Short-Term Plasticity Combines with Excitation-Inhibition Balance to Expand Cerebellar Purkinje Cell Dynamic Range

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.

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.

Climbing fibers provide essential instructive signals for associative learning

Supervised learning depends on instructive signals that shape the output of neural circuits to support learned changes in behavior. Climbing fiber (CF) inputs to the cerebellar cortex represent one of the strongest candidates in the vertebrate brain for conveying neural instructive signals. However, recent studies have shown that Purkinje cell stimulation can also drive cerebellar learning and the relative importance of these two neuron types in providing instructive signals for cerebellum-dependent behaviors remains unresolved. In the present study we used cell-type-specific perturbations of various cerebellar circuit elements to systematically evaluate their contributions to delay eyeblink conditioning in mice. Our findings reveal that, although optogenetic stimulation of either CFs or Purkinje cells can drive learning under some conditions, even subtle reductions in CF signaling completely block learning to natural stimuli. We conclude that CFs and corresponding Purkinje cell complex spike events provide essential instructive signals for associative cerebellar learning.

Circuit-based intervention corrects excessive dentate gyrus output in the fragile X mouse model

Abnormal cellular and circuit excitability is believed to drive many core phenotypes in fragile X syndrome (FXS). The dentate gyrus is a brain area performing critical computations essential for learning and memory. However, little is known about dentate circuit defects and their mechanisms in FXS. Understanding dentate circuit dysfunction in FXS has been complicated by the presence of two types of excitatory neurons, the granule cells and mossy cells. Here we report that loss of FMRP markedly decreased excitability of dentate mossy cells, a change opposite to all other known excitability defects in excitatory neurons in FXS. This mossy cell hypo-excitability is caused by increased Kv7 function in Fmr1 knockout (KO) mice. By reducing the excitatory drive onto local hilar interneurons, hypo-excitability of mossy cells results in increased excitation/inhibition ratio in granule cells and thus paradoxically leads to excessive dentate output. Circuit-wide inhibition of Kv7 channels in Fmr1 KO mice increases inhibitory drive onto granule cells and normalizes the dentate output in response to physiologically relevant theta-gamma coupling stimulation. Our study suggests that circuit-based interventions may provide a promising strategy in this disorder to bypass irreconcilable excitability defects in different cell types and restore their pathophysiological consequences at the circuit level.

Circuit-based intervention corrects excessive dentate gyrus output in the Fragile X mouse model

Abnormal cellular and circuit excitability is believed to drive many core phenotypes in fragile X syndrome (FXS). The dentate gyrus is a brain area performing critical computations essential for learning and memory. However, little is known about dentate circuit defects and their mechanisms in FXS. Understanding dentate circuit dysfunction in FXS has been complicated by the presence of two types of excitatory neurons, the granule cells and mossy cells. Here we report that loss of FMRP markedly decreased excitability of dentate mossy cells, a change opposite to all other known excitability defects in excitatory neurons in FXS. This mossy cell hypo-excitability is caused by increased Kv7 function in Fmr1 KO mice. By reducing the excitatory drive onto local hilar interneurons, hypo-excitability of mossy cells results in increased excitation/inhibition ratio in granule cells and thus paradoxically leads to excessive dentate output. Circuit-wide inhibition of Kv7 channels in Fmr1 KO mice increases inhibitory drive onto granule cells and normalizes the dentate output in response to physiologically relevant theta-gamma coupling stimulation. Our study suggests that circuit-based interventions may provide a promising strategy in this disorder to bypass irreconcilable excitability defects in different cell types and restore their pathophysiological consequences at the circuit level.

