The Cerebellum: Adaptive Prediction for Movement and Cognition

Multidisciplinary evidence indicates a role for the cerebellum in various aspects of cognition. Due to its uniform cytoarchitecture and extensive reciprocal connections with frontal, parietal, and temporal associative cortices, theorists have sought to identify cerebellar computations that are universal across sensorimotor and associative processes. Two key concepts are prediction and error-based learning. Recent work has revealed physiological diversity across structurally similar cerebellar modules. The computational constraints that arise from this diversity may be important for understanding cerebellar processing in different functional domains. Knowledge has substantially evolved on cerebellar involvement in language and social cognition, providing representative domains to evaluate functional hypotheses of the ‘cognitive’ cerebellum and to consider how disturbances of cerebellar function may contribute to developmental and neuropsychiatric disorders. Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops. Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops. a neurological condition characterized by abnormal motor coordination due to alterations in the sensory, vestibular, or cerebellar system. Signs include problems with balance, eye movements, volitional movements and speech, especially when the movements are produced quickly and require coordination of multiple joints. a physiological network identified by rsFC spanning the medial prefrontal, medial temporal, and posterior cingulate cortex and precuneus; activated in the absence of a specific external task and thought to be involved in mental simulation for planning, self-evaluation, and social interaction. refers to movements lacking the appropriate metrics due to ataxia. Spatially, the movements may over- or undershoot the target, with the problems evident in eye, arm, or leg movements. process by which changes in behavior are driven by errors occurring as a result of the production of that behavior in a similar context. In ideal circumstances, the amount of error is reduced in a continuous manner from trial to trial, continuing until performance is error free. a representation of the predictable relationship between the input and output of a system, thus providing an estimation of a new state or outcome given an input. Forward models are typically adaptive, updated by experience. In sensorimotor systems, a forward model can take the motor command (or efference copy of the command) to predict the forthcoming sensory consequences of the movement. a representation that takes a desired sensory state as the input and generates the motor command required to achieve that state. Inverse models perform the inverse operation of a forward model. physiological mechanism of learning manifesting as the reduction of synaptic strength between two neurons typically resulting from a strong excitatory input. In the cerebellar cortex, LTD of parallel-fiber synapses onto Purkinje cells is triggered by powerful climbing-fiber input. signal arising from mismatch between the expected sensory consequences of a stimulus or movement and the actual sensory input. Thus, sensory prediction errors are a violation of a prediction. For example, when walking down the stairs, a missing tread would result in a sensory prediction error based on the absence of expected somatosensory input. a heritable degenerative disease that produces ataxia through degeneration of the cerebellum and/or structures sending critical inputs to the cerebellum. At present there are more than 40 known types, each related to specific gene mutations. Pathophysiological correlates and symptoms vary as a function of type. psychological construct that refers to the ability to infer the mental states of other individuals, particularly their beliefs, feelings, and intentions.