Molecular layer interneurons in the cerebellum encode for valence in associative learning

Consensus Paper: Cerebellum and Reward

Cerebellum is a key-structure for the modulation of motor, cognitive, social and affective functions, contributing to automatic behaviours through interactions with the cerebral cortex, basal ganglia and spinal cord. The predictive mechanisms used by the cerebellum cover not only sensorimotor functions but also reward-related tasks. Cerebellar circuits appear to encode temporal difference error and reward prediction error. From a chemical standpoint, cerebellar catecholamines modulate the rate of cerebellar-based cognitive learning, and mediate cerebellar contributions during complex behaviours. Reward processing and its associated emotions are tuned by the cerebellum which operates as a controller of adaptive homeostatic processes based on interoceptive and exteroceptive inputs. Lobules VI-VII/areas of the vermis are candidate regions for the cortico-subcortical signaling pathways associated with loss aversion and reward sensitivity, together with other nodes of the limbic circuitry. There is growing evidence that the cerebellum works as a hub of regional dysconnectivity across all mood states and that mental disorders involve the cerebellar circuitry, including mood and addiction disorders, and impaired eating behaviors where the cerebellum might be involved in longer time scales of prediction as compared to motor operations. Cerebellar patients exhibit aberrant social behaviour, showing aberrant impulsivity/compulsivity. The cerebellum is a master-piece of reward mechanisms, together with the striatum, ventral tegmental area (VTA) and prefrontal cortex (PFC). Critically, studies on reward processing reinforce our view that a fundamental role of the cerebellum is to construct internal models, perform predictions on the impact of future behaviour and compare what is predicted and what actually occurs.

Purkinje cell models: past, present and future

The investigation of the dynamics of Purkinje cell (PC) activity is crucial to unravel the role of the cerebellum in motor control, learning and cognitive processes. Within the cerebellar cortex (CC), these neurons receive all the incoming sensory and motor information, transform it and generate the entire cerebellar output. The relatively homogenous and repetitive structure of the CC, common to all vertebrate species, suggests a single computation mechanism shared across all PCs. While PC models have been developed since the 70's, a comprehensive review of contemporary models is currently lacking. Here, we provide an overview of PC models, ranging from the ones focused on single cell intracellular PC dynamics, through complex models which include synaptic and extrasynaptic inputs. We review how PC models can reproduce physiological activity of the neuron, including firing patterns, current and multistable dynamics, plateau potentials, calcium signaling, intrinsic and synaptic plasticity and input/output computations. We consider models focusing both on somatic and on dendritic computations. Our review provides a critical performance analysis of PC models with respect to known physiological data. We expect our synthesis to be useful in guiding future development of computational models that capture real-life PC dynamics in the context of cerebellar computations.

A cerebro-cerebellar network for learning visuomotor associations

Consensus is rapidly building to support a role for the cerebellum beyond motor function, but its contributions to non-motor learning remain poorly understood. Here, we provide behavioral, anatomical and computational evidence to demonstrate a causal role for the primate posterior lateral cerebellum in learning new visuomotor associations. Reversible inactivation of the posterior lateral cerebellum of male monkeys impeded the learning of new visuomotor associations, but had no effect on movement parameters, or on well-practiced performance of the same task. Using retrograde transneuronal transport of rabies virus, we identified a distinct cerebro-cerebellar network linking Purkinje cells in the posterior lateral cerebellum with a region of the prefrontal cortex that is critical in learning visuomotor associations. Together, these results demonstrate a causal role for the primate posterior lateral cerebellum in non-motor, reinforcement learning.

Sequential activity of CA1 hippocampal cells constitutes a temporal memory map for associative learning in mice

Sequential neural dynamics encoded by time cells play a crucial role in hippocampal function. However, the role of hippocampal sequential neural dynamics in associative learning is an open question. We used two-photon Ca2+ imaging of dorsal CA1 (dCA1) neurons in the stratum pyramidale (SP) in head-fixed mice performing a go-no go associative learning task to investigate how odor valence is temporally encoded in this area of the brain. We found that SP cells responded differentially to the rewarded or unrewarded odor. The stimuli were decoded accurately from the activity of the neuronal ensemble, and accuracy increased substantially as the animal learned to differentiate the stimuli. Decoding the stimulus from individual SP cells responding differentially revealed that decision-making took place at discrete times after stimulus presentation. Lick prediction decoded from the ensemble activity of cells in dCA1 correlated linearly with lick behavior. Our findings indicate that sequential activity of SP cells in dCA1 constitutes a temporal memory map used for decision-making in associative learning. VIDEO ABSTRACT.

