Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer

The granular layer, which mainly consists of granule and Golgi cells, is the first stage of the cerebellar cortex and processes spatiotemporal information transmitted by mossy fiber inputs with a wide variety of firing patterns. To study its dynamics at multiple time scales in response to inputs approximating real spatiotemporal patterns, we constructed a large-scale 3D network model of the granular layer. Patterned mossy fiber activity induces rhythmic Golgi cell activity that is synchronized by shared parallel fiber input and by gap junctions. This leads to long distance synchrony of Golgi cells along the transverse axis, powerfully regulating granule cell firing by imposing inhibition during a specific time window. The essential network mechanisms, including tunable Golgi cell oscillations, on-beam inhibition and NMDA receptors causing first winner keeps winning of granule cells, illustrate how fundamental properties of the granule layer operate in tandem to produce (1) well timed and spatially bound output, (2) a wide dynamic range of granule cell firing and (3) transient and coherent gating oscillations. These results substantially enrich our understanding of granule cell layer processing, which seems to promote spatial group selection of granule cell activity as a function of timing of mossy fiber input

Editorial: The olivo-cerebellar system

Investigation on the olivo-cerebellum system has attained a high level of sophistication leading to define several structural and functional properties of neurons, synapses, connections and circuits. Research has expanded and deepened in so many directions, and so many theories and models have been proposed, that an ensemble review of the matter is now neede

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

Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network

Reconstructing neuronal microcircuits through computational models is fundamental to simulate local neuronal dynamics. Here a scaffold model of the cerebellum has been developed in order to flexibly place neurons in space, connect them synaptically, and endow neurons and synapses with biologically-grounded mechanisms. The scaffold model can keep neuronal morphology separated from network connectivity, which can in turn be obtained from convergence/divergence ratios and axonal/dendritic field 3D geometries. We first tested the scaffold on the cerebellar microcircuit, which presents a challenging 3D organization, at the same time providing appropriate datasets to validate emerging network behaviors. The scaffold was designed to integrate the cerebellar cortex with deep cerebellar nuclei (DCN), including different neuronal types: Golgi cells, granule cells, Purkinje cells, stellate cells, basket cells, and DCN principal cells. Mossy fiber inputs were conveyed through the glomeruli. An anisotropic volume (0.077 mm3) of mouse cerebellum was reconstructed, in which point-neuron models were tuned toward the specific discharge properties of neurons and were connected by exponentially decaying excitatory and inhibitory synapses. Simulations using both pyNEST and pyNEURON showed the emergence of organized spatio-temporal patterns of neuronal activity similar to those revealed experimentally in response to background noise and burst stimulation of mossy fiber bundles. Different configurations of granular and molecular layer connectivity consistently modified neuronal activation patterns, revealing the importance of structural constraints for cerebellar network functioning. The scaffold provided thus an effective workflow accounting for the complex architecture of the cerebellar network. In principle, the scaffold can incorporate cellular mechanisms at multiple levels of detail and be tuned to test different structural and functional hypotheses. A future implementation using detailed 3D multi-compartment neuron models and dynamic synapses will be needed to investigate the impact of single neuron properties on network computation

High frequency field potentials of the cerebellar cortex

The cerebellum plays a crucial role in motor coordination along with basal ganglia and the motor areas of the cerebral cortex. Both somatosensory and the cerebro-cerebral pathways bring in massive amounts of neural information to the cerebellum. The output of the cerebellar cortex projects to various motor cortices as well as down to the spinal cord to make its contributions to the motor function. The origin and function of the field potential oscillations in the cerebellum, especially in the high frequencies, have not been explored sufficiently. The primary objective of this study was to investigate the spatio-temporal characteristics of high frequency field potentials (150-350Hz) in the cerebellar cortex in a behavioral context. To this end, the paramedian lobule in rats was recorded using micro electro-corticogram (µ-ECoG) electrode arrays while the animal performed a lever press task using the forelimb. The phase synchrony analysis shows that the high frequency oscillations recorded at multiple points across the paramedian cortex episodically synchronize immediately before and desynchronize during the lever press. The electrode contacts were grouped according to their temporal course of phase synchrony around the time of lever press. Contact groups presented patches with slightly stronger synchrony values in the medio-lateral direction, and did not appear to form parasagittal zones. Spatiotemporal synchrony of high frequency field potentials has not been reported at such large-scales previously in the cerebellar cortex

