High-fidelity transmission of sensory information by single cerebellar mossy fibre boutons

Single-vesicle imaging reveals actin-dependent spatial restriction of vesicles at the active zone, essential for sustained transmission

Synaptic-vesicle (SV) recruitment is thought to maintain reliable neurotransmitter release during high-frequency signaling. However, the mechanism underlying the SV reloading for sustained neurotransmission at central synapses remains unknown. To elucidate this, we performed direct observations of SV reloading and mobility at a single-vesicle level near the plasma membrane in cerebellar mossy fiber terminals using total internal reflection fluorescence microscopy, together with simultaneous recordings of membrane fusion by capacitance measurements. We found that actin disruption abolished the rapid SV recruitment and reduced sustained release. In contrast, induction of actin polymerization and stabilization did not affect vesicle recruitment and release, suggesting that the presence of actin filaments, rather than actin dynamics, was required for the rapid recruitment. Single-particle tracking experiments of quantum dot-labeled vesicles, which allows nanoscale resolution of vesicle mobility, revealed that actin disruption caused vesicles to diffuse more rapidly. Hidden Markov modeling with Bayesian inference revealed that SVs had two diffusion states under normal conditions: free-diffusing and trapped. After disruption of the actin filament, vesicles tended to have only the free-diffusing state. F-actin staining showed that actin filaments were localized outside the active zones (AZs) and surrounded some SV trajectories. Perturbation of SV mobility, possibly through interference with biomolecular condensates, also suggested that the restricted diffusion state determined the rate of SV recruitment. We propose that actin filaments confined SVs near the AZ to achieve rapid and efficient recruitment followed by priming and sustained synaptic transmission.

Neuronal Nitric Oxide Synthase Regulates Cerebellar Parallel Fiber Slow EPSC in Purkinje Neurons by Modulating STIM1-Gated TRPC3-Containing Channels

Responding to burst stimulation of parallel fibers (PFs), cerebellar Purkinje neurons (PNs) generate a convolved synaptic response displaying a fast excitatory postsynaptic current (EPSCFast) followed by a slow EPSC (EPSCSlow). The latter is companied with a rise of intracellular Ca2+ and critical for motor coordination. The genesis of EPSCSlow in PNs results from activation of metabotropic type 1 glutamate receptor (mGluR1), oligomerization of stromal interaction molecule 1 (STIM1) on the membrane of endoplasmic reticulum (ER) and opening of transient receptor potential canonical 3 (TRPC3) channels on the plasma membrane. Neuronal nitric oxide synthase (nNOS) is abundantly expressed in PFs and granule neurons (GNs), catalyzing the production of nitric oxide (NO) hence regulating PF-PN synaptic function. We recently found that nNOS/NO regulates the morphological development of PNs through mGluR1-regulated Ca2+-dependent mechanism. This study investigated the role of nNOS/NO in regulating EPSCSlow. Electrophysiological analyses showed that EPSCSlow in cerebellar slices of nNOS knockout (nNOS-/-) mice was significantly larger than that in wildtype (WT) mice. Activation of mGluR1 in cultured PNs from nNOS-/- mice evoked larger TRPC3-channel mediated currents and intracellular Ca2+ rise than that in PNs from WT mice. In addition, nNOS inhibitor and NO-donor increased and decreased, respectively, the TRPC3-current and Ca2+ rise in PNs. Moreover, the NO-donor effectively decreased TRPC3 currents in HEK293 cells expressing WT STIM1, but not cells expressing a STIM1 with cysteine mutants. These novel findings indicate that nNOS/NO inhibits TRPC3-containig channel mediated cation influx during EPSCSlow, at least in part, by S-nitrosylation of STIM1.

Realistic mossy fiber input patterns to unipolar brush cells evoke a continuum of temporal responses comprised of components mediated by different glutamate receptors

Unipolar brush cells (UBCs) are excitatory interneurons in the cerebellar cortex that receive mossy fiber (MF) inputs and excite granule cells. The UBC population responds to brief burst activation of MFs with a continuum of temporal transformations, but it is not known how UBCs transform the diverse range of MF input patterns that occur in vivo. Here we use cell-attached recordings from UBCs in acute cerebellar slices to examine responses to MF firing patterns that are based on in vivo recordings. We find that MFs evoke a continuum of responses in the UBC population, mediated by three different types of glutamate receptors that each convey a specialized component. AMPARs transmit timing information for single stimuli at up to 5 spikes/s, and for very brief bursts. A combination of mGluR2/3s (inhibitory) and mGluR1s (excitatory) mediates a continuum of delayed, and broadened responses to longer bursts, and to sustained high frequency activation. Variability in the mGluR2/3 component controls the time course of the onset of firing, and variability in the mGluR1 component controls the duration of prolonged firing. We conclude that the combination of glutamate receptor types allows each UBC to simultaneously convey different aspects of MF firing. These findings establish that UBCs are highly flexible circuit elements that provide diverse temporal transformations that are well suited to contribute to specialized processing in different regions of the cerebellar cortex.

Neural circuit basis of placebo pain relief

Placebo effects are notable demonstrations of mind-body interactions1,2. During pain perception, in the absence of any treatment, an expectation of pain relief can reduce the experience of pain-a phenomenon known as placebo analgesia3-6. However, despite the strength of placebo effects and their impact on everyday human experience and the failure of clinical trials for new therapeutics7, the neural circuit basis of placebo effects has remained unclear. Here we show that analgesia from the expectation of pain relief is mediated by rostral anterior cingulate cortex (rACC) neurons that project to the pontine nucleus (rACC→Pn)-a precerebellar nucleus with no established function in pain. We created a behavioural assay that generates placebo-like anticipatory pain relief in mice. In vivo calcium imaging of neural activity and electrophysiological recordings in brain slices showed that expectations of pain relief boost the activity of rACC→Pn neurons and potentiate neurotransmission in this pathway. Transcriptomic studies of Pn neurons revealed an abundance of opioid receptors, further suggesting a role in pain modulation. Inhibition of the rACC→Pn pathway disrupted placebo analgesia and decreased pain thresholds, whereas activation elicited analgesia in the absence of placebo conditioning. Finally, Purkinje cells exhibited activity patterns resembling those of rACC→Pn neurons during pain-relief expectation, providing cellular-level evidence for a role of the cerebellum in cognitive pain modulation. These findings open the possibility of targeting this prefrontal cortico-ponto-cerebellar pathway with drugs or neurostimulation to treat pain.

