The spatiotemporal organization of cerebellar network activity resolved by two-photon imaging of multiple single neurons

Developmental timing-dependent organization of synaptic connections between mossy fibers and granule cells in the cerebellum

The long-standing hypothesis that synapses between mossy fibers (MFs) and cerebellar granule cells (GCs) are organized according to the origins of MFs and locations of GC axons, parallel fibers (PFs), is supported by recent findings. However, the mechanisms of such organized synaptic connections remain unknown. Here, using our technique that enabled PF location-dependent labeling of GCs in mice, we confirmed that synaptic connections of GCs with specific MFs originating from the pontine nucleus (PN-MFs) and dorsal column nuclei (DCoN-MFs) were gently but differentially organized according to their PF locations. We then found that overall MF-GC synaptic connectivity was biased in a way that dendrites of GCs having nearby PFs tended to connect with the same MF terminals, implying that the MF origin- and PF location-dependent organization is associated with the overall biased MF-GC synaptic connectivity. Furthermore, the development of PN-MFs preceded that of DCoN-MFs, which matches the developmental sequence of GCs that preferentially connect with each type of these MFs. Thus, our results revealed that overall MF-GC synaptic connectivity is biased in terms of PF locations, and suggested that such connectivity is likely the result of synaptic formation between developmental timing-matched partners.

Full-scale scaffold model of the human hippocampus CA1 area

The increasing availability of quantitative data on the human brain is opening new avenues to study neural function and dysfunction, thus bringing us closer and closer to the implementation of digital twin applications for personalized medicine. Here we provide a resource to the neuroscience community: a computational method to generate full-scale scaffold model of human brain regions starting from microscopy images. We have benchmarked the method to reconstruct the CA1 region of a right human hippocampus, which accounts for about half of the entire right hippocampal formation. Together with 3D soma positioning we provide a connectivity matrix generated using a morpho-anatomical connection strategy based on axonal and dendritic probability density functions accounting for morphological properties of hippocampal neurons. The data and algorithms are supplied in a ready-to-use format, suited to implement computational models at different scales and detail.

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.

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.

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.

Projection-dependent heterogeneity of cerebellar granule cell calcium responses

Cerebellar granule cells (GCs) relay mossy fiber (MF) inputs to Purkinje cell dendrites via their axons, the parallel fibers (PFs), which are individually located at a given sublayer of the molecular layer (ML). Although a certain degree of heterogeneity among GCs has been recently reported, variability of GC responses to MF inputs has never been associated with their most notable structural variability, location of their projecting PFs in the ML. Here, we utilize an adeno-associated virus (AAV)-mediated labeling technique that enables us to categorize GCs according to the location of their PFs, and compare the Ca²⁺ responses to MF stimulations between three groups of GCs, consisting of either GCs having PFs at the deep (D-GCs), middle (M-GCs), or superficial (S-GCs) sublayer. Our structural analysis revealed that there was no correlation between position of GC soma in the GC layer and location of its PF in the ML, confirming that our AAV-mediated labeling was important to test the projection-dependent variability of the Ca²⁺ responses in GCs. We then found that the Ca²⁺ responses of D-GCs differed from those of M-GCs. Pharmacological experiments implied that the different Ca²⁺ responses were mainly attributable to varied distributions of GABA_A receptors (GABA_ARs) at the synaptic and extrasynaptic regions of GC dendrites. In addition to GABA_AR distributions, amounts of extrasynaptic NMDA receptors appear to be also varied, because Ca²⁺ responses were different between D-GCs and M-GCs when glutamate spillover was enhanced. Whereas the Ca²⁺ responses of S-GCs were mostly equivalent to those of D-GCs and M-GCs, the blockade of GABA uptake resulted in larger Ca²⁺ responses in S-GCs compared with D-GCs and M-GCs, implying existence of mechanisms leading to more excitability in S-GCs with increased GABA release. Thus, this study reveals MF stimulation-mediated non-uniform Ca²⁺ responses in the cerebellar GCs associated with the location of their PFs in the ML, and raises a possibility that combination of inherent functional variability of GCs and their specific axonal projection contributes to the information processing through the GCs.

