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Updated: Jun 30, 2025

Reducing State Anxiety Using Working Memory Maintenance
Published on: July 19, 2017
Trait anxiety is associated with attentional brain networks
Víctor De la Peña-Arteaga1, Pamela Chavarría-Elizondo2, Asier Juaneda-Seguí3
1Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain; Sant Pau Mental Health Research Group, Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain; Life and Health Sciences Research Institute (ICVS), School of Medicine, Universidade do Minho, Braga, Portugal.
None:
Trait anxiety is a well-established risk factor for anxiety and depressive disorders, yet its neural correlates are not clearly understood. In this study, we investigated the neural correlates of trait anxiety in a large sample (n = 179) of individuals who completed the trait and state versions of the State-Trait Anxiety Inventory and underwent resting-state functional magnetic resonance imaging. We used independent component analysis to characterize individual resting-state networks (RSNs), and multiple regression analyses to assess the relationship between trait anxiety and intrinsic connectivity. Trait anxiety was significantly associated with intrinsic connectivity in different regions of three RSNs (dorsal attention network, default mode network, and auditory network) when controlling for state anxiety. These RSNs primarily support attentional processes. Notably, when state anxiety was not controlled for, a different pattern of results emerged, highlighting the importance of considering this factor in assessing the neural correlates of trait anxiety. Our findings suggest that trait anxiety is uniquely associated with resting-state brain connectivity in networks mainly supporting attentional processes. Moreover, controlling for state anxiety is crucial when assessing the neural correlates of trait anxiety. These insights may help refine current neurobiological models of anxiety and identify potential targets for neurobiologically-based interventions.
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