The Cerebellar Cortex.

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

DART.2: bidirectional synaptic pharmacology with thousandfold cellular specificity.

Precision pharmacology aims to manipulate specific cellular interactions within complex tissues. In this pursuit, we introduce DART.2 (drug acutely restricted by tethering), a second-generation cell-specific pharmacology technology. The core advance is optimized cellular specificity-up to 3,000-fold in 15 min-enabling the targeted delivery of even epileptogenic drugs without off-target effects. Additionally, we introduce brain-wide dosing methods as an alternative to local cannulation and tracer reagents for brain-wide dose quantification. We describe four pharmaceuticals-two that antagonize excitatory and inhibitory postsynaptic receptors, and two that allosterically potentiate these receptors. Their versatility is showcased across multiple mouse-brain regions, including cerebellum, striatum, visual cortex and retina. Finally, in the ventral tegmental area, we find that blocking inhibitory inputs to dopamine neurons accelerates locomotion, contrasting with previous optogenetic and pharmacological findings. Beyond enabling the bidirectional perturbation of chemical synapses, these reagents offer intersectional precision-between genetically defined postsynaptic cells and neurotransmitter-defined presynaptic partners.

Mice lacking Astn2 have ASD-like behaviors and altered cerebellar circuit properties.

Astrotactin 2 (ASTN2) is a transmembrane neuronal protein highly expressed in the cerebellum that functions in receptor trafficking and modulates cerebellar Purkinje cell (PC) synaptic activity. Individuals with ASTN2 mutations exhibit neurodevelopmental disorders, including autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), learning difficulties, and language delay. To provide a genetic model for the role of the cerebellum in ASD-related behaviors and study the role of ASTN2 in cerebellar circuit function, we generated global and PC-specific conditional Astn2 knockout (KO and cKO, respectively) mouse lines. Astn2 KO mice exhibit strong ASD-related behavioral phenotypes, including a marked decrease in separation-induced pup ultrasonic vocalization calls, hyperactivity, repetitive behaviors, altered behavior in the three-chamber test, and impaired cerebellar-dependent eyeblink conditioning. Hyperactivity and repetitive behaviors are also prominent in Astn2 cKO animals, but they do not show altered behavior in the three-chamber test. By Golgi staining, Astn2 KO PCs have region-specific changes in dendritic spine density and filopodia numbers. Proteomic analysis of Astn2 KO cerebellum reveals a marked upregulation of ASTN2 family member, ASTN1, a neuron-glial adhesion protein. Immunohistochemistry and electron microscopy demonstrate a significant increase in Bergmann glia volume in the molecular layer of Astn2 KO animals. Electrophysiological experiments indicate a reduced frequency of spontaneous excitatory postsynaptic currents (EPSCs), as well as increased amplitudes of both spontaneous EPSCs and inhibitory postsynaptic currents in the Astn2 KO animals, suggesting that pre- and postsynaptic components of synaptic transmission are altered. Thus, ASTN2 regulates ASD-like behaviors and cerebellar circuit properties.

Acetylcholine Modulates Cerebellar Granule Cell Spiking by Regulating the Balance of Synaptic Excitation and Inhibition.

