Fast visual prediction and slow optimization of preferred walking speed

Area of Science:

• Human locomotion
• Neuroscience of movement
• Biomechanics

Background:

• Humans prefer walking speeds that minimize metabolic energy expenditure.
• Slower metabolic sensing and faster sensory feedback mechanisms influence gait adjustments.
• Predictive sensory information can approximate optimal gait but relies on experience.

Purpose of the Study:

• To investigate if the nervous system integrates rapid visual cues with slower metabolic feedback for gait optimization.
• To test the hypothesis that visual feedback aids in selecting preferred walking speeds.

Main Methods:

• Utilized virtual reality to manipulate visual flow speed relative to self-selected walking speed on a treadmill.
• Quantified walking speed adjustments in response to step changes in visual speed.
• Measured response dynamics to perturbations in the visual-to-walking speed ratio.

Main Results:

• Subjects exhibited rapid (<2s) corrective responses to visual speed perturbations, adjusting to realign visual and walking speeds.
• Responses indicated a predictive mechanism guiding speed adjustments towards the preferred walking speed.
• Slower, gradual return (>300s) to the pre-perturbation preferred speed was observed, suggesting dual optimization processes.

Conclusions:

• A rapid, visually-informed predictive process assists in selecting preferred walking speeds.
• This rapid visual mechanism likely complements a slower, metabolic-based optimization process.
• The nervous system effectively combines predictive and feedback control for efficient locomotion.