The intraindividual variability (IIV) of cognitive performance has been shown to increase with aging. While brain research has generally focused on mean performance, little is known about neural correlates of cognitive IIV. Nevertheless, some studies suggest that IIV relates more strongly than mean level of performance to the quality of white matter (WM). Our study aims to explore the relation between WM integrity and cognitive IIV by combining functional (fMRI) and structural (diffusion tensor imaging, DTI) imaging. Twelve young adults (aged 18–30 years) and thirteen older adults (61–82 years) underwent a battery of neuropsychological tasks, along with fMRI and DTI imaging. Their behavioral data were analyzed and correlated with the imaging data at WM regions of interest defined on the basis of (1) the fMRI‐activated areas and (2) the Johns Hopkins University (JHU) WM tractography atlas. For both methods, fractional anisotropy, along with the mean, radial, and axial diffusivity parameters, was computed. In accord with previous studies, our results showed that the DTI parameters were more related to IIV than to mean performance. Results also indicated that age differences in the DTI parameters were more pronounced in the regions activated primarily by young adults during a choice reaction‐time task than in those also activated in older adults.

Within-task variability across trials (intra-individual variability (IIV)) has been mainly studied using latency measures but rarely with accuracy measures. The aim of the Geneva Variability Study was to examine IIV in both latency and accuracy measures of cognitive performance across the lifespan, administering the same tasks to children, younger adults, and older adults. Six processing speed tasks (Response Time (RT) tasks, 8 conditions) and two working memory tasks scored in terms of the number of correct responses (Working Memory (WM)—verbal and visuo-spatial, 6 conditions), as well as control tasks, were administered to over 500 individuals distributed across the three age periods. The main questions were whether age differences in IIV would vary throughout the lifespan according (i) to the type of measure used (RTs vs. accuracy); and (ii) to task complexity. The objective of this paper was to present the general experimental design and to provide an essentially descriptive picture of the results. For all experimental tasks, IIV was estimated using intra-individual standard deviation (iSDr), controlling for the individual level (mean) of performance and for potential practice effects. As concerns RTs, and in conformity with a majority of the literature, younger adults were less variable than both children and older adults, and the young children were often the most variable. In contrast, IIV in the WM accuracy scores pointed to different age trends—age effects were either not observed or, when found, they indicated that younger adults were the more variable group. Overall, the findings suggest that IIV provides complementary information to that based on a mean performance, and that the relation of IIV to cognitive development depends on the type of measure used.

It is well known that cognitive decline in older adults is of smaller amplitude in longitudinal than in cross-sectional studies. Yet, the measure of interest rests generally with aggregated group data. A focus on individual developmental trajectories is rare, mainly because it is difficult to assess intraindividual change reliably. Individual differences in developmental trajectories may differ quantitatively (e.g., larger or smaller decline) or qualitatively (e.g., decline vs improvement), as well as in the degree of heterogeneity of change across different cognitive domains or different tasks. The present paper aims at exploring, within the Geneva Variability Study, individual change across several cognitive domains in 92 older adults (aged 59–89 years at baseline) over a maximum of seven years and a half. Two novel, complementary methods were used to explore change in cognitive performance while remaining entirely at the intra-individual level. A bootstrap based confidence interval was estimated, for each participant and for each experimental condition, making it possible to define three patterns: stability, increase or decrease in performance. Within-person ANOVAs were also conducted for each individual on all the tasks. Those two methods allowed quantifying the direction, the amplitude and the heterogeneity of change for each individual. Results show that trajectories differed widely among individuals and that decline is far from being the rule.

Developmental cognitive psychology (as well as cognitive psychology in general) has a long-standing tradition to ignore all variations other than age, as if individual variations were only measurement error or noise