ReviewFrontiers in human neuroscience2021
Adaptive Feedback Control in Human Reaching Adaptation to Force Fields.
Review in Frontiers in human neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Human-inspired sensorimotor controller for dynamic motion adaptation: a study in robotic arms.Frontiers in neurorobotics · 2026Article
- Article
- History-dependent muscle resistance to stretch remains high after small, posturally relevant pre-movements.The Journal of experimental biology · 2023Article
- Continuous evaluation of cost-to-go for flexible reaching control and online decisions.PLoS computational biology · 2023Article
- Separability of Human Motor Memories during reaching adaptation with force cues.PLoS computational biology · 2022Article
- Article
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Authors and funding
2 authors.
Funding
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Abstract
Sensorimotor adaptation is a central function of the nervous system, as it allows humans and other animals to flexibly anticipate their interaction with the environment. In the context of human reaching adaptation to force fields, studies have traditionally separated feedforward (FF) and feedback (FB) processes involved in the improvement of behavior. Here, we review computational models of FF adaptation to force fields and discuss them in light of recent evidence highlighting a clear involvement of feedback control. Instead of a model in which FF and FB mechanisms adapt in parallel, we discuss how online adaptation in the feedback control system can explain both trial-by-trial adaptation and improvements in online motor corrections. Importantly, this computational model combines sensorimotor control and short-term adaptation in a single framework, offering novel perspectives for our understanding of human reaching adaptation and control.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.