Excitation and Inhibition Delays within a Feedforward Inhibitory Pathway Modulate Cerebellar Purkinje Cell Output in Mice

The cerebellar cortex computes sensorimotor information from many brain areas through a feedforward inhibitory (FFI) microcircuit between the input stage, the granule cell (GC) layer, and the output stage, the Purkinje cells (PCs). Although in other brain areas FFI underlies a precise excitation versus inhibition temporal correlation, recent findings in the cerebellum highlighted more complex behaviors at GC-molecular layer interneuron (MLI)-PC pathway. To dissect the temporal organization of this cerebellar FFI pathway, we combined ex vivo patch-clamp recordings of PCs in male mice with a viral-based strategy to express Channelrhodopsin2 in a subset of mossy fibers (MFs), the major excitatory inputs to GCs. We show that although light-mediated MF activation elicited pairs of excitatory and inhibitory postsynaptic currents in PCs, excitation (E) from GCs and inhibition (I) from MLIs reached PCs with a wide range of different temporal delays. However, when GCs were directly stimulated, a low variability in E/I delays was observed. Our results demonstrate that in many recordings MF stimulation recruited different groups of GCs that trigger E and/or I, and expanded PC temporal synaptic integration. Finally, using a computational model of the FFI pathway, we showed that this temporal expansion could strongly influence how PCs integrate GC inputs. Our findings show that specific E/I delays may help PCs encoding specific MF inputs.SIGNIFICANCE STATEMENT Sensorimotor information is conveyed to the cerebellar cortex by mossy fibers. Mossy fiber inputs activate granule cells that excite molecular interneurons and Purkinje cells, the sole output of the cerebellar cortex, leading to a sequence of synaptic excitation and inhibition in Purkinje cells, thus defining a feedforward inhibitory pathway. Using electrophysiological recordings, optogenetic stimulation, and mathematical modeling, we demonstrated that different groups of granule cells can elicit synaptic excitation and inhibition with various latencies onto Purkinje cells. This temporal variability controls how granule cells influence Purkinje cell discharge and may support temporal coding in the cerebellar cortex.

A computational view of short-term plasticity and its implications for E-I balance

Short-term plasticity (STP) and excitatory-inhibitory balance (EI balance) are both ubiquitous building blocks of brain circuits across the animal kingdom. The synapses involved in EI are also subject to short-term plasticity, and several experimental studies have shown that their effects overlap. Recent computational and theoretical work has begun to highlight the functional implications of the intersection of these motifs. The findings are nuanced: while there are general computational themes, such as pattern tuning, normalization, and gating, much of the richness of these interactions comes from region- and modality specific tuning of STP properties. Together these findings point towards the STP-EI balance combination as being a versatile and highly efficient neural building block for a wide range of pattern-specific responses.

Anisotropy and Frequency Dependence of Signal Propagation in the Cerebellar Circuit Revealed by High-Density Multielectrode Array Recordings

The cerebellum is one of the most connected structures of the central nervous system and receives inputs over an extended frequency range. Nevertheless, the frequency dependence of cerebellar cortical processing remains elusive. In this work, we characterized cerebellar cortex responsiveness to mossy fibers activation at different frequencies and reconstructed the spread of activity in the sagittal and coronal planes of acute mouse cerebellar slices using a high-throughput high-density multielectrode array (HD-MEA). The enhanced spatiotemporal resolution of HD-MEA revealed the frequency dependence and spatial anisotropy of cerebellar activation. Mossy fiber inputs reached the Purkinje cell layer even at the lowest frequencies, but the efficiency of transmission increased at higher frequencies. These properties, which are likely to descend from the topographic organization of local inhibition, intrinsic electroresponsiveness, and short-term synaptic plasticity, are critical elements that have to be taken into consideration to define the computational properties of the cerebellar cortex and its pathological alterations.

Expression of a Form of Cerebellar Motor Memory Requires Learned Alterations to the Activity of Inhibitory Molecular Layer Interneurons

Procedural memories formed in the cerebellum in response to motor errors depend on changes to Purkinje cell (PC) spiking patterns that correct movement when the erroneous context is repeated. Because molecular layer interneurons (MLIs) inhibit PCs, learning-induced changes to MLI output may participate in reshaping PC spiking patterns. However, it remains unclear whether error-driven learning alters MLI activity and whether such changes are necessary for the memory engram. We addressed this knowledge gap by measuring and manipulating MLI activity in the flocculus of both sexes of mice before and after vestibulo-ocular reflex (VOR) adaptation. We found that MLIs are activated during vestibular stimuli and that their population response exhibits a phase shift after the instantiation of gain-increase VOR adaptation, a type of error-driven learning thought to require climbing-fiber-mediated instructive signaling. Although acute optogenetic suppression of MLI activity did not affect baseline VOR performance, it negated the expression of gain-increase learning, demonstrating a specific role of MLI activity changes in motor memory expression. This effect was transitory; after a multiday consolidation period, the expression of VOR gain-increase learning was no longer sensitive to MLI activity suppression. Together, our results indicate that error-driven alteration of MLI activity is necessary for labile, climbing-fiber-induced motor memory expression.SIGNIFICANCE STATEMENT In the cerebellum, motor learning induces an associative memory of the sensorimotor context of an erroneous movement that, when recalled, results in a new pattern of output that improves subsequent trials of performance. Our study shows that error-driven motor learning induces changes to the activity pattern of cerebellar molecular layer interneurons (MLIs) and that this new pattern of activity is required to express the corrective motor memory.

