Literature DB >> 32976888

Dysregulated brain salience within a triple network model in high trait anxiety individuals: A pilot EEG functional connectivity study.

Chiara Massullo1, Giuseppe Alessio Carbone1, Benedetto Farina1, Angelo Panno1, Cristina Capriotti1, Marta Giacchini1, Sérgio Machado2, Henning Budde3, Eric Murillo-Rodríguez4, Claudio Imperatori5.   

Abstract

Although previous studies have reported the association between large-scale brain networks alterations and pathological anxiety, abnormalities in the dynamic interaction among the triple network model in anxiety disorders and, especially, in trait anxiety is still poorly explored. Thus, the main aim of the current study was to investigate triple network functional dynamics in subjects with high trait anxiety during resting state (RS) through electroencephalography (EEG) connectivity. Twenty-three individuals with high-trait-anxiety (HTA) and forty-five participants with low-trait-anxiety (LTA) were enrolled. EEG analyses were conducted by means of the exact Low-Resolution Electromagnetic Tomography software (eLORETA). Compared to LTA participants, HTA subjects showed a decrease of alpha connectivity within the salience network (SN), between the dorsal anterior cingulate cortex (dACC) and both left and right anterior insula (AI). Furthermore, SN functional connectivity strength was negatively correlated with higher trait anxiety, even when controlling for potential confounding variables (e.g., depressive and obsessive-compulsive symptoms). Taken together, our results point out a specific functional connectivity pattern in HTA individuals, which consists in a dysfunctional communication within the SN, specifically in the AI-dACC pathway. This functional pattern could underline, at rest, saliency detection and brain correlates of altereted emotion regulation and cognitive control processes typically involved in anxiety.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  EEG; Salience network; Trait anxiety; Triple network; eLORETA

Year:  2020        PMID: 32976888     DOI: 10.1016/j.ijpsycho.2020.09.002

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  1 in total

1.  Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework.

Authors:  Zhongxia Shen; Gang Li; Jiaqi Fang; Hongyang Zhong; Jie Wang; Yu Sun; Xinhua Shen
Journal:  Sensors (Basel)       Date:  2022-07-20       Impact factor: 3.847

  1 in total

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