Neural structures, functioning and connectivity in Generalized Anxiety Disorder and interaction with neuroendocrine systems: a systematic review

Challenges and Frontiers in Computational Metabolic Psychiatry

One of the primary challenges in metabolic psychiatry is that the disrupted brain functions that underlie psychiatric conditions arise from a complex set of downstream and feedback processes spanning across multiple spatiotemporal scales. Importantly, the same circuit can have multiple points of failure, each of which results in a different type of dysregulation, and thus elicits distinct cascades downstream that produce divergent signs and symptoms. Here, we illustrate this challenge by examining how subtle differences in circuit perturbations can lead to divergent clinical outcomes. We also discuss how computational models can perform the spatially heterogenous integration and bridge in vitro and in vivo paradigms. By leveraging recent methodological advances and tools, computational models can integrate relevant processes across scales (e.g., TCA-cycle, ion channel, neural microassembly, whole-brain macro-circuit) and across physiological systems (e.g., neural, endocrine, immune, vascular), providing a framework that can unite these mechanistic processes in a manner that goes beyond the conceptual and descriptive, to the quantitative and generative. These hold the potential to sharpen our intuitions towards circuit-based models for personalized diagnostics and treatment.

The phobic brain: Morphometric features correctly classify individuals with small animal phobia

Specific phobia represents an anxiety disorder category characterized by intense fear generated by specific stimuli. Among specific phobias, small animal phobia (SAP) denotes a particular condition that has been poorly investigated in the neuroscientific literature. Moreover, the few previous studies on this topic have mostly employed univariate analyses, with limited and unbalanced samples, leading to inconsistent results. To overcome these limitations, and to characterize the neural underpinnings of SAP, this study aims to develop a classification model of individuals with SAP based on gray matter features, by using a machine learning method known as the binary support vector machine. Moreover, the contribution of specific structural macro-networks, such as the default mode, the salience, the executive, and the affective networks, in separating phobic subjects from controls was assessed. Thirty-two subjects with SAP and 90 matched healthy controls were tested to this aim. At a whole-brain level, we found a significant predictive model including brain structures related to emotional regulation, cognitive control, and sensory integration, such as the cerebellum, the temporal pole, the frontal cortex, temporal lobes, the amygdala and the thalamus. Instead, when considering macro-networks analysis, we found the Default, the Affective, and partially the Central Executive and the Sensorimotor networks, to significantly outperform the other networks in classifying SAP individuals. In conclusion, this study expands knowledge about the neural basis of SAP, proposing new research directions and potential diagnostic strategies.

Altered Functional Coupling of the Bed Nucleus of the Stria Terminalis and Amygdala in Spider Phobic Fear

Background: Individuals with spider phobic (SP) fear show hypervigilance and amygdala hyperactivity toward fear-associated stimuli, which may promote the development of other anxiety disorders. The amygdala is a key region within the fear network, which is connected to the anxiety system, where the bed nucleus of the stria terminalis (BNST) plays a crucial role. However, the BNST's involvement in phobic fear is unknown. Therefore, this study investigated the association of phobic fear and anxiety on these regions' functional connectivity (FC) in SP compared to healthy controls (HC). Methods: 7T-functional MRI resting-state FC of 30 individuals with SP and 45 HC was assessed to detect network differences between these groups. The association of phobic fear severity, trait anxiety, and social anxiety on FC was explored using linear regressions combined with seed-to-voxel analyses with amygdala and BNST as primary seeds, corrected for age and sex. Results: In SP, phobic fear was associated with reduced FC between the left amygdala and the right supramarginal gyrus. In contrast, anxiety severity was related to increased FC between the right BNST and the left inferior frontal gyrus. Moreover, social anxiety was related to decreased FC between bilateral BNST and left precuneus. Conclusions: These findings show changes in FC in SP, connecting fear with altered activity in the BNST and amygdala. The results suggest that persistent anxiety in phobic fear is associated with abnormal brain function in these regions, potentially explaining susceptibility to anxiety disorders and processes involved in phobic fear, such as threat perception, avoidance, and salience. Impact statement This is the first study to report altered FC mechanisms of BNST and amygdala in individuals with SP using 7T ultra-high field resting-state data. So far, only distinct characterization of brain regions, especially of BNST and amygdala, involved in those disorders exists. Our results contribute to closing this knowledge gap by providing the first evidence that deviant BNST and amygdala function in SP might elucidate the susceptibility to other anxiety disorders.

