Neural Contributions to Reduced Fluid Intelligence across the Adult Lifespan

Abstract

Fluid intelligence, the ability to solve novel, complex problems, declines steeply during healthy human aging. Using fMRI, fluid intelligence has been repeatedly associated with activation of a frontoparietal brain network, and impairment following focal damage to these regions suggests that fluid intelligence depends on their integrity. It is therefore possible that age-related functional differences in frontoparietal activity contribute to the reduction in fluid intelligence. This paper reports on analysis of the Cambridge Center for Ageing and Neuroscience data, a large, population-based cohort of healthy males and females across the adult lifespan. The data support a model in which age-related differences in fluid intelligence are partially mediated by the responsiveness of frontoparietal regions to novel problem-solving. We first replicate a prior finding of such mediation using an independent sample. We then precisely localize the mediating brain regions, and show that mediation is specifically associated with voxels most activated by cognitive demand, but not with voxels suppressed by cognitive demand. We quantify the robustness of this result to potential unmodeled confounders, and estimate the causal direction of the effects. Finally, exploratory analyses suggest that neural mediation of age-related differences in fluid intelligence is moderated by the variety of regular physical activities, more reliably than by their frequency or duration. An additional moderating role of the variety of nonphysical activities emerged when controlling for head motion. A better understanding of the mechanisms that link healthy aging with lower fluid intelligence may suggest strategies for mitigating such decline.SIGNIFICANCE STATEMENTGlobal populations are living longer, driving urgency to understand age-related cognitive declines. Fluid intelligence is of prime importance because it reflects performance across many domains, and declines especially steeply during healthy aging. Despite consensus that fluid intelligence is associated with particular frontoparietal brain regions, little research has investigated suggestions that under-responsiveness of these regions mediates age-related decline. We replicate a recent demonstration of such mediation, showing specific association with brain regions most activated by cognitive demand, and robustness to moderate confounding by unmodeled variables. By showing that this mediation model is moderated by the variety of regular physical activities, more reliably than by their frequency or duration, we identify a potential modifiable lifestyle factor that may help promote successful aging.

Linguistic inputs must be syntactically parsable to fully engage the language network

“…For example, these findings could be connected to the ERP research that has interpreted the domain-general P600 component (e.g., Osterhout & Holcomb, 1992;Patel, 2003;Núñez-Peña & Honrubia-Serrano, 2004;Cohn et al, 2012) as indexing error correction (Ryskin, Stearns et al, 2021). Our findings also make predictions about the processing of syntactically corrupt inputs in children and older adults (given that the MD network is slow to develop (Fiske & Holmboe, 2019;Schettini et al, 2023) and shows clear age-related decline (Reuter-Lorenz et al, 2000;Mitchell et al, 2023;Wu & Hoffman, 2023)). If the MD network cannot effectively support syntactic reconstruction in these populations, we should observe larger effects of syntactic degradation on the language network's responses, and greater reliance on semantic plausibility in interpreting corrupt inputs (e.g., Beese et al, 2019).…”

Reorganization of Structural Connectivity in the Brain Supports Preservation of Cognitive Ability in Healthy Aging

“…These findings can also be contextualized with respect to past research looking at the functional neural correlates of fluid intelligence. Across a range of studies fluid intelligence has been associated with regions in the frontopartietal network (Barbey et al, 2014; Gläscher et al, 2010; Mitchell et al, 2023; Momi et al, 2020; Samu et al, 2017; Smith et al, 2022; Woolgar et al, 2010). We found that YA relied on the mPFC and IPL regions of this network, in line with past research.…”

Modeling the Neurocognitive Dynamics of Language across the Lifespan

“…While previous studies focused exclusively on how dedifferentiation mediates poorer performances in fluid intelligence (Mitchell et al, 2023) and long-term memory (Koen et al, 2020), this study aimed to model the neural mechanisms that bridge dedifferentiation and compensation (section 3.3), and how the changes in this dedifferentiation-compensation dynamic relate to the age-related variability in language abilities discussed previously. Overall, we suggest that dedifferentiation-compensation follows the principle of the economy of brain network organization (Bullmore & Sporns, 2012).…”