Sensorimotor integration in the cerebellum is essential for refining motor output, and the first stage of this processing occurs in the granule cell layer. Recent evidence suggests that granule cell layer synaptic integration can be contextually modified, although the circuit mechanisms that could mediate such modulation remain largely unknown. Here we investigate the role of ACh in regulating granule cell layer synaptic integration in male rats and mice of both sexes. We find that Golgi cells, interneurons that provide the sole source of inhibition to the granule cell layer, express both nicotinic and muscarinic cholinergic receptors. While acute ACh application can modestly depolarize some Golgi cells, the net effect of longer, optogenetically induced ACh release is to strongly hyperpolarize Golgi cells. Golgi cell hyperpolarization by ACh leads to a significant reduction in both tonic and evoked granule cell synaptic inhibition. ACh also reduces glutamate release from mossy fibers by acting on presynaptic muscarinic receptors. Surprisingly, despite these consistent effects on Golgi cells and mossy fibers, ACh can either increase or decrease the spike probability of granule cells as measured by noninvasive cell-attached recordings. By constructing an integrate-and-fire model of granule cell layer population activity, we find that the direction of spike rate modulation can be accounted for predominately by the initial balance of excitation and inhibition onto individual granule cells. Together, these experiments demonstrate that ACh can modulate population-level granule cell responses by altering the ratios of excitation and inhibition at the first stage of cerebellar processing.SIGNIFICANCE STATEMENT The cerebellum plays a key role in motor control and motor learning. While it is known that behavioral context can modify motor learning, the circuit basis of such modulation has remained unclear. Here we find that a key neuromodulator, ACh, can alter the balance of excitation and inhibition at the first stage of cerebellar processing. These results suggest that ACh could play a key role in altering cerebellar learning by modifying how sensorimotor input is represented at the input layer of the cerebellum.

ASTN2 modulates synaptic strength by trafficking and degradation of surface proteins.

Surface protein dynamics dictate synaptic connectivity and function in neuronal circuits. ASTN2, a gene disrupted by copy number variations (CNVs) in neurodevelopmental disorders, including autism spectrum, was previously shown to regulate the surface expression of ASTN1 in glial-guided neuronal migration. Here, we demonstrate that ASTN2 binds to and regulates the surface expression of multiple synaptic proteins in postmigratory neurons by endocytosis, resulting in modulation of synaptic activity. In cerebellar Purkinje cells (PCs), by immunogold electron microscopy, ASTN2 localizes primarily to endocytic and autophagocytic vesicles in the cell soma and in subsets of dendritic spines. Overexpression of ASTN2 in PCs, but not of ASTN2 lacking the FNIII domain, recurrently disrupted by CNVs in patients, including in a family presented here, increases inhibitory and excitatory postsynaptic activity and reduces levels of ASTN2 binding partners. Our data suggest a fundamental role for ASTN2 in dynamic regulation of surface proteins by endocytic trafficking and protein degradation.

Serotonin regulates dynamics of cerebellar granule cell activity by modulating tonic inhibition.

Understanding how afferent information is integrated by cortical structures requires identifying the factors shaping excitation and inhibition within their input layers. The input layer of the cerebellar cortex integrates diverse sensorimotor information to enable learned associations that refine the dynamics of movement. Specifically, mossy fiber afferents relay sensorimotor input into the cerebellum to excite granule cells, whose activity is regulated by inhibitory Golgi cells. To test how this integration can be modulated, we have used an acute brain slice preparation from young adult rats and found that encoding of mossy fiber input in the cerebellar granule cell layer can be regulated by serotonin (5-hydroxytryptamine, 5-HT) via a specific action on Golgi cells. We find that 5-HT depolarizes Golgi cells, likely by activating 5-HT2A receptors, but does not directly act on either granule cells or mossy fibers. As a result of Golgi cell depolarization, 5-HT significantly increases tonic inhibition onto both granule cells and Golgi cells. 5-HT-mediated Golgi cell depolarization is not sufficient, however, to alter the probability or timing of mossy fiber-evoked feed-forward inhibition onto granule cells. Together, increased granule cell tonic inhibition paired with normal feed-forward inhibition acts to reduce granule cell spike probability without altering spike timing. Hence, these data provide a circuit mechanism by which 5-HT can reduce granule cell activity without altering temporal representations of mossy fiber input. Such changes in network integration could enable flexible, state-specific suppression of cerebellar sensorimotor input that should not be learned or enable reversal learning for unwanted associations. NEW & NOTEWORTHY Serotonin (5-hydroxytryptamine, 5-HT) regulates synaptic integration at the input stage of cerebellar processing by increasing tonic inhibition of granule cells. This circuit mechanism reduces the probability of granule cell spiking without altering spike timing, thus suppressing cerebellar input without altering its temporal representation in the granule cell layer.

