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

Neurotransmitter content heterogeneity within an interneuron class shapes inhibitory transmission at a central synapse

Neurotransmitter content is deemed the most basic defining criterion for neuronal classes, contrasting with the intercellular heterogeneity of many other molecular and functional features. Here we show, in the adult mouse brain, that neurotransmitter content variegation within a neuronal class is a component of its functional heterogeneity. Golgi cells (GoCs), the well-defined class of cerebellar interneurons inhibiting granule cells (GrCs), contain cytosolic glycine, accumulated by the neuronal transporter GlyT2, and GABA in various proportions. By performing acute manipulations of cytosolic GABA and glycine supply, we find that competition of glycine with GABA reduces the charge of IPSC evoked in GrCs and, more specifically, the amplitude of a slow component of the IPSC decay. We then pair GrCs recordings with optogenetic stimulations of single GoCs, which preserve the intracellular transmitter mixed content. We show that the strength and decay kinetics of GrCs IPSCs, which are entirely mediated by GABAA receptors, are negatively correlated to the presynaptic expression of GlyT2 by GoCs. We isolate a slow spillover component of GrCs inhibition that is also affected by the expression of GlyT2, leading to a 56% decrease in relative charge. Our results support the hypothesis that presynaptic loading of glycine negatively impacts the GABAergic transmission in mixed interneurons, most likely through a competition for vesicular filling. We discuss how the heterogeneity of neurotransmitter supply within mixed interneurons like the GoC class may provide a presynaptic mechanism to tune the gain of microcircuits such as the granular layer, thereby expanding the realm of their possible dynamic behaviors.

Regulating synchronous oscillations of cerebellar granule cells by different types of inhibition

Synchronous oscillations in neural populations are considered being controlled by inhibitory neurons. In the granular layer of the cerebellum, two major types of cells are excitatory granular cells (GCs) and inhibitory Golgi cells (GoCs). GC spatiotemporal dynamics, as the output of the granular layer, is highly regulated by GoCs. However, there are various types of inhibition implemented by GoCs. With inputs from mossy fibers, GCs and GoCs are reciprocally connected to exhibit different network motifs of synaptic connections. From the view of GCs, feedforward inhibition is expressed as the direct input from GoCs excited by mossy fibers, whereas feedback inhibition is from GoCs via GCs themselves. In addition, there are abundant gap junctions between GoCs showing another form of inhibition. It remains unclear how these diverse copies of inhibition regulate neural population oscillation changes. Leveraging a computational model of the granular layer network, we addressed this question to examine the emergence and modulation of network oscillation using different types of inhibition. We show that at the network level, feedback inhibition is crucial to generate neural oscillation. When short-term plasticity was equipped on GoC-GC synapses, oscillations were largely diminished. Robust oscillations can only appear with additional gap junctions. Moreover, there was a substantial level of cross-frequency coupling in oscillation dynamics. Such a coupling was adjusted and strengthened by GoCs through feedback inhibition. Taken together, our results suggest that the cooperation of distinct types of GoC inhibition plays an essential role in regulating synchronous oscillations of the GC population. With GCs as the sole output of the granular network, their oscillation dynamics could potentially enhance the computational capability of downstream neurons.

Non-synaptic signaling from cerebellar climbing fibers modulates Golgi cell activity

Golgi cells are the principal inhibitory neurons at the input stage of the cerebellum, providing feedforward and feedback inhibition through mossy fiber and parallel fiber synapses. In vivo studies have shown that Golgi cell activity is regulated by climbing fiber stimulation, yet there is little functional or anatomical evidence for synapses between climbing fibers and Golgi cells. Here, we show that glutamate released from climbing fibers activates ionotropic and metabotropic receptors on Golgi cells through spillover-mediated transmission. The interplay of excitatory and inhibitory conductances provides flexible control over Golgi cell spiking, allowing either excitation or a biphasic sequence of excitation and inhibition following single climbing fiber stimulation. Together with prior studies of spillover transmission to molecular layer interneurons, these results reveal that climbing fibers exert control over inhibition at both the input and output layers of the cerebellar cortex.

