The anatomical pathway from the mesodiencephalic junction to the inferior olive relays perioral sensory signals to the cerebellum in the mouse

A Systematic Review of Direct Outputs from the Cerebellum to the Brainstem and Diencephalon in Mammals

The cerebellum is involved in many motor, autonomic and cognitive functions, and new tasks that have a cerebellar contribution are discovered on a regular basis. Simultaneously, our insight into the functional compartmentalization of the cerebellum has markedly improved. Additionally, studies on cerebellar output pathways have seen a renaissance due to the development of viral tracing techniques. To create an overview of the current state of our understanding of cerebellar efferents, we undertook a systematic review of all studies on monosynaptic projections from the cerebellum to the brainstem and the diencephalon in mammals. This revealed that important projections from the cerebellum, to the motor nuclei, cerebral cortex, and basal ganglia, are predominantly di- or polysynaptic, rather than monosynaptic. Strikingly, most target areas receive cerebellar input from all three cerebellar nuclei, showing a convergence of cerebellar information at the output level. Overall, there appeared to be a large level of agreement between studies on different species as well as on the use of different types of neural tracers, making the emerging picture of the cerebellar output areas a solid one. Finally, we discuss how this cerebellar output network is affected by a range of diseases and syndromes, with also non-cerebellar diseases having impact on cerebellar output areas.

The indirect corticopontine pathway relays perioral sensory signals to the cerebellum via the mesodiencephalic junction

In the cerebro-cerebellar loop, outputs from the cerebral cortex are thought to be transmitted via monosynaptic corticopontine gray (PG) pathways and subsequently relayed to the cerebellum. However, it is unclear whether this pathway is used constitutively for cerebro-cerebellar transduction. We examined perioral sensory pathways by unit recording from Purkinje cells in ketamine/xylazine-anesthetized mice. Infraorbital nerve stimulations enhanced simple spikes (SSs) with short and long latencies (first and second peaks), followed by SS inhibition. The second peak and SS inhibition were suppressed by muscimol (a GABAA agonist) injections into not only the PG but also the mesodiencephalic junction (MDJ). The pathway from the secondary somatosensory area (SII) to the MDJ, but not the cortico-PG pathway, transmitted the second peak signals. SS inhibition was processed in the SII and primary motor area. Thus, the indirect cortico-PG pathway, via the MDJ, is recruited for perioral sensory transduction.

The integrated brain network that controls respiration

Respiration is a brain function on which our lives essentially depend. Control of respiration ensures that the frequency and depth of breathing adapt continuously to metabolic needs. In addition, the respiratory control network of the brain has to organize muscular synergies that integrate ventilation with posture and body movement. Finally, respiration is coupled to cardiovascular function and emotion. Here, we argue that the brain can handle this all by integrating a brainstem central pattern generator circuit in a larger network that also comprises the cerebellum. Although currently not generally recognized as a respiratory control center, the cerebellum is well known for its coordinating and modulating role in motor behavior, as well as for its role in the autonomic nervous system. In this review, we discuss the role of brain regions involved in the control of respiration, and their anatomical and functional interactions. We discuss how sensory feedback can result in adaptation of respiration, and how these mechanisms can be compromised by various neurological and psychological disorders. Finally, we demonstrate how the respiratory pattern generators are part of a larger and integrated network of respiratory brain regions.

Mesodiencephalic junction GABAergic inputs are processed separately from motor cortical inputs in the basilar pons

The basilar pontine nuclei (bPN) are known to receive excitatory input from the entire neocortex and constitute the main source of mossy fibers to the cerebellum. Various potential inhibitory afferents have been described, but their origin, synaptic plasticity, and network function have remained elusive. Here we identify the mesodiencephalic junction (MDJ) as a prominent source of monosynaptic GABAergic inputs to the bPN. We found no evidence that these inputs converge with motor cortex (M1) inputs at the single neuron or at the local network level. Tracing the inputs to GABAergic MDJ neurons revealed inputs to these neurons from neocortical areas. Additionally, we observed little short-term synaptic facilitation or depression in afferents from the MDJ, enabling MDJ inputs to carry sign-inversed neocortical inputs. Thus, our results show a prominent source of GABAergic inhibition to the bPN that could enrich input to the cerebellar granule cell layer.

