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

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.

The guide to dendritic spikes of the mammalian cortex in vitro and in vivo

Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.

Calcium Channel-Dependent Induction of Long-Term Synaptic Plasticity at Excitatory Golgi Cell Synapses of Cerebellum

Golgi cells, together with granule cells and mossy fibers, form a neuronal microcircuit regulating information transfer at the cerebellum input stage. Despite theoretical predictions, little was known about long-term synaptic plasticity at Golgi cell synapses. Here, we have used whole-cell patch-clamp recordings and calcium imaging to investigate long-term synaptic plasticity at excitatory synapses impinging on Golgi cells. In acute mouse cerebellar slices, mossy fiber theta-burst stimulation (TBS) could induce either long-term potentiation (LTP) or long-term depression (LTD) at mossy fiber-Golgi cell and granule cell-Golgi cell synapses. This synaptic plasticity showed a peculiar voltage dependence, with LTD or LTP being favored when TBS induction occurred at depolarized or hyperpolarized potentials, respectively. LTP required, in addition to NMDA channels, activation of T-type Ca²⁺ channels, while LTD required uniquely activation of L-type Ca²⁺ channels. Notably, the voltage dependence of plasticity at the mossy fiber-Golgi cell synapses was inverted with respect to pure NMDA receptor-dependent plasticity at the neighboring mossy fiber-granule cell synapse, implying that the mossy fiber presynaptic terminal can activate different induction mechanisms depending on the target cell. In aggregate, this result shows that Golgi cells show cell-specific forms of long-term plasticity at their excitatory synapses, that could play a crucial role in sculpting the response patterns of the cerebellar granular layer.SIGNIFICANCE STATEMENT This article shows for the first time a novel form of Ca²⁺ channel-dependent synaptic plasticity at the excitatory synapses impinging on cerebellar Golgi cells. This plasticity is bidirectional and inverted with respect to NMDA receptor-dependent paradigms, with long-term depression (LTD) and long-term potentiation (LTP) being favored at depolarized and hyperpolarized potentials, respectively. Furthermore, LTP and LTD induction requires differential involvement of T-type and L-type voltage-gated Ca²⁺ channels rather than the NMDA receptors alone. These results, along with recent computational predictions, support the idea that Golgi cell plasticity could play a crucial role in controlling information flow through the granular layer along with cerebellar learning and memory.

Cerebellar Golgi cell models predict dendritic processing and mechanisms of synaptic plasticity

The Golgi cells are the main inhibitory interneurons of the cerebellar granular layer. Although recent works have highlighted the complexity of their dendritic organization and synaptic inputs, the mechanisms through which these neurons integrate complex input patterns remained unknown. Here we have used 8 detailed morphological reconstructions to develop multicompartmental models of Golgi cells, in which Na, Ca, and K channels were distributed along dendrites, soma, axonal initial segment and axon. The models faithfully reproduced a rich pattern of electrophysiological and pharmacological properties and predicted the operating mechanisms of these neurons. Basal dendrites turned out to be more tightly electrically coupled to the axon initial segment than apical dendrites. During synaptic transmission, parallel fibers caused slow Ca-dependent depolarizations in apical dendrites that boosted the axon initial segment encoder and Na-spike backpropagation into basal dendrites, while inhibitory synapses effectively shunted backpropagating currents. This oriented dendritic processing set up a coincidence detector controlling voltage-dependent NMDA receptor unblock in basal dendrites, which, by regulating local calcium influx, may provide the basis for spike-timing dependent plasticity anticipated by theory.

Pathway-Specific Drive of Cerebellar Golgi Cells Reveals Integrative Rules of Cortical Inhibition

Cerebellar granule cells (GrCs) constitute over half of all neurons in the vertebrate brain and are proposed to decorrelate convergent mossy fiber (MF) inputs in service of learning. Interneurons within the GrC layer, Golgi cells (GoCs), are the primary inhibitors of this vast population and therefore play a major role in influencing the computations performed within the layer. Despite this central function for GoCs, few studies have directly examined how GoCs integrate inputs from specific afferents, which vary in density to regulate GrC population activity. We used a variety of methods in mice of either sex to study feedforward inhibition recruited by identified MFs, focusing on features that would influence integration by GrCs. Comprehensive 3D reconstruction and quantification of GoC axonal boutons revealed tightly clustered boutons that focus feedforward inhibition in the neighborhood of GoC somata. Acute whole-cell patch-clamp recordings from GrCs in brain slices showed that, despite high GoC bouton density, fast phasic inhibition was very sparse relative to slow spillover mediated inhibition. Dynamic-clamp simulating inhibition combined with optogenetic MF activation at moderate rates supported a predominant role of slow spillover mediated inhibition in reducing GrC activity. Whole-cell recordings from GoCs revealed a role for the density of active MFs in preferentially driving them. Thus, our data provide empirical confirmation of predicted rules by which MFs activate GoCs to regulate GrC activity levels.SIGNIFICANCE STATEMENT A unifying framework in neural circuit analysis is identifying circuit motifs that subserve common computations. Wide-field inhibitory interneurons globally inhibit neighbors and have been studied extensively in the insect olfactory system and proposed to serve pattern separation functions. Cerebellar Golgi cells (GoCs), a type of mammalian wide-field inhibitory interneuron observed in the granule cell layer, are well suited to perform normalization or pattern separation functions, but the relationship between spatial characteristics of input patterns to GoC-mediated inhibition has received limited attention. This study provides unprecedented quantitative structural details of GoCs and identifies a role for population input activity levels in recruiting inhibition using in vitro electrophysiology and optogenetics.