Enhanced diagnostics for generalized anxiety disorder: leveraging differential channel and functional connectivity features based on frontal EEG signals

Generalized Anxiety Disorder (GAD) is a chronic anxiety condition characterized by persistent excessive worry, anxiety, and fear. Current diagnostic practices primarily rely on clinicians' subjective assessments and experience, highlighting a need for more objective and reliable methods. This study collected 10-minute resting-state electroencephalogram (EEG) from 45 GAD patients and 36 healthy controls (HC), focusing on six frontal EEG channels for preprocessing, data segmentation, and frequency band division. Innovatively, this study introduced the "Differential Channel" method, which enhances classification performance by enhancing the information related to anxiety from the data, thereby highlighting signal differences. Utilizing the preprocessed EEG signals, undirected functional connectivity features (Phase Lag Index, Pearson Correlation Coefficient, and Mutual Information) and directed functional connectivity features (Partial Directed Coherence) were extracted. Multiple machine learning models were applied to distinguish between GAD patients and HC. The results show that the Deep Forest classifier achieves excellent performance with a 12-second time window of DiffFeature. In particular, the classification of GAD and HC was successfully obtained by combining OriFeature and DiffFeature on Mutual Information with a maximum accuracy of 98.08%. Furthermore, it was observed that undirected functional connectivity features significantly outperformed directed functional connectivity when fewer frontal channels were used. Overall, the methodologies developed in this study offer accurate and practical identification strategies for the early screening and clinical diagnosis of GAD, offering the necessary theoretical and technical support for further enhancing the portability of EEG devices.

Hippocampal subfield volume in older adults with and without mild cognitive impairment: Effects of worry and cognitive reappraisal

Studies have confirmed that anxiety, especially worry and rumination, are associated with increased risk for cognitive decline, including Alzheimer's disease and related dementias (ADRD). Hippocampal atrophy is a hallmark of ADRD. We investigated the association between hippocampus and its subfield volumes and late-life global anxiety, worry, and rumination, and emotion regulation strategies. We recruited 110 participants with varying worry severity who underwent magnetic resonance imaging and clinical interviews. We conducted cross-sectional regression analysis between each subfield and anxiety, worry, rumination, reappraisal, and suppression while adjusting for age, sex, race, education, cumulative illness burden, stress, neuroticism, and intracranial volume. We imputed missing data and corrected for multiple comparisons across regions. Greater worry was associated with smaller subiculum volume, whereas greater use of reappraisal was associated with larger subiculum and CA1 volume. Greater worry may be detrimental to the hippocampus and to subfields involved in early ADRD pathology. Use of reappraisal appears protective of hippocampal structure. Worry and reappraisal may be modifiable targets for ADRD prevention.

Alterations in neural circuit dynamics between the limbic network and prefrontal/default mode network in patients with generalized anxiety disorder

BACKGROUND

Widespread functional alterations have been implicated in patients with generalized anxiety disorder (GAD). However, most studies have primarily focused on static brain network features in patients with GAD. The current research focused on exploring the dynamics within functional brain networks among individuals diagnosed with GAD.

METHODS

Seventy-five participants were divided into patients with GAD and healthy controls (HCs), and resting-state functional magnetic resonance imaging data were collected. The severity of symptoms was measured using the Hamilton Anxiety Scale and the Patient Health Questionnaire. Co-activation pattern (CAP) analysis, centered on the bed nucleus of the stria terminalis, was applied to explore network dynamics. The capability of these dynamic characteristics to distinguish between patients with GAD and HCs was evaluated using a support vector machine.

