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Fronto-parietal and cerebellar circuits characterise individuals with higher trait anxiety
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  • Teresa Baggio,
  • Alessandro Grecucci,
  • Fabrice Crivello,
  • Marc Joliot,
  • Christophe Tzourio
Teresa Baggio
University of Trento

Corresponding Author:[email protected]

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Alessandro Grecucci
University of Trento
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Fabrice Crivello
University of Bordeaux
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Marc Joliot
University of Bordeaux
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Christophe Tzourio
University of Bordeaux
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Abstract

Anxiety is a diffuse condition ranging from milder manifestations to severe disorders, impacting individuals’ lives significantly. Specific sensitive periods such as adolescence and young adulthood are particularly vulnerable to anxious states, often associated with psychological traits like impulsivity, aggression, and varying coping strategies. The goal of the present study is to address the need for a comprehensive analysis of trait anxiety by employing Parallel ICA, a data fusion machine learning technique, in a sample of young individuals divided into a lower anxiety group (n=252) and a higher anxiety group (n=302), aiming to identify the joint gray-white matter networks characterizing higher versus lower trait anxiety. Additionally, we aim to characterize higher anxiety individuals for their usage of maladaptive coping strategies, and other affective dimensions. In higher anxious individuals, we identified a fronto-parieto-cerebellar network with decreased gray matter concentration, linked to bodily awareness and threat modulation, and a parieto-temporal network with increased white matter concentration, emphasizing insula and precuneus role. At the psychological level, we found higher stress, cognitive and motor impulsivity, and avoidance/emotional coping in higher anxious individuals. These findings may enhance the understanding of anxiety’s neural underpinnings in young individuals, supporting early interventions.
29 Jul 2024Submitted to European Journal of Neuroscience
31 Jul 2024Submission Checks Completed
31 Jul 2024Assigned to Editor
31 Jul 2024Review(s) Completed, Editorial Evaluation Pending
31 Jul 2024Reviewer(s) Assigned