A model of the olivo-cerebellar system as a temporal pattern generator

Linking cellular-level phenomena to brain architecture: the case of spiking cerebellar controllers

Linking cellular-level phenomena to brain architecture and behavior is a holy grail for theoretical and computational neuroscience. Advances in neuroinformatics have recently allowed scientists to embed spiking neural networks of the cerebellum with realistic neuron models and multiple synaptic plasticity rules into sensorimotor controllers. By minimizing the distance (error) between the desired and the actual sensory state, and exploiting the sensory prediction, the cerebellar network acquires knowledge about the body-environment interaction and generates corrective signals. In doing so, the cerebellum implements a generalized computational algorithm, allowing it "to learn to predict the timing between correlated events" in a rich set of behavioral contexts. Plastic changes evolve trial by trial and are distributed over multiple synapses, regulating the timing of neuronal discharge and fine-tuning high-speed movements on the millisecond timescale. Thus, spiking cerebellar built-in controllers, among various computational approaches to studying cerebellar function, are helping to reveal the cellular-level substrates of network learning and signal coding, opening new frontiers for predictive computing and autonomous learning in robots.

Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs

Prior applications of the cerebellar adaptive filter model have included a range of tasks within simulated and robotic systems. However, this has been limited to systems driven by continuous signals. Here, the adaptive filter model of the cerebellum is applied to the control of a system driven by spiking inputs by considering the problem of controlling muscle force. The performance of the standard adaptive filter algorithm is compared with the algorithm with a modified learning rule that minimizes inputs and a simple proportional-integral-derivative (PID) controller. Control performance is evaluated in terms of the number of spikes, the accuracy of spike input locations, and the accuracy of muscle force output. Results show that the cerebellar adaptive filter model can be applied without change to the control of systems driven by spiking inputs. The cerebellar algorithm results in good agreement between input spikes and force outputs and significantly improves on a PID controller. Input minimization can be used to reduce the number of spike inputs, but at the expense of a decrease in accuracy of spike input location and force output. This work extends the applications of the cerebellar algorithm and demonstrates the potential of the adaptive filter model to be used to improve functional electrical stimulation muscle control.

Consensus Paper: Ataxic Gait

The aim of this consensus paper is to discuss the roles of the cerebellum in human gait, as well as its assessment and therapy. Cerebellar vermis is critical for postural control. The cerebellum ensures the mapping of sensory information into temporally relevant motor commands. Mental imagery of gait involves intrinsically connected fronto-parietal networks comprising the cerebellum. Muscular activities in cerebellar patients show impaired timing of discharges, affecting the patterning of the synergies subserving locomotion. Ataxia of stance/gait is amongst the first cerebellar deficits in cerebellar disorders such as degenerative ataxias and is a disabling symptom with a high risk of falls. Prolonged discharges and increased muscle coactivation may be related to compensatory mechanisms and enhanced body sway, respectively. Essential tremor is frequently associated with mild gait ataxia. There is growing evidence for an important role of the cerebellar cortex in the pathogenesis of essential tremor. In multiple sclerosis, balance and gait are affected due to cerebellar and spinal cord involvement, as a result of disseminated demyelination and neurodegeneration impairing proprioception. In orthostatic tremor, patients often show mild-to-moderate limb and gait ataxia. The tremor generator is likely located in the posterior fossa. Tandem gait is impaired in the early stages of cerebellar disorders and may be particularly useful in the evaluation of pre-ataxic stages of progressive ataxias. Impaired inter-joint coordination and enhanced variability of gait temporal and kinetic parameters can be grasped by wearable devices such as accelerometers. Kinect is a promising low cost technology to obtain reliable measurements and remote assessments of gait. Deep learning methods are being developed in order to help clinicians in the diagnosis and decision-making process. Locomotor adaptation is impaired in cerebellar patients. Coordinative training aims to improve the coordinative strategy and foot placements across strides, cerebellar patients benefiting from intense rehabilitation therapies. Robotic training is a promising approach to complement conventional rehabilitation and neuromodulation of the cerebellum. Wearable dynamic orthoses represent a potential aid to assist gait. The panel of experts agree that the understanding of the cerebellar contribution to gait control will lead to a better management of cerebellar ataxias in general and will likely contribute to use gait parameters as robust biomarkers of future clinical trials.

Protein kinase Cγ in cerebellar Purkinje cells regulates Ca2+-activated large-conductance K+ channels and motor coordination

The cerebellum, the site where protein kinase C (PKC) was discovered, contains the highest amount of PKCγ in the central nervous system. PKCγ in the cerebellum is exclusively confined to Purkinje cells (PCs), sole outputs from the cerebellar cortex. Systemic PKCγ-knockout mice show impaired motor coordination; however, the cause of motor defects remains unknown. Here we show that activation of PKCγ suppresses the Ca²⁺-activated large-conductance K⁺ (BK) channels located along the PC dendrites. A consequential increase in the membrane resistance attenuates electrical signal decay during propagation, resulting in an altered complex spike waveform. Our results suggest that synaptically activated PKCγ in PCs plays a critical role in motor coordination by negative modulation of BK currents.

The cerebellum, the site where protein kinase C (PKC) was first discovered, contains the highest amount of PKC in the central nervous system, with PKCγ being the major isoform. Systemic PKCγ-knockout (KO) mice showed impaired motor coordination and deficient pruning of surplus climbing fibers (CFs) from developing cerebellar Purkinje cells (PCs). However, the physiological significance of PKCγ in the mature cerebellum and the cause of motor incoordination remain unknown. Using adeno-associated virus vectors targeting PCs, we showed that impaired motor coordination was restored by re-expression of PKCγ in mature PKCγ-KO mouse PCs in a kinase activity–dependent manner, while normal motor coordination in mature Prkcg^fl/fl mice was impaired by the Cre-dependent removal of PKCγ from PCs. Notably, the rescue or removal of PKCγ from mature PKCγ-KO or Prkcg^fl/fl mice, respectively, did not affect the CF innervation profile of PCs, suggesting the presence of a mechanism distinct from multiple CF innervation of PCs for the motor defects in PKCγ-deficient mice. We found marked potentiation of Ca²⁺-activated large-conductance K⁺ (BK) channel currents in PKCγ-deficient mice, as compared to wild-type mice, which decreased the membrane resistance, resulting in attenuation of the electrical signal during the propagation and significant alterations of the complex spike waveform. These changes in PKCγ-deficient mice were restored by the rescue of PKCγ or pharmacological suppression of BK channels. Our results suggest that PKCγ is a critical regulator that negatively modulates BK currents in PCs, which significantly influences PC output from the cerebellar cortex and, eventually, motor coordination.

Implicit manual and oculomotor sequence learning in developmental language disorder

Procedural memory functioning in developmental language disorder (DLD) has largely been investigated by examining implicit sequence learning by the manual motor system. This study examined whether poor sequence learning in DLD is present in the oculomotor domain. Twenty children with DLD and 20 age-matched typically developing (TD) children were presented with a serial reaction time (SRT) task. On the task, a visual stimulus repeatedly appears in different positions on a computer display which prompts a manual response. The children were unaware that on the first three blocks and final block of trials, the visual stimulus followed a sequence. On the fourth block, the stimulus appeared in random positions. Manual reaction times (RT) and saccadic amplitudes were recorded, which assessed sequence learning in the manual and oculomotor domains, respectively. Manual RT were sensitive to sequence learning for the TD group, but not the DLD group. For the TD group, manual RT increased when the random block was presented. This was not the case for the DLD group. In the oculomotor domain, sequence learning was present in both groups. Specifically, sequence learning was found to modulate saccadic amplitudes resulting in both DLD and TD children being able to anticipate the location of the visual stimulus. Overall, the study indicates that not all aspects of the procedural memory system are equally impaired in DLD.

A neural circuit state change underlying skilled movements

In motor neuroscience, state changes are hypothesized to time-lock neural assemblies coordinating complex movements, but evidence for this remains slender. We tested whether a discrete change from more autonomous to coherent spiking underlies skilled movement by imaging cerebellar Purkinje neuron complex spikes in mice making targeted forelimb-reaches. As mice learned the task, millimeter-scale spatiotemporally coherent spiking emerged ipsilateral to the reaching forelimb, and consistent neural synchronization became predictive of kinematic stereotypy. Before reach onset, spiking switched from more disordered to internally time-locked concerted spiking and silence. Optogenetic manipulations of cerebellar feedback to the inferior olive bi-directionally modulated neural synchronization and reaching direction. A simple model explained the reorganization of spiking during reaching as reflecting a discrete bifurcation in olivary network dynamics. These findings argue that to prepare learned movements, olivo-cerebellar circuits enter a self-regulated, synchronized state promoting motor coordination. State changes facilitating behavioral transitions may generalize across neural systems.

Contributions of Cerebellar White Matter Microstructure to Social Difficulty in Nonverbal Learning Disability

Emerging evidence suggests that the cerebellum may contribute to variety of cognitive capacities, including social cognition. Nonverbal learning disability (NVLD) is characterized by visual-spatial and social impairment. Recent functional neuroimaging studies have shown that children with NVLD have altered cerebellar resting-state functional connectivity, which is associated with various symptom domains. However, little is known about cerebellar white matter microstructure in NVLD and whether it contributes to social deficits. Twenty-seven children (12 with NVLD, 15 typically developing (TD)) contributed useable diffusion tensor imaging data. Tract-based spatial statistics (TBSS) were used to quantify fractional anisotropy (FA) in the cerebellar peduncles. Parents completed the Child Behavior Checklist, providing a measure of social difficulty. Children with NVLD had greater fractional anisotropy in the left and right inferior cerebellar peduncle. Furthermore, right inferior cerebellar peduncle FA was associated with social impairment as measured by the Child Behavior Checklist Social Problems subscale. Finally, the association between NVLD diagnosis and greater social impairment was mediated by right inferior cerebellar peduncle FA. These findings provide additional evidence that the cerebellum contributes both to social cognition and to the pathophysiology of NVLD.

Purkinje Cell Activity Determines the Timing of Sensory-Evoked Motor Initiation

Cerebellar neurons can signal sensory and motor events, but their role in active sensorimotor processing remains unclear. We record and manipulate Purkinje cell activity during a task that requires mice to rapidly discriminate between multisensory and unisensory stimuli before motor initiation. Neuropixels recordings show that both sensory stimuli and motor initiation are represented by short-latency simple spikes. Optogenetic manipulation of short-latency simple spikes abolishes or delays motor initiation in a rate-dependent manner, indicating a role in motor initiation and its timing. Two-photon calcium imaging reveals task-related coherence of complex spikes organized into conserved alternating parasagittal stripes. The coherence of sensory-evoked complex spikes increases with learning and correlates with enhanced temporal precision of motor initiation. These results suggest that both simple spikes and complex spikes govern sensory-driven motor initiation: simple spikes modulate its latency, and complex spikes refine its temporal precision, providing specific cellular substrates for cerebellar sensorimotor control.

Biologically Plausible Class Discrimination Based Recurrent Neural Network Training for Motor Pattern Generation

Biological brain stores massive amount of information. Inspired by features of the biological memory, we propose an algorithm to efficiently store different classes of spatio-temporal information in a Recurrent Neural Network (RNN). A given spatio-temporal input triggers a neuron firing pattern, known as an attractor, and it conveys information about the class to which the input belongs. These attractors are the basic elements of the memory in our RNN. Preparing a set of good attractors is the key to efficiently storing temporal information in an RNN. We achieve this by means of enhancing the “separation” and “approximation” properties associated with the attractors, during the RNN training. We furthermore elaborate how these attractors can trigger an action via the readout in the RNN, similar to the sensory motor action processing in the cerebellum cortex. We show how different voice commands by different speakers trigger hand drawn impressions of the spoken words, by means of our separation and approximation based learning. The method further recognizes the gender of the speaker. The method is evaluated on the TI-46 speech data corpus, and we have achieved 98.6% classification accuracy on the TI-46 digit corpus.

Using subthreshold events to characterize the functional architecture of the electrically coupled inferior olive network

The electrical connectivity in the inferior olive (IO) nucleus plays an important role in generating well-timed spiking activity. Here we combined electrophysiological and computational approaches to assess the functional organization of the IO nucleus in mice. Spontaneous fast and slow subthreshold events were commonly encountered during in vitro recordings. We show that whereas the fast events represent intrinsic regenerative activity, the slow events reflect the electrical connectivity between neurons (‘spikelets’). Recordings from cell pairs revealed the synchronized occurrence of distinct groups of spikelets; their rate and distribution enabled an accurate estimation of the number of connected cells and is suggestive of a clustered organization. This study thus provides a new perspective on the functional and structural organization of the olivary nucleus and a novel experimental and theoretical approach to study electrically coupled networks.

Variability and directionality of inferior olive neuron dendrites revealed by detailed 3D characterization of an extensive morphological library

The inferior olive (IO) is an evolutionarily conserved brain stem structure and its output activity plays a major role in the cerebellar computation necessary for controlling the temporal accuracy of motor behavior. The precise timing and synchronization of IO network activity has been attributed to the dendro-dendritic gap junctions mediating electrical coupling within the IO nucleus. Thus, the dendritic morphology and spatial arrangement of IO neurons governs how synchronized activity emerges in this nucleus. To date, IO neuron structural properties have been characterized in few studies and with small numbers of neurons; these investigations have described IO neurons as belonging to two morphologically distinct types, “curly” and “straight”. In this work we collect a large number of individual IO neuron morphologies visualized using different labeling techniques and present a thorough examination of their morphological properties and spatial arrangement within the olivary neuropil. Our results show that the extensive heterogeneity in IO neuron dendritic morphologies occupies a continuous range between the classically described “curly” and “straight” types, and that this continuum is well represented by a relatively simple measure of “straightness”. Furthermore, we find that IO neuron dendritic trees are often directionally oriented. Combined with an examination of cell body density distributions and dendritic orientation of adjacent IO neurons, our results suggest that the IO network may be organized into groups of densely coupled neurons interspersed with areas of weaker coupling.