Granular layEr Simulator: Design and Multi-GPU Simulation of the Cerebellar Granular Layer

In modern computational modeling, neuroscientists need to reproduce long-lasting activity of large-scale networks, where neurons are described by highly complex mathematical models. These aspects strongly increase the computational load of the simulations, which can be efficiently performed by exploiting parallel systems to reduce the processing times. Graphics Processing Unit (GPU) devices meet this need providing on desktop High Performance Computing. In this work, authors describe a novel Granular layEr Simulator development implemented on a multi-GPU system capable of reconstructing the cerebellar granular layer in a 3D space and reproducing its neuronal activity. The reconstruction is characterized by a high level of novelty and realism considering axonal/dendritic field geometries, oriented in the 3D space, and following convergence/divergence rates provided in literature. Neurons are modeled using Hodgkin and Huxley representations. The network is validated by reproducing typical behaviors which are well-documented in the literature, such as the center-surround organization. The reconstruction of a network, whose volume is 600 × 150 × 1,200 μm³ with 432,000 granules, 972 Golgi cells, 32,399 glomeruli, and 4,051 mossy fibers, takes 235 s on an Intel i9 processor. The 10 s activity reproduction takes only 4.34 and 3.37 h exploiting a single and multi-GPU desktop system (with one or two NVIDIA RTX 2080 GPU, respectively). Moreover, the code takes only 3.52 and 2.44 h if run on one or two NVIDIA V100 GPU, respectively. The relevant speedups reached (up to ~38× in the single-GPU version, and ~55× in the multi-GPU) clearly demonstrate that the GPU technology is highly suitable for realistic large network simulations.

Real Time Generation of Three Dimensional Patterns for Multiphoton Stimulation

The advent of optogenetics has revolutionized experimental research in the field of Neuroscience and the possibility to selectively stimulate neurons in 3D volumes has opened new routes in the understanding of brain dynamics and functions. The combination of multiphoton excitation and optogenetic methods allows to identify and excite specific neuronal targets by means of the generation of cloud of excitation points. The most widely employed approach to produce the points cloud is through a spatial light modulation (SLM) which works with a refresh rate of tens of Hz. However, the computational time requested to calculate 3D patterns ranges between a few seconds and a few minutes, strongly limiting the overall performance of the system. The maximum speed of SLM can in fact be employed either with high quality patterns embedded into pre-calculated sequences or with low quality patterns for real time update. Here, we propose the implementation of a recently developed compressed sensing Gerchberg-Saxton algorithm on a consumer graphical processor unit allowing the generation of high quality patterns at video rate. This, would in turn dramatically reduce dead times in the experimental sessions, and could enable applications previously impossible, such as the control of neuronal network activity driven by the feedback from single neurons functional signals detected through calcium or voltage imaging or the real time compensation of motion artifacts.

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.

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.

Adaptive optics microspectrometer for cross-correlation measurement of microfluidic flows

Mapping flows in vivo is essential for the investigation of cardiovascular pathologies in animal models. The limitation of optical-based methods, such as space-time cross correlation, is the scattering of light by the connective and fat components and the direct wave front distortion by large inhomogeneities in the tissue. Nonlinear excitation of the sample fluorescence helps us by reducing light scattering in excitation. However, there is still a limitation on the signal-background due to the wave front distortion. We develop a diffractive optical microscope based on a single spatial light modulator (SLM) with no movable parts. We combine the correction of wave front distortions to the cross-correlation analysis of the flow dynamics. We use the SLM to shine arbitrary patterns of spots on the sample, to correct their optical aberrations, to shift the aberration corrected spot array on the sample for the collection of fluorescence images, and to measure flow velocities from the cross-correlation functions computed between couples of spots. The setup and the algorithms are tested on various microfluidic devices. By applying the adaptive optics correction algorithm, it is possible to increase up to 5 times the signal-to-background ratio and to reduce approximately of the same ratio the uncertainty of the flow speed measurement. By working on grids of spots, we can correct different aberrations in different portions of the field of view, a feature that allows for anisoplanatic aberrations correction. Finally, being more efficient in the excitation, we increase the accuracy of the speed measurement by employing a larger number of spots in the grid despite the fact that the two-photon excitation efficiency scales as the fourth power of this number: we achieve a twofold decrease of the uncertainty and a threefold increase of the accuracy in the evaluation of the flow speed.

