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

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.

Download Full-text

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

10.31234/osf.io/5rdfg ◽

2019 ◽

Author(s):

Anna-Lena Schubert ◽

Dirk Hagemann ◽

Christoph Löffler ◽

Gidon T. Frischkorn

Keyword(s):

Individual Differences ◽

Age Differences ◽

Processing Speed ◽

Cognitive Aging ◽

Fluid Intelligence ◽

Higher Order ◽

Mediation Effect ◽

Model Parameters ◽

Response Planning ◽

Age Related

Download Full-text

Elucidating the contributions of processing speed, executive ability, and frontal lobe volume to normal age-related differences in fluid intelligence

Journal of the International Neuropsychological Society ◽

10.1017/s1355617700611062 ◽

2000 ◽

Vol 6 (1) ◽

pp. 52-61 ◽

Cited By ~ 114

Author(s):

DAVID SCHRETLEN ◽

GODFREY D. PEARLSON ◽

JAMES C. ANTHONY ◽

ELIZABETH H. AYLWARD ◽

ANN M. AUGUSTINE ◽

...

Keyword(s):

Frontal Lobe ◽

Processing Speed ◽

Cognitive Aging ◽

Fluid Intelligence ◽

Brain Structures ◽

Brain Volumes ◽

Spatial Intelligence ◽

Age Related ◽

Perceptual Comparison ◽

Executive Ability

One theory of normal cognitive aging asserts that decreases in simple processing speed mediate the age-related decline of fluid intelligence. Another possibility is that age-related atrophic changes in frontal brain structures undermine the functioning of executive abilities, thereby producing the same decline. In this study, we used principal components analysis to derive a measure of fluid–spatial intelligence in 197 normal adults between 20 and 92 years of age. Measures of perceptual comparison speed, working memory, and executive ability, as well as regional brain volumes based on high resolution magnetic resonance imaging were obtained from a subsample of 112 participants. We then conducted a series of hierarchical multiple regression analyses to test whether (1) the processing speed theory, (2) frontal–executive theory, or (3) some combination of these best accounted for age-related variation in fluid intelligence. The results showed that perceptual comparison speed, executive ability, and frontal lobe volume each made significant contributions to a regression equation that explained 57% of the variance in fluid intelligence. These findings suggest that both the processing speed and frontal–executive theory of cognitive aging are partially correct and complement one another. (JINS, 2000, 6, 52–61.)

Download Full-text

Modelling Age Differences in Isometric Elbow Flexion Using Hill's Three-Element Visco-Elastic Model

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193129303700210 ◽

1993 ◽

Vol 37 (2) ◽

pp. 202-205

Author(s):

R. Darin Ellis ◽

Kentaro Kotani

Keyword(s):

Mechanical Properties ◽

Steady State ◽

Age Differences ◽

Elbow Flexion ◽

Model Parameters ◽

Elastic Model ◽

Tissue Elasticity ◽

Age Related ◽

Complex Models ◽

State Force

A visco-elastic model of the mechanical properties of muscle was used to describe age-differences in the buildup of force in isometric elbow flexion. Given information from the literature on age-related physiological changes, such as decreasing connective-tissue elasticity, one would expect changes in the mechanical properties of skeletal muscle and their related model parameters. Force vs. time curves were obtained for 7 young (aged 21–27) and 7 old (aged 69–83) female subject. There were significant age group differences in steady-state force level and the best fitting model parameters. In particular, the viscous damping element of the model plays a large role in describing the increased time to reach steady-state force levels in the older subject group. Implications of this research include incorporating parameter differences into more complex models, such as crash impact models.