Long-Lasting Response Changes in Deep Cerebellar Nuclei in vivo Correlate With Low-Frequency Oscillations

The deep cerebellar nuclei (DCN) have been suggested to play a critical role in sensorimotor learning and some forms of long-term synaptic plasticity observed in vitro have been proposed as a possible substrate. However, till now it was not clear whether and how DCN neuron responses manifest long-lasting changes in vivo. Here, we have characterized DCN unit responses to tactile stimulation of the facial area in anesthetized mice and evaluated the changes induced by theta-sensory stimulation (TSS), a 4 Hz stimulation pattern that is known to induce plasticity in the cerebellar cortex in vivo. DCN units responded to tactile stimulation generating bursts and pauses, which reflected combinations of excitatory inputs most likely relayed by mossy fiber collaterals, inhibitory inputs relayed by Purkinje cells, and intrinsic rebound firing. Interestingly, initial bursts and pauses were often followed by stimulus-induced oscillations in the peri-stimulus time histograms (PSTH). TSS induced long-lasting changes in DCN unit responses. Spike-related potentiation and suppression (SR-P and SR-S), either in units initiating the response with bursts or pauses, were correlated with stimulus-induced oscillations. Fitting with resonant functions suggested the existence of peaks in the theta-band (burst SR-P at 9 Hz, pause SR-S at 5 Hz). Optogenetic stimulation of the cerebellar cortex altered stimulus-induced oscillations suggesting that Purkinje cells play a critical role in the circuits controlling DCN oscillations and plasticity. This observation complements those reported before on the granular and molecular layers supporting the generation of multiple distributed plasticities in the cerebellum following naturally patterned sensory entrainment. The unique dependency of DCN plasticity on circuit oscillations discloses a potential relationship between cerebellar learning and activity patterns generated in the cerebellar network.

Temporal Processing in Audition: Insights from Music

Music is a curious example of a temporally patterned acoustic stimulus, and a compelling pan-cultural phenomenon. This review strives to bring some insights from decades of music psychology and sensorimotor synchronization (SMS) literature into the mainstream auditory domain, arguing that musical rhythm perception is shaped in important ways by temporal processing mechanisms in the brain. The feature that unites these disparate disciplines is an appreciation of the central importance of timing, sequencing, and anticipation. Perception of musical rhythms relies on an ability to form temporal predictions, a general feature of temporal processing that is equally relevant to auditory scene analysis, pattern detection, and speech perception. By bringing together findings from the music and auditory literature, we hope to inspire researchers to look beyond the conventions of their respective fields and consider the cross-disciplinary implications of studying auditory temporal sequence processing. We begin by highlighting music as an interesting sound stimulus that may provide clues to how temporal patterning in sound drives perception. Next, we review the SMS literature and discuss possible neural substrates for the perception of, and synchronization to, musical beat. We then move away from music to explore the perceptual effects of rhythmic timing in pattern detection, auditory scene analysis, and speech perception. Finally, we review the neurophysiology of general timing processes that may underlie aspects of the perception of rhythmic patterns. We conclude with a brief summary and outlook for future research.

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.

The Potential Role of Gap Junctional Plasticity in the Regulation of State

Electrical synapses are the functional correlate of gap junctions and allow transmission of small molecules and electrical current between coupled neurons. Instead of static pores, electrical synapses are actually plastic, similar to chemical synapses. In the thalamocortical system, gap junctions couple inhibitory neurons that are similar in their biochemical profile, morphology, and electrophysiological properties. We postulate that electrical synaptic plasticity among inhibitory neurons directly interacts with the switching between different firing patterns in a state-dependent and type-dependent manner. In neuronal networks, electrical synapses may function as a modifiable resonance feedback system that enables stable oscillations. Furthermore, the plasticity of electrical synapses may play an important role in regulation of state, synchrony, and rhythmogenesis in the mammalian thalamocortical system, similar to chemical synaptic plasticity. Based on their plasticity, rich diversity, and specificity, electrical synapses are thus likely to participate in the control of consciousness and attention.

In vivo analysis of synaptic activity in cerebellar nuclei neurons unravels the efficacy of excitatory inputs

KEY POINTS

Cerebellar nuclei (CN) neurons can be classified into four groups according to their action potential (AP) waveform, corresponding to four types of neurons previously characterized. Half of the APs are generated by excitatory events, suggesting that excitatory inputs play a key role in generating CN outputs. Analysis of post-synaptic potentials reveals that the probability of excitatory inputs generating an AP is 0.1. The input from climbing fibre collaterals is characterized by a pair of synaptic potentials with a distinct interpair interval of 4.5 ms. The probability of climbing fibre collaterals initiating an AP in CN neurons is 0.15.

ABSTRACT

It is commonly agreed that the main function of the cerebellar system is to provide well-timed signals used for the execution of motor commands or prediction of sensory inputs. This function is manifested as a temporal sequence of spiking that should be expressed in the cerebellar nuclei (CN) projection neurons. Whether spiking activity is generated by excitation or release from inhibition is still a hotly debated issue. In an attempt to resolve this debate, we recorded intracellularly from CN neurons in anaesthetized mice and performed an analysis of synaptic activity that yielded a number of important observations. First, we demonstrate that CN neurons can be classified into four groups. Second, shape-index plots of the excitatory events suggest that they are distributed over the entire dendritic tree. Third, the rise time of excitatory events is linearly related to amplitude, suggesting that all excitatory events contribute equally to the generation of action potentials (APs). Fourth, we identified a temporal pattern of spontaneous excitatory events that represent climbing fibre inputs and confirm the results by direct stimulation and analysis on harmaline-evoked activity. Finally, we demonstrate that the probability of excitatory inputs generating an AP is 0.1 yet half of the APs are generated by excitatory events. Moreover, the probability of a presumably spontaneous climbing fibre input generating an AP is higher, reaching a mean population value of 0.15. In view of these results, the mode of synaptic integration at the level of the CN should be re-considered.