Purkinje cell models: past, present and future

The investigation of the dynamics of Purkinje cell (PC) activity is crucial to unravel the role of the cerebellum in motor control, learning and cognitive processes. Within the cerebellar cortex (CC), these neurons receive all the incoming sensory and motor information, transform it and generate the entire cerebellar output. The relatively homogenous and repetitive structure of the CC, common to all vertebrate species, suggests a single computation mechanism shared across all PCs. While PC models have been developed since the 70's, a comprehensive review of contemporary models is currently lacking. Here, we provide an overview of PC models, ranging from the ones focused on single cell intracellular PC dynamics, through complex models which include synaptic and extrasynaptic inputs. We review how PC models can reproduce physiological activity of the neuron, including firing patterns, current and multistable dynamics, plateau potentials, calcium signaling, intrinsic and synaptic plasticity and input/output computations. We consider models focusing both on somatic and on dendritic computations. Our review provides a critical performance analysis of PC models with respect to known physiological data. We expect our synthesis to be useful in guiding future development of computational models that capture real-life PC dynamics in the context of cerebellar computations.

Decoding state-dependent cortical-cerebellar cellular functional connectivity in the mouse brain

The cortex and cerebellum form multi-synaptic reciprocal connections. We investigate the functional connectivity between single spiking cerebellar neurons and the population activity of the mouse dorsal cortex using mesoscale imaging. Cortical representations of individual cerebellar neurons vary significantly across different brain states but are drawn from a common set of cortical networks. These cortical-cerebellar connectivity features are observed in mossy fibers and Purkinje cells as well as neurons in different cerebellar lobules, albeit with variations across cell types and regions. Complex spikes of Purkinje cells preferably associate with the sensorimotor cortex, whereas simple spikes display more diverse cortical connectivity patterns. The spontaneous functional connectivity patterns align with cerebellar neurons' functional responses to external stimuli in a modality-specific manner. The tuning properties of subsets of cerebellar neurons differ between anesthesia and awake states, mirrored by state-dependent changes in their long-range functional connectivity patterns with mesoscale cortical activity.

Simple spike patterns and synaptic mechanisms encoding sensory and motor signals in Purkinje cells and the cerebellar nuclei

Whisker stimulation in awake mice evokes transient suppression of simple spike probability in crus I/II Purkinje cells. Here, we investigated how simple spike suppression arises synaptically, what it encodes, and how it affects cerebellar output. In vitro, monosynaptic parallel fiber (PF)-excitatory postsynaptic currents (EPSCs) facilitated strongly, whereas disynaptic inhibitory postsynaptic currents (IPSCs) remained stable, maximizing relative inhibitory strength at the onset of PF activity. Short-term plasticity thus favors the inhibition of Purkinje spikes before PFs facilitate. In vivo, whisker stimulation evoked a 2-6 ms synchronous spike suppression, just 6-8 ms (∼4 synaptic delays) after sensory onset, whereas active whisker movements elicited broadly timed spike rate increases that did not modulate sensory-evoked suppression. Firing in the cerebellar nuclei (CbN) inversely correlated with disinhibition from sensory-evoked simple spike suppressions but was decoupled from slow, non-synchronous movement-associated elevations of Purkinje firing rates. Synchrony thus allows the CbN to high-pass filter Purkinje inputs, facilitating sensory-evoked cerebellar outputs that can drive movements.

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.

Mesoscale simulations predict the role of synergistic cerebellar plasticity during classical eyeblink conditioning

According to the motor learning theory by Albus and Ito, synaptic depression at the parallel fibre to Purkinje cells synapse (pf-PC) is the main substrate responsible for learning sensorimotor contingencies under climbing fibre control. However, recent experimental evidence challenges this relatively monopolistic view of cerebellar learning. Bidirectional plasticity appears crucial for learning, in which different microzones can undergo opposite changes of synaptic strength (e.g. downbound microzones-more likely depression, upbound microzones-more likely potentiation), and multiple forms of plasticity have been identified, distributed over different cerebellar circuit synapses. Here, we have simulated classical eyeblink conditioning (CEBC) using an advanced spiking cerebellar model embedding downbound and upbound modules that are subject to multiple plasticity rules. Simulations indicate that synaptic plasticity regulates the cascade of precise spiking patterns spreading throughout the cerebellar cortex and cerebellar nuclei. CEBC was supported by plasticity at the pf-PC synapses as well as at the synapses of the molecular layer interneurons (MLIs), but only the combined switch-off of both sites of plasticity compromised learning significantly. By differentially engaging climbing fibre information and related forms of synaptic plasticity, both microzones contributed to generate a well-timed conditioned response, but it was the downbound module that played the major role in this process. The outcomes of our simulations closely align with the behavioural and electrophysiological phenotypes of mutant mice suffering from cell-specific mutations that affect processing of their PC and/or MLI synapses. Our data highlight that a synergy of bidirectional plasticity rules distributed across the cerebellum can facilitate finetuning of adaptive associative behaviours at a high spatiotemporal resolution.

Patch-seq: Advances and Biological Applications

Multimodal analysis of gene-expression patterns, electrophysiological properties, and morphological phenotypes at the single-cell/single-nucleus level has been arduous because of the diversity and complexity of neurons. The emergence of Patch-sequencing (Patch-seq) directly links transcriptomics, morphology, and electrophysiology, taking neuroscience research to a multimodal era. In this review, we summarized the development of Patch-seq and recent applications in the cortex, hippocampus, and other nervous systems. Through generating multimodal cell type atlases, targeting specific cell populations, and correlating transcriptomic data with phenotypic information, Patch-seq has provided new insight into outstanding questions in neuroscience. We highlight the challenges and opportunities of Patch-seq in neuroscience and hope to shed new light on future neuroscience research.