Hyperexcitability and Hyperplasticity Disrupt Cerebellar Signal Transfer in the IB2 KO Mouse Model of Autism

Autism spectrum disorders (ASDs) are pervasive neurodevelopmental conditions that often involve mutations affecting synaptic mechanisms. Recently, the involvement of cerebellum in ASDs has been suggested, but the underlying functional alterations remained obscure. We investigated single-neuron and microcircuit properties in IB2 (Islet Brain-2) KO mice of either sex. The IB2 gene (chr22q13.3 terminal region) deletion occurs in virtually all cases of Phelan-McDermid syndrome, causing autistic symptoms and a severe delay in motor skill acquisition. IB2 KO granule cells showed a larger NMDA receptor-mediated current and enhanced intrinsic excitability, raising the excitatory/inhibitory balance. Furthermore, the spatial organization of granular layer responses to mossy fibers shifted from a "Mexican hat" to a "stovepipe hat" profile, with stronger excitation in the core and weaker inhibition in the surround. Finally, the size and extension of long-term synaptic plasticity were remarkably increased. These results show for the first time that hyperexcitability and hyperplasticity disrupt signal transfer in the granular layer of IB2 KO mice, supporting cerebellar involvement in the pathogenesis of ASD.SIGNIFICANCE STATEMENT This article shows for the first time a complex set of alterations in the cerebellum granular layer of a mouse model [IB2 (Islet Brain-2) KO] of autism spectrum disorders. The IB2 KO in mice mimics the deletion of the corresponding gene in the Phelan-McDermid syndrome in humans. The changes reported here are centered on NMDA receptor hyperactivity, hyperplasticity, and hyperexcitability. These, in turn, increase the excitatory/inhibitory balance and alter the shape of center/surround structures that emerge in the granular layer in response to mossy fiber activity. These results support recent theories suggesting the involvement of cerebellum in autism spectrum disorders.

Physiology of the cerebellum

The cerebellum is a central brain structure deeply integrated into major loops with the cerebral cortex, brainstem, and spinal cord. The cerebellum shows a complex regional organization consisting of modules with sagittal orientation. The cerebellum takes part in motor control and its lesions cause a movement incoordination syndrome called ataxia. Recent observations also imply involvement of the cerebellum in cognition and executive control, with an impact on pathologies like dyslexia and autism. The cerebellum operates as a forward controller learning to predict the precise timing of correlated events. The physiologic mechanisms of cerebellar functioning are still the object of intense research. The signals entering the cerebellum through the mossy fibers are processed in the granular layer and transmitted to Purkinje cells, while a collateral pathway activates the deep cerebellar nuclei (DCN). Purkinje cells in turn inhibit DCN, so that the cerebellar cortex operates as a side loop controlling the DCN. Learning is now known to occur through synaptic plasticity at multiple synapses in the granular layer, molecular layer, and DCN, extending the original concept of the Motor Learning Theory that predicted a single form of plasticity at the synapse between parallel fibers and Purkinje cells under the supervision of climbing fibers deriving from the inferior olive. Coordination derives from the precise regulation of timing and gain in the different cerebellar modules. The investigation of cerebellar dynamics using advanced physiologic recordings and computational models is now providing new clues on how the cerebellar network performs its internal computations.

Population-scale organization of cerebellar granule neuron signaling during a visuomotor behavior

Granule cells at the input layer of the cerebellum comprise over half the neurons in the human brain and are thought to be critical for learning. However, little is known about granule neuron signaling at the population scale during behavior. We used calcium imaging in awake zebrafish during optokinetic behavior to record transgenically identified granule neurons throughout a cerebellar population. A significant fraction of the population was responsive at any given time. In contrast to core precerebellar populations, granule neuron responses were relatively heterogeneous, with variation in the degree of rectification and the balance of positive versus negative changes in activity. Functional correlations were strongest for nearby cells, with weak spatial gradients in the degree of rectification and the average sign of response. These data open a new window upon cerebellar function and suggest granule layer signals represent elementary building blocks under-represented in core sensorimotor pathways, thereby enabling the construction of novel patterns of activity for learning.

