An Effective Method to Identify Adolescent Generalized Anxiety Disorder by Temporal Features of Dynamic Functional Connectivity

Abstract

Generalized anxiety disorder (GAD) is one of common anxiety disorders in adolescents. Although adolescents with GAD are thought to be at high risk for other mental diseases, the disease-specific alterations have not been adequately explored. Recent studies have revealed the abnormal functional connectivity (FC) in adolescents with GAD. Most previous researches have investigated the static FC which ignores the fluctuations of FC over time and focused on the structures of “fear circuit”. To figure out the alterations of dynamic FC caused by GAD and the possibilities of dynamic FC as biomarkers, we propose an effective approach to identify adolescent GAD using temporal features derived from dynamic FC. In our study, the instantaneous synchronization of pairwise signals was estimated as dynamic FC. The Hurst exponent (H) and variance, indicating regularity and variable degree of a time series respectively, were calculated as temporal features of dynamic FC. By leave-one-out cross-validation (LOOCV), a relatively high accuracy of 88.46% could be achieved when H and variance of dynamic FC were combined as features. In addition, we identified the disease-related regions, including regions belonging to default mode (DM) and cerebellar networks. The results suggest that temporal features of dynamic FC could achieve a clinically acceptable diagnostic power and serve as biomarkers of adolescent GAD. Furthermore, our work could be helpful in understanding the pathophysiological mechanism of adolescent GAD.

Network abnormalities in generalized anxiety pervade beyond the amygdala-pre-frontal cortex circuit: Insights from graph theory

“…While in recent years whole brain functional connectivity has been extensively examined in social anxiety disorder (e.g., Xing et al, 2016;Yang et al, 2017;Zhu et al, 2017), this is the first study to our knowledge that applied NBS and graph theory to address the question of whether network abnormalities are spatially restricted to the PFC-amygdala circuit, or if the integrity of brain function is globally disrupted in adults with GAD. An exception is represented by one recent study that tested whether parameters from dynamic functional connectivity could reliably classify adolescents with GAD from healthy controls in the absence of other clinical measures (Yao et al, 2017). The results supported the potential of dynamic functional connectivity measures in DMN and particularly in the medial PFC as a biomarker for adolescents with GAD.…”

Altered Default Mode Network and Salience Network Functional Connectivity in Patients with Generalized Anxiety Disorders: An ICA‐Based Resting‐State fMRI Study

“…Liao et al found that the functional connection of mPFC in the DMN was enhanced in the social anxiety disorder [ 40 ]. In addition, mPFC is the prominent region with higher sensitivity in the identification of adolescent GAD [ 41 ]. The abnormal FC dynamics associated with mPFC revealed the disrupted information exchange related to this region and might result in the failure to sense “self- and others' thinking, feeling, perceiving, imagining, reacting, attributing, and inferring,” [ 42 ] which made the GAD patients unable to control their worry and anxiety as sensitively as healthy controls.…”

Dynamic changes of amplitude of low‐frequency fluctuations in patients with generalized anxiety disorder

“…Dynamic characteristics of brain activity have been associated with cognitive adaption (Fornito, Harrison, Zalesky, & Simons, ; Wang, Ong, Patanaik, Zhou, & Chee, ), brain development (Faghiri, Stephen, Wang, Wilson, & Calhoun, ), and mental disorders (Li, Liao, et al, ; Liao et al, ; Zhang et al, ), which have been investigated in several neurological and psychiatric disorders, including depression (Pang et al, ), autism (Guo et al, ), schizophrenia (Damaraju et al, ), and GAD (Li et al, ; Yao et al, ). These studies demonstrate the utility of brain dynamics in deepening our understanding of the diseased brain and highlight its potential role in improving diagnostic accuracy.…”

“…These studies demonstrate the utility of brain dynamics in deepening our understanding of the diseased brain and highlight its potential role in improving diagnostic accuracy. As recently reported, dynamic functional connectivity (dFC) can be used to distinguish patients with GAD from healthy controls (HCs) and exhibits high accuracy (Yao et al, ). However, most of these studies have focused on reoccurring patterns of connection among brain regions using the dFC method.…”