A review of motor neural system robotic modeling approaches and instruments

In this review, we are considering an actively developing tool in neuroscience-robotic modeling. The new perspective and existing application fields, tools, and methods are discussed. We try to determine starting positions and approaches that are useful at the beginning of new research in this field. Among multiple directions of the research is robotic modeling on the level of muscles fibers and their afferents, skin surface sensors, muscles, and joints proprioceptors. Some examples of technical implementation for physical modeling are reviewed. They are software and hardware tools like event-related modeling algorithms, reduced neuron models, robotic drives constructions. We observe existing drives technologies and prospective electric motor types: switched reluctance and transverse flux motors. Next, we look at the existing examples and approaches for robotic modeling of the cerebellum and spinal cord neural networks. These examples show practical methods for the model neural network architecture and adaptation. Those methods allow the use of cortical and spinal cord reflexes for the network training and apply additional artificial blocks for data processing in other brain structures that transmit and receive data from biologically realistic models.

Input and output organization of the mesodiencephalic junction for cerebro-cerebellar communication

Most studies investigating the impact of the cerebral cortex (CC) onto the cerebellum highlight the role of the pons, which provides the mossy fibers to the cerebellum. However, cerebro‐cerebellar communication may also be mediated by the nuclei of the mesodiencephalic junction (MDJ) that project to the inferior olive (IO), which in turn provides the climbing fibers to the molecular layer. Here, we uncover the precise topographic relations of the inputs and outputs of the MDJ using multiple, classical, and transneuronal tracing methods as well as analyses of mesoscale cortical injections from Allen Mouse Brain. We show that the caudal parts of the CC predominantly project to the principal olive via the rostral MDJ and that the rostral parts of the CC predominantly project to the rostral medial accessory olive via the caudal MDJ. Moreover, using triple viral tracing technology, we show that the cerebellar nuclei directly innervate the neurons in the MDJ that receive input from CC and project to the IO. By unraveling these topographic and prominent, mono‐ and disynaptic projections through the MDJ, this work establishes that cerebro‐cerebellar communication is not only mediated by the pontine mossy fiber system, but also by the climbing fiber system.

Homologous organization of cerebellar pathways to sensory, motor, and associative forebrain

Cerebellar outputs take polysynaptic routes to reach the rest of the brain, impeding conventional tracing. Here, we quantify pathways between the cerebellum and forebrain by using transsynaptic tracing viruses and a whole-brain analysis pipeline. With retrograde tracing, we find that most descending paths originate from the somatomotor cortex. Anterograde tracing of ascending paths encompasses most thalamic nuclei, especially ventral posteromedial, lateral posterior, mediodorsal, and reticular nuclei. In the neocortex, sensorimotor regions contain the most labeled neurons, but we find higher densities in associative areas, including orbital, anterior cingulate, prelimbic, and infralimbic cortex. Patterns of ascending expression correlate with c-Fos expression after optogenetic inhibition of Purkinje cells. Our results reveal homologous networks linking single areas of the cerebellar cortex to diverse forebrain targets. We conclude that shared areas of the cerebellum are positioned to provide sensory-motor information to regions implicated in both movement and nonmotor function.

Pisano et al. use transsynaptic tracing and whole-brain light-sheet microscopy to quantitatively map cerebellar paths to and from the forebrain, including relatively dense projections to the prefrontal neocortex. Divergence of paths from single injection sites suggests that a single cerebellar region can influence multiple thalamic and neocortical targets at once.