RESULTS

Patients with GAD exhibited disruptions in the limbic-prefrontal and limbic-default-mode network circuits. Particularly noteworthy was the marked reduction in dynamic indicators such as occurrence, EntriesFromBaseline, ExitsToBaseline, in-degree, out-degree, and resilience. Moreover, these decreased dynamic features effectively distinguished the GAD group from the HC in this study.

CONCLUSIONS

The current findings revealed the underlying brain networks associated with compromised emotion regulation in individuals with GAD. The dynamic reduction in connectivity between the limbic-default mode network and limbic-prefrontal networks could potentially act as a biomarker and therapeutic target for GAD in the future.

Exploring volumetric abnormalities in subcortical L-HPA axis structures in pediatric generalized anxiety disorder

BACKGROUND

Pediatric generalized anxiety disorder (GAD) is debilitating and increasingly prevalent, yet its etiology remains unclear. Some believe the disorder to be propagated by chronic dysregulation of the limbic-hypothalamic-pituitary-adrenal (L-HPA) axis, but morphometric studies of implicated subcortical areas have been largely inconclusive. Recognizing that certain subcortical subdivisions are more directly involved in L-HPA axis functioning, this study aims to detect specific abnormalities in these critical areas.

METHODS

Thirty-eight MRI scans of preschool children with (n = 15) and without (n = 23) GAD underwent segmentation and between-group volumetric comparisons of the basolateral amygdala (BLA), ventral hippocampal subiculum (vSC), and mediodorsal medial magnocellular (MDm) area of the thalamus.

RESULTS

Children with GAD displayed significantly larger vSC compared to healthy peers, F(1, 31) = 6.50, pFDR = .048. On average, children with GAD presented with larger BLA and MDm, Fs(1, 31) ≥ 4.86, psFDR ≤ .054. Exploratory analyses revealed right-hemispheric lateralization of all measures, most notably the MDm, F(1, 31) = 8.13, pFDR = .024, the size of which scaled with symptom severity, r = .83, pFDR = .033.

CONCLUSION

The BLA, vSC, and MDm are believed to be involved in the regulation of anxiety and stress, both individually and collectively through the excitation and inhibition of the L-HPA axis. All were found to be enlarged in children with GAD, perhaps reflecting hypertrophy related to hyperexcitability, or early neuronal overgrowth. Longitudinal studies should investigate the relationship between these early morphological differences and the long-term subcortical atrophy previously observed.

Deficient sleep, altered hypothalamic functional connectivity, depression and anxiety in cigarette smokers

Background

Deficient sleep is implicated in nicotine dependence as well as depressive and anxiety disorders. The hypothalamus regulates the sleep-wake cycle and supports motivated behavior, and hypothalamic dysfunction may underpin comorbid nicotine dependence, depression and anxiety. We aimed to investigate whether and how the resting state functional connectivities (rsFCs) of the hypothalamus relate to cigarette smoking, deficient sleep, depression and anxiety.

Methods

We used the data of 64 smokers and 198 age- and sex-matched adults who never smoked, curated from the Human Connectome Project. Deficient sleep and psychiatric problems were each assessed with Pittsburgh Sleep Quality Index (PSQI) and Achenbach Adult Self-Report. We processed the imaging data with published routines and evaluated the results at a corrected threshold, all with age, sex, and the severity of alcohol use as covariates.

Results

Smokers vs. never smokers showed poorer sleep quality and greater severity of depression and anxiety. In smokers only, the total PSQI score, indicating more sleep deficits, was positively associated with hypothalamic rsFCs with the right inferior frontal/insula/superior temporal and postcentral (rPoCG) gyri. Stronger hypothalamus-rPoCG rsFCs were also associated with greater severity of depression and anxiety in smokers but not never smokers. Additionally, in smokers, the PSQI score completely mediated the relationships of hypothalamus-rPoCG rsFCs with depression and anxiety severity.

