Broadscale dampening of uncertainty adjustment in the aging brain

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 modeling 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 whose modulation more closely resembled that of younger adults also exhibit better maintenance of cognitive control. Our results highlight neural mechanisms whose maintenance plausibly enables flexible task-set, perception, and decision computations across the adult lifespan.

Fig. 1. Older adults show constrained decision-related adjustments to rising uncertainty.

a A Multi-Attribute Attention Task (“MAAT”) requires participants to sample up to four visual features of a compound stimulus for a subsequent perceptual decision. On each trial, participants were first cued to the set of possible probe features (here: motion direction and color). The compound stimulus (which always included all four features) was then presented for 3 s, followed by a single-feature probe (here: prevalence of red vs. green color in the preceding stimulus). Uncertainty was manipulated as the number of target features (one to four) in the pre-stimulus cue (see also Supplementary Fig. 1). b Behavioral data were modeled with a drift diffusion model, in which evidence for options is accumulated with a ‘drift rate’. Older adults exhibited reduced drift rates for single targets (top) and were marked by more limited drift reductions under elevated uncertainty (bottom). Data points represent individual averages across EEG and fMRI sessions. Table S1 reports within-group statistics. c The Centro-parietal positivity (CPP) provides an a priori neural signature of evidence accumulation. The rate of evidence accumulation was estimated as the linear slope of the CPP during the time window indicated by the black bar. Older adults exhibited reduced integration slopes for single targes (top) and were marked by constrained load-related slope shallowing under elevated uncertainty (bottom). To illustrate age- (blue: younger, red: older) and condition-differences (color saturation) in integration slope, responses have been rescaled to the [0, 1] range for visualization. Supplementary Fig. 6 shows original traces. p-values result from two-sided independent t-tests (see Statistical analyses). YA: N = 42. OA: N = 53.

Fig. 2. Decoding of prevalent options from visual cortex.

a Decoding accuracy for cued and uncued features across age groups (means ± SEM; N = 93). Gray shading indicates the approximate timing of stimulus presentation considering the temporal lag in the hemodynamic response. Lines indicate periods of statistically significant differences from chance decoding accuracy (50%) as assessed by cluster-based permutation tests. The inset highlights the visual cortex mask from which signals were extracted for decoding. b Same as in a, but for separate feature probes. Bars indicate sign. above-chance accuracy during the approximate time of stimulus presentation. c Decoding accuracy for probed and unprobed features as a function of the number of cued targets; and decoding accuracy for all features as a function of age. Accuracy was averaged across significant decoding timepoints for cued features. Means ± within-subject SEM for (un)probed features, means ± SEM for age analysis (younger N = 42, older N = 51). Plots illustrate in-text statistical results derived from linear mixed effects models (see methods: fMRI decoding of prevalent feature options).

Fig. 3. MAAT evidence integration relates to prepotent response inhibition.

a Centro-Parietal Positivity (CPP) traces and speech signal power suggest high validity for the semi-automatically labeled speech onset times (SOTs). The CPP trace has been averaged across age and congruency conditions and displays means ± SEM (N = 98). The inset shows the mean EEG topography during the final 300 ms prior to speech onset. b The voiced Stroop task indicated robust interference costs whose magnitude was larger in older adults. Table S1 reports within-group statistics. c Participants with larger MAAT drift rates showed faster responses to incongruent trials (e.g., responding blue to the inset stimulus; two-sided Pearson correlation), also after accounting for categorical age (squares: younger; diamonds: older adults) and covariation with congruent SOTs (see main text).

Fig. 4. EEG and pupil markers of control demands.