Electrical Coupling and Synchronized Subthreshold Oscillations in the Inferior Olive of the Rhesus Macaque

Inferior olive (IO) neurons are critical for motor coordination and exhibit oscillations in membrane potential that are subthreshold for spiking. The prevalence, coherence, and continuity of those subthreshold oscillations (STOs) depend upon resonant interactions between neighboring neurons supported by electrical coupling. Many studies of the olivocerebellar system in rodents, in which STOs were related to tremor, whisking, and licking, fueled a debate over whether IO STOs were relevant for primates whose repertoire of movement is generally less periodic. The debate was never well informed due to the lack of a direct examination of the physiological properties of primate IO neurons. Here, we obtained dual patch-clamp recordings of neighboring IO neurons from young adult macaques in brainstem slices and compared them to identical recordings from rats. Macaque IO neurons exhibited an equivalent prevalence of continuous STOs as rats (45 vs 54%, respectively). However, macaque STOs were slower (1-4 Hz) and did not overlap with the dominant 4-9 Hz frequency of rats. The slower STO frequency of macaques was at least partially due to a prolonged membrane time constant and increased membrane capacitance that could be attributed to stronger electrical coupling and greater total dendritic length. The presence of synchronized STOs in the IO of adult macaques, coincident with strong and prevalent electrical coupling, answers a fundamental outstanding question in cerebellar neuroscience and is consistent with a prominent role for synchronized oscillation in primate sensory-motor control.

SIGNIFICANCE STATEMENT

It was debated whether inferior olive (IO) neurons of primates behave as synchronized oscillators as was found for rodents using intracellular, optical, and multielectrode recordings. An inability to resolve this issue using single-Purkinje cell extracellular recordings in monkeys limited our understanding of timing mechanisms in the primate brain. Using dual whole-cell recordings from the IO of young adult rhesus macaques in acutely prepared brainstem slices, our work demonstrates that pairs of primate IO neurons show synchronized oscillations in membrane potential. The findings have strong mechanistic and translational relevance, as IO activation has been implicated in humans' perceptual timing of sensory events and motricity.

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.

Long Pauses in Cerebellar Interneurons in Anesthetized Animals

Are long pauses in the firing of cerebellar interneurons (CINs) related to Purkinje cell (PC) pauses? If PC pauses affect the larger network, then we should find a close relationship between CIN pauses and those in PCs. We recorded activity of 241 cerebellar cortical neurons (206 CINs and 35 PCs) in three anesthetized cats. One fifth of the CINs and more than half of the PCs were identified as pausing. Pauses in CINs and PCs showed some differences: CIN mean pause length was shorter, and, after pauses, only CINs had sustained reduction in their firing rate (FR). Almost all pausing CINs fell into same cluster when we used different methods of clustering CINs by their spontaneous activity. The mean spontaneous firing rate of that cluster was approximately 53 Hz. We also examined cross-correlations in simultaneously recorded neurons. Of 39 cell pairs examined, 14 (35 %) had cross-correlations significantly different from those expected by chance. Almost half of the pairs with two CINs showed statistically significant negative correlations. In contrast, PC/CIN pairs did not often show significant effects in the cross-correlation (12/15 pairs). However, for both CIN/CIN and PC/CIN pairs, pauses in one unit tended to correspond to a reduction in the firing rate of the adjacent unit. In our view, our results support the possibility that previously reported PC bistability is part of a larger network response and not merely a biophysical property of PCs. Any functional role for PC bistability should probably be sought in the context of the broader network.

Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in.

Contribution of Cerebellar Loops to Action Timing

Recent studies of sensorimotor processing have benefited from decision-making paradigms that emphasize the selection of appropriate movements. Selecting when to make those responses, or action timing, is important as well. Although the cerebellum is commonly viewed as a controller of movement dynamics, its role in action timing is also firmly supported. Several lines of research have now extended this idea. Anatomical findings have revealed connections between the cerebellum and broader timing circuits, neurophysiological results have suggested mechanisms for timing within its microcircuitry, and theoretical work has indicated how temporal signals are processed through it and decoded by its targets. These developments are inspiring renewed studies of the role of the cerebellar loops in action timing.

Chronic imaging of movement-related Purkinje cell calcium activity in awake behaving mice

Purkinje cells (PCs) are a major site of information integration and plasticity in the cerebellum, a brain region involved in motor task refinement. Thus PCs provide an ideal location for studying the mechanisms necessary for cerebellum-dependent motor learning. Increasingly, sophisticated behavior tasks, used in combination with genetic reporters and effectors of activity, have opened up the possibility of studying cerebellar circuits during voluntary movement at an unprecedented level of quantitation. However, current methods used to monitor PC activity do not take full advantage of these advances. For example, single-unit or multiunit electrode recordings, which provide excellent temporal information regarding electrical activity, only monitor a small population of cells and can be quite invasive. Bolus loading of cell-permeant calcium (Ca(2+)) indicators is short-lived, requiring same-day imaging immediately after surgery and/or indicator injection. Genetically encoded Ca(2+) indicators (GECIs) overcome many of these limits and have garnered considerable use in many neuron types but only limited use in PCs. Here we employed these indicators to monitor Ca(2+) activity in PCs over several weeks. We could repeatedly image from the same cerebellar regions across multiple days and observed stable activity. We used chronic imaging to monitor PC activity in crus II, an area previously linked to licking behavior, and identified a region of increased activity at the onset of licking. We then monitored this same region after training tasks to initiate voluntary licking behavior in response to different sensory stimuli. In all cases, PC Ca(2+) activity increased at the onset of rhythmic licking.

The role of cerebellar circuitry alterations in the pathophysiology of autism spectrum disorders

The cerebellum has been repeatedly implicated in gene expression, rodent model and post-mortem studies of autism spectrum disorder (ASD). How cellular and molecular anomalies of the cerebellum relate to clinical manifestations of ASD remains unclear. Separate circuits of the cerebellum control different sensorimotor behaviors, such as maintaining balance, walking, making eye movements, reaching, and grasping. Each of these behaviors has been found to be impaired in ASD, suggesting that multiple distinct circuits of the cerebellum may be involved in the pathogenesis of patients' sensorimotor impairments. We will review evidence that the development of these circuits is disrupted in individuals with ASD and that their study may help elucidate the pathophysiology of sensorimotor deficits and core symptoms of the disorder. Preclinical studies of monogenetic conditions associated with ASD also have identified selective defects of the cerebellum and documented behavioral rescues when the cerebellum is targeted. Based on these findings, we propose that cerebellar circuits may prove to be promising targets for therapeutic development aimed at rescuing sensorimotor and other clinical symptoms of different forms of ASD.

Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum

The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

A novel inhibitory nucleo-cortical circuit controls cerebellar Golgi cell activity

The cerebellum, a crucial center for motor coordination, is composed of a cortex and several nuclei. The main mode of interaction between these two parts is considered to be formed by the inhibitory control of the nuclei by cortical Purkinje neurons. We now amend this view by showing that inhibitory GABA-glycinergic neurons of the cerebellar nuclei (CN) project profusely into the cerebellar cortex, where they make synaptic contacts on a GABAergic subpopulation of cerebellar Golgi cells. These spontaneously firing Golgi cells are inhibited by optogenetic activation of the inhibitory nucleo-cortical fibers both in vitro and in vivo. Our data suggest that the CN may contribute to the functional recruitment of the cerebellar cortex by decreasing Golgi cell inhibition onto granule cells.

