Modeling the Neurocognitive Dynamics of Language across the Lifespan

Abstract

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed in language performances. Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this cognitive variability. At the cognitive level, our findings suggest that language processing is not an isolated function but is modulated throughout an individual's lifespan by the extent of inter-cognitive synergy between language, long-term memory, and executive functions. At the cerebral level, we show that the coupling between DMN (Default Mode Network) and FPN (Fronto-Parietal Network) regions may be the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related cognitive decline in language production, fluid processing, and verbal fluency. Notably, the dynamic of cognitive resilience provided by this synergistic coupling seems to follow the Seneca effect typically found in complex systems: a slow rise followed by an abrupt decline. Specifically, we argue that reducing the DMN-FPN coupling could trigger accelerated cognitive decline around age 50. We summarize our findings in a novel SENECA model (Synergistic, Economical, Nonlinear, Emergent, Cognitive Aging), integrating connectomic and cognitive perspectives within a complex system perspective. Our study furthers our understanding of the dedifferentiation-compensation mechanisms that uphold inter-cognitive functioning during healthy aging and suggests that the fifth decade of life could transition towards less synergistic processing.