortex. Moreover, firing probability of climbing fibres following sensory stimulation depends strongly on the recent history of activity, showing a tendency to homeostatic dampening.

ABSTRACT

Cerebellar Purkinje cells integrate sensory information with motor efference copies to adapt movements to behavioural and environmental requirements. They produce complex spikes that are triggered by the activity of climbing fibres originating in neurons of the inferior olive. These complex spikes can shape the onset, amplitude and direction of movements and the adaptation of such movements to sensory feedback. Clusters of nearby inferior olive neurons project to parasagittally aligned stripes of Purkinje cells, referred to as 'microzones'. It is currently unclear to what extent individual Purkinje cells within a single microzone integrate climbing fibre inputs from multiple sources of different sensory origins, and to what extent sensory-evoked climbing fibre responses depend on the strength and recent history of activation. Here we imaged complex spike responses in cerebellar lobule crus 1 to various types of sensory stimulation in awake mice. We find that different sensory modalities and receptive fields have a mild, but consistent, tendency to converge on individual Purkinje cells, with climbing fibres showing some degree of input-specificity. Purkinje cells encoding the same stimulus show increased events with coherent complex spike firing and tend to lie close together. Moreover, whereas complex spike firing is only mildly affected by variations in stimulus strength, it depends strongly on the recent history of climbing fibre activity. Our data point towards a mechanism in the olivo-cerebellar system that regulates complex spike firing during mono- or multi-sensory stimulation around a relatively low set-point, highlighting an integrative coding scheme of complex spike firing under homeostatic control.

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.

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

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

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

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

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.

Conditioned climbing fiber responses in cerebellar cortex and nuclei

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

Encoding of error and learning to correct that error by the Purkinje cells of the cerebellum

The primary output cells of the cerebellar cortex, Purkinje cells, make kinematic predictions about ongoing movements via high-frequency simple spikes, but receive sensory error information about that movement via low-frequency complex spikes (CS). How is the vector space of sensory errors encoded by this low-frequency signal? Here we measured Purkinje cell activity in the oculomotor vermis of animals during saccades, then followed the chain of events from experience of visual error, generation of CS, modulation of simple spikes, and ultimately change in motor output. We found that while error direction affected the probability of CS, error magnitude altered its temporal distribution. Production of CS changed the simple spikes on the next trial, but regardless of the actual visual error, this change biased the movement only along a vector that was parallel to the Purkinje cell's preferred error. From these results, we inferred the anatomy of a sensory-to-motor adaptive controller that transformed visual error vectors into motor-corrections.

Calcium Imaging Reveals Coordinated Simple Spike Pauses in Populations of Cerebellar Purkinje Cells

The brain's control of movement is thought to involve coordinated activity between cerebellar Purkinje cells. The results reported here demonstrate that somatic Ca²⁺ imaging is a faithful reporter of Na⁺-dependent "simple spike" pauses and enables us to optically record changes in firing rates in populations of Purkinje cells in brain slices and in vivo. This simultaneous calcium imaging of populations of Purkinje cells reveals a striking spatial organization of pauses in Purkinje cell activity between neighboring cells. The source of this organization is shown to be the presynaptic gamma-Aminobutyric acid producing (GABAergic) network, and blocking ionotropic gamma-Aminobutyric acid receptor (GABA_ARs) abolishes the synchrony. These data suggest that presynaptic interneurons synchronize (in)activity between neighboring Purkinje cells, and thereby maximize their effect on downstream targets in the deep cerebellar nuclei.

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

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

Climbing Fibers Control Purkinje Cell Representations of Behavior

A crucial issue in understanding cerebellar function is the interaction between simple spike (SS) and complex spike (CS) discharge, the two fundamentally different activity modalities of Purkinje cells. Although several hypotheses have provided insights into the interaction, none fully explains or is completely consistent with the spectrum of experimental observations. Here, we show that during a pseudo-random manual tracking task in the monkey (Macaca mulatta), climbing fiber discharge dynamically controls the information present in the SS firing, triggering robust and rapid changes in the SS encoding of motor signals in 67% of Purkinje cells. The changes in encoding, tightly coupled to CS occurrences, consist of either increases or decreases in the SS sensitivity to kinematics or position errors and are not due to differences in SS firing rates or variability. Nor are the changes in sensitivity due to CS rhythmicity. In addition, the CS-coupled changes in encoding are not evoked by changes in kinematics or position errors. Instead, CS discharge most often leads alterations in behavior. Increases in SS encoding of a kinematic parameter are associated with larger changes in that parameter than are decreases in SS encoding. Increases in SS encoding of position error are followed by and scale with decreases in error. The results suggest a novel function of CSs, in which climbing fiber input dynamically controls the state of Purkinje cell SS encoding in advance of changes in behavior.SIGNIFICANCE STATEMENT Purkinje cells, the sole output of the cerebellar cortex, manifest two fundamentally different activity modalities, complex spike (CS) discharge and simple spike (SS) firing. Elucidating cerebellar function will require an understanding of the interactions, both short- and long-term, between CS and SS firing. This study shows that CSs dynamically control the information encoded in a Purkinje cell's SS activity by rapidly increasing or decreasing the SS sensitivity to kinematics and/or performance errors independent of firing rate. In many cases, the CS-coupled shift in SS encoding leads a change in behavior. These novel findings on the interaction between CS and SS firing provide for a new hypothesis in which climbing fiber input adjusts the encoding of SS information in advance of a change in behavior.

The Errors of Our Ways: Understanding Error Representations in Cerebellar-Dependent Motor Learning

The cerebellum is essential for error-driven motor learning and is strongly implicated in detecting and correcting for motor errors. Therefore, elucidating how motor errors are represented in the cerebellum is essential in understanding cerebellar function, in general, and its role in motor learning, in particular. This review examines how motor errors are encoded in the cerebellar cortex in the context of a forward internal model that generates predictions about the upcoming movement and drives learning and adaptation. In this framework, sensory prediction errors, defined as the discrepancy between the predicted consequences of motor commands and the sensory feedback, are crucial for both on-line movement control and motor learning. While many studies support the dominant view that motor errors are encoded in the complex spike discharge of Purkinje cells, others have failed to relate complex spike activity with errors. Given these limitations, we review recent findings in the monkey showing that complex spike modulation is not necessarily required for motor learning or for simple spike adaptation. Also, new results demonstrate that the simple spike discharge provides continuous error signals that both lead and lag the actual movements in time, suggesting errors are encoded as both an internal prediction of motor commands and the actual sensory feedback. These dual error representations have opposing effects on simple spike discharge, consistent with the signals needed to generate sensory prediction errors used to update a forward internal model.