Autistic-like behaviour and cerebellar dysfunction in Purkinje cell Tsc1 mutant mice.

Autism spectrum disorders (ASDs) are highly prevalent neurodevelopmental disorders, but the underlying pathogenesis remains poorly understood. Recent studies have implicated the cerebellum in these disorders, with post-mortem studies in ASD patients showing cerebellar Purkinje cell (PC) loss, and isolated cerebellar injury has been associated with a higher incidence of ASDs. However, the extent of cerebellar contribution to the pathogenesis of ASDs remains unclear. Tuberous sclerosis complex (TSC) is a genetic disorder with high rates of comorbid ASDs that result from mutation of either TSC1 or TSC2, whose protein products dimerize and negatively regulate mammalian target of rapamycin (mTOR) signalling. TSC is an intriguing model to investigate the cerebellar contribution to the underlying pathogenesis of ASDs, as recent studies in TSC patients demonstrate cerebellar pathology and correlate cerebellar pathology with increased ASD symptomatology. Functional imaging also shows that TSC patients with ASDs display hypermetabolism in deep cerebellar structures, compared to TSC patients without ASDs. However, the roles of Tsc1 and the sequelae of Tsc1 dysfunction in the cerebellum have not been investigated so far. Here we show that both heterozygous and homozygous loss of Tsc1 in mouse cerebellar PCs results in autistic-like behaviours, including abnormal social interaction, repetitive behaviour and vocalizations, in addition to decreased PC excitability. Treatment of mutant mice with the mTOR inhibitor, rapamycin, prevented the pathological and behavioural deficits. These findings demonstrate new roles for Tsc1 in PC function and define a molecular basis for a cerebellar contribution to cognitive disorders such as autism.

Active Dendrites and Differential Distribution of Calcium Channels Enable Functional Compartmentalization of Golgi Cells.

Interneurons are essential to controlling excitability, timing, and synaptic integration in neuronal networks. Golgi cells (GoCs) serve these roles at the input layer of the cerebellar cortex by releasing GABA to inhibit granule cells (grcs). GoCs are excited by mossy fibers (MFs) and grcs and provide feedforward and feedback inhibition to grcs. Here we investigate two important aspects of GoC physiology: the properties of GoC dendrites and the role of calcium signaling in regulating GoC spontaneous activity. Although GoC dendrites are extensive, previous studies concluded they are devoid of voltage-gated ion channels. Hence, the current view holds that somatic voltage signals decay passively within GoC dendrites, and grc synapses onto distal dendrites are not amplified and are therefore ineffective at firing GoCs because of strong passive attenuation. Using whole-cell recording and calcium imaging in rat slices, we find that dendritic voltage-gated sodium channels allow somatic action potentials to activate voltage-gated calcium channels (VGCCs) along the entire dendritic length, with R-type and T-type VGCCs preferentially located distally. We show that R- and T-type VGCCs located in the dendrites can boost distal synaptic inputs and promote burst firing. Active dendrites are thus critical to the regulation of GoC activity, and consequently, to the processing of input to the cerebellar cortex. In contrast, we find that N-type channels are preferentially located near the soma, and control the frequency and pattern of spontaneous firing through their close association with calcium-activated potassium (KCa) channels. Thus, VGCC types are differentially distributed and serve specialized functions within GoCs. SIGNIFICANCE STATEMENT: Interneurons are essential to neural processing because they modulate excitability, timing, and synaptic integration within circuits. At the input layer of the cerebellar cortex, a single type of interneuron, the Golgi cell (GoC), carries these functions. The extent of inhibition depends on both spontaneous activity of GoCs and the excitatory synaptic input they receive. In this study, we find that different types of calcium channels are differentially distributed, with dendritic calcium channels being activated by somatic activity, boosting synaptic inputs and enabling bursting, and somatic calcium cannels promoting regular firing. We therefore challenge the current view that GoC dendrites are passive and identify the mechanisms that contribute to GoCs regulating the flow of sensory information in the cerebellar cortex.