Bicuculline restores frequency-dependent hippocampal I/E ratio and circuit function in PGC-1ɑ null mice

Altered inhibition/excitation (I/E) balance contributes to various brain disorders. Dysfunctional GABAergic interneurons enhance or reduce inhibition, resulting in I/E imbalances. Differences in short-term plasticity between excitation and inhibition cause frequency-dependence of the I/E ratio, which can be altered by GABAergic dysfunction. However, it is unknown whether I/E imbalances can be rescued pharmacologically using a single dose when the imbalance magnitude is frequency-dependent. Loss of PGC-1α (peroxisome proliferator activated receptor γ coactivator 1α) causes transcriptional dysregulation in hippocampal GABAergic interneurons. PGC-1α-/- slices have enhanced baseline inhibition onto CA1 pyramidal cells, causing increased I/E ratio and impaired circuit function. High frequency stimulation reduces the I/E ratio and recovers circuit function in PGC-1α-/- slices. Here we tested if using a low dose of bicuculline that can restore baseline I/E ratio can also rescue the frequency-dependent I/E imbalances in these mice. Remarkably, bicuculline did not reduce the I/E ratio below that of wild type during high frequency stimulation. Interestingly, bicuculline enhanced the paired-pulse ratio (PPR) of disynaptic inhibition without changing the monosynaptic inhibition PPR, suggesting that bicuculline modifies interneuron recruitment and not GABA release. Bicuculline improved CA1 output in PGC-1α-/- slices, enhancing EPSP-spike coupling to wild type levels at high and low frequencies. Our results show that it is possible to rescue frequency-dependent I/E imbalances in an animal model of transcriptional dysregulation with a single treatment.

What Can We Learn from Synaptic Connectivity Maps about Cerebellar Internal Models?

The cerebellum is classically associated with fine motor control, motor learning, and timing of actions. However, while its anatomy is well described and many synaptic plasticity have been identified, the computation performed by the cerebellar cortex is still debated. We, here, review recent advances on how the description of the functional synaptic connectivity between granule cells and Purkinje cells support the hypothesis that the cerebellum stores internal models of the body coordinates. We propose that internal models are specific of the task and of the locomotor context of each individual.

Short-Term Synaptic Plasticity Makes Neurons Sensitive to the Distribution of Presynaptic Population Firing Rates

The ability to discriminate spikes that encode a particular stimulus from spikes produced by background activity is essential for reliable information processing in the brain. We describe how synaptic short-term plasticity (STP) modulates the output of presynaptic populations as a function of the distribution of the spiking activity and find a strong relationship between STP features and sparseness of the population code, which could solve this problem. Furthermore, we show that feedforward excitation followed by inhibition (FF-EI), combined with target-dependent STP, promote substantial increase in the signal gain even for considerable deviations from the optimal conditions, granting robustness to this mechanism. A simulated neuron driven by a spiking FF-EI network is reliably modulated as predicted by a rate analysis and inherits the ability to differentiate sparse signals from dense background activity changes of the same magnitude, even at very low signal-to-noise conditions. We propose that the STP-based distribution discrimination is likely a latent function in several regions such as the cerebellum and the hippocampus.

Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum

The functional properties of cerebellar stellate cells and the way they regulate molecular layer activity are still unclear. We have measured stellate cells electroresponsiveness and their activation by parallel fiber bursts. Stellate cells showed intrinsic pacemaking, along with characteristic responses to depolarization and hyperpolarization, and showed a marked short-term facilitation during repetitive parallel fiber transmission. Spikes were emitted after a lag and only at high frequency, making stellate cells to operate as delay-high-pass filters. A detailed computational model summarizing these physiological properties allowed to explore different functional configurations of the parallel fiber-stellate cell-Purkinje cell circuit. Simulations showed that, following parallel fiber stimulation, Purkinje cells almost linearly increased their response with input frequency, but such an increase was inhibited by stellate cells, which leveled the Purkinje cell gain curve to its 4 Hz value. When reciprocal inhibitory connections between stellate cells were activated, the control of stellate cells over Purkinje cell discharge was maintained only at very high frequencies. These simulations thus predict a new role for stellate cells, which could endow the molecular layer with low-pass and band-pass filtering properties regulating Purkinje cell gain and, along with this, also burst delay and the burst-pause responses pattern.

Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways

The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented through various types of neural pathways interactively routing excitation and inhibition converged to PCs. Such tuning of excitation and inhibition, coming from the gating of specific pathways as well as short-term plasticity (STP) of the synapses, plays a dominant role in controlling the PC dynamics in terms of firing rate and spike timing. PCs receive cascade feedforward inputs from two major neural pathways: the first one is the feedforward excitatory pathway from granule cells (GCs) to PCs; the second one is the feedforward inhibition pathway from GCs, via molecular layer interneurons (MLIs), to PCs. The GC-PC pathway, together with short-term dynamics of excitatory synapses, has been a focus over past decades, whereas recent experimental evidence shows that MLIs also greatly contribute to controlling PC activity. Therefore, it is expected that the diversity of excitation gated by STP of GC-PC synapses, modulated by strong inhibition from MLI-PC synapses, can promote the computation performed by PCs. However, it remains unclear how these two neural pathways are interacted to modulate PC dynamics. Here using a computational model of PC network installed with these two neural pathways, we addressed this question to investigate the change of PC firing dynamics at the level of single cell and network. We show that the nonlinear characteristics of excitatory STP dynamics can significantly modulate PC spiking dynamics mediated by inhibition. The changes in PC firing rate, firing phase, and temporal spike pattern, are strongly modulated by these two factors in different ways. MLIs mainly contribute to variable delays in the postsynaptic action potentials of PCs while modulated by excitation STP. Notably, the diversity of synchronization and pause response in the PC network is governed not only by the balance of excitation and inhibition, but also by the synaptic STP, depending on input burst patterns. Especially, the pause response shown in the PC network can only emerge with the interaction of both pathways. Together with other recent findings, our results show that the interaction of feedforward pathways of excitation and inhibition, incorporated with synaptic short-term dynamics, can dramatically regulate the PC activities that consequently change the network dynamics of the cerebellar circuit.

It is well known that the dynamics of neuronal networks are controlled by various types of neural pathways that are interactively routing excitation and inhibition converged to postsynaptic neurons. In addition, gating of a specific neural pathway is enhanced by short-term plasticity of the synapses between neurons. However, it remains unclear how a combination of these factors, the strengths of excitation and inhibition, and their short-term dynamics respectively, contributes to the dynamics of single cells and neuronal networks. Using a network model of cerebellar Purkinje cells embedded with the feedforward excitatory pathway from granule cells and feedforward inhibition pathway of molecular layer interneurons. We show that the dynamics of firing rate, firing phase, and temporal spike pattern are notably yet differently modulated by these two pathways. At the single cell level, excitatory short-term plasticity nonlinearly modulates the input-output relationship of firing activity. At the network level, the diversity of synchronization and pause response is governed not only by the balance of excitation and inhibition, but also by synaptic short-term dynamics. Only when both neural pathways are incorporated, there is a strong pause response shown in the network. Our results, together with recent in vivo experimental observations in the cerebellum, show that the interaction of feedforward pathways of excitation and inhibition, together with synaptic short-term dynamics, can dramatically change the network dynamics of Purkinje cells.