Uncertainty increases theta power (a) and pupil diameter (b) across the adult lifespan, but increases are attenuated in older age. (Left) The topography indicates mean bootstrap ratios (BSR) from the task partial least squares (PLS) model. “Brainscores” summarize the expression of this pattern into a single score for each condition and participant (see methods; Supplementary Fig. 10 shows condition-wise Brainscores). (Center) Age comparison of linear Brainscore changes under uncertainty (~age x load interaction; p-values refer to unpaired t-tests). Both signatures exhibited significant uncertainty modulation in younger, as well as older adults (as assessed via one-sample t-tests; see Table S1), with constrained modulation in older adults. (Right) Time series data are presented as means ± within-subject S.E.Ms. Target amount corresponds to increasing color saturation. Orange shading in a indicates the timepoints across which data have been averaged for the task PLS. Black lines in (b) indicate time points exceeding a BSR of 3 (~99% threshold). The uncertainty modulation of pupil diameter occurred on top of a general pupil constriction due to stimulus-evoked changes in luminance upon task onset (see inset). Luminance did by stimulus design not systematically differ across load levels.

Fig. 5. Only younger adults upregulate cortical excitability under increased uncertainty.

Results of task partial least squares (PLS) models, assessing relations of alpha power (a), sample entropy (b) and aperiodic 1/f slope (c) to uncertainty. (Left) Topographies indicate mean bootstrap ratios (BSR). Orange dots indicate the sensors across which data were averaged for data visualization. (Center) Age comparison of linear uncertainty effects (~age x uncertainty interaction). Statistics refer to two-sided unpaired t-tests (younger N = 42, older N = 53; see Statistical analyses). For condition-wise Brainscores, see Supplementary Fig. 10. All three signatures exhibited significant uncertainty modulation in younger, but not in older adults. Table S1 reports within-group statistics. (Right) Time series data for a and b are presented as means ± within-subject S.E.M.s (younger N = 47, older N = 53). Orange shading indicates the timepoints across which data have been averaged for the respective task-PLS. For (c), average spectra during stimulus presentation are shown as a function of the number of targets. Plots with gray and orange background highlight low- and high-frequency ranges, respectively.

Fig. 6. Multivariate relation of EEG/pupil/behavioral signatures to fMRI BOLD uncertainty modulation.

a Results of a behavioral partial least squares (PLS) analysis linking linear changes in BOLD activation to interindividual EEG, pupil, and behavioral differences. Table S4 lists peak coordinates. b The multivariate expression of BOLD changes alongside rising uncertainty was reduced in older (N = 53) compared with younger adults (N = 42). Table S1 reports within-group statistics. c Individual fMRI Brainscore differences related to behavioral composite scores, also after accounting for age covariation. Squares = younger individuals; diamonds = older individuals. d Contributing signatures to the fMRI Brainscore. All signature estimates refer to linear uncertainty changes. Data are presented as mean values ± bootstrapped 95% confidence intervals (N = 1000 bootstraps). e Major nuclei and projection zones in which behavioral relations are maximally reliable according to average Bootstrap ratios (red) and the percentage of voxels in each subregion exceeding a BSR of 3. See Methods for abbreviations. Strongest expression is observed in nuclei that project to fronto-parietal cortical targets. f Visualization of uncertainty modulation for the mediodorsal nucleus, a “higher order” nucleus, and the LGN, a visual relay nucleus. Traces display mean ± SEM, for younger (red) and older adults (black), and varying target amount (broken: single, continuous: four). The green shading indicates the approximate stimulus presentation period after accounting for the delay in the hemodynamic response function.

Fig. 7. Schematic model summary.

a In static contexts, prefrontal-hippocampal networks may signal high confidence in the current task state, which enables stable task sets, and a targeted processing of specific sensory representations with high acuity. Such selective processing of specific task-relevant features benefits their efficient evidence integration. Such selectivity would be suboptimal in contexts with uncertain or changing task sets, however. An MD-ACC circuit may track such uncertainty and enhance stochastic task set flexibility in changing or ambiguous contexts. In coordination with posterior-parietal cortex, this feasibly enables more diverse albeit less precise perceptual representations. b The neural system of younger adults may more dynamically adjust feature fidelity during stimulus presentation to the degree of uncertainty. Observed effects align with a switch between a specific high-acuity processing of individual features (blue), and a more diverse, if less precise processing of multiple features (red; see also Thiele & Bellgrove, 2018). In contrast, the aged neural system may be stuck in a suboptimal middle ground that affords neither stable precision, nor flexible imprecision. mPFC medial prefrontal cortex, HC hippocampus, ACC anterior cingulate cortex, MD mediodorsal thalamus.