Reappraisal of Interpersonal Criticism in Social Anxiety Disorder: A Brain Network Hierarchy Perspective

Relationships between depression, anxiety, and motivation in the real-world: Effects of physical activity and screentime

Background

Mood and anxiety disorders are highly prevalent and comorbid worldwide, with variability in symptom severity that fluctuates over time. Digital phenotyping, a growing field that aims to characterize clinical, cognitive and behavioral features via personal digital devices, enables continuous quantification of symptom severity in the real world, and in real-time.

Methods

In this study, N=114 individuals with a mood or anxiety disorder (MA) or healthy controls (HC) were enrolled and completed 30-days of ecological momentary assessments (EMA) of symptom severity. Novel real-world measures of anxiety, distress and depression were developed based on the established Mood and Anxiety Symptom Questionnaire (MASQ). The full MASQ was also completed in the laboratory (in-lab). Additional EMA measures related to extrinsic and intrinsic motivation, and passive activity data were also collected over the same 30-days. Mixed-effects models adjusting for time and individual tested the association between real-world symptom severity EMA and the corresponding full MASQ sub-scores. A graph theory neural network model (DEPNA) was applied to all data to estimate symptom interactions.

Results

There was overall good adherence over 30-days (MA=69.5%, HC=71.2% completion), with no group difference (t(58)=0.874, p=0.386). Real-world measures of anxiety/distress/depression were associated with their corresponding MASQ measure within the MA group (t's > 2.33, p's < 0.024). Physical activity (steps) was negatively associated with real-world distress and depression (IRRs > 0.93, p's ≤ 0.05). Both intrinsic and extrinsic motivation were negatively associated with real-world distress/depression (IRR's > 0.82, p's < 0.001). DEPNA revealed that both extrinsic and intrinsic motivation significantly influenced other symptom severity measures to a greater extent in the MA group compared to the HC group (extrinsic/intrinsic motivation: t(46) = 2.62, p < 0.02, q FDR < 0.05, Cohen's d = 0.76; t(46) = 2.69, p < 0.01, q FDR < 0.05, Cohen's d = 0.78 respectively), and that intrinsic motivation significantly influenced steps (t(46) = 3.24, p < 0.003, q FDR < 0.05, Cohen's d = 0.94).

Conclusions

Novel real-world measures of anxiety, distress and depression significantly related to their corresponding established in-lab measures of these symptom domains in individuals with mood and anxiety disorders. Novel, exploratory measures of extrinsic and intrinsic motivation also significantly related to real-world mood and anxiety symptoms and had the greatest influencing degree on patients' overall symptom profile. This suggests that measures of cognitive constructs related to drive and activity may be useful in characterizing phenotypes in the real-world.

The deficit in cognitive reappraisal capacity in individuals with anxiety or depressive disorders: meta-analyses of behavioral and neuroimaging studies

BACKGROUND

The deficit in cognitive reappraisal capacity is a key factor in developing and maintaining emotional disorders such as anxiety disorders and depressive disorders. However, the results from both neuroimaging and behavioral studies are mixed. Therefore, we systematically conducted a series of meta-analyses based on behavioral and neuroimaging studies to clarify this issue.

METHODS

In behavioral meta-analyses, we used three-level random-effects models to summarize the overall effect sizes based on Hedges' g. In neuroimaging meta-analyses, we used SDM-PSI to summarize the brain activation patterns.

RESULTS

Behavioral meta-analyses found that individuals with anxiety disorders or depressive disorders could reduce negative reactivity through reappraisal; the reduction of negative emotions through reappraisal by individuals with anxiety disorders was similar to that by healthy individuals; the reduction by depressive disorders was lower than that of healthy individuals. Neuroimaging meta-analyses showed that individuals with anxiety disorders or depressive disorders activated regions of cognitive control during cognitive reappraisal; the activation in individuals with anxiety disorders was lower than in healthy individuals; while the activation in individuals with depressive disorders was similar to that in healthy individuals.

CONCLUSION

Individuals with anxiety and depressive disorders showed dissociation in behaviour and neuroimaging patterns of cognitive reappraisal capacity deficit.

