Generalized anxiety disorder (GAD) is a common anxiety disorder characterized by excessive and uncontrollable worry about various aspects of life, accompanied by somatic symptoms including muscle tension, fatigue, and sleep disturbance (American Psychiatric Association, 2013). Given its non-invasive nature and relatively high spatial resolution compared with other functional neuroimage technologies (e.g., electroencephalography, magnetoencephalography), resting-state functional MRI (R-fMRI) has been extensively applied to investigations of brain connectivity in individuals from both community and clinical settings (Biswal et al., 1995; Kelly et al., 2012), including individuals with GAD. Prior R-fMRI research in GAD mainly focused on local functional abnormalities in certain predefined regions (e.g., amygdala, hippocampus) (Etkin et al., 2009; Chen and Etkin, 2013) and functional connectivity (FC) disruptions, including FC between amygdala and prefrontal cortex (PFC) (Etkin et al., 2009; Liu et al., 2015), posterior cingulate cortex (PCC) (Strawn et al., 2012), ventral cingulate cortex (Etkin and Schatzberg, 2011), temporal pole (Li et al., 2016), between medial prefrontal cortex (mPFC) and PCC (Andreescu et al., 2014), and between hippocampus and fusiform (Cui et al., 2016).

In addition to alterations in specific regions and FC, a review by Sylvester et al. (2012) suggests that patients with GAD display extensive disruptions in several subnetworks (e.g., default mode network, fronto-parietal network). Recently, combinations of R-fMRI and graph theory offer a new way to reveal detailed and comprehensive FC information across the whole brain (Bullmore and Sporns, 2009; Kelly et al., 2012). This approach is conducive to examining the interactions of the brain in a general state (Biswal et al., 2010; Cole et al., 2010). However, whole-brain functional connectome abnormalities of GAD using graph metrics still remains unclear. Identifying such alterations can shed light on the pathological mechanisms that may underlie the multi-domain disruptions of GAD (e.g., emotion, cognition, and somatosensory), which may further provide novel insights and potential biomarkers for clinical prevention of, and interventions for, this disorder.

In the present study, we used R-fMRI and voxel-based graph theory analysis to investigate abnormal brain connectivity in first-episode, medication-naive, adolescent GAD patients without comorbidity in comparison with healthy controls (HCs). The voxel-based analysis used here avoids potential topological changes due to different parcellation approaches (de Reus and van den Heuvel, 2013). We aimed at determining the comprehensive FC disruptions among adolescents with GAD, and whether such alterations could be associated with clinical characteristics in GAD.

In the current study, we used resting-state fMRI to examine voxel-wise functional connectivity alterations in adolescents with GAD. We found that adolescents with GAD showed decreased FCS in right SMG and SPG compared with adolescents in the HCs group. GAD patients also displayed reduced FC within the SMG-based network, the SPG-based network, and between the SMG-based network and SPG-based network. The effect sizes of these observed GAD-related functional connectivity abnormality were relatively large (Fritz et al., 2012). The disrupted intra-network connectivity and inter-network connectivity were correlated with clinical measures of GAD patients, and explained 25.5–39.5% of the variance of clinical symptoms. Notably, GAD usually begins in adolescence (Costello et al., 2003; Merikangas et al., 2010), and early onset (e.g., in adolescence) of GAD was associated with an indicator of adulthood depression (Copeland et al., 2012), highlighting the importance of investigating the pathology of adolescent GAD.

