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Bayesian integration during sensorimotor estimation in elite athletes.

Osmar Pinto Neto¹, Victor Curty², Leonardo Crespim²

¹Biomedical Engineering Department, Anhembi University, São Paulo, SP, Brazil; Arena235 Research Lab, São José dos Campos, SP, Brazil; Center for Innovation, Technology and Education - CITE, Parque Tecnológico de São José dos Campos, São José dos Campos, SP, Brazil.

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Summary

This summary is machine-generated.

Elite athletes demonstrate superior sensorimotor estimation under sensory uncertainty compared to non-athletes. Athletic experience enhances the use of probabilistic information for more accurate performance.

Keywords:

Athletic performance Bayesian integration Motor control Sensorimotor estimation

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Area of Science:

Neuroscience
Sports Science
Human Motor Control

Background:

Sensorimotor estimation relies on integrating sensory information.
Sensory uncertainty can challenge estimation accuracy and precision.
Elite athletes may possess enhanced sensorimotor processing capabilities.

Purpose of the Study:

To investigate the impact of sensory uncertainty on sensorimotor estimation in elite athletes versus non-athletes.
To compare the strategies used by athletes and non-athletes in integrating probabilistic information.
To determine if athletic experience influences the ability to adapt to sensory uncertainty.

Main Methods:

Nineteen elite athletes and 16 non-athletes performed temporal and spatial estimation tasks.
A Bayesian analysis was employed to assess estimation strategies.
Performance was evaluated under conditions of certainty and sensory uncertainty.

Main Results:

Both groups utilized Bayesian integration strategies for estimation.
Reduced spatial variability was observed under uncertainty, particularly for non-athletes.
Non-athletes exhibited greater spatial and timing errors than athletes, suggesting less certainty in probabilistic information processing.

Conclusions:

Athletic experience appears to enhance the utilization of probabilistic information for sensorimotor estimation.
Elite athletes demonstrate greater robustness in sensorimotor performance when faced with sensory uncertainty.
Findings suggest that training may optimize the integration of likelihood information in sensorimotor tasks.