Conclusions

These findings associate hypothalamic circuit dysfunction to sleep deficiency and severity of depression and anxiety symptoms in adults who smoke. Future studies may investigate the roles of the hypothalamic circuit in motivated behaviors to better characterize the inter-related neural markers of smoking, deficient sleep, depression and anxiety.

Examining the relationship between anxiety and regional brain volumes in the National Alzheimer's Coordinating Center uniform, imaging, and biomarker datasets

Anxiety has been associated with a greater risk of Alzheimer's disease (AD). Existing research has identified structural differences in regional brain tissue in participants with anxiety, but results have been inconsistent. We sought to determine the association between anxiety and regional brain volumes, and the moderation effect of APOE ε4. Using data from participants in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set, with complete imaging (MRI) and biomarker data (n = 1533), multiple linear regression estimated the adjusted effect of anxiety on 30 structural MRI regions. The moderation effect of APOE ε4 on the relation between structural MRI regions and anxiety was assessed as was the moderation effect of cognitive status. False discovery rate was used to adjust for multiple comparisons. After controlling for intracranial volume, age, sex, years of education, race, Hispanic ethnicity, and cognitive status, seven MRI regions demonstrated lower volumes among participants with anxiety: total cerebrum gray matter volume, right hippocampus volume, hippocampal volume (total), right and left frontal lobe cortical gray matter volume, and right and total temporal lobe cortical gray matter volume. Findings suggest that anxiety is associated with significant atrophy in multiple brain regions, with corresponding ventricular enlargement. Future research should investigate if anxiety-related changes to brain morphology contribute to greater AD risk.

Feasibility of applying graph theory to diagnosing generalized anxiety disorder using machine learning models

The aim of this study was to investigate whether the alterations of topological properties can facilitate the diagnosis of generalized anxiety disorder (GAD). Twenty first-episode drug-naive Chinese individuals with GAD and twenty age-sex-education-matched healthy controls (HCs) were included in the primary training set, and the results of which were validated using nineteen drug-free patients with GAD and nineteen unmatched HCs. Two 3 T scanners were used to acquire T1, diffusion tensor, and resting-state functional images. Topological properties were altered in the functional cerebral networks among patients with GAD, but not in the structural networks. Using the nodal topological properties in the anti-correlated functional networks, machine learning models distinguished drug-naive GADs from their matched HCs independent of the type of kernels and the amount of features. Although the models built with drug-naive GADs failed to distinguish drug-free GADs from HCs, the features selected for those models could be used to build new models for distinguishing drug-free GADs from HCs. Our findings suggested that it is feasible to utilize the topological characteristics of brain network to facilitate the diagnosis of GAD. However, further research with decent sample sizes, multimodal features, and improved modeling methods are needed to build more robust models.

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

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.

A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia

Background

Late-life depression (LLD) is linked to various medical conditions and influenced by aging-related processes. Sleep disturbances and insomnia symptoms may be early indicators or risk factors for depression. Neuroimaging studies have attempted to understand the neural mechanisms underlying LLD, focusing on different brain networks. This study aims to further delineate discriminative brain structural profiles for LLD with insomnia using MRI.

Methods

We analyzed 24 cases in the LLD with insomnia group, 26 cases in the LLD group, and 26 in the healthy control (HC) group. Patients were evaluated using the Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA), Mini-Mental State Examination (MMSE), and Pittsburgh Sleep Quality Index (PSQI). Structural MRI data were gathered and analyzed using voxel-based morphometry (VBM) to identify differences in gray matter volume (GMV) among the groups. Correlation analyses were conducted to explore the relationships between GMV and clinical characteristics.

