When people walk over holes or gaps, they pick the easiest way to cross—like stepping over or stepping down and up—based on which one feels like it uses less energy, even if they can’t feel it until after they’ve decided.
Scientific Claim
Healthy young adults select locomotor strategies to cross obstacles based on the predicted total mechanical energy cost across multiple steps, choosing the option with the lowest integrated energy expenditure, even when the optimal strategy changes with obstacle geometry (e.g., short/deep vs. long/shallow holes), demonstrating that energy minimization guides decision-making in complex terrain.
Original Statement
“Strategy selection was consistent with task CoTtot minimization... the magnitude of the task CoTtot difference between the two possible strategies predicted the probability that a given strategy would be chosen.”
Evidence Quality Assessment
Claim Status
overstated
Study Design Support
Design supports claim
Appropriate Language Strength
association
Can only show association/correlation
Assessment Explanation
The study is observational with within-subject comparisons but lacks randomization or control of confounders, so it cannot establish causation. The authors use causal language ('reveals the capacity', 'demonstrating the capacity'), which overstates the evidence.
More Accurate Statement
“Healthy young adults' selection of locomotor strategies to cross obstacles is associated with the predicted total mechanical energy cost across multiple steps, with a higher likelihood of choosing the strategy that minimizes integrated energy expenditure.”
Gold Standard Evidence Needed
According to GRADE and EBM methodology, here is what ideal scientific evidence would look like to definitively prove or disprove this specific claim, ordered from strongest to weakest evidence.
Randomized Controlled TrialLevel 1aThat manipulating predicted energy cost (via visual cues) directly causes changes in obstacle negotiation strategy selection.
That manipulating predicted energy cost (via visual cues) directly causes changes in obstacle negotiation strategy selection.
What This Would Prove
That manipulating predicted energy cost (via visual cues) directly causes changes in obstacle negotiation strategy selection.
Ideal Study Design
A double-blind, within-subject RCT with 50 healthy young adults (18–35 years) who are randomly assigned to view either a high-energy-cost or low-energy-cost visual simulation of an obstacle (e.g., 3D projection of hole depth/length) before each trial, with strategy choice recorded; primary outcome is strategy selection probability under manipulated energy cost cues, with crossover design and washout periods.
Limitation: Cannot isolate whether energy prediction is learned or innate, or whether other sensory cues (e.g., subtle auditory or proprioceptive) influence choice.
Prospective Cohort StudyLevel 2bThat individuals who more accurately predict energy costs during obstacle negotiation over time show better locomotor efficiency and lower metabolic expenditure in real-world environments.
That individuals who more accurately predict energy costs during obstacle negotiation over time show better locomotor efficiency and lower metabolic expenditure in real-world environments.
What This Would Prove
That individuals who more accurately predict energy costs during obstacle negotiation over time show better locomotor efficiency and lower metabolic expenditure in real-world environments.
Ideal Study Design
A 6-month prospective cohort of 100 healthy adults (20–40 years) performing daily obstacle navigation tasks in natural environments (e.g., urban sidewalks with varied steps/curbs), using wearable motion sensors and metabolic monitors to correlate predicted vs. actual energy cost accuracy with long-term locomotor efficiency.
Limitation: Cannot control for environmental variability or self-selection bias in route choice.
Cross-Sectional StudyLevel 3That the ability to predict energy cost during obstacle negotiation correlates with neural activity in motor planning regions (e.g., prefrontal cortex, cerebellum) in healthy adults.
That the ability to predict energy cost during obstacle negotiation correlates with neural activity in motor planning regions (e.g., prefrontal cortex, cerebellum) in healthy adults.
What This Would Prove
That the ability to predict energy cost during obstacle negotiation correlates with neural activity in motor planning regions (e.g., prefrontal cortex, cerebellum) in healthy adults.
Ideal Study Design
A cross-sectional fMRI study of 40 healthy adults (20–35 years) performing virtual obstacle negotiation tasks while brain activity is recorded, measuring correlation between predicted energy cost accuracy and activation in motor planning and visual-spatial integration regions.
Limitation: Cannot determine if neural activity causes better prediction or is a consequence of experience.
Animal Model StudyLevel 4That energy cost prediction during obstacle negotiation is an evolutionarily conserved behavior across species.
That energy cost prediction during obstacle negotiation is an evolutionarily conserved behavior across species.
What This Would Prove
That energy cost prediction during obstacle negotiation is an evolutionarily conserved behavior across species.
Ideal Study Design
A controlled experiment with 30 rats or non-human primates trained to choose between two obstacle-crossing paths with differing mechanical energy costs, using food reward as incentive, measuring choice consistency and learning speed across trials.
Limitation: Cannot directly translate neural or cognitive mechanisms to humans.
Evidence from Studies
Supporting (1)
Human locomotion over obstacles reveals real-time prediction of energy expenditure for optimized decision-making
People chose how to step over holes based on which way would use the least energy, even before they touched the ground — and they did it just by looking, not by feeling it out.