Areas with significantly reduced FCS in GAD patients were mainly distributed in the parietal cortex, including the right SMG and SPG. Prior studies suggested that the SMG is involved in integrating multiple sensory signals (Lopez and Blanke, 2011; Zu Eulenburg et al., 2012), overcoming emotional egocentricity (Silani et al., 2013), and processing communicative intentions (Enrici et al., 2011), which are crucial to social perception. Since GAD patients tend to perceive ambiguous social situations as negative, reduced FCS in SMG may be a potential neural substrate of inaccurate sensory integration and interpretation of social stimuli, which may lead to more vulnerability to negative emotions (e.g., anxiety). Moreover, we also found reduced functional connectivity in the SMG-based network in GAD patients, including bilateral precuneus, cuneus, left FFG, ITG, and PHG. These findings are in line with previous studies that reported decreased functional connectivity in a network formed by SMG, FFG, PHG, and precuneus in individuals with high trait anxiety (Modi et al., 2015), and disrupted functioning of FFG and PHG in anxiety disorders including GAD and social anxiety disorder (SAD) (Ball et al., 2013; Frick et al., 2013; Hattingh et al., 2013; Cui et al., 2016). Specifically, the FFG is particularly associated with the processing of fearful facial and body expressions (Hadjikhani and de Gelder, 2003), whereas the PHG belongs to the paralimbic system which supports the information transition between the limbic system and the neocortex to facilitate emotion regulation (Mesulam, 2000; Kiehl, 2006). The decreased functional connectivity between the SMG and the FFG/PHG cluster in the present study, therefore, may mirror the dysfunctional attention orientation and integration of sensorimotor signals in GAD patients, which is the foundation for subsequent emotion regulation. In addition, we also observed decreased functional connectivity between SMG and the precuneus/cuneus cluster in GAD patients. The structural and functional abnormalities of precuneus and cuneus have been consistently implicated in pathological anxiety (Liao et al., 2010; Strawn et al., 2013, 2014; Wehry et al., 2015). These regions are involved in self-processing, theory of mind, and social cognition (Cavanna and Trimble, 2006; Völlm et al., 2006; Gentili et al., 2009). More importantly, previous studies have linked SMG and precuneus to the attention regulation process of emotional reactivity and regulation in both community populations and individuals with anxiety disorders (Goldin et al., 2009; Domes et al., 2010). Based on these previous findings, the reduced functional connectivity between SMG and precuneus/cuneus in the current study may reflect the aberrant sensorimotor integration and biased interpretations of social stimuli, which may result in excessive and uncontrollable worry in GAD. Taken together, this evidence implies that the SMG-based network possibly plays an important role in sensory perception and integration which facilitate social cognition and emotion regulation in GAD patients.

We also observed reduced FCS in the right SPG in adolescents with GAD. SPG is associated with top-down attention and cognitive control (Astafiev et al., 2003; Egner and Hirsch, 2005), thus the weakened FCS in this region may mirror the attentional bias toward threat in individuals with GAD as indicated by a meta-analysis (Bar-Haim et al., 2007). Furthermore, weakened functional connectivity in the SPG-based network was also found in GAD patients, including SMA and MCG. It is intriguing that SMA and MCG are not only involved in sensorimotor processing (Nachev et al., 2008; Stevens et al., 2011), but also implicated in top-down executive control on attentional and emotional process (Hopfinger et al., 2000; Nachev et al., 2008; Kalisch, 2009; Stevens et al., 2011; Kohn et al., 2014; Etkin et al., 2015). The SMA and MCG cluster in the current study also overlaps with the regions involved in cognitive reappraisal, an important process underlying successful emotion regulation (Ochsner and Gross, 2005; Kalisch, 2009). Therefore, decreased functional connectivity in the SPG-based network may imply the failure of cognitive control over salience detection and internal emotional signals, which could engender information processing bias (e.g., a preference for noticing potential threatening signals) and emotion regulation failure in GAD patients. Supporting this notion, a previous study demonstrated that GAD patients had difficulty in drawing attention away from fearful stimuli (Olatunji et al., 2011). In summary, our observations highlight the role of the SPG-based network in GAD and add evidence to the effectiveness of the treatments centered on modifying cognitive bias in GAD to some extent (e.g., cognitive-behavioral therapy).

Furthermore, functional connectivity between the SMG-based network and the SPG-based network was also reduced in the GAD patient group. Numerous studies have corroborated the role of the between-network interactions in regulating emotions (e.g., fear) (Ochsner and Gross, 2005; Delgado et al., 2008), indicating that mental disorders related to emotion regulation failure (e.g., anxiety disorders) could result from aberrant information exchange among multiple brain networks (Sylvester et al., 2012). Our observation of the decreased functional connectivity between the SMG-based network and the SPG-based network may serve as the neural representation of ineffective top-down modulation of the sensorimotor signals in GAD, which is in accordance with the characteristics of over-sensitivity to interoceptive information in anxiety disorders (Domschke et al., 2010). In summary, our findings support the multiple-networks interaction hypothesis in psychopathology, and more specifically, the notion that GAD patients have difficulty in exchanging and integrating signals among different networks (Sylvester et al., 2012).