Recent data on the cerebellum require new models and theories

The cerebellum has been a popular topic for theoretical studies because its structure was thought to be simple. Since David Marr and James Albus related its function to motor skill learning and proposed the Marr-Albus cerebellar learning model, this theory has guided and inspired cerebellar research. In this review, we summarize the theoretical progress that has been made within this framework of error-based supervised learning. We discuss the experimental progress that demonstrates more complicated molecular and cellular mechanisms in the cerebellum as well as new cell types and recurrent connections. We also cover its involvement in diverse non-motor functions and evidence of other forms of learning. Finally, we highlight the need to explain these new experimental findings into an integrated cerebellar model that can unify its diverse computational functions.

Social memory deficit caused by dysregulation of the cerebellar vermis

Social recognition memory (SRM) is a key determinant of social interactions. While the cerebellum emerges as an important region for social behavior, how cerebellar activity affects social functions remains unclear. We selectively increased the excitability of molecular layer interneurons (MLIs) to suppress Purkinje cell firing in the mouse cerebellar vermis. Chemogenetic perturbation of MLIs impaired SRM without affecting sociability, anxiety levels, motor coordination or object recognition. Optogenetic interference of MLIs during distinct phases of a social recognition test revealed the cerebellar engagement in the retrieval, but not encoding, of social information. c-Fos mapping after the social recognition test showed that cerebellar manipulation decreased brain-wide interregional correlations and altered network structure from medial prefrontal cortex and hippocampus-centered to amygdala-centered modules. Anatomical tracing demonstrated hierarchical projections from the central cerebellum to the social brain network integrating amygdalar connections. Our findings suggest that the cerebellum organizes the neural matrix necessary for SRM.

Early molecular layer interneuron hyperactivity triggers Purkinje neuron degeneration in SCA1

Toxic proteinaceous deposits and alterations in excitability and activity levels characterize vulnerable neuronal populations in neurodegenerative diseases. Using in vivo two-photon imaging in behaving spinocerebellar ataxia type 1 (Sca1) mice, wherein Purkinje neurons (PNs) degenerate, we identify an inhibitory circuit element (molecular layer interneurons [MLINs]) that becomes prematurely hyperexcitable, compromising sensorimotor signals in the cerebellum at early stages. Mutant MLINs express abnormally elevated parvalbumin, harbor high excitatory-to-inhibitory synaptic density, and display more numerous synaptic connections on PNs, indicating an excitation/inhibition imbalance. Chemogenetic inhibition of hyperexcitable MLINs normalizes parvalbumin expression and restores calcium signaling in Sca1 PNs. Chronic inhibition of mutant MLINs delayed PN degeneration, reduced pathology, and ameliorated motor deficits in Sca1 mice. Conserved proteomic signature of Sca1 MLINs, shared with human SCA1 interneurons, involved the higher expression of FRRS1L, implicated in AMPA receptor trafficking. We thus propose that circuit-level deficits upstream of PNs are one of the main disease triggers in SCA1.

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

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

Deconstruction of Vermal Cerebellum in Ramp Locomotion in Mice

The cerebellum is involved in encoding balance, posture, speed, and gravity during locomotion. However, most studies are carried out on flat surfaces, and little is known about cerebellar activity during free ambulation on slopes. Here, it has been imaged the neuronal activity of cerebellar molecular interneurons (MLIs) and Purkinje cells (PCs) using a miniaturized microscope while a mouse is walking on a slope. It has been found that the neuronal activity of vermal MLIs specifically enhanced during uphill and downhill locomotion. In addition, a subset of MLIs is activated during entire uphill or downhill positions on the slope and is modulated by the slope inclines. In contrast, PCs showed counter-balanced neuronal activity to MLIs, which reduced activity at the ramp peak. So, PCs may represent the ramp environment at the population level. In addition, chemogenetic inactivation of lobule V of the vermis impaired uphill locomotion. These results revealed a novel micro-circuit in the vermal cerebellum that regulates ambulatory behavior in 3D terrains.