How Merkel cells transduce mechanical stimuli: A biophysical model of Merkel cells

Merkel cells combine with Aβ afferents, producing slowly adapting type 1(SA1) responses to mechanical stimuli. However, how Merkel cells transduce mechanical stimuli into neural signals to Aβ afferents is still unclear. Here we develop a biophysical model of Merkel cells for mechanical transduction by incorporating main ingredients such as Ca2+ and K+ voltage-gated channels, Piezo2 channels, internal Ca2+ stores, neurotransmitters release, and cell deformation. We first validate our model with several experiments. Then we reveal that Ca2+ and K+ channels on the plasma membrane shape the depolarization of membrane potentials, further regulating the Ca2+ transients in the cells. We also show that Ca2+ channels on the plasma membrane mainly inspire the Ca2+ transients, while internal Ca2+ stores mainly maintain the Ca2+ transients. Moreover, we show that though Piezo2 channels are rapidly adapting mechanical-sensitive channels, they are sufficient to inspire sustained Ca2+ transients in Merkel cells, which further induce the release of neurotransmitters for tens of seconds. Thus our work provides a model that captures the membrane potentials and Ca2+ transients features of Merkel cells and partly explains how Merkel cells transduce the mechanical stimuli by Piezo2 channels.

Mesotrode chronic simultaneous mesoscale cortical imaging and subcortical or peripheral nerve spiking activity recording in mice

Brain function originates from hierarchical spatial-temporal neural dynamics distributed across cortical and subcortical networks. However, techniques available to assess large-scale brain network activity with single-neuron resolution in behaving animals remain limited. Here, we present Mesotrode that integrates chronic wide-field mesoscale cortical imaging and compact multi-site cortical/subcortical cellular electrophysiology in head-fixed mice that undergo self-initiated running or orofacial movements. Specifically, we harnessed the flexibility of chronic multi-site tetrode recordings to monitor single-neuron activity in multiple subcortical structures while simultaneously imaging the mesoscale activity of the entire dorsal cortex. A mesoscale spike-triggered averaging procedure allowed the identification of cortical activity motifs preferentially associated with single-neuron spiking. Using this approach, we were able to characterize chronic single-neuron-related functional connectivity maps for up to 60 days post-implantation. Neurons recorded from distinct subcortical structures display diverse but segregated cortical maps, suggesting that neurons of different origins participate in distinct cortico-subcortical pathways. We extended the capability of Mesotrode by implanting the micro-electrode at the facial motor nerve and found that facial nerve spiking is functionally associated with the PTA, RSP, and M2 network, and optogenetic inhibition of the PTA area significantly reduced the facial movement of the mice. These findings demonstrate that Mesotrode can be used to sample different combinations of cortico-subcortical networks over prolonged periods, generating multimodal and multi-scale network activity from a single implant, offering new insights into the neural mechanisms underlying specific behaviors.

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.

Long-Term Synaptic Plasticity Tunes the Gain of Information Channels through the Cerebellum Granular Layer

A central hypothesis on brain functioning is that long-term potentiation (LTP) and depression (LTD) regulate the signals transfer function by modifying the efficacy of synaptic transmission. In the cerebellum, granule cells have been shown to control the gain of signals transmitted through the mossy fiber pathway by exploiting synaptic inhibition in the glomeruli. However, the way LTP and LTD control signal transformation at the single-cell level in the space, time and frequency domains remains unclear. Here, the impact of LTP and LTD on incoming activity patterns was analyzed by combining patch-clamp recordings in acute cerebellar slices and mathematical modeling. LTP reduced the delay, increased the gain and broadened the frequency bandwidth of mossy fiber burst transmission, while LTD caused opposite changes. These properties, by exploiting NMDA subthreshold integration, emerged from microscopic changes in spike generation in individual granule cells such that LTP anticipated the emission of spikes and increased their number and precision, while LTD sorted the opposite effects. Thus, akin with the expansion recoding process theoretically attributed to the cerebellum granular layer, LTP and LTD could implement selective filtering lines channeling information toward the molecular and Purkinje cell layers for further processing.

Model simulations unveil the structure-function-dynamics relationship of the cerebellar cortical microcircuit

The cerebellar network is renowned for its regular architecture that has inspired foundational computational theories. However, the relationship between circuit structure, function and dynamics remains elusive. To tackle the issue, we developed an advanced computational modeling framework that allows us to reconstruct and simulate the structure and function of the mouse cerebellar cortex using morphologically realistic multi-compartmental neuron models. The cerebellar connectome is generated through appropriate connection rules, unifying a collection of scattered experimental data into a coherent construct and providing a new model-based ground-truth about circuit organization. Naturalistic background and sensory-burst stimulation are used for functional validation against recordings in vivo, monitoring the impact of cellular mechanisms on signal propagation, inhibitory control, and long-term synaptic plasticity. Our simulations show how mossy fibers entrain the local neuronal microcircuit, boosting the formation of columns of activity travelling from the granular to the molecular layer providing a new resource for the investigation of local microcircuit computation and of the neural correlates of behavior.

Computational models of neurotransmission at cerebellar synapses unveil the impact on network computation

The neuroscientific field benefits from the conjoint evolution of experimental and computational techniques, allowing for the reconstruction and simulation of complex models of neurons and synapses. Chemical synapses are characterized by presynaptic vesicle cycling, neurotransmitter diffusion, and postsynaptic receptor activation, which eventually lead to postsynaptic currents and subsequent membrane potential changes. These mechanisms have been accurately modeled for different synapses and receptor types (AMPA, NMDA, and GABA) of the cerebellar cortical network, allowing simulation of their impact on computation. Of special relevance is short-term synaptic plasticity, which generates spatiotemporal filtering in local microcircuits and controls burst transmission and information flow through the network. Here, we present how data-driven computational models recapitulate the properties of neurotransmission at cerebellar synapses. The simulation of microcircuit models is starting to reveal how diverse synaptic mechanisms shape the spatiotemporal profiles of circuit activity and computation.

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.

Non-Linear Frequency Dependence of Neurovascular Coupling in the Cerebellar Cortex Implies Vasodilation-Vasoconstriction Competition

Neurovascular coupling (NVC) is the process associating local cerebral blood flow (CBF) to neuronal activity (NA). Although NVC provides the basis for the blood oxygen level dependent (BOLD) effect used in functional MRI (fMRI), the relationship between NVC and NA is still unclear. Since recent studies reported cerebellar non-linearities in BOLD signals during motor tasks execution, we investigated the NVC/NA relationship using a range of input frequencies in acute mouse cerebellar slices of vermis and hemisphere. The capillary diameter increased in response to mossy fiber activation in the 6-300 Hz range, with a marked inflection around 50 Hz (vermis) and 100 Hz (hemisphere). The corresponding NA was recorded using high-density multi-electrode arrays and correlated to capillary dynamics through a computational model dissecting the main components of granular layer activity. Here, NVC is known to involve a balance between the NMDAR-NO pathway driving vasodilation and the mGluRs-20HETE pathway driving vasoconstriction. Simulations showed that the NMDAR-mediated component of NA was sufficient to explain the time course of the capillary dilation but not its non-linear frequency dependence, suggesting that the mGluRs-20HETE pathway plays a role at intermediate frequencies. These parallel control pathways imply a vasodilation-vasoconstriction competition hypothesis that could adapt local hemodynamics at the microscale bearing implications for fMRI signals interpretation.