Cerebellar Purkinje cells can differentially modulate coherence between sensory and motor cortex depending on region and behavior

Activity of sensory and motor cortices is essential for sensorimotor integration. In particular, coherence between these areas may indicate binding of critical functions like perception, motor planning, action, or sleep. Evidence is accumulating that cerebellar output modulates cortical activity and coherence, but how, when, and where it does so is unclear. We studied activity in and coherence between S1 and M1 cortices during whisker stimulation in the absence and presence of optogenetic Purkinje cell stimulation in crus 1 and 2 of awake mice, eliciting strong simple spike rate modulation. Without Purkinje cell stimulation, whisker stimulation triggers fast responses in S1 and M1 involving transient coherence in a broad spectrum. Simultaneous stimulation of Purkinje cells and whiskers affects amplitude and kinetics of sensory responses in S1 and M1 and alters the estimated S1-M1 coherence in theta and gamma bands, allowing bidirectional control dependent on behavioral context. These effects are absent when Purkinje cell activation is delayed by 20 ms. Focal stimulation of Purkinje cells revealed site specificity, with cells in medial crus 2 showing the most prominent and selective impact on estimated coherence, i.e., a strong suppression in the gamma but not the theta band. Granger causality analyses and computational modeling of the involved networks suggest that Purkinje cells control S1-M1 phase consistency predominantly via ventrolateral thalamus and M1. Our results indicate that activity of sensorimotor cortices can be dynamically and functionally modulated by specific cerebellar inputs, highlighting a widespread role of the cerebellum in coordinating sensorimotor behavior.

Multiple signals evoked by unisensory stimulation converge onto cerebellar granule and Purkinje cells in mice

The cerebellum receives signals directly from peripheral sensory systems and indirectly from the neocortex. Even a single tactile stimulus can activate both of these pathways. Here we report how these different types of signals are integrated in the cerebellar cortex. We used in vivo whole-cell recordings from granule cells and unit recordings from Purkinje cells in mice in which primary somatosensory cortex (S1) could be optogenetically inhibited. Tactile stimulation of the upper lip produced two-phase granule cell responses (with latencies of ~8 ms and 29 ms), for which only the late phase was S1 dependent. In Purkinje cells, complex spikes and the late phase of simple spikes were S1 dependent. These results indicate that individual granule cells combine convergent inputs from the periphery and neocortex and send their outputs to Purkinje cells, which then integrate those signals with climbing fiber signals from the neocortex.

Modular output circuits of the fastigial nucleus for diverse motor and nonmotor functions of the cerebellar vermis

The cerebellar vermis, long associated with axial motor control, has been implicated in a surprising range of neuropsychiatric disorders and cognitive and affective functions. Remarkably little is known, however, about the specific cell types and neural circuits responsible for these diverse functions. Here, using single-cell gene expression profiling and anatomical circuit analyses of vermis output neurons in the mouse fastigial (medial cerebellar) nucleus, we identify five major classes of glutamatergic projection neurons distinguished by gene expression, morphology, distribution, and input-output connectivity. Each fastigial cell type is connected with a specific set of Purkinje cells and inferior olive neurons and in turn innervates a distinct collection of downstream targets. Transsynaptic tracing indicates extensive disynaptic links with cognitive, affective, and motor forebrain circuits. These results indicate that diverse cerebellar vermis functions could be mediated by modular synaptic connections of distinct fastigial cell types with posturomotor, oromotor, positional-autonomic, orienting, and vigilance circuits.

Prediction signals in the cerebellum: beyond supervised motor learning

While classical views of cerebellar learning have suggested that this structure predominantly operates according to an error-based supervised learning rule to refine movements, emerging evidence suggests that the cerebellum may also harness a wider range of learning rules to contribute to a variety of behaviors, including cognitive processes. Together, such evidence points to a broad role for cerebellar circuits in generating and testing predictions about movement, reward, and other non-motor operations. However, this expanded view of cerebellar processing also raises many new questions about how such apparent diversity of function arises from a structure with striking homogeneity. Hence, this review will highlight both current evidence for predictive cerebellar circuit function that extends beyond the classical view of error-driven supervised learning, as well as open questions that must be addressed to unify our understanding cerebellar circuit function.

