Reduced vmPFC-insula functional connectivity in generalized anxiety disorder: a Bayesian confirmation study

Abstract

Differences in the correlated activity of networked brain regions have been reported in individuals with generalized anxiety disorder (GAD) but an overreliance on null-hypothesis significance testing (NHST) limits the identification of disorder-relevant relationships. In this preregistered study, we applied both a Bayesian statistical framework and NHST to the analysis of resting-state fMRI scans from females with GAD and matched healthy comparison females. Eleven a-priori hypotheses about functional connectivity (FC) were evaluated using Bayesian (multilevel model) and frequentist (t-test) inference. Reduced FC between the ventromedial prefrontal cortex (vmPFC) and the posterior-mid insula (PMI) was confirmed by both statistical approaches and was associated with anxiety sensitivity. FC between the vmPFC-anterior insula, the amygdala-PMI, and the amygdala-dorsolateral prefrontal cortex (dlPFC) region pairs did not survive multiple comparison correction using the frequentist approach. However, the Bayesian model provided evidence for these region pairs having decreased FC in the GAD group. Leveraging Bayesian modeling, we demonstrate decreased FC of the vmPFC, insula, amygdala, and dlPFC in females with GAD. Exploiting the Bayesian framework revealed FC abnormalities between region pairs excluded by the frequentist analysis and other previously undescribed regions in GAD, demonstrating the value of applying this approach to resting-state FC data in clinical investigations.

Introduction

Generalized anxiety disorder (GAD) is a psychiatric disorder characterized by disproportionate and uncontrollable worry in addition to somatic symptoms including muscle tension, sleep disturbances, fatigue, and difficulty concentrating. It is a common anxiety disorder, and is associated with substantial functional impairments and economic costs as well as high rates of comorbidity with other psychiatric disorders¹. While the neurobiology of GAD has been investigated extensively², technical advancements in functional neuroimaging in recent decades have afforded insights into abnormalities of regional and network-level neural communication underlying this condition³. Results from many imaging studies suggest that brain regions are organized in distinguishable networks that facilitate complex cognitive functions⁴. Given the aforementioned functional impairments in GAD it is conceivable that these networks (or the nodes within them) are dysfunctional as well^5,6. Among the most frequently described neural networks are the default mode network (DMN, active during the absence of a specific task)⁷, the salience network (SN, responsible for shifting attention to behaviorally relevant internal and external stimuli)⁸, and the central executive network (CEN, involved in cognitively demanding functions like management of attention)⁹. Although only a few studies have examined these three networks explicitly in GAD and with heterogenous results^10,64, and predictive processing⁵⁹, which is in line with increased insula activity during emotional processing tasks in anxiety-prone individuals⁶⁵. Recent results from our group collected in the same sample show blunted vmPFC activity during an interoceptive perturbation task (pharmacologic infusions of a fast-acting peripheral adrenaline analog resulting in cardiorespiratory modulation²⁹), a method that has been reliably shown to activate the insula⁶⁶.

The results from this current study suggest the implication of the vmPFC and insula as networked brain regions in the pathophysiology of GAD. More precisely, reduced vmPFC-PMI FC could support the idea that individuals with GAD may have difficulty exercising top-down regulation of emotion due to aberrant processing of bottom-up signals flowing through an interoceptive hub: the insula. This hypothesis is backed by our observations of vmPFC and PMI differences between HC and GAD, which were confirmed by both statistical approaches. While reduced vmPFCI-PMI FC at rest could partly be explained by increased sensitivity of the insula to interoceptive events in the GAD group, it seems plausible that impaired prefrontal regulation of negatively valenced interoceptive states plays a stronger role in this connection based on the observation of vmPFC hypoactivation during the aforementioned cardiorespiratory perturbation task in the same sample²⁹. We also found that FC between the vmPFC and PMI was negatively associated with anxiety sensitivity, which is broadly defined as the fear of experiencing anxiety-related sensations especially those arising from within the body (e.g., heart palpitations or dyspnea)⁶⁷. In a clinical context, this could mean that the smaller the correlated activity between the vmPFC and the insula at rest, the more likely patients are to experience internal body states as anxiety provoking. However, this interpretation is preliminary and other clinical scores were not correlated with vmPFC-PMI FC, suggesting that this relation might be specific to the anxiety sensitivity construct. Also, this result was statistically significant only before Bonferroni correction and while the Bayes factor indicated that a relationship between vmPFC-insula FC and anxiety sensitivity is likely, our dual statistical approach did not converge on this result. In conclusion, this finding provides some initial evidence of functional association between abnormal neural activity in the vmPFC and PMI and a transdiagnostic trait underlying the initiation and maintenance of pathological anxiety⁶⁸.

