Towards Modeling Human Motor Learning Dynamics in High-Dimensional Spaces

Kamboj, Ankur; Ranganathan, Rajiv; Tan, Xiaobo; Srivastava, Vaibhav

doi:10.23919/acc53348.2022.9867377

2022 American Control Conference (ACC) 2022

DOI: 10.23919/acc53348.2022.9867377

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Towards Modeling Human Motor Learning Dynamics in High-Dimensional Spaces

Ankur Kamboj

Rajiv Ranganathan

Xiaobo Tan

et al.

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2024

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Human motor learning dynamics in high-dimensional tasks

Kamboj,

Ranganathan,

Tan

et al. 2024

PLoS Comput Biol

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Conventional approaches to enhance movement coordination, such as providing instructions and visual feedback, are often inadequate in complex motor tasks with multiple degrees of freedom (DoFs). To effectively address coordination deficits in such complex motor systems, it becomes imperative to develop interventions grounded in a model of human motor learning; however, modeling such learning processes is challenging due to the large DoFs. In this paper, we present a computational motor learning model that leverages the concept of motor synergies to extract low-dimensional learning representations in the high-dimensional motor space and the internal model theory of motor control to capture both fast and slow motor learning processes. We establish the model’s convergence properties and validate it using data from a target capture game played by human participants. We study the influence of model parameters on several motor learning trade-offs such as speed-accuracy, exploration-exploitation, satisficing, and flexibility-performance, and show that the human motor learning system tunes these parameters to optimize learning and various output performance metrics.

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Human motor learning dynamics in high-dimensional tasks

Kamboj,

Ranganathan,

Tan

et al. 2024

PLoS Comput Biol

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show abstract

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Towards Modeling Human Motor Learning Dynamics in High-Dimensional Spaces

Cited by 1 publication

References 28 publications

Human motor learning dynamics in high-dimensional tasks

Human motor learning dynamics in high-dimensional tasks

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