Hyperpolarization induces a long-term increase in the spontaneous firing rate of cerebellar Golgi cells.

Golgi cells (GoCs) are inhibitory interneurons that influence the cerebellar cortical response to sensory input by regulating the excitability of the granule cell layer. While GoC inhibition is essential for normal motor coordination, little is known about the circuit dynamics that govern the activity of these cells. In particular, although GoC spontaneous spiking influences the extent of inhibition and gain throughout the granule cell layer, it is not known whether this spontaneous activity can be modulated in a long-term manner. Here we describe a form of long-term plasticity that regulates the spontaneous firing rate of GoCs in the rat cerebellar cortex. We find that membrane hyperpolarization, either by mGluR2 activation of potassium channels, or by somatic current injection, induces a long-lasting increase in GoC spontaneous firing. This spike rate plasticity appears to result from a strong reduction in the spike after hyperpolarization. Pharmacological manipulations suggest the involvement of calcium-calmodulin-dependent kinase II and calcium-activated potassium channels in mediating these firing rate increases. As a consequence of this plasticity, GoC spontaneous spiking is selectively enhanced, but the gain of evoked spiking is unaffected. Hence, this plasticity is well suited for selectively regulating the tonic output of GoCs rather than their sensory-evoked responses.

Reward-driven cerebellar climbing fiber activity influences both neural and behavioral learning.

The cerebellum plays a key role in motor coordination and learning. In contrast with classical supervised learning models, recent work has revealed that CFs can signal reward-predictive information in some behaviors. This raises the question of whether CFs may also operate according to principles similar to those described by reinforcement learning models. To test how CFs operate during reward-guided behavior, and evaluate the role of reward-related CF activity in learning, we have measured CF responses in Purkinje cells of the lateral cerebellum during a Pavlovian task using 2-photon calcium imaging. Specifically, we have performed multi-stimulus experiments to determine whether CF activity meets the requirements of a reward prediction error (rPE) signal for transfer from an unexpected reward to a reward-predictive cue. We find that once CF activity is transferred to a conditioned stimulus, and there is no longer a response to reward, CFs cannot generate learned responses to a second conditioned stimulus that carries the same reward prediction. In addition, by expressing the inhibitory opsin GtACR2 in neurons of the inferior olive, and optically inhibiting these neurons across behavioral training at the time of unexpected reward, we find that the transfer of CF signals to the conditioned stimulus is impaired. Moreover, this optogenetic inhibition also impairs learning, resulting in a deficit in anticipatory lick timing. Together, these results indicate that CF signals can exhibit several characteristics in common with rPEs during reinforcement learning, and that the cerebellum can harness these learning signals to generate accurately timed motor behavior.

Cerebellar climbing fibers signal flexible, rapidly adapting reward predictions.

Classical models of cerebellar computation posit that climbing fibers (CFs) operate according to supervised learning rules, correcting movements by signaling the occurrence of motor errors. However, recent findings suggest that in some behaviors, CF activity can exhibit features that resemble the instructional signals necessary for reinforcement learning, namely reward prediction errors (rPEs). Despite these initial observations, many key properties of reward-related CF responses remain unclear, thus limiting our understanding of how they operate to guide cerebellar learning. Here, we have measured the postsynaptic responses of CFs onto cerebellar Purkinje cells using two-photon calcium imaging to test how they respond to learned stimuli that either do or do not predict reward. We find that CFs can develop generalized responses to similar cues of the same modality, regardless of whether they are reward predictive. However, this generalization depends on temporal context, and does not extend across sensory modalities. Further, learned CF responses are flexible, and can be rapidly updated according to new reward contingencies. Together these results suggest that CFs can generate learned, reward-predictive responses that flexibly adapt to the current environment in a context-sensitive manner.

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

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

Specialized connectivity of molecular layer interneuron subtypes leads to disinhibition and synchronous inhibition of cerebellar Purkinje cells.