Novel Cerebello-Amygdala Connections Provide Missing Link Between Cerebellum and Limbic System

The cerebellum is emerging as a powerful regulator of cognitive and affective processing and memory in both humans and animals and has been implicated in affective disorders. How the cerebellum supports affective function remains poorly understood. The short-latency (just a few milliseconds) functional connections that were identified between the cerebellum and amygdala—a structure crucial for the processing of emotion and valence—more than four decades ago raise the exciting, yet untested, possibility that a cerebellum-amygdala pathway communicates information important for emotion. The major hurdle in rigorously testing this possibility is the lack of knowledge about the anatomy and functional connectivity of this pathway. Our initial anatomical tracing studies in mice excluded the existence of a direct monosynaptic connection between the cerebellum and amygdala. Using transneuronal tracing techniques, we have identified a novel disynaptic circuit between the cerebellar output nuclei and the basolateral amygdala. This circuit recruits the understudied intralaminar thalamus as a node. Using ex vivo optophysiology and super-resolution microscopy, we provide the first evidence for the functionality of the pathway, thus offering a missing mechanistic link between the cerebellum and amygdala. This discovery provides a connectivity blueprint between the cerebellum and a key structure of the limbic system. As such, it is the requisite first step toward obtaining new knowledge about cerebellar function in emotion, thus fundamentally advancing understanding of the neurobiology of emotion, which is perturbed in mental and autism spectrum disorders.

Mid-lateral cerebellar complex spikes encode multiple independent reward-related signals during reinforcement learning

Although the cerebellum has been implicated in simple reward-based learning recently, the role of complex spikes (CS) and simple spikes (SS), their interaction and their relationship to complex reinforcement learning and decision making is still unclear. Here we show that in a context where a non-human primate learned to make novel visuomotor associations, classifying CS responses based on their SS properties revealed distinct cell-type specific encoding of the probability of failure after the stimulus onset and the non-human primate's decision. In a different context, CS from the same cerebellar area also responded in a cell-type and learning independent manner to the stimulus that signaled the beginning of the trial. Both types of CS signals were independent of changes in any motor kinematics and were unlikely to instruct the concurrent SS activity through an error based mechanism, suggesting the presence of context dependent, flexible, multiple independent channels of neural encoding by CS and SS. This diversity in neural information encoding in the mid-lateral cerebellum, depending on the context and learning state, is well suited to promote exploration and acquisition of wide range of cognitive behaviors that entail flexible stimulus-action-reward relationships but not necessarily motor learning.

Adaptive Prediction for Social Contexts: The Cerebellar Contribution to Typical and Atypical Social Behaviors

Social interactions involve processes ranging from face recognition to understanding others' intentions. To guide appropriate behavior in a given context, social interactions rely on accurately predicting the outcomes of one's actions and the thoughts of others. Because social interactions are inherently dynamic, these predictions must be continuously adapted. The neural correlates of social processing have largely focused on emotion, mentalizing, and reward networks, without integration of systems involved in prediction. The cerebellum forms predictive models to calibrate movements and adapt them to changing situations, and cerebellar predictive modeling is thought to extend to nonmotor behaviors. Primary cerebellar dysfunction can produce social deficits, and atypical cerebellar structure and function are reported in autism, which is characterized by social communication challenges and atypical predictive processing. We examine the evidence that cerebellar-mediated predictions and adaptation play important roles in social processes and argue that disruptions in these processes contribute to autism.

Multidimensional population activity in an electrically coupled inhibitory circuit in the cerebellar cortex

Inhibitory neurons orchestrate the activity of excitatory neurons and play key roles in circuit function. Although individual interneurons have been studied extensively, little is known about their properties at the population level. Using random-access 3D two-photon microscopy, we imaged local populations of cerebellar Golgi cells (GoCs), which deliver inhibition to granule cells. We show that population activity is organized into multiple modes during spontaneous behaviors. A slow, network-wide common modulation of GoC activity correlates with the level of whisking and locomotion, while faster (<1 s) differential population activity, arising from spatially mixed heterogeneous GoC responses, encodes more precise information. A biologically detailed GoC circuit model reproduced the common population mode and the dimensionality observed experimentally, but these properties disappeared when electrical coupling was removed. Our results establish that local GoC circuits exhibit multidimensional activity patterns that could be used for inhibition-mediated adaptive gain control and spatiotemporal patterning of downstream granule cells.

Cerebellar network organization across the human menstrual cycle

The cerebellum contains the vast majority of neurons in the brain and houses distinct functional networks that constitute at least two homotopic maps of cerebral networks. It is also a major site of sex steroid hormone action. While the functional organization of the human cerebellum has been characterized, the influence of sex steroid hormones on intrinsic cerebellar network dynamics has yet to be established. Here we investigated the extent to which endogenous fluctuations in estradiol and progesterone alter functional cerebellar networks at rest in a woman densely sampled over a complete menstrual cycle (30 consecutive days). Edgewise regression analysis revealed robust negative associations between progesterone and cerebellar coherence. Graph theory metrics probed sex hormones' influence on topological brain states, revealing relationships between sex hormones and within-network integration in Ventral Attention, Dorsal Attention, and SomatoMotor Networks. Together these results suggest that the intrinsic dynamics of the cerebellum are intimately tied to day-by-day changes in sex hormones.