In the GAD patient group, intra-network connectivity of the SMG-based network and inter-network connectivity between the SMG-based network and the SPG-based network were positively correlated with the STAI score and the trait score of STAI, respectively. However, the two neuroimaging indexes were lower while the two clinical scores were higher in the GAD patient group compared with HCs. Indeed, this counterintuitive brain-clinical association has been widely found in mental disorders, including GAD (Etkin et al., 2009), posttraumatic stress disorder (PTSD) (Villarreal et al., 2004; Kim et al., 2007), attention deficit hyperactivity disorder (ADHD) (Suskauer et al., 2008; Tao et al., 2017), and schizophrenia (Gur et al., 1998). Although the understanding of the paradoxical brain-clinical correlation in clinical neuroscience is still limited, we tentatively provided a possible explanation in the current study. Given the reduced functional connectivity in the SMG-based network and between the SMG-based network and the SPG-based network, GAD patients may try to increase functional connectivity to become “normal” by using certain emotion regulation strategies. However, these strategies are ineffective, or even increase anxiety. One example of these deleterious strategies is the positive beliefs on worry, which has been frequently employed by GAD patients (Borkovec et al., 1999). These individuals with GAD tend to believe that worry can help them cope with adversity more successfully (Llera and Newman, 2010), but it ends up reinforcing worry, and this creates a vicious cycle. In other words, the positive correlations between functional connectivity and anxiety severity may reflect the maladaptive strategies employed by GAD patients to deal with negative emotions. Notably, these hypotheses were not directly tested in the current study, thus should be treated with caution and tested in future studies.

Furthermore, the linear regression model demonstrated that 25.5% variance of STAI and 39.5% variance of the trait score of STAI could be explained by functional connectivity. These results imply that the functional connectivity measures can serve as biomarkers for GAD. It is interesting that none of the three predictors (intra-network connectivity of the SMG-based network, the SPG-based network, and inter-network connectivity between the SMG-based network and the SPG-based network) managed to predict clinical symptoms independently, while the combined regression models did successfully explain the symptom variance. These findings indicate that the interactions among networks are more crucial than any individual network to predict GAD symptoms. Therefore, they further support the advantages of understanding the pathological mechanisms of GAD by investigating multiple subnetworks.

Notably, some GAD-related regional alterations demonstrated in previous work were not identified in the present study [e.g., amygdala, hippocampus, ventral gyrus of anterior cingulate cortex (vgACC), and DLPFC]. This discrepancy may result from different methodologies. Previous studies basically hypothesized specific regional disruptions in GAD and predefined these regions as the seed regions (e.g., Etkin et al., 2009; Chen and Etkin, 2013; Andreescu et al., 2014; Li et al., 2016). In the current study, however, we used a whole-brain voxel-wise data-driven approach, which gives a bigger picture of the aberrant functional architecture of GAD. Another possibility is the heterogeneity of the GAD sample. Most previous R-fMRI studies examining the abnormal functional architecture of GAD recruited adult patients (Etkin et al., 2009; Etkin and Schatzberg, 2011; Chen and Etkin, 2013; Andreescu et al., 2014; Liu et al., 2015; Cui et al., 2016; Li et al., 2016). In the few studies that centered on adolescent GAD patients, medication use could be a potential confound (Strawn et al., 2012; Liu et al., 2015).

Based on our findings, we proposed a theoretical model of GAD (Figure 4). We suggest that the decreased functional connectivity within the SMG-based network, the SPG-based network, and between the SMG-based network and the SPG-based network could be the underlying psychopathological mechanisms in the functional brain network in this disorder. This model will need further validation by future research, which will contribute to the understanding of GAD.

Several limitations and methodological issues should be considered further. First, the sample size of the current study is relatively small, which decreases the statistical power. Future research recruiting more participants would be quite valuable and informative. Second, although one possibility of the counterintuitive brain-behavior association was provided in the current study, it still remains untested. Future studies are needed to test this interpretation and also consider other potential explanations. Finally, the abnormal functional connectivity maps of GAD are probably associated with structural characteristics (e.g., cortical thickness, regional volumes). Future research is recommended to investigate structural and functional coupling in GAD, which could help develop a more sophisticated pathological model of this disorder.

The present study used resting-state fMRI to explore the functional connectivity alterations in neural subnetworks of adolescents with GAD, and found decreased functional connectivity in the SMG-based network, the SPG-based network, and between the SMG-based network and the SPG-based network in this disorder. Our findings highlight the aberrant functional architecture in the SMG-based network and the SPG-based network in GAD, providing novel insights into the pathophysiological mechanisms of this disorder.

FY, YZ, LL, LS, and ZD designed the study. TZ and ML acquired the data, which LF, JM, and FY analyzed. LF, ZD, YL, JM, and YW wrote the article, which all authors reviewed and approved for publication.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.