Molecular layer interneurons (MLIs) account for approximately 80% of the inhibitory interneurons in the cerebellar cortex and are vital to cerebellar processing. MLIs are thought to primarily inhibit Purkinje cells (PCs) and suppress the plasticity of synapses onto PCs. MLIs also inhibit, and are electrically coupled to, other MLIs, but the functional significance of these connections is not known. Here, we find that two recently recognized MLI subtypes, MLI1 and MLI2, have a highly specialized connectivity that allows them to serve distinct functional roles. MLI1s primarily inhibit PCs, are electrically coupled to each other, fire synchronously with other MLI1s on the millisecond timescale in vivo, and synchronously pause PC firing. MLI2s are not electrically coupled, primarily inhibit MLI1s and disinhibit PCs, and are well suited to gating cerebellar-dependent behavior and learning. The synchronous firing of electrically coupled MLI1s and disinhibition provided by MLI2s require a major re-evaluation of cerebellar processing.

Mice lacking Astn2 have ASD-like behaviors and altered cerebellar circuit properties.

Astrotactin 2 (ASTN2) is a transmembrane neuronal protein highly expressed in the cerebellum that functions in receptor trafficking and modulates cerebellar Purkinje cell (PC) synaptic activity. We recently reported a family with a paternally inherited intragenic ASTN2 duplication with a range of neurodevelopmental disorders, including autism spectrum disorder (ASD), learning difficulties, and speech and language delay. To provide a genetic model for the role of the cerebellum in ASD-related behaviors and study the role of ASTN2 in cerebellar circuit function, we generated global and PC-specific conditional Astn2 knockout (KO and cKO, respectively) mouse lines. Astn2 KO mice exhibit strong ASD-related behavioral phenotypes, including a marked decrease in separation-induced pup ultrasonic vocalization calls, hyperactivity and repetitive behaviors, altered social behaviors, and impaired cerebellar-dependent eyeblink conditioning. Hyperactivity and repetitive behaviors were also prominent in Astn2 cKO animals. By Golgi staining, Astn2 KO PCs have region-specific changes in dendritic spine density and filopodia numbers. Proteomic analysis of Astn2 KO cerebellum reveals a marked upregulation of ASTN2 family member, ASTN1, a neuron-glial adhesion protein. Immunohistochemistry and electron microscopy demonstrates a significant increase in Bergmann glia volume in the molecular layer of Astn2 KO animals. Electrophysiological experiments indicate a reduced frequency of spontaneous excitatory postsynaptic currents (EPSCs), as well as increased amplitudes of both spontaneous EPSCs and inhibitory postsynaptic currents (IPSCs) in the Astn2 KO animals, suggesting that pre- and postsynaptic components of synaptic transmission are altered. Thus, ASTN2 regulates ASD-like behaviors and cerebellar circuit properties.

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

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

Cerebellar circuits for disinhibition and synchronous inhibition.

The cerebellar cortex contributes to diverse behaviors by transforming mossy fiber inputs into predictions in the form of Purkinje cell (PC) outputs, and then refining those predictions1. Molecular layer interneurons (MLIs) account for approximately 80% of the inhibitory interneurons in the cerebellar cortex2, and are vital to cerebellar processing1,3. MLIs are thought to primarily inhibit PCs and suppress the plasticity of excitatory synapses onto PCs. MLIs also inhibit, and are electrically coupled to, other MLIs4-7, but the functional significance of these connections is not known1,3. Behavioral studies suggest that cerebellar-dependent learning is gated by disinhibition of PCs, but the source of such disinhibition has not been identified8. Here we find that two recently recognized MLI subtypes2, MLI1 and MLI2, have highly specialized connectivity that allows them to serve very different functional roles. MLI1s primarily inhibit PCs, are electrically coupled to each other, fire synchronously with other MLI1s on the millisecond time scale in vivo, and synchronously pause PC firing. MLI2s are not electrically coupled, they primarily inhibit MLI1s and disinhibit PCs, and are well suited to gating cerebellar-dependent learning8. These findings require a major reevaluation of processing within the cerebellum in which disinhibition, a powerful circuit motif present in the cerebral cortex and elsewhere9-17, greatly increases the computational power and flexibility of the cerebellum. They also suggest that millisecond time scale synchronous firing of electrically-coupled MLI1s helps regulate the output of the cerebellar cortex by synchronously pausing PC firing, which has been shown to evoke precisely-timed firing in PC targets18.