Discovering Microcircuit Secrets With Multi-Spot Imaging and Electrophysiological Recordings: The Example of Cerebellar Network Dynamics

The cerebellar cortex microcircuit is characterized by a highly ordered neuronal architecture having a relatively simple and stereotyped connectivity pattern. For a long time, this structural simplicity has incorrectly led to the idea that anatomical considerations would be sufficient to understand the dynamics of the underlying circuitry. However, recent experimental evidence indicates that cerebellar operations are much more complex than solely predicted by anatomy, due to the crucial role played by neuronal and synaptic properties. To be able to explore neuronal and microcircuit dynamics, advanced imaging, electrophysiological techniques and computational models have been combined, allowing us to investigate neuronal ensembles activity and to connect microscale to mesoscale phenomena. Here, we review what is known about cerebellar network organization, neural dynamics and synaptic plasticity and point out what is still missing and would require experimental assessments. We consider the available experimental techniques that allow a comprehensive assessment of circuit dynamics, including voltage and calcium imaging and extracellular electrophysiological recordings with multi-electrode arrays (MEAs). These techniques are proving essential to investigate the spatiotemporal pattern of activity and plasticity in the cerebellar network, providing new clues on how circuit dynamics contribute to motor control and higher cognitive functions.

Heterogeneity of glutamatergic synapses: cellular mechanisms and network consequences

Chemical synapses are commonly known as a structurally and functionally highly diverse class of cell-cell contacts specialized to mediate communication between neurons. They represent the smallest "computational" unit of the brain and are typically divided into excitatory and inhibitory as well as modulatory categories. These categories are subdivided into diverse types, each representing a different structure-function repertoire that in turn are thought to endow neuronal networks with distinct computational properties. The diversity of structure and function found among a given category of synapses is referred to as heterogeneity. The main building blocks for this heterogeneity are synaptic vesicles, the active zone, the synaptic cleft, the postsynaptic density, and glial processes associated with the synapse. Each of these five structural modules entails a distinct repertoire of functions, and their combination specifies the range of functional heterogeneity at mammalian excitatory synapses, which are the focus of this review. We describe synapse heterogeneity that is manifested on different levels of complexity ranging from the cellular morphology of the pre- and postsynaptic cells toward the expression of different protein isoforms at individual release sites. We attempt to define the range of structural building blocks that are used to vary the basic functional repertoire of excitatory synaptic contacts and discuss sources and general mechanisms of synapse heterogeneity. Finally, we explore the possible impact of synapse heterogeneity on neuronal network function.

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.

Using ephaptic coupling to estimate the synaptic cleft resistivity of the calyx of Held synapse

At synapses, the pre- and postsynaptic cells get so close that currents entering the cleft do not flow exclusively along its conductance, gcl. A prominent example is found in the calyx of Held synapse in the medial nucleus of the trapezoid body (MNTB), where the presynaptic action potential can be recorded in the postsynaptic cell in the form of a prespike. Here, we developed a theoretical framework for ephaptic coupling via the synaptic cleft, and we tested its predictions using the MNTB prespike recorded in voltage-clamp. The shape of the prespike is predicted to resemble either the first or the second derivative of the inverted presynaptic action potential if cleft currents dissipate either mostly capacitively or resistively, respectively. We found that the resistive dissipation scenario provided a better description of the prespike shape. Its size is predicted to scale with the fourth power of the radius of the synapse, explaining why intracellularly recorded prespikes are uncommon in the central nervous system. We show that presynaptic calcium currents also contribute to the prespike shape. This calcium prespike resembled the first derivative of the inverted calcium current, again as predicted by the resistive dissipation scenario. Using this calcium prespike, we obtained an estimate for gcl of ~1 μS. We demonstrate that, for a circular synapse geometry, such as in conventional boutons or the immature calyx of Held, gcl is scale-invariant and only defined by extracellular resistivity, which was ~75 Ωcm, and by cleft height. During development the calyx of Held develops fenestrations. We show that these fenestrations effectively minimize the cleft potentials generated by the adult action potential, which might otherwise interfere with calcium channel opening. We thus provide a quantitative account of the dissipation of currents by the synaptic cleft, which can be readily extrapolated to conventional, bouton-like synapses.

Cerebellar granule cell axons support high-dimensional representations

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

GluA4 facilitates cerebellar expansion coding and enables associative memory formation

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

Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses

Rigorous investigation of synaptic transmission requires analysis of unitary synaptic events by simultaneous recording from presynaptic terminals and postsynaptic target neurons. However, this has been achieved at only a limited number of model synapses, including the squid giant synapse and the mammalian calyx of Held. Cortical presynaptic terminals have been largely inaccessible to direct presynaptic recording, due to their small size. Here, we describe a protocol for improved subcellular patch-clamp recording in rat and mouse brain slices, with the synapse in a largely intact environment. Slice preparation takes ~2 h, recording ~3 h and post hoc morphological analysis 2 d. Single presynaptic hippocampal mossy fiber terminals are stimulated minimally invasively in the bouton-attached configuration, in which the cytoplasmic content remains unperturbed, or in the whole-bouton configuration, in which the cytoplasmic composition can be precisely controlled. Paired pre-postsynaptic recordings can be integrated with biocytin labeling and morphological analysis, allowing correlative investigation of synapse structure and function. Paired recordings can be obtained from mossy fiber terminals in slices from both rats and mice, implying applicability to genetically modified synapses. Paired recordings can also be performed together with axon tract stimulation or optogenetic activation, allowing comparison of unitary and compound synaptic events in the same target cell. Finally, paired recordings can be combined with spontaneous event analysis, permitting collection of miniature events generated at a single identified synapse. In conclusion, the subcellular patch-clamp techniques detailed here should facilitate analysis of biophysics, plasticity and circuit function of cortical synapses in the mammalian central nervous system.