Modular organization of cerebellar climbing fiber inputs during goal-directed behavior

The cerebellum has a parasagittal modular architecture characterized by precisely organized climbing fiber (CF) projections that are congruent with alternating aldolase C/zebrin II expression. However, the behavioral relevance of CF inputs into individual modules remains poorly understood. Here, we used two-photon calcium imaging in the cerebellar hemisphere Crus II in mice performing an auditory go/no-go task to investigate the functional differences in CF inputs to modules. CF signals in medial modules show anticipatory decreases, early increases, secondary increases, and reward-related increases or decreases, which represent quick motor initiation, go cues, fast motor behavior, and positive reward outcomes. CF signals in lateral modules show early increases and reward-related decreases, which represent no-go and/or go cues and positive reward outcomes. The boundaries of CF functions broadly correspond to those of aldolase C patterning. These results indicate that spatially segregated CF inputs in different modules play distinct roles in the execution of goal-directed behavior.

Quasiperiodic rhythms of the inferior olive

Inferior olivary activity causes both short-term and long-term changes in cerebellar output underlying motor performance and motor learning. Many of its neurons engage in coherent subthreshold oscillations and are extensively coupled via gap junctions. Studies in reduced preparations suggest that these properties promote rhythmic, synchronized output. However, the interaction of these properties with torrential synaptic inputs in awake behaving animals is not well understood. Here we combine electrophysiological recordings in awake mice with a realistic tissue-scale computational model of the inferior olive to study the relative impact of intrinsic and extrinsic mechanisms governing its activity. Our data and model suggest that if subthreshold oscillations are present in the awake state, the period of these oscillations will be transient and variable. Accordingly, by using different temporal patterns of sensory stimulation, we found that complex spike rhythmicity was readily evoked but limited to short intervals of no more than a few hundred milliseconds and that the periodicity of this rhythmic activity was not fixed but dynamically related to the synaptic input to the inferior olive as well as to motor output. In contrast, in the long-term, the average olivary spiking activity was not affected by the strength and duration of the sensory stimulation, while the level of gap junctional coupling determined the stiffness of the rhythmic activity in the olivary network during its dynamic response to sensory modulation. Thus, interactions between intrinsic properties and extrinsic inputs can explain the variations of spiking activity of olivary neurons, providing a temporal framework for the creation of both the short-term and long-term changes in cerebellar output.

Activity of the inferior olive, transmitted via climbing fibers to the cerebellum, regulates initiation and amplitude of movements, signals unexpected sensory feedback, and directs cerebellar learning. It is characterized by widespread subthreshold oscillations and synchronization promoted by strong electrotonic coupling. In brain slices, subthreshold oscillations gate which inputs can be transmitted by inferior olivary neurons and which will not—dependent on the phase of the oscillation. We tested whether the subthreshold oscillations had a measurable impact on temporal patterning of climbing fiber activity in intact, awake mice. We did so by recording neural activity of the postsynaptic Purkinje cells, in which complex spike firing faithfully represents climbing fiber activity. For short intervals (<300 ms) many Purkinje cells showed spontaneously rhythmic complex spike activity. However, our experiments designed to evoke conditional responses indicated that complex spikes are not predominantly predicated on stimulus history. Our realistic network model of the inferior olive explains the experimental observations via continuous phase modulations of the subthreshold oscillations under the influence of synaptic fluctuations. We conclude that complex spike activity emerges from a quasiperiodic rhythm that is stabilized by electrotonic coupling between its dendrites, yet dynamically influenced by the status of their synaptic inputs.

Neurons of the inferior olive respond to broad classes of sensory input while subject to homeostatic control

KEY POINTS

Purkinje cells in the cerebellum integrate input from sensory organs with that from premotor centres. Purkinje cells use a variety of sensory inputs relaying information from the environment to modify motor control. Here we investigated to what extent the climbing fibre inputs to Purkinje cells signal mono- or multi-sensory information, and to what extent this signalling is subject to recent history of activity. We show that individual climbing fibres convey multiple types of sensory information, together providing a rich mosaic projection pattern of sensory signals across the cerebellar cortex. Moreover, firing probability of climbing fibres following sensory stimulation depends strongly on the recent history of activity, showing a tendency to homeostatic dampening.

