The role of the cerebellum in learning to predict reward: evidence from cerebellar ataxia

Abstract

Recent findings in animals have challenged the traditional view of the cerebellum solely as the site of motor control, suggesting that the cerebellum may also be important for learning to predict reward from trial-and-error feedback. Yet, evidence for the role of the cerebellum in reward learning in humans is lacking. Moreover, open questions remain about which specific aspects of reward learning the cerebellum may contribute to. Here we address this gap through an investigation of multiple forms of reward learning in individuals with cerebellum dysfunction, represented by cerebellar ataxia cases. Nineteen participants with cerebellar ataxia and 57 age- and sex-matched healthy controls completed two separate tasks that required learning about reward contingencies from trial-and-error. To probe the selectivity of reward learning processes, the tasks differed in their underlying structure: while one task measured incremental reward learning ability alone, the other allowed participants to use an alternative learning strategy based on episodic memory alongside incremental reward learning. We found that individuals with cerebellar ataxia were profoundly impaired at reward learning from trial-and-error feedback on both tasks, but retained the ability to learn to predict reward based on episodic memory. These findings provide evidence from humans for a specific and necessary role for the cerebellum in incremental learning of reward associations based on reinforcement. More broadly, the findings suggest that alongside its role in motor learning, the cerebellum likely operates in concert with the basal ganglia to support reinforcement learning from reward.

Exploring the role of task success in implicit motor adaptation

“…By extension, the specific cerebellar microzones involved in implicit reach adaptation may be insensitive to reward, despite the fact that reward may play a role in tasks dependent on other cerebellar circuits and the popular presupposition of a single cerebellar computation (Diedrichsen et al 2019; Kostadinov and Häusser 2022). Indeed, the idea that cerebellar circuits for implicit motor learning and reward processing are divided is supported by observations that patients with cerebellar degeneration can engage in many aspects of typical reward-driven reinforcement learning despite showing substantial deficits in adaptation (Morehead et al 2017; Nicholas et al 2022; Therrien et al 2016). Such a division of reward-based and sensory prediction error-based learning would be consistent with classical observations of differences between sensory-prediction error-based supervised motor learning and reinforcement learning (for review see Gershman and Uchida 2019; Raymond and Medina 2018).…”

Reinforcement motor learning after cerebellar damage is related to state estimation

“…Indeed, there is evidence from studies of animal models that the cerebellum encodes information about appetitive and social rewards [54][55][56][57]. Studies in humans have also shown that cerebellar damage can disrupt learning from monetary rewards in non-motor tasks [58][59][60]. However, important differences exist between the cerebellar encoding of reward and the canonical reward encoding in midbrain dopaminergic neurons [54,61].…”