Accounting for uncertainty: inhibition for neural inference in the cerebellum

Sensorimotor coordination is thought to rely on cerebellar-based internal models for state estimation, but the underlying neural mechanisms and specific contribution of the cerebellar components is unknown. A central aspect of any inferential process is the representation of uncertainty or conversely precision characterizing the ensuing estimates. Here, we discuss the possible contribution of inhibition to the encoding of precision of neural representations in the granular layer of the cerebellar cortex. Within this layer, Golgi cells influence excitatory granule cells, and their action is critical in shaping information transmission downstream to Purkinje cells. In this review, we equate the ensuing excitation-inhibition balance in the granular layer with the outcome of a precision-weighted inferential process, and highlight the physiological characteristics of Golgi cell inhibition that are consistent with such computations.

Kilohertz-frequency stimulation of the nervous system: A review of underlying mechanisms

BACKGROUND

Electrical stimulation in the kilohertz-frequency range has gained interest in the field of neuroscience. The mechanisms underlying stimulation in this frequency range, however, are poorly characterized to date.

OBJECTIVE/HYPOTHESIS

To summarize the manifold biological effects elicited by kilohertz-frequency stimulation in the context of the currently existing literature and provide a mechanistic framework for the neural responses observed in this frequency range.

METHODS

A comprehensive search of the peer-reviewed literature was conducted across electronic databases. Relevant computational, clinical, and mechanistic studies were selected for review.

RESULTS

The effects of kilohertz-frequency stimulation on neural tissue are diverse and yield effects that are distinct from conventional stimulation. Broadly, these can be divided into 1) subthreshold, 2) suprathreshold, 3) synaptic and 4) thermal effects. While facilitation is the dominating mechanism at the subthreshold level, desynchronization, spike-rate adaptation, conduction block, and non-monotonic activation can be observed during suprathreshold kilohertz-frequency stimulation. At the synaptic level, kilohertz-frequency stimulation has been associated with the transient depletion of the available neurotransmitter pool - also known as synaptic fatigue. Finally, thermal effects associated with extrinsic (environmental) and intrinsic (associated with kilohertz-frequency stimulation) temperature changes have been suggested to alter the neural response to stimulation paradigms.

CONCLUSION

The diverse spectrum of neural responses to stimulation in the kilohertz-frequency range is distinct from that associated with conventional stimulation. This offers the potential for new therapeutic avenues across stimulation modalities. However, stimulation in the kilohertz-frequency range is associated with distinct challenges and caveats that need to be considered in experimental paradigms.

In Vivo Whole-Cell Patch-Clamp Methods: Recent Technical Progress and Future Perspectives

Brain functions are fundamental for the survival of organisms, and they are supported by neural circuits consisting of a variety of neurons. To investigate the function of neurons at the single-cell level, researchers often use whole-cell patch-clamp recording techniques. These techniques enable us to record membrane potentials (including action potentials) of individual neurons of not only anesthetized but also actively behaving animals. This whole-cell recording method enables us to reveal how neuronal activities support brain function at the single-cell level. In this review, we introduce previous studies using in vivo patch-clamp recording techniques and recent findings primarily regarding neuronal activities in the hippocampus for behavioral function. We further discuss how we can bridge the gap between electrophysiology and biochemistry.

Intersectin-Mediated Clearance of SNARE Complexes Is Required for Fast Neurotransmission

The rapid replenishment of release-ready synaptic vesicles (SVs) at a limiting number of presynaptic release sites is required to sustain high-frequency neurotransmission in CNS neurons. Failure to clear release sites from previously exocytosed material has been shown to impair vesicle replenishment and, therefore, fast neurotransmission. The identity of this material and the machinery that removes it from release sites have remained enigmatic. Here we show that the endocytic scaffold protein intersectin 1 clears release sites by direct SH3 domain-mediated association with a non-canonical proline-rich segment of synaptobrevin assembled into the SNARE complex for neuroexocytosis. Acute structure-based or sustained genetic interference with SNARE complex recognition by intersectin 1 causes a rapid stimulation frequency-dependent depression of neurotransmission due to impaired replenishment of release-ready SVs. These findings identify a key molecular mechanism that underlies exo-endocytic coupling during fast neurotransmitter release at central synapses.

How and Why the Cerebellum Recodes Input Signals: An Alternative to Machine Learning

Mossy fiber input to the cerebellum is received by granule cells where it is thought to be recoded into internal signals received by Purkinje cells, which alone carry the output of the cerebellar cortex. In any neural network, variables are contained in groups of signals as well as signals themselves—which cells are active and how many, for example, and statistical variables coded in rates, such as the mean and range, and which rates are strongly represented, in a defined population. We argue that the primary function of recoding is to confine translation to an effect of some variables and not others—both where input is recoded into internal signals and the translation downstream of internal signals into an effect on Purkinje cells. The cull of variables is harsh. Internal signaling is group coded. This allows coding to exploit statistics for a reliable and precise effect despite needing to work with high-dimensional input which is a highly unpredictably variable. An important effect is to normalize eclectic input signals, so that the basic, repeating cerebellar circuit, preserved across taxa, does not need to specialize (within regional variations). With this model, there is no need to slavishly conserve or compute data coded in single signals. If we are correct, a learning algorithm—for years, a mainstay of cerebellar modeling—would be redundant.

Increased responsiveness at the cerebellar input stage in the PRRT2 knockout model of paroxysmal kinesigenic dyskinesia

PRoline-Rich Transmembrane protein-2 (PRRT2) is a recently described neuron-specific type-2 integral membrane protein with a large cytosolic N-terminal domain that distributes in presynaptic and axonal domains where it interacts with several presynaptic proteins and voltage-gated Na⁺ channels. Several PRRT2 mutations are the main cause of a wide and heterogeneous spectrum of paroxysmal disorders with a loss-of-function pathomechanism. The highest expression levels of PRRT2 in brain occurs in cerebellar granule cells (GCs) and cerebellar dysfunctions participate in the dyskinetic phenotype of PRRT2 knockout (KO) mice. We have investigated the effects of PRRT2 deficiency on the intrinsic excitability of GCs and the input-output relationships at the mossy fiber-GC synapses. We show that PRRT2 KO primary GCs display increased expression of Na⁺ channels, increased amplitude of Na⁺ currents and increased length of the axon initial segment, leading to an overall enhancement of intrinsic excitability. In acute PRRT2 KO cerebellar slices, GCs were more prone to action potential discharge in response to mossy fiber activation and exhibited an enhancement of transient and persistent Na⁺ currents, in the absence of changes at the mossy fiber-GC synapses. The results support a key role of PRRT2 expressed in GCs in the physiological regulation of the excitatory input to the cerebellum and are consistent with a major role of a cerebellar dysfunction in the pathogenesis of the PRRT2-linked paroxysmal pathologies.