Neurones glycinergiques et transmission inhibitrice dans les noyaux cérébelleux

The cerebellum is composed of a three-layered cortex and of nuclei and is responsible for the learned fine control of posture and movements. I combined a genetic approach (based on the use of transgenic mouse lines) with anatomical tracings, immunohistochemical stainings, electrophysiological recordings and optogenetic stimulations to establish the distinctive characteristics of the inhibitory neurons of the cerebellar nuclei and to detail their connectivity and their role in the cerebellar circuitry.We showed that the glycinergic inhibitory neurons of the cerebellar nuclei constitute a distinct neuronal population and are characterized by their mixed inhibitory GABAergic/glycinergic phenotype. Those inhibitory neurons are also distinguished by their axonal plexus which includes a local arborization with the cerebellar nuclei where they contact principal output neurons and a projection to the granular layer of the cerebellar cortex where they end onto Golgi cells dendrites. Finally, the inhibitory neurons of the cerebellar nuclei receive inhibitory afferents from Purkinje cells and may be contacted by mossy fibers or climbing fibers.We provided the first evidence of functional mixed transmission in the cerebellar nuclei and the first demonstration of a mixed inhibitory nucleo-cortical projection. Overall, our data establish the inhibitory neurons as the third cellular component of the cerebellar nuclei. Their importance in the modular organization of the cerebellum and their impact on sensory-motor integration need to be confirmed by optogenetic experiments in vivo.Le cervelet, composé d'un cortex et de noyaux, est responsable du contrôle moteur fin des mouvements et de la posture. En combinant une approche génétique (basée sur l'utilisation de lignées de souris transgéniques) avec des traçages anatomiques, des marquages immunohistochimiques et des expériences d'électrophysiologie et d'optogénétique, nous établissons les caractères distinctifs des neurones inhibiteurs des noyaux cérébelleux et en détaillons la connectivité ainsi que les fonctions dans le circuit cérébelleux. Les neurones inhibiteurs glycinergiques des noyaux profonds constituent une population de neurones distincts des autres types cellulaires identifiables par leur phénotype inhibiteur mixte GABAergique/glycinergique. Ces neurones se distinguent également par leur plexus axonal qui comporte une arborisation locale dans les noyaux cérébelleux où ils contactent les neurones principaux et une projection vers le cortex cérébelleux où ils contactent les cellules de Golgi. Ces neurones inhibiteurs reçoivent également des afférences inhibitrices des cellules de Purkinje et pourraient être contactés par les fibres moussues ou les fibres grimpantes.Nous apportons ainsi la première étude d'une transmission mixte fonctionnelle par les neurones inhibiteurs des noyaux cérébelleux, projetant à la fois dans les noyaux et le cortex cérébelleux. L'ensemble de nos données établissent les neurones inhibiteurs mixtes des noyaux cérébelleux comme la troisième composante cellulaire des noyaux profonds. Leur importance dans l'organisation modulaire du cervelet, ainsi que leur impact sur l'intégration sensori-motrice, devront être confirmés par des études optogénétiques in vivo

Adaptive Robotic Control Driven by a Versatile Spiking Cerebellar Network

The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.European Union (Human Brain Project) REALNET FP7-ICT270434 CEREBNET FP7-ITN238686 HBP-60410

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

High frequency burst firing of granule cells ensures transmission at the parallel fiber to purkinje cell synapse at the cost of temporal coding.

Cerebellar granule cells (GrCs) convey information from mossy fibers (MFs) to Purkinje cells (PCs) via their parallel fibers (PFs). MF to GrC signaling allows transmission of frequencies up to 1 kHz and GrCs themselves can also fire bursts of action potentials with instantaneous frequencies up to 1 kHz. So far, in the scientific literature no evidence has been shown that these high-frequency bursts also exist in awake, behaving animals. More so, it remains to be shown whether such high-frequency bursts can transmit temporally coded information from MFs to PCs and/or whether these patterns of activity contribute to the spatiotemporal filtering properties of the GrC layer. Here, we show that, upon sensory stimulation in both un-anesthetized rabbits and mice, GrCs can show bursts that consist of tens of spikes at instantaneous frequencies over 800 Hz. In vitro recordings from individual GrC-PC pairs following high-frequency stimulation revealed an overall low initial release probability of ~0.17. Nevertheless, high-frequency burst activity induced a short-lived facilitation to ensure signaling within the first few spikes, which was rapidly followed by a reduction in transmitter release. The facilitation rate among individual GrC-PC pairs was heterogeneously distributed and could be classified as either "reluctant" or "responsive" according to their release characteristics. Despite the variety of efficacy at individual connections, grouped activity in GrCs resulted in a linear relationship between PC response and PF burst duration at frequencies up to 300 Hz allowing rate coding to persist at the network level. Together, these findings support the hypothesis that the cerebellar granular layer acts as a spatiotemporal filter between MF input and PC output (D'Angelo and De Zeeuw, 2009)