Error Correction, Sensory Prediction, and Adaptation in Motor Control
TLDR
Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors, and is used to produce a lifetime of calibrated movements.Abstract:
Motor control is the study of how organisms make accurate goal-directed movements. Here we consider two problems that the motor system must solve in order to achieve such control. The first problem is that sensory feedback is noisy and delayed, which can make movements inaccurate and unstable. The second problem is that the relationship between a motor command and the movement it produces is variable, as the body and the environment can both change. A solution is to build adaptive internal models of the body and the world. The predictions of these internal models, called forward models because they transform motor commands into sensory consequences, can be used to both produce a lifetime of calibrated movements, and to improve the ability of the sensory system to estimate the state of the body and the world around it. Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors.read more
Citations
More filters
Journal ArticleDOI
Dopamine in Motivational Control: Rewarding, Aversive, and Alerting
TL;DR: It is proposed that dopamine neurons come in multiple types that are connected with distinct brain networks and have distinct roles in motivational control, and it is hypothesized that these dopaminergic pathways for value, salience, and alerting cooperate to support adaptive behavior.
Journal ArticleDOI
An integrated theory of language production and comprehension
Martin J. Pickering,Simon Garrod +1 more
TL;DR: It is asserted that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other.
Journal ArticleDOI
Neuroplasticity subserving motor skill learning.
Eran Dayan,Leonardo G. Cohen +1 more
TL;DR: Findings demonstrating functional and structural plasticity across different spatial and temporal scales that mediate motor skill learning are reviewed while identifying converging areas of interest and possible avenues for future research.
Journal ArticleDOI
Neuroscience Needs Behavior: Correcting a Reductionist Bias
John W. Krakauer,Asif A. Ghazanfar,Alex Gomez-Marin,Malcolm A. MacIver,David Poeppel,David Poeppel +5 more
TL;DR: A more pluralistic notion of neuroscience is advocated when it comes to the brain-behavior relationship: behavioral work provides understanding, whereas neural interventions test causality.
Journal ArticleDOI
Consensus Paper: The Cerebellum's Role in Movement and Cognition
Leonard F. Koziol,Deborah Ely Budding,Nancy C. Andreasen,Stefano D'Arrigo,Sara Bulgheroni,Hiroshi Imamizu,Masao Ito,Mario Manto,Cherie L. Marvel,Krystal L. Parker,Giovanni Pezzulo,Narender Ramnani,Daria Riva,Jeremy D. Schmahmann,Larry Vandervert,Tadashi Yamazaki +15 more
TL;DR: The cerebellum in relation to neurocognitive development, language function, working memory, executive function, and the development of cerebellar internal control models is considered and some of the ways in which better understanding the Cerebellum's status as a “supervised learning machine” can enrich the ability to understand human function and adaptation are considered.
References
More filters
Journal ArticleDOI
Humans integrate visual and haptic information in a statistically optimal fashion.
TL;DR: The nervous system seems to combine visual and haptic information in a fashion that is similar to a maximum-likelihood integrator, and this model behaved very similarly to humans in a visual–haptic task.
Journal ArticleDOI
Optimal feedback control as a theory of motor coordination.
TL;DR: This work shows that the optimal strategy in the face of uncertainty is to allow variability in redundant (task-irrelevant) dimensions, and proposes an alternative theory based on stochastic optimal feedback control, which emerges naturally from this framework.
Journal ArticleDOI
Adaptive representation of dynamics during learning of a motor task
TL;DR: The investigation of how the CNS learns to control movements in different dynamical conditions, and how this learned behavior is represented, suggests that the elements of the adaptive process represent dynamics of a motor task in terms of the intrinsic coordinate system of the sensors and actuators.
Journal ArticleDOI
Forward models for physiological motor control
R. C. Miall,Daniel M. Wolpert +1 more
TL;DR: The uses of such internal models for solving several fundamental computational problems in motor control are outlined and the evidence for their existence and use by the central nervous system is reviewed.