Results

Significant difference in sex distribution was observed across the groups (p = 0.029). However, no significant differences were detected in age and MMSE scores among the groups. LLD with insomnia group exhibited significantly higher HAMA (p = 0.041) and PSQI scores (p < 0.05) compared to the LLD group. ANOVA identified significant difference in GMV of anterior lobe of cerebellum (peak MNI coordinate: x = 52, y = -40, z = -30) among HC, LLD, and LLD with insomnia. Post-hoc two-sample t-tests revealed that the significant difference in GMV was only found between the LLD group and the HC group (p < 0.05). The mean GMV in the cerebellum was positively correlated with HAMA scale in LLD patients (r = 0.47, p < 0.05).

Conclusion

There is significant difference in GMV in the LLD group, the association between late-life depression and insomnia may be linked to anxiety. This study provides insights into the discriminative brain structural profiles of LLD and LLD with insomnia, advancing the understanding of the underlying neural mechanisms and potential targets for intervention.

Difference analysis of multidimensional electroencephalogram characteristics between young and old patients with generalized anxiety disorder

Growing evidences indicate that age plays an important role in the development of mental disorders, but few studies focus on the neuro mechanisms of generalized anxiety disorder (GAD) in different age groups. Therefore, this study attempts to reveal the neurodynamics of Young_GAD (patients with GAD under the age of 50) and Old_GAD (patients with GAD over 50 years old) through statistical analysis of multidimensional electroencephalogram (EEG) features and machine learning models. In this study, 10-min resting-state EEG data were collected from 45 Old_GAD and 33 Young_GAD. And multidimensional EEG features were extracted, including absolute power (AP), fuzzy entropy (FE), and phase-lag-index (PLI), on which comparison and analyses were performed later. The results showed that Old_GAD exhibited higher power spectral density (PSD) value and FE value in beta rhythm compared to theta, alpha1, and alpha2 rhythms, and functional connectivity (FC) also demonstrated significant reorganization of brain function in beta rhythm. In addition, the accuracy of machine learning classification between Old_GAD and Young_GAD was 99.67%, further proving the feasibility of classifying GAD patients by age. The above findings provide an objective basis in the field of EEG for the age-specific diagnosis and treatment of GAD.

Accelerated low-intensity rTMS does not rescue anxiety behaviour or abnormal connectivity in young adult rats following chronic restraint stress

Currently approved repetitive transcranial magnetic stimulation (rTMS) protocols for the treatment of major depressive disorder (MDD) involve once-daily (weekday) stimulation sessions, with 10 Hz or intermittent theta burst stimulation (iTBS) frequencies, over 4-6 weeks. Recently, accelerated treatment protocols (multiple daily stimulation sessions for 1-2 weeks) have been increasingly studied to optimize rTMS treatments. Accelerated protocols might confer unique advantages for adolescents and young adults but there are many knowledge gaps related to dosing in this age group. Off-label, clinical practice frequently outpaces solid evidence as rigorous clinical trials require substantial time and resources. Murine models present an opportunity for high throughput dose finding studies to focus subsequent clinical trials in humans. This project investigated the brain and behavioural effects of an accelerated low-intensity rTMS (LI-rTMS) protocol in a young adult rodent model of chronic restraint stress (CRS). Depression and anxiety-related behaviours were induced in young adult male Sprague Dawley rats using the CRS model, followed by the 3-times-daily delivery of 10 Hz LI-rTMS, for two weeks. Behaviour was assessed using the Elevated Plus Maze and Forced Swim Test, and functional, chemical, and structural brain changes measured using magnetic resonance imaging techniques. CRS induced an agitated depression-like phenotype but therapeutic effects from the accelerated protocol were not detected. Our findings suggest that the age of rodents may impact response to CRS and LI-rTMS. Future studies should also examine higher intensities of rTMS and accelerated theta burst protocols.

Reduced cortical volume of the default mode network in adolescents with generalized anxiety disorder

BACKGROUND

Widespread structural alterations have been shown to be implicated in individuals with generalized anxiety disorder (GAD). However, there have been inconsistent findings in cortical volume (CV) differences. Most structural neuroimaging studies looking at GAD used region-based approach with relatively small sample sizes, let alone be specific to adolescents with GAD. We believe this is the first study to look at CV measures using a network-based approach in a larger sample of adolescents with GAD. The goal of the current study was to focus on three different brain networks (i.e., Limbic, Frontoparietal, and Default Mode Network [DMN]) in adolescents with GAD.