Purkinje-Enriched snRNA-seq in SCA7 Cerebellum Reveals Zebrin Identity Loss as a Central Feature of Polyglutamine Ataxias.

Spinocerebellar ataxia type 7 (SCA7) is an inherited neurodegenerative disorder caused by a CAG-polyglutamine repeat expansion. SCA7 patients display a striking loss of Purkinje cell (PC) neurons with disease progression; however, PCs are rare, making them difficult to characterize. We developed a PC nuclei enrichment protocol and applied it to single-nucleus RNA-seq of a SCA7 knock-in mouse model. Our results unify prior observations into a central mechanism of cell identity loss, impacting both glia and PCs, driving accumulation of inhibitory synapses and altered PC spiking. Zebrin-II subtype dysregulation is the predominant signal in PCs, leading to complete loss of zebrin-II striping at motor symptom onset in SCA7 mice. We show this zebrin-II subtype degradation is shared across Polyglutamine Ataxia mouse models and SCA7 patients. It has been speculated that PC subtype organization is critical for cerebellar function, and our results suggest that a breakdown of zebrin-II parasagittal striping is pathological.

Neocortical disynaptic inhibition requires somatodendritic integration in interneurons.

In his theory of functional polarity, Ramon y Cajal first identified the soma and dendrites as the principal recipient compartments of a neuron and the axon as its main output structure. Despite notable exceptions in other parts of the nervous system (Schoppa and Urban, 2003; Wässle, 2004; Howard et al., 2005), this route of signal propagation has been shown to underlie the functional properties of most neocortical circuits studied so far. Recent evidence, however, suggests that neocortical excitatory cells may trigger the release of the inhibitory neurotransmitter GABA by directly depolarizing the axon terminals of inhibitory interneurons, thus bypassing their somatodendritic compartments (Ren et al., 2007). By using a combination of optical and electrophysiological approaches, we find that synaptically released glutamate fails to trigger GABA release through a direct action on GABAergic terminals under physiological conditions. Rather, our evidence suggests that glutamate triggers GABA release only after somatodendritic depolarization and action potential generation at GABAergic interneurons. These data indicate that neocortical inhibition is recruited by classical somatodendritic integration rather than direct activation of interneuron axon terminals.

Postsynaptic mechanisms govern the differential excitation of cortical neurons by thalamic inputs.

Thalamocortical (TC) afferents relay sensory input to the cortex by making synapses onto both excitatory regular-spiking principal cells (RS cells) and inhibitory fast-spiking interneurons (FS cells). This divergence plays a crucial role in coordinating excitation with inhibition during the earliest steps of somatosensory processing in the cortex. Although the same TC afferents contact both FS and RS cells, FS cells receive larger and faster excitatory inputs from individual TC afferents. Here, we show that this larger thalamic excitation of FS cells occurs via GluR2-lacking AMPA receptors (AMPARs), and results from a fourfold larger quantal amplitude compared with the thalamic inputs onto RS cells. Thalamic afferents also activate NMDA receptors (NMDARs) at synapses onto both cells types, yet RS cell NMDAR currents are slower and pass more current at physiological membrane potentials. Because of these synaptic specializations, GluR2-lacking AMPARs selectively maintain feedforward inhibition of RS cells, whereas NMDARs contribute to the spiking of RS cells and hence to cortical recurrent excitation. Thus, thalamic afferent activity diverges into two routes that rely on unique complements of postsynaptic AMPARs and NMDARs to orchestrate the dynamic balance of excitation and inhibition as sensory input enters the cortex.

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.