Changes in complex spike activity during classical conditioning

The cerebellar cortex is necessary for adaptively timed conditioned responses (CRs) in eyeblink conditioning. During conditioning, Purkinje cells acquire pause responses or "Purkinje cell CRs" to the conditioned stimuli (CS), resulting in disinhibition of the cerebellar nuclei (CN), allowing them to activate motor nuclei that control eyeblinks. This disinhibition also causes inhibition of the inferior olive (IO), via the nucleo-olivary pathway (N-O). Activation of the IO, which relays the unconditional stimulus (US) to the cortex, elicits characteristic complex spikes in Purkinje cells. Although Purkinje cell activity, as well as stimulation of the CN, is known to influence IO activity, much remains to be learned about the way that learned changes in simple spike firing affects the IO. In the present study, we analyzed changes in simple and complex spike firing, in extracellular Purkinje cell records, from the C3 zone, in decerebrate ferrets undergoing training in a conditioning paradigm. In agreement with the N-O feedback hypothesis, acquisition resulted in a gradual decrease in complex spike activity during the conditioned stimulus, with a delay that is consistent with the long N-O latency. Also supporting the feedback hypothesis, training with a short interstimulus interval (ISI), which does not lead to acquisition of a Purkinje cell CR, did not cause a suppression of complex spike activity. In contrast, observations that extinction did not lead to a recovery in complex spike activity and the irregular patterns of simple and complex spike activity after the conditioned stimulus are less conclusive.

Bidirectional modulation of deep cerebellar nuclear cells revealed by optogenetic manipulation of inhibitory inputs from Purkinje cells

In the mammalian cerebellum, deep cerebellar nuclear (DCN) cells convey all information from cortical Purkinje cells (PCs) to premotor nuclei and other brain regions. However, how DCN cells integrate inhibitory input from PCs with excitatory inputs from other sources has been difficult to assess, in part due to the large spatial separation between cortical PCs and their target cells in the nuclei. To circumvent this problem we have used a Cre-mediated genetic approach to generate mice in which channelrhodopsin-2 (ChR2), fused with a fluorescent reporter, is selectively expressed by GABAergic neurons, including PCs. In recordings from brain slice preparations from this model, mammalian PCs can be robustly depolarized and discharged by brief photostimulation. In recordings of postsynaptic DCN cells, photostimulation of PC axons induces a strong inhibition that resembles these cells' responses to focal electrical stimulation, but without a requirement for the glutamate receptor blockers typically applied in such experiments. In this optogenetic model, laser pulses as brief as 1 ms can reliably induce an inhibition that shuts down the spontaneous spiking of a DCN cell for ∼50 ms. If bursts of such brief light pulses are delivered, a fixed pattern of bistable bursting emerges. If these pulses are delivered continuously to a spontaneously bistable cell, the immediate response to such photostimulation is inhibitory in the cell's depolarized state and excitatory when the membrane has repolarized; a less regular burst pattern then persists after stimulation has been terminated. These results indicate that the spiking activity of DCN cells can be bidirectionally modulated by the optically activated synaptic inhibition of cortical PCs.

The ever-changing electrical synapse

A wealth of research has revealed that electrical synapses in the central nervous system exhibit a high degree of plasticity. Several recent studies, particularly in the retina and inferior olive, highlight this plasticity. Three classes of mechanisms can alter electrical coupling over time courses ranging from milliseconds to days. Changes of membrane conductance through synaptic input or spiking activity shunt current and decouple neurons on the millisecond time scale. Such activity can also alter coupling symmetry, rectifying electrical synapses. More stable rectification can be accomplished through molecular asymmetry of the synapse itself. On the minutes time scale, changes in connexin phosphorylation can change coupling quasi-stably with an order of magnitude dynamic range. On the hours to days time scale, changes in expression level of connexins alter coupling through the course of circadian time, over developmental time, or in response to tissue injury. Combined, all of these mechanisms allow electrical coupling to be highly dynamic, changing in response to demands at the whole network level, in small portions of a network, or at the level of an individual synapse.

Realistic modeling of neurons and networks: towards brain simulation

Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

Cerebellar inhibitory input to the inferior olive decreases electrical coupling and blocks subthreshold oscillations

GABAergic projection neurons in the cerebellar nuclei (CN) innervate the inferior olive (IO) that in turn is the source of climbing fibers targeting Purkinje neurons in the cerebellar cortex. Anatomical evidence suggests that CN synapses modulate electrical coupling between IO neurons. In vivo studies indicate that they are also involved in controlling synchrony and rhythmicity of IO neurons. Here, we demonstrate using virally targeted channelrhodopsin in the cerebellar nucleo-olivary neurons that synaptic input can indeed modulate both the strength and symmetry of electrical coupling between IO neurons and alter network activity. Similar synaptic modifications of electrical coupling are likely to occur in other brain regions, where rapid modification of the spatiotemporal features of the coupled networks is needed to adequately respond to behavioral demands.

Synaptically induced long-term modulation of electrical coupling in the inferior olive

Electrical coupling mediated by gap junctions is widespread in the mammalian CNS, and the interplay between chemical and electrical synapses on the millisecond timescale is crucial for determining patterns of synchrony in many neural circuits. Here we show that activation of glutamatergic synapses drives long-term depression of electrical coupling between neurons of the inferior olive. We demonstrate that this plasticity is not triggered by postsynaptic spiking alone and that it requires calcium entry following synaptic NMDA receptor activation. These results reveal that glutamatergic synapses can instruct plasticity at electrical synapses, providing a means for excitatory inputs to homeostatically regulate the long-term dynamics of microzones in olivocerebellar circuits.

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Chemical synapses trigger long-term depression of inferior olive electrical coupling

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Depression of electrical coupling requires NMDAR activation and calcium entry

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Plasticity is not triggered by postsynaptic spiking alone and EPSPs remain unchanged

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Excitatory inputs can thus homeostatically regulate synchrony patterns in the olive

The olivo-cerebellar system: a key to understanding the functional significance of intrinsic oscillatory brain properties

The reflexological view of brain function (Sherrington, 1906) has played a crucial role in defining both the nature of connectivity and the role of the synaptic interactions among neuronal circuits. One implicit assumption of this view, however, has been that CNS function is fundamentally driven by sensory input. This view was questioned as early as the beginning of the last century when a possible role for intrinsic activity in CNS function was proposed by Thomas Graham Brow (Brown, 1911, 1914). However, little progress was made in addressing intrinsic neuronal properties in vertebrates until the discovery of calcium conductances in vertebrate central neurons leading dendritic electroresponsiveness (Llinás and Hess, 1976; Llinás and Sugimori, 1980a,b) and subthreshold neuronal oscillation in mammalian inferior olive (IO) neurons (Llinás and Yarom, 1981a,b). This happened in parallel with a similar set of findings concerning invertebrate neuronal system (Marder and Bucher, 2001). The generalization into a more global view of intrinsic rhythmicity, at forebrain level, occurred initially with the demonstration that the thalamus has similar oscillatory properties (Llinás and Jahnsen, 1982) and the ionic properties responsible for some oscillatory activity were, in fact, similar to those in the IO (Jahnsen and Llinás, 1984; Llinás, 1988). Thus, lending support to the view that not only motricity, but cognitive properties, are organized as coherent oscillatory states (Pare et al., 1992; Singer, 1993; Hardcastle, 1997; Llinás et al., 1998; Varela et al., 2001).