Simultaneous high-speed imaging and optogenetic inhibition in the intact mouse brain

Genetically encoded calcium indicators and optogenetic actuators can report and manipulate the activity of specific neuronal populations. However, applying imaging and optogenetics simultaneously has been difficult to establish in the mammalian brain, even though combining the techniques would provide a powerful approach to reveal the functional organization of neural circuits. Here, we developed a technique based on patterned two-photon illumination to allow fast scanless imaging of GCaMP6 signals in the intact mouse brain at the same time as single-photon optogenetic inhibition with Archaerhodopsin. Using combined imaging and electrophysiological recording, we demonstrate that single and short bursts of action potentials in pyramidal neurons can be detected in the scanless modality at acquisition frequencies up to 1 kHz. Moreover, we demonstrate that our system strongly reduces the artifacts in the fluorescence detection that are induced by single-photon optogenetic illumination. Finally, we validated our technique investigating the role of parvalbumin-positive (PV) interneurons in the control of spontaneous cortical dynamics. Monitoring the activity of cellular populations on a precise spatiotemporal scale while manipulating neuronal activity with optogenetics provides a powerful tool to causally elucidate the cellular mechanisms underlying circuit function in the intact mammalian brain.

Scanless functional imaging of hippocampal networks using patterned two-photon illumination through GRIN lenses

Patterned illumination through the phase modulation of light is increasingly recognized as a powerful tool to investigate biological tissues in combination with two-photon excitation and light-sensitive molecules. However, to date two-photon patterned illumination has only been coupled to traditional microscope objectives, thus limiting the applicability of these methods to superficial biological structures. Here, we show that phase modulation can be used to efficiently project complex two-photon light patterns, including arrays of points and large shapes, in the focal plane of graded index (GRIN) lenses. Moreover, using this approach in combination with the genetically encoded calcium indicator GCaMP6, we validate our system performing scanless functional imaging in rodent hippocampal networks in vivo ~1.2 mm below the brain surface. Our results open the way to the application of patterned illumination approaches to deep regions of highly scattering biological tissues, such as the mammalian brain.

Heterosynaptic GABAergic plasticity bidirectionally driven by the activity of pre- and postsynaptic NMDA receptors

Dynamic changes of the strength of inhibitory synapses play a crucial role in processing neural information and in balancing network activity. Here, we report that the efficacy of GABAergic connections between Golgi cells and granule cells in the cerebellum is persistently altered by the activity of glutamatergic synapses. This form of plasticity is heterosynaptic and is expressed as an increase (long-term potentiation, LTPGABA) or a decrease (long-term depression, LTDGABA) of neurotransmitter release. LTPGABA is induced by postsynaptic NMDA receptor activation, leading to calcium increase and retrograde diffusion of nitric oxide, whereas LTDGABA depends on presynaptic NMDA receptor opening. The sign of plasticity is determined by the activation state of target granule and Golgi cells during the induction processes. By controlling the timing of spikes emitted by granule cells, this form of bidirectional plasticity provides a dynamic control of the granular layer encoding capacity.

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.

Biphasic modulation of parallel fibre synaptic transmission by co-activation of presynaptic GABAA and GABAB receptors in mice

KEY POINTS

Many excitatory synapses co-express presynaptic GABAA and GABAB receptors, despite their opposing actions on synaptic transmission. It is still unclear how co-activation of these receptors modulates synapse function. We measured presynaptic GABA receptor function at parallel fibre synapses onto stellate cells in the cerebellum using whole-cell patch-clamp recording and photolytic uncaging of RuBi-GABA. Activation of presynaptic GABA receptors results in a transient (∼100 ms) enhancement of synaptic transmission (mediated by GABAA receptors) followed by a long lasting (>500 ms) inhibition of transmission (mediated by GABAB receptors). When activated just prior to high-frequency trains of stimulation, presynaptic GABAA and GABAB receptors work together to reduce short-term facilitation/enhance depression, altering the filtering properties of synaptic transmission. Inhibition of synaptic transmission by GABAB receptors is more sensitive to GABA than enhancement by GABAA receptors, suggesting GABAB receptors may be activated by ambient GABA or release from greater distances.