Other results from the frequentist analysis indicated abnormal FC of the amygdala in GAD. Though contrary to our hypothesis, we observed decreased rather than increased FC between the amygdala and the PMI. The direction of this finding also contrasts with previous reports of an amygdala-insula resting state network in both anxious adults⁶⁹ and adolescents¹⁵, but on the other hand aligns with other previous findings of reduced amygdala-insula FC¹³. Additionally, FC between the amygdala and the dlPFC was decreased, not increased, in our GAD sample. This finding was against our hypothesis that was based on previous literature¹³. Decreased FC between the amygdala and the dlPFC, which is a central node in the CEN, could be argued to reflect a dysfunctional management of attention (a key function of the CEN⁹) towards threat-related stimuli, which is a key clinical feature of GAD⁷⁰. However, the overly general view of the amygdala as the central hub of fear processing is challenged by the absence of amygdala involvement in human fear extinction in a recent meta-analysis⁷¹, and heterogenous amygdala findings across reviews of neuroimaging literature in GAD^5,72. While the results from our cross-sectional study might hint at the possibility that the role of the amygdala might not be as pivotal to the maintenance of GAD as expected, both amygdala-related findings (i.e., reduced FC for the PMI-amygdala and the dlPFC-amygdala in the GAD group) did not withstand correction for multiplicity and would therefore not be considered statistically significant using the NHST model framework. On the other hand, evaluation of the results from the BML indicated high probabilities for a group difference regarding those region pairs, raising the question whether overly rigorous multiplicity correction might have induced a type II error in our NHST-analysis of those brain regions. Viewing the data from a different, i.e., Bayesian, perspective thus strengthened the validity of our reduced amygdala FC findings, permitting us to discuss these results and consider their potential implications for GAD. Further insight into FC of the amygdala (and more generally, all of the selected ROIs) could be gained by employing seed-based whole-brain voxel wise FC analysis, a common approach to identify the networked connectivity of brain regions⁷³. However, large datasets are required with this method to have sufficient statistical power and consequently, efforts have been made by the ENIGMA consortium to provide an analysis pipeline for employing seed-based FC analysis on pooled datasets from multicenter studies⁷⁴ that can provide such large sample sizes.

Bayesian multilevel modeling further allowed us to investigate relationships in GAD that were not hypothesized a-priori with minimal risk of information loss. Our analysis identified high probabilities for decreased FC of the PMI with the dlPFC, the dmPFC, and the TP. Decreased functional coupling of the PMI and the dlPFC could be interpreted to reflect abnormal signaling of internal body systems to a key region for executive functions like working memory⁷⁵ and attention⁷⁶: aspects of cognition known to be impaired in anxiety^77,78. The reduced PMI FC between both the dmPFC (a brain area known to be hyperactivated in GAD during emotional processing¹⁷ and at rest⁷⁹), and the TP (an area implicated in social and emotional processing⁸⁰), align well with a proposed model of the insula as an “integral hub” for detecting salient events, and for switching attention to these stimuli in preparation for regulatory (i.e., visceromotor) processing⁸¹. These additional findings suggest that the insula shows decreased functional coupling at rest with brain areas that have previously been found to show aberrant activity and/or connectivity in anxious individuals and whose functions are relevant to the clinical characteristics of GAD. However, this interpretation remains preliminary and requires causal examination in further experiments.

The Bayesian multilevel analysis also revealed diminished FC of the vmPFC-dmPFC region pair in GAD, two key components of the DMN⁷. This finding is consistent with previous reports of DMN alterations in GAD¹², albeit decreased FC between the vmPFC and dmPFC has not been reported previously. These regions of the DMN are hypothesized to promote functions like processing of emotion and self-referential cognition⁷, which are impaired in GAD⁸². Lastly, the Bayesian analysis revealed reduced FC with the vmPFC and the dlPFC, which are key components, respectively, of the DMN and CEN networks⁸. Additionally, the GAD group exhibited decreased FC of both these regions with the dACC, a key node in the salience network and hypothesized to facilitate “switching” between the spontaneous cognition of the DMN⁸³ and executive functioning of the CEN⁸. These results hint at the possibility that decreased FC between the vmPFC and dlPFC could be mediated by reduced functional coupling of these regions to the dACC.

Limitations

Limitations of this study include a female-only sample with modest size (that is still above average compared to fMRI studies in recent years⁸⁴), selected psychotropic medication allowance, and the methodological limitation that correlational analysis cannot determine the causality or directionality (i.e., responsible region) for impaired FC observed within region pairs (see Supplement for further discussion). The choice of brain regions we investigated was based on previous literature, but is not exhaustive. Other brain areas relevant to pathological mechanisms in GAD (e.g., thalamus⁸⁵ or striatum^44,86) should be investigated in future studies. As mentioned in the “Discussion”, testing FC differences between region pairs does not allow for network analysis as commonly employed in seed-based FC analysis across the whole brain. Our focus on females with GAD was based on the fact that females outnumber males with the disorder by a factor of two to one⁸⁷, and that our sample was drawn from a larger study examining psychiatric disorders predominantly affecting females (e.g., anorexia nervosa and GAD). Future research is needed to establish whether our findings extend to males, i.e., whether sex differences in FC play a role in GAD. A recent mega-analysis found structural brain differences only in males with GAD but no general effect of GAD on brain structure⁸⁸, indicating that a dynamic approach using functional MRI could provide better insight into the neurobiology of GAD.

Conclusion

We leveraged the strengths of the Bayesian inference framework to convergently identify reduced FC between the vmPFC and the PMI in GAD and identified an association of this relationship with the anxiety sensitivity trait. Bayesian multilevel modeling allowed us to identify decreased FC between region pairs excluded by the frequentist analysis and other previously undescribed regions, emphasizing the utility of this method for probing the pathophysiological basis of psychiatric disorders. Future fMRI studies of resting state FC may benefit from a similar approach.