A rapid whisker-based decision underlying skilled locomotion in mice

Skilled motor behavior requires rapidly integrating external sensory input with information about internal state to decide which movements to make next. Using machine learning approaches for high-resolution kinematic analysis, we uncover the logic of a rapid decision underlying sensory-guided locomotion in mice. After detecting obstacles with their whiskers mice select distinct kinematic strategies depending on a whisker-derived estimate of obstacle location together with the position and velocity of their body. Although mice rely on whiskers for obstacle avoidance, lesions of primary whisker sensory cortex had minimal impact. While motor cortex manipulations affected the execution of the chosen strategy, the decision-making process remained largely intact. These results highlight the potential of machine learning for reductionist analysis of naturalistic behaviors and provide a case in which subcortical brain structures appear sufficient for mediating a relatively sophisticated sensorimotor decision.

Intrinsic plasticity of cerebellar stellate cells is mediated by NMDA receptor regulation of voltage-gated Na+ channels

KEY POINTS

We show that NMDA receptors (NMDARs) elicit a long-term increase in the firing rates of inhibitory stellate cells of the cerebellum NMDARs induce intrinsic plasticity through a Ca²⁺ - and CaMKII-dependent pathway that drives shifts in the activation and inactivation properties of voltage-gated Na⁺ (Na_v ) channels An identical Ca²⁺ - and CaMKII-dependent signalling pathway is triggered during whole-cell recording which lowers the action potential threshold by causing a hyperpolarizing shift in the gating properties of Na_v channels. Our findings open the more general possibility that NMDAR-mediated intrinsic plasticity found in other cerebellar neurons may involve similar shifts in Na_v channel gating.

ABSTRACT

Memory storage in the mammalian brain is mediated not only by long-lasting changes in the efficacy of neurotransmitter receptors but also by long-term modifications to the activity of voltage-gated ion channels. Activity-dependent plasticity of voltage-gated ion channels, or intrinsic plasticity, is found throughout the brain in virtually all neuronal types, including principal cells and interneurons. Although intrinsic plasticity has been identified in neurons of the cerebellum, it has yet to be studied in inhibitory cerebellar stellate cells of the molecular layer which regulate activity outflow from the cerebellar cortex by feedforward inhibition onto Purkinje cells. The study of intrinsic plasticity in stellate cells has been particularly challenging as membrane patch breakthrough in electrophysiology experiments unintentionally triggers changes in spontaneous firing rates. Using cell-attached patch recordings to avoid disruption, we show that activation of extrasynaptic N-methyl-d-aspartate receptors (NMDARs) elicits a long-term increase in the firing properties of stellate cells by stimulating a rise in cytosolic Ca²⁺ and activation of Ca²⁺/calmodulin-dependent protein kinase II (CaMKII). An identical signalling pathway is triggered during whole-cell recording which lowers the action potential threshold by causing a hyperpolarizing shift in the gating properties of voltage-gated sodium (Na_v ) channels. Together, our findings identify an unappreciated role of Na_v channel-dependent intrinsic plasticity in cerebellar stellate cells which, in concert with non-canonical NMDAR signalling, provides the cerebellum with an unconventional mechanism to fine-tune motor behaviour.

Cellular-resolution mapping uncovers spatial adaptive filtering at the rat cerebellum input stage

Long-term synaptic plasticity is thought to provide the substrate for adaptive computation in brain circuits but very little is known about its spatiotemporal organization. Here, we combined multi-spot two-photon laser microscopy in rat cerebellar slices with realistic modeling to map the distribution of plasticity in multi-neuronal units of the cerebellar granular layer. The units, composed by ~300 neurons activated by ~50 mossy fiber glomeruli, showed long-term potentiation concentrated in the core and long-term depression in the periphery. This plasticity was effectively accounted for by an NMDA receptor and calcium-dependent induction rule and was regulated by the inhibitory Golgi cell loops. Long-term synaptic plasticity created effective spatial filters tuning the time-delay and gain of spike retransmission at the cerebellum input stage and provided a plausible basis for the spatiotemporal recoding of input spike patterns anticipated by the motor learning theory.

Casali, Tognolina et al. use two-photon laser microscopy to spatially map long-term synaptic plasticity in rat cerebellar granular cells following stimulation of mossy fibers. Their data allow them to apply realistic modeling to test hypotheses about the synaptic spiking dynamics and reveal the importance of synaptic inhibition to defining these microcircuits.

Presynaptic PRRT2 Deficiency Causes Cerebellar Dysfunction and Paroxysmal Kinesigenic Dyskinesia

PRRT2 loss-of-function mutations have been associated with familial paroxysmal kinesigenic dyskinesia (PKD), infantile convulsions and choreoathetosis, and benign familial infantile seizures. Dystonia is the foremost involuntary movement disorder manifest by patients with PKD. Using a lacZ reporter and quantitative reverse-transcriptase PCR, we mapped the temporal and spatial distribution of Prrt2 in mouse brain and showed the highest levels of expression in cerebellar cortex. Further investigation into PRRT2 localization within the cerebellar cortex revealed that Prrt2 transcripts reside in granule cells but not Purkinje cells or interneurons within cerebellar cortex, and PRRT2 is presynaptically localized in the molecular layer. Analysis of synapses in the cerebellar molecular layer via electron microscopy showed that Prrt2^-/- mice have increased numbers of docked vesicles but decreased vesicle numbers overall. In addition to impaired performance on several motor tasks, approximately 5% of Prrt2^-/- mice exhibited overt PKD with clear face validity manifest as dystonia. In Prrt2 mutants, we found reduced parallel fiber facilitation at parallel fiber-Purkinje cell synapses, reduced Purkinje cell excitability, and normal cerebellar nuclear excitability, establishing a potential mechanism by which altered cerebellar activity promotes disinhibition of the cerebellar nuclei, driving motor abnormalities in PKD. Overall, our findings replicate, refine, and expand upon previous work with PRRT2 mouse models, contribute to understanding of paroxysmal disorders of the nervous system, and provide mechanistic insight into the role of cerebellar cortical dysfunction in dystonia.