ABSTRACT

GABAA and GABAB receptors are co-expressed at many presynaptic terminals in the central nervous system. Previous studies have shown that GABAA receptors typically enhance vesicle release while GABAB receptors inhibit release. However, it is not clear how the competing actions of these receptors modulate synaptic transmission when co-activated, as is likely in vivo. We investigated this question at parallel fibre synapses in the cerebellum, which co-express presynaptic GABAA and GABAB receptors. In acute slices from C57BL/6 mice, we find that co-activation of presynaptic GABA receptors by photolytic uncaging of RuBi-GABA has a biphasic effect on EPSC amplitudes recorded from stellate cells. Synchronous and asynchronous EPSCs evoked within ∼100 ms of GABA uncaging were increased, while EPSCs evoked ∼300-600 ms after GABA uncaging were reduced compared to interleaved control sweeps. We confirmed these effects are presynaptic by measuring the paired-pulse ratio, variance of EPSC amplitudes, and response probability. During trains of high-frequency stimulation GABAA and GABAB receptors work together (rather than oppose one another) to reduce short-term facilitation when GABA is uncaged just prior to the onset of stimulation. We also find that GABAB receptor-mediated inhibition can be elicited by lower GABA concentrations than GABAA receptor-mediated enhancement of EPSCs, suggesting GABAB receptors may be selectively activated by ambient GABA or release from more distance synapses. These data suggest that GABA, acting through both presynaptic GABAA and GABAB receptors, modulate the amplitude and short-term plasticity of excitatory synapses, a result not possible from activation of either receptor type alone.

A Hybrid Model for the Computationally-Efficient Simulation of the Cerebellar Granular Layer

The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system) and its continuous counterpart (PDE system) obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables. Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least 270 times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround, and time-windowing.

Long-Term Spatiotemporal Reconfiguration of Neuronal Activity Revealed by Voltage-Sensitive Dye Imaging in the Cerebellar Granular Layer

Understanding the spatiotemporal organization of long-term synaptic plasticity in neuronal networks demands techniques capable of monitoring changes in synaptic responsiveness over extended multineuronal structures. Among these techniques, voltage-sensitive dye imaging (VSD imaging) is of particular interest due to its good spatial resolution. However, improvements of the technique are needed in order to overcome limits imposed by its low signal-to-noise ratio. Here, we show that VSD imaging can detect long-term potentiation (LTP) and long-term depression (LTD) in acute cerebellar slices. Combined VSD imaging and patch-clamp recordings revealed that the most excited regions were predominantly associated with granule cells (GrCs) generating EPSP-spike complexes, while poorly responding regions were associated with GrCs generating EPSPs only. The correspondence with cellular changes occurring during LTP and LTD was highlighted by a vector representation obtained by combining amplitude with time-to-peak of VSD signals. This showed that LTP occurred in the most excited regions lying in the core of activated areas and increased the number of EPSP-spike complexes, while LTD occurred in the less excited regions lying in the surround. VSD imaging appears to be an efficient tool for investigating how synaptic plasticity contributes to the reorganization of multineuronal activity in neuronal circuits.

An excitatory GABA loop operating in vivo

While it has been proposed that the conventional inhibitory neurotransmitter GABA can be excitatory in the mammalian brain, much remains to be learned concerning the circumstances and the cellular mechanisms governing potential excitatory GABA action. Using a combination of optogenetics and two-photon calcium imaging in vivo, we find that activation of chloride-permeable GABA_A receptors in parallel fibers (PFs) of the cerebellar molecular layer of adult mice causes parallel fiber excitation. Stimulation of PFs at submaximal stimulus intensities leads to GABA release from molecular layer interneurons (MLIs), thus creating a positive feedback loop that enhances excitation near the center of an activated PF bundle. Our results imply that elevated chloride concentration can occur in specific intracellular compartments of mature mammalian neurons and suggest an excitatory role for GABA_A receptors in the cerebellar cortex of adult mice.

The effect of desflurane on neuronal communication at a central synapse

Although general anesthetics are thought to modify critical neuronal functions, their impact on neuronal communication has been poorly examined. We have investigated the effect induced by desflurane, a clinically used general anesthetic, on information transfer at the synapse between mossy fibers and granule cells of cerebellum, where this analysis can be carried out extensively. Mutual information values were assessed by measuring the variability of postsynaptic output in relationship to the variability of a given set of presynaptic inputs. Desflurane synchronized granule cell firing and reduced mutual information in response to physiologically relevant mossy fibers patterns. The decrease in spike variability was due to an increased postsynaptic membrane excitability, which made granule cells more prone to elicit action potentials, and to a strengthened synaptic inhibition, which markedly hampered membrane depolarization. These concomitant actions on granule cells firing indicate that desflurane re-shapes the transfer of information between neurons by providing a less informative neurotransmission rather than completely silencing neuronal activity.

