Relational thinking in later adulthood.

Abstract

The research addressed the role of relational processing capacity in cognitive aging focusing on (a) age-differences in complex relational processing, (b) the domain-generality of complex relational processing, and (c) associations of complex relational processing with other processes. Participants were 125 adults in three groups with mean ages of 30.55 (younger), 53.43 (middle), and 74.41 years (older). Each relational processing task (sentence comprehension, n-term premise integration, Latin square) included items at three complexity levels. Accuracy was lower on more complex items and relational complexity had a greater effect in the older group. Confirmatory factor analyses confirmed a single complex relational processing factor, consistent with a domain-general capacity. Relational processing was related to other executive processes. This relationship was stronger in the older than younger and middle groups, possibly reflecting dedifferentiation or neural noise. In structural models with planning (Tower of London) and class reasoning as outcome variables, complex relational processing had a significant impact (β = .455, p < .001 and β = .661, p < .001, respectively) over and above age, processing speed, working memory, task switching, response inhibition, and Stroop interference. In the structural model with fluid intelligence (matrix reasoning) as the outcome variable, age had a significant impact (β = −.222, p < .001), over and above all other variables, suggesting that the processes underpinning age-related declines in matrix reasoning are more diverse than those assessed in the current research. Complex relational processing is an important factor in cognitive aging, possibly reflecting its reliance on prefrontal brain regions.

Relational Integration in the Human Brain: A Review and Synthesis

“…Although not focused on the RLPFC per se, several other neuropsychological studies have provided evidence that relational integration depends on pFC more generally. For various types of problems, including both matrices and pictorial analogy tasks, older adults (subject to neural decline in frontal function) are especially impaired in solving problems at higher levels of complexity (Todd, Andrews, & Conlon, 2019;Viskontas, Holyoak, & Knowlton, 2005;Viskontas, Morrison, Holyoak, Hummel, & Knowlton, 2004). Similarly, high relational complexity is problematic for patients experiencing Alzheimer's disease, especially those with neuropsychological profiles indicative of pFC dysfunction ( Waltz et al, 2004), as well as for patients who have had strokes impacting pFC (Andrews, Halford, Chapell, Maujean, & Shum, 2014;Andrews et al, 2013).…”

A novel dynamic network imaging analysis method reveals aging-related fragmentation of cortical networks in mouse

“…Normal aging is associated with a gradual loss of cognitive function ( Glisky, 2007 ; Horn, 1982 ; Horn & Cattell, 1967 ; Salthouse, 2003 ; Todd, Andrews, & Conlon, 2019 ). The mechanisms responsible for this cognitive loss are not yet known, but given the aging of the population ( Beard, Officer, & Cassels, 2016 ), it will be important to understand how brain networks fail with aging.…”

Relations between Executive Functions, Theory of Mind, and Functional Outcomes in Middle Childhood

“…Despite ongoing debate surrounding the precise nature and strength of the relation between EF and intelligence, it is generally understood that the two constructs are related (Ackerman et al, 2005). Fluid intelligence (Gf) allows individuals to reason and problem-solve without having to rely on other knowledge and is often measured using tests of inductive relational reasoning (Todd, Andrews, & Conlon, 2019). The prefrontal cortex is one brain region that supports performance on tests of Gf (e.g., Raven's Progressive Matrices; Todd et al, 2019), which is also believed to support cool EF (Gray, Chabris, & Braver, 2003).…”

“…Fluid intelligence (Gf) allows individuals to reason and problem-solve without having to rely on other knowledge and is often measured using tests of inductive relational reasoning (Todd, Andrews, & Conlon, 2019). The prefrontal cortex is one brain region that supports performance on tests of Gf (e.g., Raven's Progressive Matrices; Todd et al, 2019), which is also believed to support cool EF (Gray, Chabris, & Braver, 2003). Therefore, the two abilities are interconnected but also separable.…”