Internal models in the cerebellum.

By D. M. Wolpert, R. Miall, Mitsuo Kawato. 1998

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Citations in the corpus

What can the brain teach us about building artificial intelligence? (2016, background): “1995), the cerebellum to implement fast time-scale computations possibly acquired with supervised learning (Kawato et al. 2011; Wolpert et al. 1998), and the limbic brain structures interfacing the brain to the body and generating motivations, emotions, and the value of things (Mirolli et al.”
Towards Continual Reinforcement Learning: A Review and Perspectives (2020, methodology): “Doya et al. (2002) proposed a modular control architecture using multiple prediction models based on the computational model of the cerebellum proposed by Wolpert, Miall, and Kawato (1998).”
Re-evaluating circuit mechanisms underlying pattern separation (2019, positive): “The cerebellum is thought to use associative learning to coordinate movements and predict the sensory consequences of active movement (Wolpert et al., 1998; Kennedy et al., 2014; Brooks et al., 2015; Singla et al., 2017).”
The Cerebellum, Sensitive Periods, and Autism (2014, background): “Cerebellar supervised learning has also been proposed as a means of acquiring internal models (both forward and inverse) about the environment (Wolpert et al., 1998).”
Unstable or Insufficiently Activated Internal Models and Feedback-Biased Motor Control as Sources of Dysfluency: A Theoretical Model of Stuttering (2004, background): “…work has suggested primarily the cerebellum (Blakemore et al., 2001; Imamizu et al., 2000; Miall, Weir, Wopert, & Stein, 1993; Wolpert, Miall, & Kawato, 1998) and posterior parietal cortex (Desmurget & Grafton, 2000; Wolpert et al., 1998) as possible sites for the formation of internal models.”
Coding and use of tactile signals from the fingertips in object manipulation tasks (2009, background): “Computational studies have referred to the cerebellum as a principal brain structure for the storage of forward internal models that support predictive motor contro”
Listening to musical rhythms recruits motor regions of the brain. (2008, result): “These findings concur with present models of cerebellar function that propose it integrates sensory and motor information to generate internal models for predictive motor control ( Wolpert et al. 1998; Ohyama et al. 2003; Bastian 2006).”
Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex (2016, background): “Supervised learning in the cerebellum, including the cerebellar cortex and nuclei, can create a Bforward model^ that predicts the results of executed actions [64].”
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning (2002, background): “Such model-based control and learning has also become increasingly more an accepted hypothesis of how biological movements acquire and perform skilled movement [26, 27].”
Multiple Model-Based Reinforcement Learning (2002, methodology): “The modular control architecture using multiple prediction models was proposed by Wolpert and Kawato as a computational model of the cerebellum (Wolpert et al., 1998; Wolpert & Kawato, 1998).”
Beyond the comparator model: a multifactorial two-step account of agency. (2008, background): “…in some cases why largely distorted sensory feedback of subjects' actions evokes the perceptual experience that the arising sensory events feel strange and discordant to subjects' expectations, in certain tasks even resulting in a feeling of tickliness (Blakemore, Goodbody, & Wolpert, 1998b).”
Computational principles of sensorimotor control that minimize uncertainty and variability (2007, background): “The cerebellar architecture appears to be highly modular (Oscarsson, 1979; Bower & Woolston, 1983), so it is possible that the cerebellum implements many forward and inverse models simultaneously (Wolpert & Kawato, 1998; Wolpert et al. 1998; Haruno et al. 2001).”
Cerebellum-like structures and their implications for cerebellar function. (2008, background): “…in generating predictions concerning expected sensory input or states of the system (Bell et al. 1997a, Devor 2000), and a variety of experimental, clinical, and theoretical studies of the cerebellum support this hypothesis (Diedrichsen et al. 2007, Nixon 2001, Paulin 2005, Wolpert et al. 1998).”
From the perception of action to the understanding of intention (2001, background): “There is evidence that the cerebellum is involved in such a predictive system, storing representations of motor commands and their sensory consequences, body kinematics, external tools and action contexts, from which predictions are mad”