Multiple signals evoked by unisensory stimulation converge onto cerebellar granule and Purkinje cells in mice

The cerebellum receives signals directly from peripheral sensory systems and indirectly from the neocortex. Even a single tactile stimulus can activate both of these pathways. Here we report how these different types of signals are integrated in the cerebellar cortex. We used in vivo whole-cell recordings from granule cells and unit recordings from Purkinje cells in mice in which primary somatosensory cortex (S1) could be optogenetically inhibited. Tactile stimulation of the upper lip produced two-phase granule cell responses (with latencies of ~8 ms and 29 ms), for which only the late phase was S1 dependent. In Purkinje cells, complex spikes and the late phase of simple spikes were S1 dependent. These results indicate that individual granule cells combine convergent inputs from the periphery and neocortex and send their outputs to Purkinje cells, which then integrate those signals with climbing fiber signals from the neocortex.

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

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

Direct imaging of rapid tethering of synaptic vesicles accompanying exocytosis at a fast central synapse

A high rate of synaptic vesicle (SV) release is required at cerebellar mossy fiber terminals for rapid information processing. As the number of release sites is limited, fast SV reloading is necessary to achieve sustained release. However, rapid reloading has not been observed directly. Here, we visualize SV movements near presynaptic membrane using total internal reflection fluorescence (TIRF) microscopy. Upon stimulation, SVs appeared in the TIRF-field and became tethered to the presynaptic membrane with unexpectedly rapid time course, almost as fast as SVs disappeared due to release. However, such stimulus-induced tethering was abolished by inhibiting exocytosis, suggesting that the tethering is tightly coupled to preceding exocytosis. The newly tethered vesicles became fusion competent not immediately but only 300 ms to 400 ms after tethering. Together with model simulations, we propose that rapid tethering leads to an immediate filling of vacated spaces and release sites within <100 nm of the active zone by SVs, which serve as precursors of readily releasable vesicles, thereby shortening delays during sustained activity.

Short-Term Plasticity at Hippocampal Mossy Fiber Synapses Is Induced by Natural Activity Patterns and Associated with Vesicle Pool Engram Formation

Post-tetanic potentiation (PTP) is an attractive candidate mechanism for hippocampus-dependent short-term memory. Although PTP has a uniquely large magnitude at hippocampal mossy fiber-CA3 pyramidal neuron synapses, it is unclear whether it can be induced by natural activity and whether its lifetime is sufficient to support short-term memory. We combined in vivo recordings from granule cells (GCs), in vitro paired recordings from mossy fiber terminals and postsynaptic CA3 neurons, and “flash and freeze” electron microscopy. PTP was induced at single synapses and showed a low induction threshold adapted to sparse GC activity in vivo. PTP was mainly generated by enlargement of the readily releasable pool of synaptic vesicles, allowing multiplicative interaction with other plasticity forms. PTP was associated with an increase in the docked vesicle pool, suggesting formation of structural “pool engrams.” Absence of presynaptic activity extended the lifetime of the potentiation, enabling prolonged information storage in the hippocampal network.

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Natural activity patterns in hippocampal GCs in vivo induce PTP at mossy fiber synapses

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PTP is primarily caused by an increase in the readily releasable vesicle pool

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PTP is associated with an increase in the number of docked vesicles at active zones

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Sparse activity extends pool engram lifetime, increasing overlap with short-term memory

Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage

The cerebellar granule cells (GrCs) are classically described as a homogeneous neuronal population discharging regularly without adaptation. We show that GrCs in fact generate diverse response patterns to current injection and synaptic activation, ranging from adaptation to acceleration of firing. Adaptation was predicted by parameter optimization in detailed computational models based on available knowledge on GrC ionic channels. The models also predicted that acceleration required additional mechanisms. We found that yet unrecognized TRPM4 currents specifically accounted for firing acceleration and that adapting GrCs outperformed accelerating GrCs in transmitting high-frequency mossy fiber (MF) bursts over a background discharge. This implied that GrC subtypes identified by their electroresponsiveness corresponded to specific neurotransmitter release probability values. Simulations showed that fine-tuning of pre- and post-synaptic parameters generated effective MF-GrC transmission channels, which could enrich the processing of input spike patterns and enhance spatio-temporal recoding at the cerebellar input stage.

Nitric Oxide Signaling Strengthens Inhibitory Synapses of Cerebellar Molecular Layer Interneurons through a GABARAP-Dependent Mechanism

Nitric oxide (NO) is an important signaling molecule that fulfills diverse functional roles as a neurotransmitter or diffusible second messenger in the developing and adult CNS. Although the impact of NO on different behaviors such as movement, sleep, learning, and memory has been well documented, the identity of its molecular and cellular targets is still an area of ongoing investigation. Here, we identify a novel role for NO in strengthening inhibitory GABA_A receptor-mediated transmission in molecular layer interneurons of the mouse cerebellum. NO levels are elevated by the activity of neuronal NO synthase (nNOS) following Ca²⁺ entry through extrasynaptic NMDA-type ionotropic glutamate receptors (NMDARs). NO activates protein kinase G with the subsequent production of cGMP, which prompts the stimulation of NADPH oxidase and protein kinase C (PKC). The activation of PKC promotes the selective strengthening of α3-containing GABA_ARs synapses through a GΑΒΑ receptor-associated protein-dependent mechanism. Given the widespread but cell type-specific expression of the NMDAR/nNOS complex in the mammalian brain, our data suggest that NMDARs may uniquely strengthen inhibitory GABAergic transmission in these cells through a novel NO-mediated pathway.SIGNIFICANCE STATEMENT Long-term changes in the efficacy of GABAergic transmission is mediated by multiple presynaptic and postsynaptic mechanisms. A prominent pathway involves crosstalk between excitatory and inhibitory synapses whereby Ca²⁺-entering through postsynaptic NMDARs promotes the recruitment and strengthening of GABA_A receptor synapses via Ca²⁺/calmodulin-dependent protein kinase II. Although Ca²⁺ transport by NMDARs is also tightly coupled to nNOS activity and NO production, it has yet to be determined whether this pathway affects inhibitory synapses. Here, we show that activation of NMDARs trigger a NO-dependent pathway that strengthens inhibitory GABAergic synapses of cerebellar molecular layer interneurons. Given the widespread expression of NMDARs and nNOS in the mammalian brain, we speculate that NO control of GABAergic synapse efficacy may be more widespread than has been appreciated.

