Trait-level Attention Control Emerges from Dynamic Frontoparietal Control Network Interactions

Attention control predicts academic achievement, professional success, and health outcomes. However, the neural basis of stable, trait-level differences in attention control remains unclear. Prior research has emphasized momentary fluctuations in attentional engagement, often overlooking enduring individual differences. Here, we applied the quasi-periodic pattern (QPP) analysis of infraslow fMRI dynamics in a large sample (N = 191) to test whether trait attention control is reflected in network-level brain activity as well as the locus coeruleus. Using latent-variable measures of attention control, working memory capacity, and fluid intelligence, we isolated the unique contribution of attention control across rest, 1-back, and 3-back conditions. Under heightened cognitive demand, individuals with higher attention control exhibited more flexible coordination of the frontoparietal control network (FPCN): they showed stronger decoupling from the default mode network (DMN), enhanced coupling with the dorsal attention network (DAN), and greater engagement with the locus coeruleus (LC). Even at rest, high attention individuals demonstrated stronger FPCN-DAN coupling, and little to no correlation between FPCN-DMN, indicating that attentional capacity is reflected in both task-evoked reconfiguration and baseline network architecture. These findings reveal how attention control, as a trait, is instantiated in the brain’s dynamic architecture.

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Publication Details

Published
2025-10-02
DOI
https://doi.org/10.31234/osf.io/qzv47_v1
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00

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article

Trait-level Attention Control Emerges from Dynamic Frontoparietal Control Network Interactions

Vishwadeep Ahluwalia, Nan Xu, Jason S. Tsukahara, Randall W Engle et al.
Neural dynamics and brain function
article

Trait-level Attention Control Emerges from Dynamic Frontoparietal Control Network Interactions

Vishwadeep Ahluwalia, Nan Xu, Jason S. Tsukahara, Randall W Engle, Shella Keilholz, Dolly T. Seeburger
article en

Abstract

Attention control predicts academic achievement, professional success, and health outcomes. However, the neural basis of stable, trait-level differences in attention control remains unclear. Prior research has emphasized momentary fluctuations in attentional engagement, often overlooking enduring individual differences. Here, we applied the quasi-periodic pattern (QPP) analysis of infraslow fMRI dynamics in a large sample (N = 191) to test whether trait attention control is reflected in network-level brain activity as well as the locus coeruleus. Using latent-variable measures of attention control, working memory capacity, and fluid intelligence, we isolated the unique contribution of attention control across rest, 1-back, and 3-back conditions. Under heightened cognitive demand, individuals with higher attention control exhibited more flexible coordination of the frontoparietal control network (FPCN): they showed stronger decoupling from the default mode network (DMN), enhanced coupling with the dorsal attention network (DAN), and greater engagement with the locus coeruleus (LC). Even at rest, high attention individuals demonstrated stronger FPCN-DAN coupling, and little to no correlation between FPCN-DMN, indicating that attentional capacity is reflected in both task-evoked reconfiguration and baseline network architecture. These findings reveal how attention control, as a trait, is instantiated in the brain’s dynamic architecture.

Georgia Institute of Technology (US)
Office of Naval Research
Openalex Percentile: Top 73%
Neural dynamics and brain function
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Trait-level Attention Control Emerges from Dynamic Frontoparietal Control Network Interactions — Vishwadeep Ahluwalia, Nan Xu, et al. · (2025) | TGRS Research Map | TGRS