Cerebellar Synaptic Plasticity and the Credit Assignment Problem

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

At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters

Models of the cerebellar microcircuit often assume that input signals from the mossy-fibers are expanded and recoded to provide a foundation from which the Purkinje cells can synthesize output filters to implement specific input-signal transformations. Details of this process are however unclear. While previous work has shown that recurrent granule cell inhibition could in principle generate a wide variety of random outputs suitable for coding signal onsets, the more general application for temporally varying signals has yet to be demonstrated. Here we show for the first time that using a mechanism very similar to reservoir computing enables random neuronal networks in the granule cell layer to provide the necessary signal separation and extension from which Purkinje cells could construct basis filters of various time-constants. The main requirement for this is that the network operates in a state of criticality close to the edge of random chaotic behavior. We further show that the lack of recurrent excitation in the granular layer as commonly required in traditional reservoir networks can be circumvented by considering other inherent granular layer features such as inverted input signals or mGluR2 inhibition of Golgi cells. Other properties that facilitate filter construction are direct mossy fiber excitation of Golgi cells, variability of synaptic weights or input signals and output-feedback via the nucleocortical pathway. Our findings are well supported by previous experimental and theoretical work and will help to bridge the gap between system-level models and detailed models of the granular layer network.

ON and OFF unipolar brush cells transform multisensory inputs to the auditory system

Unipolar brush cells (UBCs) of the dorsal cochlear nucleus (DCN) and vestibular cerebellar cortex receive glutamatergic mossy fiber input on an elaborate brush-like dendrite. Two subtypes of UBC have been established based on immunohistochemical markers and physiological profiles, but the relation of these subtypes to the response to mossy fiber input is not clear. We examined the synaptic physiology of auditory UBCs in mouse brain slices, identifying two response profiles, and correlated each with a specific UBC subtype. One subtype had a striking biphasic excitatory response mediated by AMPAR and mGluR1α. The second was mGluR1α negative and was dominated by a strongly inhibitory outward K(+) current. These two subtypes upregulated or downregulated spontaneous firing, respectively. By analogy to the retina, we propose that UBCs comprise ON and OFF cells with respect to their response to glutamatergic input and may therefore provide distinct parallel processing of multisensory input to their targets.

The contribution of extrasynaptic signaling to cerebellar information processing

The diversity of synapses within the simple modular structure of the cerebellum has been crucial for study of the phasic extrasynaptic signaling by fast neurotransmitters collectively referred to as "spillover." Additionally, the accessibility of cerebellar components for in vivo recordings and their recruitment by simple behaviors or sensory stimuli has allowed for both direct and indirect demonstrations of the effects of transmitter spillover in the intact brain. The continued study of spillover in the cerebellum not only promotes our understanding of information transfer through cerebellar structures but also how extrasynaptic signaling may be regulated and interpreted throughout the CNS.

Model cerebellar granule cells can faithfully transmit modulated firing rate signals

A crucial assumption of many high-level system models of the cerebellum is that information in the granular layer is encoded in a linear manner. However, granule cells are known for their non-linear and resonant synaptic and intrinsic properties that could potentially impede linear signal transmission. In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.e., uncorrelated inhibitory feedback (open-loop mode). A detailed one-compartment granule cell model was excited in simulation by either direct current or mossy-fiber synaptic inputs. Vestibular signals were represented as tonic inputs to the flocculus modulated at frequencies up to 20 Hz (approximate upper frequency limit of vestibular-ocular reflex, VOR). Model outputs were assessed using estimates of both the transfer function, and the fidelity of input-signal reconstruction measured as variance-accounted-for. The detailed granule cell model with realistic mossy-fiber synaptic inputs could transmit information faithfully and linearly in the frequency range of the vestibular-ocular reflex. This was achieved most simply if the model neurons had a firing rate at least twice the highest required frequency of modulation, but lower rates were also adequate provided a population of neurons was utilized, especially in combination with push-pull coding. The exact number of neurons required for faithful transmission depended on the precise values of firing rate and noise. The model neurons were also able to combine excitatory and inhibitory signals linearly, and could be replaced by a simpler (modified) integrate-and-fire neuron in the case of high tonic firing rates. These findings suggest that granule cells can in principle code modulated firing-rate inputs in a linear manner, and are thus consistent with the high-level adaptive-filter model of the cerebellar microcircuit.