METHOD

The study involved 81 adolescents with GAD and 112 typically developing (TD) comparison individuals matched on age (15.98 and 15.63 respective means), sex (42F/39M and 45F/67M), and IQ (101.90 and 103.94 respective means). Participants underwent structural MRI. Freesurfer was used to estimate CV (both network-specific and region-specific within networks) and region-specific sub-cortical volume measures. Multivariate analysis of covariance (MANCOVA; with sex, age, IQ, and intracranial volume [ICV] as potential covariates) was used to estimate group differences.

RESULTS

We found significantly lower CV for the DMN in adolescents with GAD, compared with TD individuals. Adolescents with GAD also showed significantly lower hemispheric mean CV of the default-mode regions (particularly the prefrontal and temporal regions) and the hippocampus, compared with TD individuals.

CONCLUSION

The current findings suggest structural alterations in adolescents with GAD. These structural alterations will need to be addressed when implementing and developing treatments for patients with GAD.

Guts Imbalance Imbalances the Brain: A Review of Gut Microbiota Association With Neurological and Psychiatric Disorders

Over the last 10 years, there has been a growing interest in the relationship between gut microbiota, the brain, and neurologic-associated affections. As multiple preclinical and clinical research studies highlight gut microbiota’s potential to modulate the general state of health state, it goes without saying that gut microbiota plays a significant role in neurogenesis, mental and cognitive development, emotions, and behaviors, and in the progression of neuropsychiatric illnesses. Gut microbiota produces important biologic products that, through the gut-brain axis, are directly connected with the appearance and evolution of neurological and psychiatric disorders such as depression, anxiety, bipolar disorder, autism, schizophrenia, Parkinson’s disease, Alzheimer’s disease, dementia, multiple sclerosis, and epilepsy. This study reviews recent research on the link between gut microbiota and the brain, and microbiome’s role in shaping the development of the most common neurological and psychiatric illnesses. Moreover, special attention is paid to the use of probiotic formulations as a potential non-invasive therapeutic opportunity for prevention and management of neuropsychiatric-associated affections.

Toward Linguistic Recognition of Generalized Anxiety Disorder

Background

Generalized anxiety disorder (GAD) refers to extreme, uncontrollable, and persistent worry and anxiety. The disorder is known to affect the social functioning and well-being of millions of people, but despite its prevalence and burden to society, it has proven difficult to identify unique behavioral markers. Interestingly, the worrying behavior observed in GAD is argued to stem from a verbal linguistic process. Therefore, the aim of the present study was to investigate if GAD can be predicted from the language people use to put their anxious worries into words. Given the importance of avoidance sensitivity (a higher likelihood to respond anxiously to novel or unexpected triggers) in GAD, this study also explored if prediction accuracy increases when individual differences in behavioral avoidance and approach sensitivity are taken into account.

Method

An expressive writing exercise was used to explore whether GAD can be predicted from linguistic characteristics of written narratives. Specifically, 144 undergraduate student participants were asked to recall an anxious experience during their university life, and describe this experience in written form. Clinically validated behavioral measures for GAD and self-reported sensitivity in behavioral avoidance/inhibition (BIS) and behavioral approach (BAS), were collected. A set of classification experiments was performed to evaluate GAD predictability based on linguistic features, BIS/BAS scores, and a concatenation of the two.

Results

The classification results show that GAD can, indeed, be successfully predicted from anxiety-focused written narratives. Prediction accuracy increased when differences in BIS and BAS were included, which suggests that, under those conditions, negatively valenced emotion words and words relating to social processes could be sufficient for recognition of GAD.

