Abstract
Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic fluctuations are static throughout the entire scan. However, it has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and thus may act as biomarkers of disease.Methods: In this study, the resting-state functional MRI (fMRI) data were collected from 26 patients with GAD, 22 patients with PD, and 26 healthy controls (HCs). We investigated dynamic functional connectivity (DFC) by using the group spatial independent component analysis, a sliding window approach, and the k-means clustering methods. For group comparisons, the temporal properties of DFC states were analyzed statistically.Results: The dynamic analysis demonstrated two discrete connectivity “States” across the entire group, namely, a more segregated State I and a strongly integrated State II. Compared with HCs, patients with both GAD and PD spent more time in the weakly within-network State I, while performing fewer transitions and dwelling shorter in the integrated State II. Additionally, the analysis of DFC strength showed that connections associated with ADs were identified including the regions that belonged to default mode (DM), executive control (EC), and salience (SA) networks, especially the connections between SA and DM networks. However, no significant difference was found between the GAD and PD groups in temporal features and connection strength.Conclusions: More common but less specific alterations were detected in the GAD and PD groups, which implied that they might have similar state-dependent neurophysiological mechanisms and, in addition, could hopefully help us better understand their abnormal affective and cognitive performances in the clinic.
Highlights
Anxiety disorders (ADs) are a group of mental disorders characterized by excessive fear, anxiety, and related behavioral abnormalities, which have a great impact on the social function and quality of life of the patients, and impose a great burden on the family and society (Grupp et al, 2014)
By using the independent component analysis (ICA) and dynamic functional connectivity (DFC) analysis on the resting-state functional MRI (RS-fMRI) data, we aimed to reveal the characteristics of dynamic connectivity in patients with generalized anxiety disorder (GAD) and with panic disorder (PD)
Our findings may suggest that patients with AD can be distinguished from healthy controls (HCs) according to the DFC alterations in the resting state
Summary
Anxiety disorders (ADs) are a group of mental disorders characterized by excessive fear, anxiety, and related behavioral abnormalities, which have a great impact on the social function and quality of life of the patients, and impose a great burden on the family and society (Grupp et al, 2014). Among them, generalized anxiety disorder (GAD) and panic disorder (PD), with anxiety as the core emotional experience, are very similar in clinical features, forms of the disease, and treatment, and often coexist. Current studies have revealed that DFC metrics may index the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior (Hutchison et al, 2013), and be of great significance for the early diagnosis and prediction of the severity of mental illness (Damaraju et al, 2014; Li et al, 2014; Ou et al, 2015). It has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and may act as biomarkers of disease
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