Distributed resting-state functional connectivity patterns predict language performance in later adulthood

Abstract Language ability in later adulthood depends on functional brain organisation extending beyond classically defined language regions, yet whether resting-state functional connectivity (rs-FC) captures this distributed architecture, and whether predictive information is concentrated within a language-specific network or spread across domain-general systems, remains unclear. Using data from the Human Connectome Project Aging dataset (N = 445; age range: 40–86 years), we combined connectome-based predictive modelling (CPM) and graph-theory analyses to examine the intrinsic neural architecture supporting vocabulary comprehension (TPVT) and single-word reading recognition (READ). CPM yielded significant out-of-sample predictions for both measures (TPVT: r=.233, p=.001; READ: r=.196, p=.001), with predictive edges predominantly spanning inter-network connections across the default mode, fronto-parietal, and dorsal and ventral attention networks; language network edges constituted a non-majority of top-ranked features in both models. Graph-theory analyses of a functionally defined resting-state language network revealed that within-network global efficiency was positively associated with TPVT in lower-educated individuals but negatively so in higher-educated individuals, whose performance was instead linked to greater cross-network connectivity across left temporal, parietal, and prefrontal nodes. Node-wise PCs showed age-dependent reversals in left temporal and temporo-occipital regions for both tasks, with higher cross-network integration benefiting younger but not older adults, consistent with dedifferentiation accounts of cognitive ageing. Together, these findings position language performance in healthy ageing as a whole-brain phenomenon shaped by the interplay between domain-general and language-specific network organisation and its interaction with life-course factors, calling for a shift away from language-centric models toward frameworks that foreground distributed connectivity.

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Publication Details

Journal
Research Square
Published
2026-11-04
DOI
https://doi.org/10.21203/rs.3.rs-10920236/v1
Primary Topic
Functional Brain Connectivity Studies
Type
preprint
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preprint

Distributed resting-state functional connectivity patterns predict language performance in later adulthood

Arianna Menardi, Antonino Vallesi, Irene Bellin, Xueqing Li
Research Square
Functional Brain Connectivity Studies
preprint

Distributed resting-state functional connectivity patterns predict language performance in later adulthood

Arianna Menardi, Antonino Vallesi, Irene Bellin, Xueqing Li
preprint en

Abstract

Abstract Language ability in later adulthood depends on functional brain organisation extending beyond classically defined language regions, yet whether resting-state functional connectivity (rs-FC) captures this distributed architecture, and whether predictive information is concentrated within a language-specific network or spread across domain-general systems, remains unclear. Using data from the Human Connectome Project Aging dataset (N = 445; age range: 40–86 years), we combined connectome-based predictive modelling (CPM) and graph-theory analyses to examine the intrinsic neural architecture supporting vocabulary comprehension (TPVT) and single-word reading recognition (READ). CPM yielded significant out-of-sample predictions for both measures (TPVT: r=.233, p=.001; READ: r=.196, p=.001), with predictive edges predominantly spanning inter-network connections across the default mode, fronto-parietal, and dorsal and ventral attention networks; language network edges constituted a non-majority of top-ranked features in both models. Graph-theory analyses of a functionally defined resting-state language network revealed that within-network global efficiency was positively associated with TPVT in lower-educated individuals but negatively so in higher-educated individuals, whose performance was instead linked to greater cross-network connectivity across left temporal, parietal, and prefrontal nodes. Node-wise PCs showed age-dependent reversals in left temporal and temporo-occipital regions for both tasks, with higher cross-network integration benefiting younger but not older adults, consistent with dedifferentiation accounts of cognitive ageing. Together, these findings position language performance in healthy ageing as a whole-brain phenomenon shaped by the interplay between domain-general and language-specific network organisation and its interaction with life-course factors, calling for a shift away from language-centric models toward frameworks that foreground distributed connectivity.

Research Square
University of Padua (IT)
Functional Brain Connectivity Studies
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