Dataset Information

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence.

ABSTRACT: Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

SUBMITTER: Schubert AL

PROVIDER: S-EPMC7151009 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence.

Schubert Anna-Lena AL Hagemann Dirk D Löffler Christoph C Frischkorn Gidon T GT

Journal of Intelligence 20191225 1

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceiv ...[more]

PMID: 31881681

Similar Datasets

Project description:Although aging is associated with changes in brain structure and cognition it remains unclear which specific structural changes mediate individual cognitive changes. Several studies have reported that white matter (WM) integrity, as assessed by diffusion tensor imaging (DTI), mediates, in part, age-related differences in processing speed (PS). There is less evidence for WM integrity mediating age-related differences in higher order abilities (e.g., memory and executive functions). In 165 typically aging adults (age range 54-89) we show that WM integrity in select cerebral regions is associated with higher cognitive abilities and accounts variance not accounted for by PS or age. Specifically, voxel-wise analyses using tract-based spatial statistics (TBSS) revealed that WM integrity was associated with reasoning, cognitive flexibility and PS, but not memory or word fluency, after accounting for age and gender. While cerebral fractional anisotropy (FA) was only associated with PS; mean (MD), axial (AD) and radial (RD) diffusivity were associated with reasoning and flexibility. Reasoning was selectively associated with left prefrontal AD, while cognitive flexibility was associated with MD, AD and RD throughout the cerebrum. Average WM metrics within select WM regions of interest accounted for 18% and 29% of the variance in reasoning and flexibility, respectively, similar to the amount of variance accounted for by age. WM metrics mediated ~50% of the age-related variance in reasoning and flexibility and different proportions, 11% for reasoning and 44% for flexibility, of the variance accounted for by PS. In sum, (i) WM integrity is significantly, but variably, related to specific higher cognitive abilities and can account for a similar proportion of variance as age, and (ii) while FA is selectively associated with PS; while MD, AD and RD are associated with reasoning, flexibility and PS. This illustrates both the anatomical and cognitive selectivity of structure-cognition relationships in the aging brain.

Project description:BackgroundEcological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not.ResultsWe present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges-87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors.ConclusionsTo reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses. Video abstract.

Dataset Information

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence.

Publications

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets