Internal Models in Biological Control
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Publication Date
2019-05-01Journal Title
Annual Review of Control, Robotics, and Autonomous Systems
ISSN
2573-5144
Publisher
Annual Reviews
Volume
2
Pages
339-364
Type
Article
Metadata
Show full item recordCitation
McNamee, D., & Wolpert, D. (2019). Internal Models in Biological Control. Annual Review of Control, Robotics, and Autonomous Systems, 2 339-364. https://doi.org/10.1146/annurev-control-060117-105206
Abstract
Rationality principles such as optimal feedback control and Bayesian inference underpin a probabilistic framework that has accounted for a range of empirical phenomena in biological sensorimotor control. To facilitate the optimization of flexible and robust behaviors consistent with these theories, the ability to construct internal models of the motor system and environmental dynamics can be crucial. In the context of this theoretic formalism, we review the computational roles played by such internal models and the neural and behavioral evidence for their implementation in the brain.
Keywords
internal model, state estimation, predictive control, planning, optimal feedback control, Bayesian inference
Sponsorship
Wellcome Trust (097803/Z/11/Z)
Royal Society (RP120142)
Wellcome Trust (110257/Z/15/Z)
Embargo Lift Date
2100-01-01
Identifiers
External DOI: https://doi.org/10.1146/annurev-control-060117-105206
This record's URL: https://www.repository.cam.ac.uk/handle/1810/283097
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Licence:
http://www.rioxx.net/licenses/all-rights-reserved
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