Emergence of a 600-Hz buzz UP state Purkinje cell firing in alert mice

Purkinje cell (PC) firing represents the sole output from the cerebellar cortex onto the deep cerebellar and vestibular nuclei. Here, we explored the different modes of PC firing in alert mice by extracellular recording. We confirm the existence of a tonic and/or bursting and quiescent modes corresponding to UP and DOWN state, respectively. We demonstrate the existence of a novel 600-Hz buzz UP state of firing characterized by simple spikes (SS) of very small amplitude. Climbing fiber (CF) input is able to switch the 600-Hz buzz to the DOWN state, as for the classical UP-to-DOWN state transition. Conversely, the CF input can initiate a typical SS pattern terminating into 600-Hz buzz. The 600-Hz buzz was transiently suppressed by whisker pad stimulation demonstrating that it remained responsive to peripheral input. It must not be mistaken for a DOWN state or the sign of PC inhibition. Complex spike (CS) frequency was increased during the 600-Hz buzz, indicating that this PC output actively contributes to the cerebello-olivary loop by triggering a disinhibition of the inferior olive. During the 600-Hz buzz, the first depolarizing component of the CS was reduced and the second depolarizing component was suppressed. Consistent with our experimental observations, using a 559-compartment single-PC model - in which PC UP state (of about -43mV) was obtained by the combined action of large tonic AMPA conductances and counterbalancing GABAergic inhibition - removal of this inhibition produced the 600-Hz buzz; the simulated buzz frequency decreased following an artificial CS.

Long-term depression as a model of cerebellar plasticity

Long-term depression (LTD) here concerned is persistent attenuation of transmission efficiency from a bundle of parallel fibers to a Purkinje cell. Uniquely, LTD is induced by conjunctive activation of the parallel fibers and the climbing fiber that innervates that Purkinje cell. Cellular and molecular processes underlying LTD occur postsynaptically. In the 1960s, LTD was conceived as a theoretical possibility and in the 1980s, substantiated experimentally. Through further investigations using various pharmacological or genetic manipulations of LTD, a concept was formed that LTD plays a major role in learning capability of the cerebellum (referred to as "Marr-Albus-Ito hypothesis"). In this chapter, following a historical overview, recent intensive investigations of LTD are reviewed. Complex signal transduction and receptor recycling processes underlying LTD are analyzed, and roles of LTD in reflexes and voluntary movements are defined. The significance of LTD is considered from viewpoints of neural network modeling. Finally, the controversy arising from the recent finding in a few studies that whereas LTD is blocked pharmacologically or genetically, motor learning in awake behaving animals remains seemingly unchanged is examined. We conjecture how this mismatch arises, either from a methodological problem or from a network nature, and how it might be resolved.

Decorrelation learning in the cerebellum: computational analysis and experimental questions

Many cerebellar models use a form of synaptic plasticity that implements decorrelation learning. Parallel fibers carrying signals positively correlated with climbing-fiber input have their synapses weakened (long-term depression), whereas those carrying signals negatively correlated with climbing input have their synapses strengthened (long-term potentiation). Learning therefore ceases when all parallel-fiber signals have been decorrelated from climbing-fiber input. This is a computationally powerful rule for supervised learning and can be cast in a spike-timing dependent plasticity form for comparison with experimental evidence. Decorrelation learning is particularly well suited to sensory prediction, for example, in the reafference problem where external sensory signals are interfered with by reafferent signals from the organism's own movements, and the required circuit appears similar to the one found to mediate classical eye blink conditioning. However, for certain stimuli, avoidance is a much better option than simple prediction, and decorrelation learning can also be used to acquire appropriate avoidance movements. One example of a stimulus to be avoided is retinal slip that degrades visual processing, and decorrelation learning appears to play a role in the vestibulo-ocular reflex that stabilizes gaze in the face of unpredicted head movements. Decorrelation learning is thus suitable for both sensory prediction and motor control. It may also be well suited for generic spatial and temporal coordination, because of its ability to remove the unwanted side effects of movement. Finally, because it can be used with any kind of time-varying signal, the cerebellum could play a role in cognitive processing.

Motor thalamus integration of cortical, cerebellar and basal ganglia information: implications for normal and parkinsonian conditions

Motor thalamus (Mthal) is implicated in the control of movement because it is strategically located between motor areas of the cerebral cortex and motor-related subcortical structures, such as the cerebellum and basal ganglia (BG). The role of BG and cerebellum in motor control has been extensively studied but how Mthal processes inputs from these two networks is unclear. Specifically, there is considerable debate about the role of BG inputs on Mthal activity. This review summarizes anatomical and physiological knowledge of the Mthal and its afferents and reviews current theories of Mthal function by discussing the impact of cortical, BG and cerebellar inputs on Mthal activity. One view is that Mthal activity in BG and cerebellar-receiving territories is primarily "driven" by glutamatergic inputs from the cortex or cerebellum, respectively, whereas BG inputs are modulatory and do not strongly determine Mthal activity. This theory is steeped in the assumption that the Mthal processes information in the same way as sensory thalamus, through interactions of modulatory inputs with a single driver input. Another view, from BG models, is that BG exert primary control on the BG-receiving Mthal so it effectively relays information from BG to cortex. We propose a new "super-integrator" theory where each Mthal territory processes multiple driver or driver-like inputs (cortex and BG, cortex and cerebellum), which are the result of considerable integrative processing. Thus, BG and cerebellar Mthal territories assimilate motivational and proprioceptive motor information previously integrated in cortico-BG and cortico-cerebellar networks, respectively, to develop sophisticated motor signals that are transmitted in parallel pathways to cortical areas for optimal generation of motor programmes. Finally, we briefly review the pathophysiological changes that occur in the BG in parkinsonism and generate testable hypotheses about how these may affect processing of inputs in the Mthal.