Regenerative glutamate release in the hippocampus of Rett syndrome model mice

Excess glutamate during intense neuronal activity is not instantly cleared and may accumulate in the extracellular space. This has various long-term consequences such as ectopic signaling, modulation of synaptic efficacy and excitotoxicity; the latter implicated in various neurodevelopmental and neurodegenerative diseases. In this study, the quantitative imaging of glutamate homeostasis of hippocampal slices from methyl-CpG binding protein 2 knock-out (Mecp2-/y) mice, a model of Rett syndrome (RTT), revealed unusual repetitive glutamate transients. They appeared in phase with bursts of action potentials in the CA1 neurons. Both glutamate transients and bursting activity were suppressed by the blockade of sodium, AMPA and voltage-gated calcium channels (T- and R-type), and enhanced after the inhibition of HCN channels. HCN and calcium channels in RTT and wild-type (WT) CA1 neurons displayed different voltage-dependencies and kinetics. Both channels modulated postsynaptic integration and modified the pattern of glutamate spikes in the RTT hippocampus. Spontaneous glutamate transients were much less abundant in the WT preparations, and, when observed, had smaller amplitude and frequency. The basal ambient glutamate levels in RTT were higher and transient glutamate increases (spontaneous and evoked by stimulation of Schaffer collaterals) decayed slower. Both features indicate less efficient glutamate uptake in RTT. To explain the generation of repetitive glutamate spikes, we designed a novel model of glutamate-induced glutamate release. The simulations correctly predicted the patterns of spontaneous glutamate spikes observed under different experimental conditions. We propose that pervasive spontaneous glutamate release is a hallmark of Mecp2-/y hippocampus, stemming from and modulating the hyperexcitability of neurons.

Differential Dendritic Integration of Synaptic Potentials and Calcium in Cerebellar Interneurons

Dendritic voltage integration determines the transformation of synaptic inputs into output firing, while synaptic calcium integration drives plasticity mechanisms thought to underlie memory storage. Dendritic calcium integration has been shown to follow the same synaptic input-output relationship as dendritic voltage, but whether similar operations apply to neurons exhibiting sublinear voltage integration is unknown. We examined the properties and cellular mechanisms of these dendritic operations in cerebellar molecular layer interneurons using dendritic voltage and calcium imaging, in combination with synaptic stimulation or glutamate uncaging. We show that, while synaptic potentials summate sublinearly, concomitant dendritic calcium signals summate either linearly or supralinearly depending on the number of synapses activated. The supralinear dendritic calcium triggers a branch-specific, short-term suppression of neurotransmitter release that alters the pattern of synaptic activation. Thus, differential voltage and calcium integration permits dynamic regulation of neuronal input-output transformations without altering intrinsic nonlinear integration mechanisms.

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate “realistic” models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems.

Only a Minority of the Inhibitory Inputs to Cerebellar Golgi Cells Originates from Local GABAergic Cells

Cerebellar Golgi cells (GoCs) efficiently control the spiking activity of granule cells through GABAA receptor-mediated tonic and phasic inhibition. Recent experiments provided compelling evidence for the extensive interconnection of GoCs through electrical synapses, but their chemical inhibitory synaptic inputs are debated. Here, we investigated the GABAergic synaptic inputs of GoCs using in vitro electrophysiology and quantitative light microscopy (LM) and electron microscopy (EM). We characterized GABAA receptor-mediated IPSCs in GoCs and Lugaro cells (LuCs), and found that IPSCs in GoCs have lower frequencies, smaller amplitudes, and much slower decay kinetics. Pharmacological and LM immunolocalization experiments revealed that GoCs express α3, whereas LuCs express α1 subunit-containing GABAA receptors. The selective expression and clustered distribution of the α3 subunit in GoCs allowed the quantitative analysis of GABAergic synapses on their dendrites in the molecular layer (ML). EM and LM experiments in rats, and wild-type and GlyT2-GFP transgenic mice revealed that only one third of axon terminals establishing GABAergic synapses on GoC dendrites contain GlyT2, ruling out LuCs, globular cells, and any noncortical glycinergic inputs as major inhibitory sources. We also show that axon terminals of stellate/basket cells very rarely innervate GlyT2-GFP-expressing GoCs, indicating that only a minority of the inhibitory inputs to GoCs in the ML originates from local interneurons, and the majority of their inhibitory inputs exclusively releases GABA.

Conditional Spike Transmission Mediated by Electrical Coupling Ensures Millisecond Precision-Correlated Activity among Interneurons In Vivo

Many GABAergic interneurons are electrically coupled and in vitro can display correlated activity with millisecond precision. However, the mechanisms underlying correlated activity between interneurons in vivo are unknown. Using dual patch-clamp recordings in vivo, we reveal that in the presence of spontaneous background synaptic activity, electrically coupled cerebellar Golgi cells exhibit robust millisecond precision-correlated activity which is enhanced by sensory stimulation. This precisely correlated activity results from the cooperative action of two mechanisms. First, electrical coupling ensures slow subthreshold membrane potential correlations by equalizing membrane potential fluctuations, such that coupled neurons tend to approach action potential threshold together. Second, fast spike-triggered spikelets transmitted through gap junctions conditionally trigger postjunctional spikes, depending on both neurons being close to threshold. Electrical coupling therefore controls the temporal precision and degree of both spontaneous and sensory-evoked correlated activity between interneurons, by the cooperative effects of shared synaptic depolarization and spikelet transmission.

•

Double patch-clamp recordings from Golgi cells reveal millisecond synchrony in vivo

•

Millisecond synchrony requires gap junctions and is enhanced by sensory stimuli

•

Gap junctions drive synchrony via slow V_m equalization and fast spikelet transmission

•

Modeling shows these findings can be generalized to any electrically coupled neurons

Surface dynamics of voltage-gated ion channels

Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks.