Abstract
This review surveys physiological, behavioral, and morphological evidence converging to the view of the cerebro-cerebellum as loci of internal forward models. The cerebro-cerebellum, the phylogenetically newest expansion in the cerebellum, receives convergent inputs from cortical, subcortical, and spinal sources, and is thought to perform the predictive computation for both motor control, motor learning, and cognitive functions. This predictive computation is known as an internal forward model. First, we elucidate the theoretical foundations of an internal forward model and its role in motor control and motor learning within the framework of the optimal feedback control model. Then, we discuss a neural mechanism that generates various patterns of outputs from the cerebro-cerebellum. Three lines of supporting evidence for the internal-forward-model hypothesis are presented in detail. First, we provide physiological evidence that the cerebellar outputs (activities of dentate nucleus cells) are predictive for the cerebellar inputs [activities of mossy fibers (MFs)]. Second, we provide behavioral evidence that a component of movement kinematics is predictive for target motion in control subjects but lags behind a target motion in patients with cerebellar ataxia. Third, we provide morphological evidence that the cerebellar cortex and the dentate nucleus receive separate MF projections, a prerequisite for optimal estimation. Finally, we speculate that the predictive computation in the cerebro-cerebellum could be deployed to not only motor control but also to non-motor, cognitive functions. This review concludes that the predictive computation of the internal forward model is the unifying algorithmic principle for understanding diverse functions played by the cerebro-cerebellum.
Highlights
The cerebellum has developed in the sensory domain of the central nervous system (CNS) as evidenced by the fact that it has emerged in the alar plate
The cerebellum may be better understood if we ask ‘‘how the cerebellum computes’’ than ‘‘what the cerebellum computes.’’ In contrast to previous studies that have focused on neural representations of an internal forward model, we explored how the cerebellum transforms its inputs [mossy fibers (MFs)] to its outputs [dentate nucleus cells (DNCs); Tanaka et al, 2019]
Our observation suggests that activation of DNCs by disinhibition from Purkinje cells (PCs) facilitates the execution of wrist movement, whereas suppression of the DNCs due to increased PC activity contributes to the stabilization of proximal muscles and improves task performance
Summary
The cerebellum has developed in the sensory domain of the central nervous system (CNS) as evidenced by the fact that it has emerged in the alar plate (i.e., the sensory part (dorsal half) of the neural tube of the rhombencephalon of primitive jawless vertebrate such as myxinoids (hagfish) or petromyzonts (lampreys; Larsell, 1967; Sugahara et al, 2016). The local neural circuitry of the cerebellar cortex is characterized by its superb homogeneity, sometimes expressed as being ‘‘crystal-like,’’ whereas the inputs to and the outputs from the cerebellum are heterogeneous from one region to another. It is commonly postulated that the functional diversity of the cerebellum originates from heterogeneous input-output connectivity and is processed through a common algorithm that is implemented in the homogenous neural circuitry in the cerebellar cortex. This review article provides physiological, behavioral, and morphological evidence that converges to the cerebro-cerebellum as a neural substrate of the internal forward model. We will discuss how the input-output organization of the cerebro-cerebellum may contribute to forward models for higher (i.e., non-motor) brain functions. Section ‘‘Functional Evidence for Cerebellar Forward Model’’ summarizes neural and behavioral evidence that the cerebellum performs predictive computation. Section ‘‘Remaining Issues About Cerebellar Internal Models’’ concludes the internal-model hypothesis of the cerebellum and enumerates unresolved issues toward the goal of understanding the cerebro-cerebellum
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