Transient dynamics and rhythm coordination of inferior olive spatio-temporal patterns

The inferior olive (IO) is a neural network belonging to the olivo-cerebellar system whose neurons are coupled with electrical synapses and display subthreshold oscillations and spiking activity. The IO is frequently proposed as the generator of timing signals to the cerebellum. Electrophysiological and imaging recordings show that the IO network generates complex spatio-temporal patterns. The generation and modulation of coherent spiking activity in the IO is one key issue in cerebellar research. In this work, we build a large scale IO network model of electrically coupled conductance-based neurons to study the emerging spatio-temporal patterns of its transient neuronal activity. Our modeling reproduces and helps to understand important phenomena observed in IO in vitro and in vivo experiments, and draws new predictions regarding the computational properties of this network and the associated cerebellar circuits. The main factors studied governing the collective dynamics of the IO network were: the degree of electrical coupling, the extent of the electrotonic connections, the presence of stimuli or regions with different excitability levels and the modulatory effect of an inhibitory loop (IL). The spatio-temporal patterns were analyzed using a discrete wavelet transform to provide a quantitative characterization. Our results show that the electrotonic coupling produces quasi-synchronized subthreshold oscillations over a wide dynamical range. The synchronized oscillatory activity plays the role of a timer for a coordinated representation of spiking rhythms with different frequencies. The encoding and coexistence of several coordinated rhythms is related to the different clusterization and coherence of transient spatio-temporal patterns in the network, where the spiking activity is commensurate with the quasi-synchronized subthreshold oscillations. In the presence of stimuli, different rhythms are encoded in the spiking activity of the IO neurons that nevertheless remains constrained to a commensurate value of the subthreshold frequency. The stimuli induced spatio-temporal patterns can reverberate for long periods, which contributes to the computational properties of the IO. We also show that the presence of regions with different excitability levels creates sinks and sources of coordinated activity which shape the propagation of spike wave fronts. These results can be generalized beyond IO studies, as the control of wave pattern propagation is a highly relevant problem in the context of normal and pathological states in neural systems (e.g., related to tremor, migraine, epilepsy) where the study of the modulation of activity sinks and sources can have a potential large impact.

Strength and timing of motor responses mediated by rebound firing in the cerebellar nuclei after Purkinje cell activation

The cerebellum refines the accuracy and timing of motor performance. How it encodes information to perform these functions is a major topic of interest. We performed whole cell and extracellular recordings of Purkinje cells (PCs) and cerebellar nuclei neurons (CNs) in vivo, while activating PCs with light in transgenic mice. We show for the first time that graded activation of PCs translates into proportional CN inhibition and induces rebound activity in CNs, which is followed by graded motor contractions timed to the cessation of the stimulus. Moreover, activation of PC ensembles led to disinhibition of climbing fiber activity, which coincided with rebound activity in CNs. Our data indicate that cessation of concerted activity in ensembles of PCs can regulate both timing and strength of movements via control of rebound activity in CNs.

The contribution of brain sub-cortical loops in the expression and acquisition of action understanding abilities

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Focusing on cortical areas is too restrictive to explain action understanding ability.

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We propose that sub-cortical areas support action understanding ability.

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Cortical and sub-cortical processes allow acquisition of action understanding ability.

Research on action understanding in cognitive neuroscience has led to the identification of a wide “action understanding network” mainly encompassing parietal and premotor cortical areas. Within this cortical network mirror neurons are critically involved implementing a neural mechanism according to which, during action understanding, observed actions are reflected in the motor patterns for the same actions of the observer. We suggest that focusing only on cortical areas and processes could be too restrictive to explain important facets of action understanding regarding, for example, the influence of the observer's motor experience, the multiple levels at which an observed action can be understood, and the acquisition of action understanding ability. In this respect, we propose that aside from the cortical action understanding network, sub-cortical processes pivoting on cerebellar and basal ganglia cortical loops could crucially support both the expression and the acquisition of action understanding abilities. Within the paper we will discuss how this extended view can overcome some limitations of the “pure” cortical perspective, supporting new theoretical predictions on the brain mechanisms underlying action understanding that could be tested by future empirical investigations.

Linking oscillations in cerebellar circuits

In many neuroscience fields, the study of local and global rhythmicity has been receiving increasing attention. These network influences could directly impact on how neuronal groups interact together, organizing for different contexts. The cerebellar cortex harbors a variety of such local circuit rhythms, from the rhythms in the cerebellar cortex per se, or those dictated from important afferents. We present here certain cerebellar oscillatory phenomena that have been recorded in rodents and primates. Those take place in a range of frequencies: from the more known oscillations in the 4-25 Hz band, such as the olivocerebellar oscillatory activity and the granule cell layer oscillations, to the more recently reported slow (<1 Hz oscillations), and the fast (>150 Hz) activity in the Purkinje cell layer. Many of these oscillations appear spontaneously in the circuits, and are modulated by behavioral imperatives. We review here how those oscillations are recorded, some of their modulatory mechanisms, and also identify some of the cerebellar nodes where they could interact. A particular emphasis has been placed on how these oscillations could be modulated by movement and certain neuropathological manifestations. Many of those oscillations could have a definite impact on the way information is processed in the cerebellum and how it interacts with other structures in a variety of contexts.

Oscillatory activity, phase differences, and phase resetting in the inferior olivary nucleus

The generation of temporal patterns is one of the most fascinating functions of the brain. Unlike the response to external stimuli temporal patterns are generated within the system and recalled for a specific use. To generate temporal patterns one needs a timing machine, a “master clock” that determines the temporal framework within which temporal patterns can be generated and implemented. Here we present the concept that in this putative “master clock” phase and frequency interact to generate temporal patterns. We define the requirements for a neuronal “master clock” to be both reliable and versatile. We introduce this concept within the inferior olive nucleus which at least by some scientists is regarded as the source of timing for cerebellar function. We review the basic properties of the subthreshold oscillation recorded from olivary neurons, analyze the phase relationships between neurons and demonstrate that the phase and onset of oscillation is tightly controlled by synaptic input. These properties endowed the olivary nucleus with the ability to act as a “master clock.”

An integrator circuit in cerebellar cortex

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

Multivoxel patterns reveal functionally differentiated networks underlying auditory feedback processing of speech

The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection, and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations within a multivoxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was used to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during vocalization, compared with during passive listening. One network of regions appears to encode an "error signal" regardless of acoustic features of the error: this network, including right angular gyrus, right supplementary motor area, and bilateral cerebellum, yielded consistent neural patterns across acoustically different, distorted feedback types, only during articulation (not during passive listening). In contrast, a frontotemporal network appears sensitive to the speech features of auditory stimuli during passive listening; this preference for speech features was diminished when the same stimuli were presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple, interactive, functionally differentiated neural systems.

