Synaptic mechanisms for associative learning in the cerebellar nuclei

Acute aerobic exercise enhances associative learning in regular exercisers but not in non-regular exercisers

Introduction

Physical exercise has repeatedly been reported to have advantageous effects on brain functions, including learning and memory formation. However, objective tools to measure such effects are often lacking. Eyeblink conditioning is a well-characterized method for studying the neural basis of associative learning. As such, this paradigm has potential as a tool to assess to what extent exercise affects one of the most basic forms of learning. Until recently, however, using this paradigm for testing human subjects in their daily life was technically challenging. As a consequence, no studies have investigated how exercise affects eyeblink conditioning in humans. Here we hypothesize that acute aerobic exercise is associated with improved performance in eyeblink conditioning. Furthermore, we explored whether the effects of exercise differed for people engaging in regular exercise versus those who were not.

Methods

We conducted a case-control study using a smartphone-based platform for conducting neurometric eyeblink conditioning in healthy adults aged between 18 and 40 years (n = 36). Groups were matched on age, sex, and education level. Our primary outcome measures included the amplitude and timing of conditioned eyelid responses over the course of eyeblink training. As a secondary measure, we studied the amplitude of the unconditioned responses.

Results

Acute exercise significantly enhanced the acquisition of conditioned eyelid responses; however, this effect was only true for regularly exercising individuals. No statistically significant effects were established for timing of the conditioned responses and amplitude of the unconditioned responses.

Discussion

This study highlights a facilitative role of acute aerobic exercise in associative learning and emphasizes the importance of accounting for long-term exercise habits when investigating the acute effects of exercise on brain functioning.

Purkinje cells in Crus I and II encode the visual stimulus and the impending choice as monkeys learn a reinforcement based visuomotor association task

Visuomotor association involves linking an arbitrary visual cue to a well-learned movement. Transient inactivation of Crus I/II impairs primates' ability to learn new associations and delays motor responses without affecting the kinematics of the movement. The simple spikes of Purkinje cells in the Crus regions signal cognitive errors as monkeys learn to associate specific fractal stimuli with movements of the left or right hand. Here we show that as learning progresses, the simple spike activity of individual neurons becomes more selective for stimulus-response associations, with selectivity developing closer to the appearance of visual stimuli. Initially, most neurons respond to both associations, irrespective of the identity of the stimulus and the associated movement, but as learning advances, more neurons distinguish between specific stimulus-hand associations. Using a linear decoder, it was found that in early learning stages, the visual stimulus can be decoded only when the choice can also be decoded. As learning improves, the visual stimulus is decoded earlier than the choice. A simple model can replicate the observed simple spike signals and the monkeys' behavior in both the early and late learning stages.

Discrimination training affects stimulus generalization in mice during Pavlovian eyeblink conditioning

The delicate balance between discrimination and generalization of responses is crucial for survival in our ever-changing environment. In particular, it is important to understand how stimulus discrimination affects the level of stimulus generalization. For example, when we use non-differential training for Pavlovian eyeblink conditioning to investigate generalization of cerebellar-related eyelid motor responses, we find generalization effects on amount, amplitude and timing of the conditioned responses. However, it is unknown what the generalization effects are following differential training. We trained mice to close their eyelids to a 10 kHz tone with an air-puff as the reinforcing stimulus (CS+), while alternatingly exposing them to a tone frequency of either 4 kHz, 9 kHz or 9.5 kHz without the air-puff (CS-) during the training blocks. We tested the generalization effects during the expression of the responses after the training period with tones ranging from 2 kHz to 20 kHz. Our results show that the level of generalization tended to positively correlate with the difference between the CS+ and the CS- training stimuli. These effects of generalization were found for the probability, amplitude but not for the timing of the conditioned eyelid responses. These data indicate the specificity of the generalization effects following differential versus non-differential training, highlighting the relevance of discrimination learning for stimulus generalization.

Keeping track of time: An interaction of mossy fibers and climbing fibers

Precisely tracking time over second-long timescales is important for accurate anticipation and consequential actions, yet the neurobiological underpinnings remain unknown. In this issue of Neuron, Garcia-Garcia and colleagues1 show that computations in the cerebellum resulting from interactions between the mossy fiber and climbing fiber pathways contribute to long-interval learning during operant conditioning.

Plasticity mechanisms of genetically distinct Purkinje cells

Despite its uniform appearance, the cerebellar cortex is highly heterogeneous in terms of structure, genetics and physiology. Purkinje cells (PCs), the principal and sole output neurons of the cerebellar cortex, can be categorized into multiple populations that differentially express molecular markers and display distinctive physiological features. Such features include action potential rate, but also their propensity for synaptic and intrinsic plasticity. However, the precise molecular and genetic factors that correlate with the differential physiological properties of PCs remain elusive. In this article, we provide a detailed overview of the cellular mechanisms that regulate PC activity and plasticity. We further perform a pathway analysis to highlight how molecular characteristics of specific PC populations may influence their physiology and plasticity mechanisms.

Climbing fibers provide essential instructive signals for associative learning

Supervised learning depends on instructive signals that shape the output of neural circuits to support learned changes in behavior. Climbing fiber (CF) inputs to the cerebellar cortex represent one of the strongest candidates in the vertebrate brain for conveying neural instructive signals. However, recent studies have shown that Purkinje cell stimulation can also drive cerebellar learning and the relative importance of these two neuron types in providing instructive signals for cerebellum-dependent behaviors remains unresolved. In the present study we used cell-type-specific perturbations of various cerebellar circuit elements to systematically evaluate their contributions to delay eyeblink conditioning in mice. Our findings reveal that, although optogenetic stimulation of either CFs or Purkinje cells can drive learning under some conditions, even subtle reductions in CF signaling completely block learning to natural stimuli. We conclude that CFs and corresponding Purkinje cell complex spike events provide essential instructive signals for associative cerebellar learning.

The Role of Cerebellar Intrinsic Neuronal Excitability, Synaptic Plasticity, and Perineuronal Nets in Eyeblink Conditioning

Evidence is strong that, in addition to fine motor control, there is an important role for the cerebellum in cognition and emotion. The deep nuclei of the mammalian cerebellum also contain the highest density of perineural nets-mesh-like structures that surround neurons-in the brain, and it appears there may be a connection between these nets and cognitive processes, particularly learning and memory. Here, we review how the cerebellum is involved in eyeblink conditioning-a particularly well-understood form of learning and memory-and focus on the role of perineuronal nets in intrinsic membrane excitability and synaptic plasticity that underlie eyeblink conditioning. We explore the development and role of perineuronal nets and the in vivo and in vitro evidence that manipulations of the perineuronal net in the deep cerebellar nuclei affect eyeblink conditioning. Together, these findings provide evidence of an important role for perineuronal net in learning and memory.