Emerging connections between cerebellar development, behaviour and complex brain disorders

The human cerebellum has a protracted developmental timeline compared with the neocortex, expanding the window of vulnerability to neurological disorders. As the cerebellum is critical for motor behaviour, it is not surprising that most neurodevelopmental disorders share motor deficits as a common sequela. However, evidence gathered since the late 1980s suggests that the cerebellum is involved in motor and non-motor function, including cognition and emotion. More recently, evidence indicates that major neurodevelopmental disorders such as intellectual disability, autism spectrum disorder, attention-deficit hyperactivity disorder and Down syndrome have potential links to abnormal cerebellar development. Out of recent findings from clinical and preclinical studies, the concept of the 'cerebellar connectome' has emerged that can be used as a framework to link the role of cerebellar development to human behaviour, disease states and the design of better therapeutic strategies.

Climbing Fibers Provide Graded Error Signals in Cerebellar Learning

The cerebellum plays a critical role in coordinating and learning complex movements. Although its importance has been well recognized, the mechanisms of learning remain hotly debated. According to the classical cerebellar learning theory, depression of parallel fiber synapses instructed by error signals from climbing fibers, drives cerebellar learning. The uniqueness of long-term depression (LTD) in cerebellar learning has been challenged by evidence showing multi-site synaptic plasticity. In Purkinje cells, long-term potentiation (LTP) of parallel fiber synapses is now well established and it can be achieved with or without climbing fiber signals, making the role of climbing fiber input more puzzling. The central question is how individual Purkinje cells extract global errors based on climbing fiber input. Previous data seemed to demonstrate that climbing fibers are inefficient instructors, because they were thought to carry “binary” error signals to individual Purkinje cells, which significantly constrains the efficiency of cerebellar learning in several regards. In recent years, new evidence has challenged the traditional view of “binary” climbing fiber responses, suggesting that climbing fibers can provide graded information to efficiently instruct individual Purkinje cells to learn. Here we review recent experimental and theoretical progress regarding modulated climbing fiber responses in Purkinje cells. Analog error signals are generated by the interaction of varying climbing fibers inputs with simultaneous other synaptic input and with firing states of targeted Purkinje cells. Accordingly, the calcium signals which trigger synaptic plasticity can be graded in both amplitude and spatial range to affect the learning rate and even learning direction. We briefly discuss how these new findings complement the learning theory and help to further our understanding of how the cerebellum works.

Short-term plasticity at cerebellar granule cell to molecular layer interneuron synapses expands information processing

Information processing by cerebellar molecular layer interneurons (MLIs) plays a crucial role in motor behavior. MLI recruitment is tightly controlled by the profile of short-term plasticity (STP) at granule cell (GC)-MLI synapses. While GCs are the most numerous neurons in the brain, STP diversity at GC-MLI synapses is poorly documented. Here, we studied how single MLIs are recruited by their distinct GC inputs during burst firing. Using slice recordings at individual GC-MLI synapses of mice, we revealed four classes of connections segregated by their STP profile. Each class differentially drives MLI recruitment. We show that GC synaptic diversity is underlain by heterogeneous expression of synapsin II, a key actor of STP and that GC terminals devoid of synapsin II are associated with slow MLI recruitment. Our study reveals that molecular, structural and functional diversity across GC terminals provides a mechanism to expand the coding range of MLIs.

Inhibition gates supralinear Ca2+ signaling in Purkinje cell dendrites during practiced movements

Motor learning involves neural circuit modifications in the cerebellar cortex, likely through re-weighting of parallel fiber inputs onto Purkinje cells (PCs). Climbing fibers instruct these synaptic modifications when they excite PCs in conjunction with parallel fiber activity, a pairing that enhances climbing fiber-evoked Ca²⁺ signaling in PC dendrites. In vivo, climbing fibers spike continuously, including during movements when parallel fibers are simultaneously conveying sensorimotor information to PCs. Whether parallel fiber activity enhances climbing fiber Ca²⁺ signaling during motor behaviors is unknown. In mice, we found that inhibitory molecular layer interneurons (MLIs), activated by parallel fibers during practiced movements, suppressed parallel fiber enhancement of climbing fiber Ca²⁺ signaling in PCs. Similar results were obtained in acute slices for brief parallel fiber stimuli. Interestingly, more prolonged parallel fiber excitation revealed latent supralinear Ca²⁺ signaling. Therefore, the balance of parallel fiber and MLI input onto PCs regulates concomitant climbing fiber Ca²⁺ signaling.