Seeking a unified framework for cerebellar function and dysfunction: from circuit operations to cognition

Following the fundamental recognition of its involvement in sensory-motor coordination and learning, the cerebellum is now also believed to take part in the processing of cognition and emotion. This hypothesis is recurrent in numerous papers reporting anatomical and functional observations, and it requires an explanation. We argue that a similar circuit structure in all cerebellar areas may carry out various operations using a common computational scheme. On the basis of a broad review of anatomical data, it is conceivable that the different roles of the cerebellum lie in the specific connectivity of the cerebellar modules, with motor, cognitive, and emotional functions (at least partially) segregated into different cerebro-cerebellar loops. We here develop a conceptual and operational framework based on multiple interconnected levels (a meta-levels hypothesis): from cellular/molecular to network mechanisms leading to generation of computational primitives, thence to high-level cognitive/emotional processing, and finally to the sphere of mental function and dysfunction. The main concept explored is that of intimate interplay between timing and learning (reminiscent of the “timing and learning machine” capabilities long attributed to the cerebellum), which reverberates from cellular to circuit mechanisms. Subsequently, integration within large-scale brain loops could generate the disparate cognitive/emotional and mental functions in which the cerebellum has been implicated. We propose, therefore, that the cerebellum operates as a general-purpose co-processor, whose effects depend on the specific brain centers to which individual modules are connected. Abnormal functioning in these loops could eventually contribute to the pathogenesis of major brain pathologies including not just ataxia but also dyslexia, autism, schizophrenia, and depression.

Bistability in Purkinje neurons: ups and downs in cerebellar research

The output of cerebellar Purkinje cells has been characterized extensively and theories regarding the role of simple spike (SS) and complex spike (CS) patterns have evolved through many different studies. A bistable pattern of SS output can be observed in vitro; however, differing views exist regarding the occurrence of bistable SS output in vivo. Bistability in Purkinje cell output is characterized by abrupt transitions between tonic firing and quiescence, usually evoked by synaptic inputs to the neuron. This is in contrast to the trimodal pattern of activity which has been found in vitro and in vivo when climbing fiber input to Purkinje cells is removed. The mechanisms underlying bistable membrane properties in Purkinje cells have been determined through in vitro studies and computational analysis. In vitro studies have further established that Purkinje cells possess the ability to toggle between firing states, but in vivo studies in both awake and anesthetized animals have found conflicting results as to the presence of toggling in the intact circuit. Here, we provide an overview of the current state of research on bistability, examining the mechanisms underlying bistability and current findings from in vivo studies. We also suggest possible reasons for discrepancies between in vivo studies and propose future studies which would aid in clarifying the role of bistability in the cerebellar circuit.

The generation of phase differences and frequency changes in a network model of inferior olive subthreshold oscillations

It is commonly accepted that the Inferior Olive (IO) provides a timing signal to the cerebellum. Stable subthreshold oscillations in the IO can facilitate accurate timing by phase-locking spikes to the peaks of the oscillation. Several theoretical models accounting for the synchronized subthreshold oscillations have been proposed, however, two experimental observations remain an enigma. The first is the observation of frequent alterations in the frequency of the oscillations. The second is the observation of constant phase differences between simultaneously recorded neurons. In order to account for these two observations we constructed a canonical network model based on anatomical and physiological data from the IO. The constructed network is characterized by clustering of neurons with similar conductance densities, and by electrical coupling between neurons. Neurons inside a cluster are densely connected with weak strengths, while neurons belonging to different clusters are sparsely connected with stronger connections. We found that this type of network can robustly display stable subthreshold oscillations. The overall frequency of the network changes with the strength of the inter-cluster connections, and phase differences occur between neurons of different clusters. Moreover, the phase differences provide a mechanistic explanation for the experimentally observed propagating waves of activity in the IO. We conclude that the architecture of the network of electrically coupled neurons in combination with modulation of the inter-cluster coupling strengths can account for the experimentally observed frequency changes and the phase differences.

There is a profound interest in the dynamics of neuronal networks and the simulation of network models is a prevalent approach to study these dynamics. Generally, network models contain neurons that are connected mostly through chemical synapses to form either a completely regular topology (such as nearest neighbor connections), a completely random topology, small-world networks or scale-free networks. We investigate the dynamics of an atypical network, inspired by the Inferior Olive (IO) network, a brain structure located at the end of the brainstem that is responsible for timely execution of motor commands. This network is atypical in the sense that it has neurons in a clustered topology, which are connected solely by electrical synapses. The dynamics in the IO are enigmatic as the membrane voltage of some neurons can oscillate at the same frequency while maintaining phase difference with other neurons. It has also been demonstrated that propagating waves of activity occur spontaneously in this network. Using computer simulations we unraveled the mechanism underlying these previously enigmatic experimental observations. In so doing, we stress the importance of investigating more realistic network topologies to explore complex brain dynamics.

Tunable oscillations in the Purkinje neuron

In this paper, we experimentally study the dynamics of slow oscillations in Purkinje neurons in vitro, and derive a strong association with a forced parametric oscillator model. We observed the precise rhythmicity of these oscillations in Purkinje neurons, as well as a dynamic tunability of this oscillation using a photoswitchable compound. We found that this slow oscillation can be induced in every Purkinje neuron measured, having periods ranging between 10 and 25 s. Starting from a Hodgkin-Huxley model, we demonstrate that this oscillation can be externally modulated, and that the neurons will return to their intrinsic firing frequency after the forced oscillation is concluded. These findings signify an additional timing functional role of tunable oscillations within the cerebellum, as well as a dynamic control of a time scale in the brain in the range of seconds.

Neural circuits of the cerebellum: hypothesis for function

The rapid growth of cerebellar research is going to clarify several aspects of cellular and circuit physiology. However, the concepts about cerebellar mechanisms of function are still largely related to clinical observations and to models elaborated before the last discoveries appeared. In this paper, the major issues are revisited, suggesting that previous concepts can now be refined and modified. The cerebellum is fundamentally involved in timing and in controlling the ordered and precise execution of motor sequences. The fast reaction of the cerebellum to the inputs is sustained by specific cellular mechanisms ensuring precision on the millisecond scale. These include burst-burst reconversion in the granular layer and instantaneous frequency modulation on the 100-Hz band in Purkinje and deep cerebellar nuclei cells. Precisely timed signals can be used for perceptron operations in Purkinje cells and to establish appropriate correlations with climbing fiber signals inducing learning at parallel fiber synapses. In the granular layer, plasticity turns out to be instrumental to timing, providing a conceptual solution to the discrepancy between cerebellar learning and timing. The granular layer sub-circuit can be tuned by long-term synaptic plasticity and synaptic inhibition to delay the incoming signals over a 100-ms range. For longer sequences, large circuit sections can be entrained into coherent activity in 100-ms cycles. These dynamic aspects, which have not been accounted for by original theories, could in fact represent the essence of cerebellar functioning. It is suggested that the cerebellum can, in this way, operate the realignment of temporally incongruent signals, allowing their binding and pattern recognition in Purkinje cells. The demonstration of these principles, their behavioral relevance and their relationship with internal model theories represent a challenge for future cerebellar research.