Download Full-text

Interactive effects of age and inflammation on change in ecologically-assessed cognitive functioning

Innovation in Aging ◽

10.1093/geroni/igab046.2621 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 705-706

Author(s):

Christopher Engeland ◽

Erik Knight ◽

Martin Sliwinski ◽

Jennifer Graham-Engeland

Keyword(s):

Working Memory ◽

Cognitive Functioning ◽

Processing Speed ◽

Cognitive Aging ◽

Spatial Working Memory ◽

Ex Vivo ◽

Cognitive Testing ◽

Interactive Effects ◽

Test Accuracy ◽

Age Related

Abstract Inflammation has been implicated as a precursor to steeper declines in age-associated cognitive decline. Here we investigated biomarkers of peripheral inflammation [basal cytokines, stimulated cytokines (ex vivo), C-reactive protein (CRP)] as moderators of age-related changes in cognitive functioning. As part of the Effects of Stress on Cognitive Aging, Physiology, and Emotion (ESCAPE) study, participants (N = 233; 65% female; 63% Black, 25% Hispanic; 25-65 years of age) completed up to four instances of ambulatory cognitive testing per day across two weeks, over three waves of annual assessments. After each 2-week ecological momentary assessment (EMA) burst, blood was collected and assayed for inflammatory biomarkers. Performance on spatial working memory (mean Euclidean distance errors), processing speed (mean symbol search reaction time), and working memory (n-back test accuracy) tasks were averaged across all instances within an EMA burst. CRP and age interactively predicted change in spatial working memory (B = 0.003, [0.000, 0.005], t(133.60) = 2.350, p = 0.020) such that higher CRP at older ages (~60 years) was associated with a loss of the expected practice effects across waves; at younger ages, CRP did not relate to change in spatial working memory. In a similar fashion, basal (B = -0.002, [-0.004, -0.000], t(103.26) = -2.399, p = 0.018) and stimulated cytokine levels (B = -0.002, [-0.004, -0.000], t(126.65) = -2.183, p = 0.031) interacted with age to predict change in processing speed across waves. These results indicate that inflammation may be critically associated with changes in cognitive functioning in older mid-life adults.

Download Full-text

Situation model updating in young and older adults

International Journal of Behavioral Development ◽

10.1177/0165025419874125 ◽

2019 ◽

pp. 016502541987412

Author(s):

Lara Hoeben Mannaert ◽

Katinka Dijkstra

Keyword(s):

Older Adults ◽

Age Differences ◽

Language Comprehension ◽

Cognitive Aging ◽

Model Updating ◽

Situation Model ◽

Future Research ◽

Situation Models ◽

The Past ◽

Age Related

Over the past decade or so, developments in language comprehension research in the domain of cognitive aging have converged on support for resilience in older adults with regard to situation model updating when reading texts. Several studies have shown that even though age-related declines in language comprehension appear at the level of the surface form and text base of the text, these age differences do not apply to the creation and updating of situation models. In fact, older adults seem more sensitive to certain manipulations of situation model updating. This article presents a review of theories on situation model updating as well how they match with research on situation model updating in younger and older adults. Factors that may be responsible for the resilience of language comprehension in older age will be discussed as well as avenues for future research.

Download Full-text

Decision-Making Competence: More Than Intelligence?

Current Directions in Psychological Science ◽

10.1177/0963721420901592 ◽

2020 ◽

Vol 29 (2) ◽

pp. 186-192 ◽

Cited By ~ 3

Author(s):

Wändi Bruine de Bruin ◽

Andrew M. Parker ◽

Baruch Fischhoff

Keyword(s):

Older Adults ◽

Decision Making ◽

Individual Differences ◽

Fluid Intelligence ◽

Psychological Research ◽

Future Research ◽

Experimental Conditions ◽

Crystallized Intelligence ◽

Age Related ◽

Development And Validation

Decision-making competence refers to the ability to make better decisions, as defined by decision-making principles posited by models of rational choice. Historically, psychological research on decision-making has examined how well people follow these principles under carefully manipulated experimental conditions. When individual differences received attention, researchers often assumed that individuals with higher fluid intelligence would perform better. Here, we describe the development and validation of individual-differences measures of decision-making competence. Emerging findings suggest that decision-making competence may tap not only into fluid intelligence but also into motivation, emotion regulation, and experience (or crystallized intelligence). Although fluid intelligence tends to decline with age, older adults may be able to maintain decision-making competence by leveraging age-related improvements in these other skills. We discuss implications for interventions and future research.