Neuronal oscillations in Golgi cells and Purkinje cells are accompanied by decreases in Shannon information entropy

Neuronal oscillations have been shown to contribute to the function of the cerebral cortex by coordinating the neuronal activities of distant cortical regions via a temporal synchronization of neuronal discharge patterns. This can occur regardless whether these regions are linked by cortico-cortical pathways or not. Less is known concerning the role of neuronal oscillations in the cerebellum. Golgi cells and Purkinje cells are both principal cell types in the cerebellum. Purkinje cells are the sole output cells of the cerebellar cortex while Golgi cells contribute to information processing at the input stage of the cerebellar cortex. Both cell types have large cell bodies, as well as dendritic structures, that can generate large currents. The discharge patterns of both these cell types also exhibit oscillations. In view of the massive afferent information conveyed by the mossy fiber-granule cell system to different and distant areas of the cerebellar cortex, it is relevant to inquire the role of cerebellar neuronal oscillations in information processing. In this study, we compared the discharge patterns of Golgi cells and Purkinje cells in conscious rats and in rats anesthetized with urethane. We assessed neuronal oscillations by analyzing the regularity in the timing of individual spikes within a spike train by using autocorrelograms and fast-Fourier transform. We measured the differences in neuronal oscillations and the amount of information content in a spike train (defined by Shannon entropy processed per unit time) in rats under anesthesia and in conscious, awake rats. Our findings indicated that anesthesia caused more prominent neuronal oscillations in both Golgi cells and Purkinje cells accompanied by decreases in Shannon information entropy in their spike trains.

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

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

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

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

An integrator circuit in cerebellar cortex

The brain builds dynamic models of the body and the outside world to predict the consequences of actions and stimuli. A well-known example is the oculomotor integrator, which anticipates the position-dependent elasticity forces acting on the eye ball by mathematically integrating over time oculomotor velocity commands. Many models of neural integration have been proposed, based on feedback excitation, lateral inhibition or intrinsic neuronal nonlinearities. We report here that a computational model of the cerebellar cortex, a structure thought to implement dynamic models, reveals a hitherto unrecognized integrator circuit. In this model, comprising Purkinje cells, molecular layer interneurons and parallel fibres, Purkinje cells were able to generate responses lasting more than 10 s, to which both neuronal and network mechanisms contributed. Activation of the somatic fast sodium current by subthreshold voltage fluctuations was able to maintain pulse-evoked graded persistent activity, whereas lateral inhibition among Purkinje cells via recurrent axon collaterals further prolonged the responses to step and sine wave stimulation. The responses of Purkinje cells decayed with a time-constant whose value depended on their baseline spike rate, with integration vanishing at low (< 1 per s) and high rates (> 30 per s). The model predicts that the apparently fast circuit of the cerebellar cortex may control the timing of slow processes without having to rely on sensory feedback. Thus, the cerebellar cortex may contain an adaptive temporal integrator, with the sensitivity of integration to the baseline spike rate offering a potential mechanism of plasticity of the response time-constant.

Probabilistic identification of cerebellar cortical neurones across species

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

Golgi cell-mediated activation of postsynaptic GABA(B) receptors induces disinhibition of the Golgi cell-granule cell synapse in rat cerebellum

In the cerebellar glomerulus, GABAergic synapses formed by Golgi cells regulate excitatory transmission from mossy fibers to granule cells through feed-forward and feedback mechanisms. In acute cerebellar slices, we found that stimulating Golgi cell axons with a train of 10 impulses at 100 Hz transiently inhibited both the phasic and the tonic components of inhibitory responses recorded in granule cells. This effect was blocked by the GABA_B receptor blocker CGP35348, and could be mimicked by bath-application of baclofen (30 µM). This depression of IPSCs was prevented when granule cells were dialyzed with GDPβS. Furthermore, when synaptic transmission was blocked, GABA_A currents induced in granule cells by localized muscimol application were inhibited by the GABA_B receptor agonist baclofen. These findings indicate that postsynaptic GABA_B receptors are primarily responsible for the depression of IPSCs. This inhibition of inhibitory events results in an unexpected excitatory action by Golgi cells on granule cell targets. The reduction of Golgi cell-mediated inhibition in the cerebellar glomerulus may represent a regulatory mechanism to shift the balance between excitation and inhibition in the glomerulus during cerebellar information processing.

Distributed synergistic plasticity and cerebellar learning

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