High-throughput spatial light modulation two-photon microscopy for fast functional imaging

The optical monitoring of multiple single neuron activities requires high-throughput parallel acquisition of signals at millisecond temporal resolution. To this aim, holographic two-photon microscopy (2PM) based on spatial light modulators (SLMs) has been developed in combination with standard laser scanning microscopes. This requires complex coordinate transformations for the generation of holographic patterns illuminating the points of interest. We present a simpler and fully digital setup (SLM-2PM) which collects three-dimensional two-photon images by only exploiting the SLM. This configuration leads to an accurate placement of laser beamlets over small focal volumes, eliminating mechanically moving parts and making the system stable over long acquisition times. Fluorescence signals are diffraction limited and are acquired through a pixelated detector, setting the actual limit to the acquisition rate. High-resolution structural images were acquired by raster-scanning the sample with a regular grid of excitation focal volumes. These images allowed the selection of the structures to be further investigated through an interactive operator-guided selection process. Functional signals were collected by illuminating all the preselected points with a single hologram. This process is exemplified for high-speed (up to 1 kHz) two-photon calcium imaging on acute cerebellar slices.

Optical dissection of brain circuits with patterned illumination through the phase modulation of light

Brain function relies on electrical signaling among ensembles of neurons. These signals are encoded in space - neurons are organized in complex three-dimensional networks - and in time-cells generate electrical signals on a millisecond scale. How the spatial and temporal structure of these signals controls higher brain functions is largely unknown. The recent advent of novel molecules that manipulate and monitor electrical activity in genetically identified cells provides, for the first time, the ability to causally test the contribution of specific cell subpopulations in these complex brain phenomena. However, most of the commonly used approaches are limited in their ability to illuminate brain tissue with high spatial and temporal precision. In this review article, we focus on one technique, patterned illumination through the phase modulation of light using liquid crystal spatial light modulators (LC-SLMs), which has the potential to overcome some of the major limitations of current experimental approaches.

Coding of stimulus strength via analog calcium signals in Purkinje cell dendrites of awake mice

The climbing fiber input to Purkinje cells acts as a teaching signal by triggering a massive influx of dendritic calcium that marks the occurrence of instructive stimuli during cerebellar learning. Here, we challenge the view that these calcium spikes are all-or-none and only signal whether the instructive stimulus has occurred, without providing parametric information about its features. We imaged ensembles of Purkinje cell dendrites in awake mice and measured their calcium responses to periocular airpuffs that serve as instructive stimuli during cerebellar-dependent eyeblink conditioning. Information about airpuff duration and pressure was encoded probabilistically across repeated trials, and in two additional signals in single trials: the synchrony of calcium spikes in the Purkinje cell population, and the amplitude of the calcium spikes, which was modulated by a non-climbing fiber pathway. These results indicate that calcium-based teaching signals in Purkinje cells contain analog information that encodes the strength of instructive stimuli trial-by-trial.

DOI:http://dx.doi.org/10.7554/eLife.03663.001

A region of the brain known as the cerebellum plays a key role in learning how to anticipate an event. For example, if you know that a puff of air is going to be directed at your eye, it's a good idea to close it in advance. However, how much you need to close it depends on how strong that puff of air is. A very strong puff might require closing the eye completely to protect it. In contrast, it is probably better to only partially close the eye if you know a lighter puff of air is coming, so that you can still see.

Extensive research has focused on how neurons in and around the cerebellum work together to achieve this goal. When an event—such as a puff of air—occurs, signals are sent to large neurons in the cerebellum, called Purkinje cells, by ‘climbing fibers’. However, climbing fibers were thought to be able to respond in only two ways: either they fire in a single burst to signal that an event has occurred, or they don't fire. It was therefore unclear how the finer details of the event (for example, the strength of the puff of air) are transmitted to the cerebellum.

Najafi et al. imaged the level of calcium in the cerebellum of mice, as this indicates how active the neurons are. When a puff of air was directed at the eyes of the mice, Najafi et al. saw that the size of the response of the Purkinje cells corresponded with how big the puff of air was. Najafi et al. show that the size of this response, which is based mostly on input from the climbing fibers, is also influenced by input from an additional unknown source.

These findings show that Purkinje cells of the cerebellum receive detailed information about the nature of an event, such as a puff of air. What remains to be seen is whether the cerebellum uses this information to learn the correct response, that is how hard to blink to avoid the expected puff.