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.

Regulation and roles of mitophagy at synapses

Maintenance of synaptic homeostasis is a challenging task, due to the intricate spatial organization and intense activity of synapses. Typically, synapses are located far away from the neuronal cell body, where they orchestrate neuronal signalling and communication, through neurotransmitter release. Stationary mitochondria provide energy required for synaptic vesicle cycling, and preserve ionic balance by buffering intercellular calcium at synapses. Thus, synaptic homeostasis is critically dependent on proper mitochondrial function. Indeed, defective mitochondrial metabolism is a common feature of several neurodegenerative and psychiatric disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), bipolar disorders and schizophrenia among others, which are also accompanied by excessive synaptic abnormalities. Specialized and compartmentalized quality control mechanisms have evolved to restore and maintain synaptic energy metabolism. Here, we survey recent advances towards the elucidation of the pivotal role of mitochondria in neurotransmission and implicating mitophagy in the maintenance of synaptic homeostasis during ageing.

Gradients in the mammalian cerebellar cortex enable Fourier-like transformation and improve storing capacity

Cerebellar granule cells (GCs) make up the majority of all neurons in the vertebrate brain, but heterogeneities among GCs and potential functional consequences are poorly understood. Here, we identified unexpected gradients in the biophysical properties of GCs in mice. GCs closer to the white matter (inner-zone GCs) had higher firing thresholds and could sustain firing with larger current inputs than GCs closer to the Purkinje cell layer (outer-zone GCs). Dynamic Clamp experiments showed that inner- and outer-zone GCs preferentially respond to high- and low-frequency mossy fiber inputs, respectively, enabling dispersion of the mossy fiber input into its frequency components as performed by a Fourier transformation. Furthermore, inner-zone GCs have faster axonal conduction velocity and elicit faster synaptic potentials in Purkinje cells. Neuronal network modeling revealed that these gradients improve spike-timing precision of Purkinje cells and decrease the number of GCs required to learn spike-sequences. Thus, our study uncovers biophysical gradients in the cerebellar cortex enabling a Fourier-like transformation of mossy fiber inputs.

Neocortex-Cerebellum Circuits for Cognitive Processing

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

Diverse Neuron Properties and Complex Network Dynamics in the Cerebellar Cortical Inhibitory Circuit

Neuronal inhibition can be defined as a spatiotemporal restriction or suppression of local microcircuit activity. The importance of inhibition relies in its fundamental role in shaping signal processing in single neurons and neuronal circuits. In this context, the activity of inhibitory interneurons proved the key to endow networks with complex computational and dynamic properties. In the last 50 years, the prevailing view on the functional role of cerebellar cortical inhibitory circuits was that excitatory and inhibitory inputs sum spatially and temporally in order to determine the motor output through Purkinje cells (PCs). Consequently, cerebellar inhibition has traditionally been conceived in terms of restricting or blocking excitation. This assumption has been challenged, in particular in the cerebellar cortex where all neurons except granule cells (and unipolar brush cells in specific lobules) are inhibitory and fire spontaneously at high rates. Recently, a combination of electrophysiological recordings in vitro and in vivo, imaging, optogenetics and computational modeling, has revealed that inhibitory interneurons play a much more complex role in regulating cerebellar microcircuit functions: inhibition shapes neuronal response dynamics in the whole circuit and eventually regulate the PC output. This review elaborates current knowledge on cerebellar inhibitory interneurons [Golgi cells, Lugaro cells (LCs), basket cells (BCs) and stellate cells (SCs)], starting from their ontogenesis and moving up to their morphological, physiological and plastic properties, and integrates this knowledge with that on the more renown granule cells and PCs. We will focus on the circuit loops in which these interneurons are involved and on the way they generate feed-forward, feedback and lateral inhibition along with complex spatio-temporal response dynamics. In this perspective, inhibitory interneurons emerge as the real controllers of cerebellar functioning.

Response Dynamics in an Olivocerebellar Spiking Neural Network With Non-linear Neuron Properties

Sensorimotor signals are integrated and processed by the cerebellar circuit to predict accurate control of actions. In order to investigate how single neuron dynamics and geometrical modular connectivity affect cerebellar processing, we have built an olivocerebellar Spiking Neural Network (SNN) based on a novel simplification algorithm for single point models (Extended Generalized Leaky Integrate and Fire, EGLIF) capturing essential non-linear neuronal dynamics (e.g., pacemaking, bursting, adaptation, oscillation and resonance). EGLIF models specifically tuned for each neuron type were embedded into an olivocerebellar scaffold reproducing realistic spatial organization and physiological convergence and divergence ratios of connections. In order to emulate the circuit involved in an eye blink response to two associated stimuli, we modeled two adjacent olivocerebellar microcomplexes with a common mossy fiber input but different climbing fiber inputs (either on or off). EGLIF-SNN model simulations revealed the emergence of fundamental response properties in Purkinje cells (burst-pause) and deep nuclei cells (pause-burst) similar to those reported in vivo. The expression of these properties depended on the specific activation of climbing fibers in the microcomplexes and did not emerge with scaffold models using simplified point neurons. This result supports the importance of embedding SNNs with realistic neuronal dynamics and appropriate connectivity and anticipates the scale-up of EGLIF-SNN and the embedding of plasticity rules required to investigate cerebellar functioning at multiple scales.

HCN channel-mediated neuromodulation can control action potential velocity and fidelity in central axons

Hyperpolarization-activated cyclic-nucleotide-gated (HCN) channels control electrical rhythmicity and excitability in the heart and brain, but the function of HCN channels at the subcellular level in axons remains poorly understood. Here, we show that the action potential conduction velocity in both myelinated and unmyelinated central axons can be bidirectionally modulated by a HCN channel blocker, cyclic adenosine monophosphate (cAMP), and neuromodulators. Recordings from mouse cerebellar mossy fiber boutons show that HCN channels ensure reliable high-frequency firing and are strongly modulated by cAMP (EC50 40 µM; estimated endogenous cAMP concentration 13 µM). In addition, immunogold-electron microscopy revealed HCN2 as the dominating subunit in cerebellar mossy fibers. Computational modeling indicated that HCN2 channels control conduction velocity primarily by altering the resting membrane potential and are associated with significant metabolic costs. These results suggest that the cAMP-HCN pathway provides neuromodulators with an opportunity to finely tune energy consumption and temporal delays across axons in the brain.