Conclusions

Undergraduate students with a high GAD score can be identified based on their written recollection of an anxious experience during university life. This insight is an important first step toward development of text-based digital health applications and technologies aimed at remote screening for GAD. Future work should investigate the extent to which these results uniquely apply to university campus populations or generalize to other demographics.

Depression and anxiety increase the odds of developing delirium in ICU patients; a prospective observational study

BACKGROUND

Delirium is prevalent among hospitalised patients, especially in critically ill patients. Preventing delirium by recognising its modifiable risk factors could improve life quality, decrease mortality and restrain its devastating consequences.

METHOD

We investigated 50 patients who had been hospitalised in the general ICU and monitored them for developing delirium. We employed CAM and CAM-ICU Scales to assess delirium, RASS score to determine the consciousness level, HADS questionnaire for anxiety and depression, and the demographic data questionnaire.

RESULTS

We found that 20% of ICU patients developed delirium and found a meaningful correlation between the incident delirium, older ages, visual impairment, and higher anxiety and depression scores (HADS) of first and second days of hospitalisation. By utilising logistic regression, we found that older ages, visual impairment, higher anxiety and depression scores (HADS) of the first day of hospitalisation were statistically significant to predict the risk model of developing delirium.

CONCLUSION

Depressive and anxiety symptoms were associated with higher odds of transitioning to delirium; so, at the admission time, it may be useful to screen patients for the symptoms of affective disorders, particularly, who are at higher risks for developing delirium.

ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.

Prefrontal cortex alterations in major depressive disorder, generalized anxiety disorder and their comorbidity during a verbal fluency task assessed by multi-channel near-infrared spectroscopy

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are frequently comorbid with each other, and both associated with substantial cognitive impairments; however, it is still unclear whether their impairments are neurobiologically similar or distinct. This study aims to investigate the cognitive functions of the prefrontal cortex (PFC) in patients with MDD and GAD during the verbal fluency task (VFT) using functional near-infrared spectroscopy (fNIRS). Fifty-two patients with MDD, fifty-one patients with GAD, fifty-two patients with the comorbidity of MDD and GAD (CMG), and forty-seven healthy controls (HC) participated in the study. Significant hypoactivation in the left ventrolateral and the left dorsolateral PFC was common in all patient groups when compared to HCs, suggesting a shared etiology. Furthermore,  MDD patients showed significant hypoactivation at the right frontal pole cortex (FPoC) when compared to HCs and significant hypoactivation at the middle FPoC when compared to the CMG patients. Our work is the first fNIRS study to reveal the shared and unique neurobiological profiles of MDD, GAD and their comorbidity under the same standard experimentation condition, suggesting fNIRS holds promise as an adjutant to assist clinical diagnosis.

Coping Strategies, Neural Structure, and Depression and Anxiety During the COVID-19 Pandemic: A Longitudinal Study in a Naturalistic Sample Spanning Clinical Diagnoses and Subclinical Symptoms

BACKGROUND

Although the COVID-19 pandemic has been shown to worsen anxiety and depression symptoms, we do not understand which behavioral and neural factors may mitigate this impact. To address this gap, we assessed whether adaptive and maladaptive coping strategies affect symptom trajectory during the pandemic. We also examined whether pre-pandemic integrity of brain regions implicated in depression and anxiety affect pandemic symptoms.

METHODS

In a naturalistic sample of 169 adults (66.9% female; age 19-74 years) spanning psychiatric diagnoses and subclinical symptoms, we assessed anhedonia, tension, and anxious arousal symptoms using validated components (21-item Depression, Anxiety, and Stress Scale), coping strategies (Brief-Coping Orientation to Problems Experienced), and gray matter volume (amygdala) and cortical thickness (hippocampus, insula, anterior cingulate cortex) from magnetic resonance imaging T1-weighted scans. We conducted general linear mixed-effects models to test preregistered hypotheses that 1) maladaptive coping pre-pandemic and 2) lower structural integrity pre-pandemic would predict more severe pandemic symptoms; and 3) coping would interact with neural structure to predict pandemic symptoms.

