von Krause · Nature human behaviour 2022 · cross-sectional computational modeling study · n=1,200,000

Mental speed is high until age 60 as revealed by analysis of over a million participants.

Cited 54 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional observational study applying computational modeling to large-scale data (graded by non-clinical design analogy).

PubMed 35177809 · doi:10.1038/s41562-021-01282-7 · record verified 2026-08-26

What was done

Researchers applied a Bayesian diffusion model to cross-sectional response time data from 1.2 million participants to decompose raw response times into distinct cognitive components (information processing speed, decision caution, and non-decisional processes). Efficient parameter estimation on the massive dataset was conducted using specialized neural network-assisted Bayesian inference across different age groups.

What was found

Raw response times showed slowing starting as early as age 20. However, computational decomposition revealed that this early slowing was attributable to increases in decision caution and slower non-decisional processes rather than a loss of mental speed. Actual mental speed remained high throughout adulthood and began declining only after approximately age 60 (the abstract reports age thresholds but no numeric model estimates or confidence intervals).

Why it matters

This finding challenges the prevailing model of cognitive aging, suggesting that apparent cognitive slowing across early and middle adulthood reflects strategic shifts toward caution and peripheral motor/perceptual slowing rather than an intrinsic loss of information processing speed.

Limits

The study is cross-sectional rather than longitudinal, making it susceptible to cohort effects and selection bias. The abstract does not provide specific numerical parameter values, effect sizes, participant demographic distributions, or details about the specific behavioral tasks analyzed.

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