Download Full-text

MULTI-OMICS ANALYSIS IDENTIFIES GENE NETWORKS ASSOCIATED WITH COGNITIVE AGING AND ALZHEIMER’S DISEASE

Innovation in Aging ◽

10.1093/geroni/igz038.2179 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S587-S588

Author(s):

Catherine Kaczorowski ◽

Sarah Heuer ◽

Chris Gaiteri ◽

Catherine Kaczorowski

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Individual Differences ◽

Cognitive Aging ◽

Gene Networks ◽

Cognitive Outcomes ◽

Transcriptional Networks ◽

Biological Processes ◽

Mouse Population ◽

Age Related

Abstract Alzheimer’s disease (AD) is the leading cause of age-related dementia, yet no treatment exists. AD is heterogeneous, and is resultant of the dysregulation of many genetic and biological processes. To decipher this complexity, we leveraged the first translational mouse population of AD to identify 15 gene networks related to individual differences in cognitive outcomes. Using QTL mapping, we also identified a novel putative driver of a module, Gstk1, highly conserved in humans that also significantly correlated with memory outcomes. Together, these transcriptional networks provide new mechanistic insight into the biological processes that regulate individual differences in cognitive function across a genetically diverse population. We could identify how demographics (age, sex, causal AD mutations) influence these modules and how they relate to cognitive outcomes. Finally, the high degree of conservation between our mouse modules to human modules reflects the translatability of our model to human AD, adding to its face validity.

Download Full-text

Stability and Change in Diffusion Model Parameters over Two Years

Journal of Intelligence ◽

10.3390/jintelligence9020026 ◽

2021 ◽

Vol 9 (2) ◽

pp. 26

Author(s):

Mischa von Krause ◽

Stefan T. Radev ◽

Andreas Voss ◽

Martin Quintus ◽

Boris Egloff ◽

...

Keyword(s):

Individual Differences ◽

Diffusion Model ◽

Processing Speed ◽

Rank Order ◽

Temporal Stability ◽

Model Parameters ◽

Stability And Change ◽

Trade Offs ◽

Time Period ◽

Speed Accuracy

In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research.

Download Full-text

No effect of age on emotion recognition after accounting for cognitive factors and depression

Quarterly Journal of Experimental Psychology ◽

10.1177/1747021819859514 ◽

2019 ◽

Vol 72 (11) ◽

pp. 2690-2704

Author(s):

Jennifer Murphy ◽

Edward Millgate ◽

Hayley Geary ◽

Caroline Catmur ◽

Geoffrey Bird

Keyword(s):

Emotion Recognition ◽

Processing Speed ◽

Fluid Intelligence ◽

Internal State ◽

Affective Factors ◽

Unique Variance ◽

Age Related ◽

Recognition Ability ◽

Emotion Recognition Ability ◽

Effect Of Age

A decline in emotion recognition ability across the lifespan has been well documented. However, whether age predicts emotion recognition difficulties after accounting for potentially confounding factors which covary with age remains unclear. Although previous research suggested that age-related decline in emotion recognition ability may be partly a consequence of cognitive (fluid intelligence, processing speed) and affective (e.g., depression) factors, recent theories highlight a potential role for alexithymia (difficulty identifying and describing one’s emotions) and interoception (perception of the body’s internal state). This study therefore aimed to examine the recognition of anger and disgust across the adult lifespan in a group of 140 20–90-year-olds to see whether an effect of age would remain after controlling for a number of cognitive and affective factors potentially impacted by age. In addition, using an identity recognition control task, the study aimed to determine whether the factors accounting for the effects of age on emotion discrimination also contribute towards generalised face processing difficulties. Results revealed that discrimination of disgust and anger across the lifespan was predicted by processing speed and fluid intelligence, and negatively by depression. No effect of age was found after these factors were accounted for. Importantly, these effects were specific to emotion discrimination; only crystallised intelligence accounted for unique variance in identity discrimination. Contrary to expectations, although interoception and alexithymia were correlated with emotion discrimination abilities, these factors did not explain unique variance after accounting for other variables.

Download Full-text