Emotion regulation of social pain: double dissociation of lateral prefrontal cortices supporting reappraisal and distraction

The dorsolateral prefrontal cortex (DLPFC) and ventrolateral prefrontal cortex (VLPFC) are both crucial regions involved in voluntary emotion regulation. However, it remains unclear whether the two regions show functional specificity for reappraisal and distraction. This study employed transcranial magnetic stimulation (TMS) to explore, in a real social interactive scenario, whether different lateral prefrontal regions play relatively specific roles in downregulating social pain via reappraisal and distraction. Participants initially took part in a social interactive game, followed by receiving either active (the DLPFC- or VLPFC-activated group, n = 100 per group) or control (the vertex-activated group, n = 100) TMS session. They were then instructed to use both distraction and reappraisal strategies to downregulate any negative emotions evoked by the social evaluation given by their peers who interacted with them previously. Results demonstrated that the TMS-activated DLPFC has a greater beneficial effect during distraction, whereas the activated VLPFC has a greater beneficial effect during reappraisal. This result investigated the direct experience of social pain and extended previous findings on empathy-related responses to affective pictures while also controlling for confounding factors such as empathic concern. Therefore, we are now confident in the double dissociation proposal of the DLPFC and VLPFC in distraction and reappraisal.

A preliminary study of the effects of mindfulness-based cognitive therapy on structural brain networks in mood-dysregulated youth with a familial risk for bipolar disorder

BACKGROUND

Mindfulness-based cognitive therapy for children (MBCT-C), as a psychotherapeutic intervention, has been shown to be effective for treating mood dysregulation (MD). While previous neuroimaging studies of MD have reported both pre-treatment structural and functional alterations, the effects of MBCT-C on brain morphological network organisation has not been investigated.

METHODS

We investigated brain morphological network organisation in 10 mood-dysregulated youth with familial risk for bipolar disorder and 15 matched healthy comparison youth (HC). Effects of 12 weeks of MBCT-C were examined in the mood-dysregulated youth. Topological properties of brain networks used for analyses were constructed based on morphological similarities in regional grey matter using a graph-theory approach using MRI data.

RESULTS

At baseline, compared with the HC group, the mood-dysregulated group exhibited increased global efficiency (E_glob ), decreased path length (L_p ), and abnormal nodal properties, mainly in the limbic system. Right temporal pole alterations at baseline predicted change in Child and Adolescent Mindfulness Measure scores after treatment. The mood-dysregulated group showed significant decreases in both the E_glob and L_p metrics after MBCT-C, suggesting an improved capacity for optimal information processing. Changes in L_p were correlated with changes in Emotion Regulation Checklist scores. Our results show significant topological alterations in the mood-dysregulated group as compared to controls at baseline. After MBCT-C, disrupted topological properties in the mood-dysregulated group were significantly reduced.

CONCLUSION

MBCT-C may facilitate clinically meaningful changes in the brain structural network in mood-dysregulated individuals.

Organization of the social cognition network predicts future depression and interpersonal impairment: a prospective family-based study

Deficits in social cognition and functioning are common in major depressive disorder (MDD). Still, no study into the pathophysiology of MDD has examined the social cognition-related neural pathways through which familial risk for MDD leads to depression and interpersonal impairments. Using resting-state fMRI, we applied a graph theoretical analysis to quantify the influence of nodes within the fronto-temporo-parietal cortical social cognition network in 108 generation 2 and generation 3 offspring at high and low-risk for MDD, defined by the presence or absence, respectively, of moderate to severe MDD in generation 1. New MDD episodes, future depressive symptoms, and interpersonal impairments were tested for associations with social cognition nodal influence, using regression analyses applied in a generalized estimating equations approach. Increased familial risk was associated with reduced nodal influence within the network, and this predicted new depressive episodes, worsening depressive symptomatology, and interpersonal impairments, 5-8 years later. Findings remained significant after controlling for current depressive/anxiety symptoms and current/lifetime MDD and anxiety disorders. Path-analysis models indicate that increased familial risk impacted offspring's brain function in two ways. First, high familial risk was indirectly associated with future depression, both new MDD episodes and symptomatology, via reduced nodal influence of the right posterior superior temporal gyrus (pSTG). Second, high familial risk was indirectly associated with future interpersonal impairments via reduced nodal influence of right inferior frontal gyrus (IFG). Finally, reduced nodal influence was associated with high familial risk in (1) those who had never had MDD at the time of scanning and (2) a subsample (n = 52) rescanned 8 years later. Together, findings reveal a potential pathway for the intergenerational transmission of vulnerability via the aberrant social cognition network organization and suggest using the connectome of neural network related to social cognition to identify intervention and prevention targets for those particularly at risk.