DOI:http://dx.doi.org/10.7554/eLife.03663.002

Regulation of output spike patterns by phasic inhibition in cerebellar granule cells

The complex interplay of multiple molecular mechanisms taking part to synaptic integration is hard to disentangle experimentally. Therefore, we developed a biologically realistic computational model based on the rich set of data characterizing the cerebellar glomerulus microcircuit. A specific issue was to determine the relative role of phasic and tonic inhibition in dynamically regulating granule cell firing, which has not been clarified yet. The model comprised the excitatory mossy fiber—granule cell and the inhibitory Golgi cell—granule cell synapses and accounted for vesicular release processes, neurotransmitter diffusion and activation of different receptor subtypes. Phasic inhibition was based on stochastic GABA release and spillover causing activation of two major classes of postsynaptic receptors, α1 and α6, while tonic inhibition was based on steady regulation of a Cl⁻ leakage. The glomerular microcircuit model was validated against experimental responses to mossy fiber bursts while metabotropic receptors were blocked. Simulations showed that phasic inhibition controlled the number of spikes during burst transmission but predicted that it specifically controlled time-related parameters (firing initiation and conclusion and first spike precision) when the relative phase of excitation and inhibition was changed. In all conditions, the overall impact of α6 was larger than that of α1 subunit-containing receptors. However, α1 receptors controlled granule cell responses in a narrow ±10 ms band while α6 receptors showed broader ±50 ms tuning. Tonic inhibition biased these effects without changing their nature substantially. These simulations imply that phasic inhibitory mechanisms can dynamically regulate output spike patterns, as well as calcium influx and NMDA currents, at the mossy fiber—granule cell relay of cerebellum without the intervention of tonic inhibition.

Electron multiplying charge-coupled device-based fluorescence cross-correlation spectroscopy for blood velocimetry on zebrafish embryos

Biomedical issues in vasculogenesis and cardiogenesis require methods to follow hemodynamics with high spatial (micrometers) and time (milliseconds) resolution. At the same time, we need to follow relevant morphogenetic processes on large fields of view. Fluorescence cross-correlation spectroscopy coupled to scanning or wide-field microscopy meets these needs but has limited flexibility in the excitation pattern. To overcome this limitation, we develop here a two-photon two-spots setup coupled to an all-reflective near-infrared (NIR) optimized scanning system and to an electron multiplying charge-coupled device. Two NIR laser spots are spaced at adjustable micron-size distances (1 to 50 μm) by means of a Twyman-Green interferometer and repeatedly scanned on the sample, allowing acquisition of information on flows at 4 ms-3 μm time-space resolution in parallel on an extended field of view. We analyze the effect of nonhomogeneous and variable flow on the cross-correlation function by numerical simulations and show exemplary application of this setup in studies of blood flow in zebrafish embryos in vivo. By coupling the interferometer with the scanning mirrors and by computing the cross-correlation function of fluorescent red blood cells, we are able to map speed patterns in embryos' vessels.

The organization of plasticity in the cerebellar cortex: from synapses to control

The cerebellum is thought to play a critical role in procedural learning, but the relationship between this function and the underlying cellular and synaptic mechanisms remains largely speculative. At present, at least nine forms of long-term synaptic and nonsynaptic plasticity (some of which are bidirectional) have been reported in the cerebellar cortex and deep cerebellar nuclei. These include long-term potentiation (LTP) and long-term depression at the mossy fiber-granule cell synapse, at the synapses formed by parallel fibers, climbing fibers, and molecular layer interneurons on Purkinje cells, and at the synapses formed by mossy fibers and Purkinje cells on deep cerebellar nuclear cells, as well as LTP of intrinsic excitability in granule cells, Purkinje cells, and deep cerebellar nuclear cells. It is suggested that the complex properties of cerebellar learning would emerge from the distribution of plasticity in the network and from its dynamic remodeling during the different phases of learning. Intrinsic and extrinsic factors may hold the key to explain how the different forms of plasticity cooperate to select specific transmission channels and to regulate the signal-to-noise ratio through the cerebellar cortex. These factors include regulation of neuronal excitation by local inhibitory networks, engagement of specific molecular mechanisms by spike bursts and theta-frequency oscillations, and gating by external neuromodulators. Therefore, a new and more complex view of cerebellar plasticity is emerging with respect to that predicted by the original "Motor Learning Theory," opening issues that will require experimental and computational testing.