ABSTRACT

Cerebellar Purkinje cells integrate sensory information with motor efference copies to adapt movements to behavioural and environmental requirements. They produce complex spikes that are triggered by the activity of climbing fibres originating in neurons of the inferior olive. These complex spikes can shape the onset, amplitude and direction of movements and the adaptation of such movements to sensory feedback. Clusters of nearby inferior olive neurons project to parasagittally aligned stripes of Purkinje cells, referred to as 'microzones'. It is currently unclear to what extent individual Purkinje cells within a single microzone integrate climbing fibre inputs from multiple sources of different sensory origins, and to what extent sensory-evoked climbing fibre responses depend on the strength and recent history of activation. Here we imaged complex spike responses in cerebellar lobule crus 1 to various types of sensory stimulation in awake mice. We find that different sensory modalities and receptive fields have a mild, but consistent, tendency to converge on individual Purkinje cells, with climbing fibres showing some degree of input-specificity. Purkinje cells encoding the same stimulus show increased events with coherent complex spike firing and tend to lie close together. Moreover, whereas complex spike firing is only mildly affected by variations in stimulus strength, it depends strongly on the recent history of climbing fibre activity. Our data point towards a mechanism in the olivo-cerebellar system that regulates complex spike firing during mono- or multi-sensory stimulation around a relatively low set-point, highlighting an integrative coding scheme of complex spike firing under homeostatic control.

Potentiation of cerebellar Purkinje cells facilitates whisker reflex adaptation through increased simple spike activity

Cerebellar plasticity underlies motor learning. However, how the cerebellum operates to enable learned changes in motor output is largely unknown. We developed a sensory-driven adaptation protocol for reflexive whisker protraction and recorded Purkinje cell activity from crus 1 and 2 of awake mice. Before training, simple spikes of individual Purkinje cells correlated during reflexive protraction with the whisker position without lead or lag. After training, simple spikes and whisker protractions were both enhanced with the spiking activity now leading behavioral responses. Neuronal and behavioral changes did not occur in two cell-specific mouse models with impaired long-term potentiation at their parallel fiber to Purkinje cell synapses. Consistent with cerebellar plasticity rules, increased simple spike activity was prominent in cells with low complex spike response probability. Thus, potentiation at parallel fiber to Purkinje cell synapses may contribute to reflex adaptation and enable expression of cerebellar learning through increases in simple spike activity.

Rodents use their whiskers to explore the world around them. When the whiskers touch an object, it triggers involuntary movements of the whiskers called whisker reflexes. Experiencing the same sensory stimulus multiple times enables rodents to fine-tune these reflexes, e.g., by making their movements larger or smaller. This type of learning is often referred to as motor learning.

A part of the brain called cerebellum controls motor learning. It contains some of the largest neurons in the nervous system, the Purkinje cells. Each Purkinje cell receives input from thousands of extensions of small neurons, known as parallel fibers. It is thought that decreasing the strength of the connections between parallel fibers and Purkinje cells can help mammals learn new movements. This is the case in a type of learning called Pavlovian conditioning. It takes its name from the Russian scientist, Pavlov, who showed that dogs can learn to salivate in response to a bell signaling food. Pavlovian conditioning enables animals to optimize their responses to sensory stimuli.

But Romano et al. now show that increasing the strength of connections between parallel fibers and Purkinje cells can also support learning. To trigger reflexive whisker movements, a machine blew puffs of air onto the whiskers of awake mice. After repeated exposure to the air puffs, the mice increased the size of their whisker reflexes. At the same time, their Purkinje cells became more active and the connections between Purkinje cells and parallel fibers grew stronger. Artificially increasing Purkinje cell activity triggered the same changes in whisker reflexes as the air puffs themselves.

Textbooks still report that only weakening of connections within the cerebellum enables animals to learn and modify movements. The data obtained by Romano al. thus paint a new picture of how the cerebellum works in the context of whisker learning. They show that strengthening these connections can also support movement-related learning.