White matter structural network disturbances in first-episode, drug-naïve adolescents with generalized anxiety disorder

BACKGROUND

Previous studies have suggested that individuals with generalized anxiety disorder (GAD) would show inefficient whole-brain communication and dysconnectivity in the fronto-parietal-subcortical sub-networks in the white matter (WM) structural network. However, these hypotheses have yet to be tested.

METHODS

Individual WM structural networks were constructed based on diffusion MRI data and deterministic tractography in 34 first-episode, medication-naïve adolescents with GAD and 27 healthy controls (HCs). Graph theory was applied to investigate the topological organization alterations of the structural network.

RESULTS

GAD patients showed disrupted small-world configurations (i.e., increased path length and decreased clustering coefficient) and hub organization (i.e., less connection strength in the feeder and local connections). A decreased connection strength was found in a GAD-related sub-network (mainly involving the frontal-subcortical circuits), which was able to distinguish GAD patients from HCs with higher accuracy (area under the curve of 0.96, sensitivity of 94%, specificity of 89%) than clinical scores and other topological alternations.

LIMITATIONS

The current study just compared GAD patients with HCs based on a small sample, leaving whether the alternations found here are specific to GAD still an open question. Future studies are recommended to recruit patients with other anxiety disorders (e.g., social anxiety disorder) and/or comorbid mood disorders to identify the GAD-specific WM alterations using a larger sample.

CONCLUSIONS

Our findings highlight the disruption of the topological organization of the whole-brain WM structural network (especially the frontal-subcortical circuits) in GAD, and suggest the potential of using structural connectivity of the GAD-related sub-network as a biomarker for GAD patients.

White Matter Structural Brain Connectivity of Young Healthy Individuals With High Trait Anxiety

Background: Although functional brain connectivity in anxiety-related disorders has been studied, brain connectivity in non-clinical populations with high trait anxiety has been rarely reported. Whether structural brain connectivity changes in young healthy individuals with high trait anxiety remains unknown.

Methods: Thirty-eight young healthy individuals with high anxiety levels and 34 healthy subjects with low anxiety levels who were matched by age, gender, and educational level were recruited. Diffusion tensor images were acquired to analyze white matter connectivity. A two-sample t-test was used for group comparison of weighted networks and graph properties.

Results: Different connections were detected in fractional anisotropy- and fiber number-weighted networks. These connections were widely distributed in various regions, where relative significance was located in the inter-hemispheric frontal lobe, the frontal-limbic lobe in the right intra-hemisphere, and the frontal-temporal lobe in the ipsilateral hemisphere. However, no significant difference was found in fiber length-weighted network and in graph properties among the three networks.

Conclusions: The structural connectivity of white matter may be a vulnerability marker. Hence, healthy individuals with high trait anxiety levels are susceptible to anxiety-related psychopathology. The findings may help elucidate the pathological mechanism of anxiety and establish interventions for populations susceptible to anxiety disorders.

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group for future development of Parkinson's disease (PD) and have demonstrated task related fMRI changes. However, resting-state networks have received less research focus, thus this study aimed to assess the integrity of the motor, default mode (DMN), salience (SAL), and dorsal attention (DAN) networks among this unique population by using two different connectivity measures: interregional functional connectivity analysis and Dependency network analysis (D_EP NA). Machine learning classification methods were used to distinguish connectivity between the two groups of participants. Forty-four NMC and 41 non-manifesting non-carriers (NMNC) participated in this study; while no behavioral differences on standard questionnaires could be detected, NMC demonstrated lower connectivity measures in the DMN, SAL, and DAN compared to NMNC but not in the motor network. Significant correlations between NMC connectivity measures in the SAL and attention were identified. Machine learning classification separated NMC from NMNC with an accuracy rate above 0.8. Reduced integrity of non-motor networks was detected among NMC of the G2019S mutation in the LRRK2 gene prior to identifiable changes in connectivity of the motor network, indicating significant non-motor cerebral changes among populations "at risk" for future development of PD.