0. Abstract
The ability to prioritize among input features according to relevance enables adaptive behaviors across the human lifespan. However, relevance often remains ambiguous, and such uncertainty increases demands for dynamic control. While both cognitive stability and flexibility decline during healthy ageing, it is unknown whether aging alters how uncertainty impacts perception and decision-making, and if so, via which neural mechanisms. Here, we assess uncertainty adjustment across the adult lifespan (N = 100; cross-sectional) via behavioral modelling and a theoretically informed set of EEG-, fMRI-, and pupil-based signatures. On the group level, older adults show a broad dampening of uncertainty adjustment relative to younger adults. At the individual level, older individuals with more young-like neural responses also showed better maintained cognitive control. Our results highlight neural mechanisms whose maintenance plausibly enables flexible task-set, perception, and decision computations across the adult lifespan.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
1. More consistent and accessible framing of the task uncertainty manipulation, including a revised task description and novel visualization 2. Extended discussion of uncertainty age-effects in the context of variable set-selection costs across the adult lifespan 3. Convergence of fMRI activation pattern with prior state uncertainty assessment 4. Con- & divergence of uncertainty fMRI activation with meta-analytic working memory and attention maps 5. Analysis of age differences at low and high working memory load, and discussion of relation to working memory capacity 6. Robustness of age differences in decision-making (drift rates) and fMRI modulation to variations in the accuracy of individual features (i.e., variable perceptual/choice difficulty) 7. Independence of stimulus-related pupil modulation from cue-related luminance differences 8. Robustness of decoding results to reaction time variations 9. CPP control analysis
