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The cerebellum is a master-piece for the control of skilled behavior. It is assumed that the huge cerebellar connectivity with extracerebellar neuraxis facilitates internal models to enable predictions with a goal of task optimization. The cerebellum takes into account the numerous internal and external ...

The cerebellum is a master-piece for the control of skilled behavior. It is assumed that the huge cerebellar connectivity with extracerebellar neuraxis facilitates internal models to enable predictions with a goal of task optimization. The cerebellum takes into account the numerous internal and external constraints of motion and thought. Neuroanatomical, neurophysiological, neuropsychological, and computational studies have demonstrated that the functional domains of cerebellar circuitry extend far beyond motor control. The cerebellum is now conceptualized as a machine-learning device and a unique predictive structure not only for motor but also for affective, social and cognitive operations. The segregated loops between the cerebellum and prefrontal cortex, parietal cortex, paralimbic cortex and superior temporal sulcus represent the anatomical substrates of these operations.

Despite its apparent homogeneity in terms of cellular arrangements, microzones and microcomplexes, the cerebellum is composed of multiple modules linking Purkinje neurons, nuclear neurons and the inferior olivary complex. Activations of parasagittal bands of Purkinje neurons are task-selective and the synaptic structures are characterized by a high degree of adaptability.

This Research Topic aims to gather insightful articles to increase our knowledge regarding the roles of cerebello-cerebellar circuits in the underpinnings of predictions.

The following topics will be of particularly high interest :
-the predictions in language
-the predictions underlying social interactions
-the errors in predictions in Schmahmann’s syndrome
-the role of paraflocculus in oculomotor predictions
-the sensory consequences of motion
-the error representations and motor learning
-the predictions for human gait
-the motor impairment in immune ataxias
-the predictive signals in the granular layer
-the predicting spatiotemporal aspects of motion
-the predictions for advances in culture
-the implementation of predictions during sequencing
-the sensorimotor adaptation tasks
-the forward models in the cerebellum
-the predictions for damping
-the cerebellum, basal ganglia and planning
-anticipation, predictions and working memory
-plasticity and predictions

Keywords: Cerebellum, Purkinje neuron, predictions, internal models, sequencing


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