RESULTS

Greater use of maladaptive coping strategies was associated with more severe anxious arousal symptoms during the pandemic (p = .011, false discovery rate-corrected p [p FDR] = .035), specifically less self-distraction (p = .014, p FDR = .042) and greater self-blame (p = .002, p FDR = .012). Reduced insula thickness pre-pandemic predicted more severe anxious arousal symptoms (p = .001, p FDR = .027). Self-distraction interacted with amygdala volume to predict anhedonia symptoms (p = .005, p FDR = .020).

CONCLUSIONS

Maladaptive coping strategies and structural variation in brain regions may influence clinical symptoms during a prolonged stressful event (e.g., COVID-19 pandemic). Future studies that identify behavioral and neural factors implicated in responses to global health crises are warranted for fostering resilience.

Identify potential neuroimaging-based scalp acupuncture and neuromodulation targets for anxiety

Anxiety is a common psychiatric symptom with unsatisfactory treatment. Scalp acupuncture is a new type of acupuncture based on the functions of different brain regions. However, recent brain neuroimaging findings have not been well-integrated into scalp acupuncture practice and research since it was developed. In parallel, recently developed brain stimulation methods have also been applied to treat anxiety. In this study, we integrated meta-analysis (using Neurosynth), resting-state functional connectivity, and diffusion tensor imaging (using the amygdala as the region of interest) to identify potential locations of scalp acupuncture/neuromodulation for anxiety. We found that the superior/middle frontal gyrus, middle/superior temporal gyrus, precentral gyrus, supplementary motor area, supramarginal gyrus, angular gyrus, and superior/inferior occipital gyrus are involved in the pathophysiology of anxiety, and, thus, may be used as the target areas of scalp stimulation for alleviating anxiety. Integrating multidisciplinary brain methods to identify key surface cortical areas associated with a certain disorder may shed light on the development of scalp acupuncture/neuromodulation, particularly in the domain of identifying stimulation locations.

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

Systematic transdiagnostic review of magnetic-resonance imaging results: Depression, anxiety disorders and their co-occurrence

BACKGROUND

Major depressive disorder (MDD) and anxiety disorders (ANX) share core symptoms such as negative affect and often co-exist. Magnetic-resonance imaging (MRI) research suggests shared neuroanatomical/neurofunctional underpinnings. So far, studies considering transdiagnostic and disorder-specific neural alterations in MDD and ANX as well as the comorbid condition (COM) have not been reviewed systematically.

METHODS

Following PRISMA guidelines, the literature was screened and N = 247 articles were checked according to the PICOS criteria: MRI studies investigating transdiagnostic (across MDD, ANX, COM compared to healthy controls) and/or disorder-specific (between MDD, ANX, COM) neural alterations. N = 35, thereof n = 13 structural MRI and diffusion-tensor imaging studies and n = 22 functional MRI studies investigating emotional, cognitive deficits and resting state were included and quality coded.

RESULTS

Results indicated transdiagnostic structural/functional alterations in the orbitofrontal cortex/middle frontal cortex and in limbic regions (amygdala, cingulum, hippocampus). Few and inconsistent disorder-specific alterations were reported. However, depression-specific functional alterations were reported for the inferior frontal gyrus and dorsolateral prefrontal cortex during emotional tasks, and limbic regions at rest. Preliminary results for anxiety-specific functional alterations were found in the insula and frontal regions during emotional tasks, in the inferior parietal lobule, superior frontal gyrus and superior temporal gyrus during cognitive tasks, and (para)limbic alterations at rest.

CONCLUSIONS

This review provides evidence to support existing transdiagnostic fronto-limbic neural models in MDD and ANX. On top, it expands existing knowledge taking into account comorbidity and comparing MDD with ANX. Heterogeneous evidence exists for disorder-specific alterations. Research focusing on ANX sub-types, and the consideration of COM would contribute to a better understanding of basic neural underpinnings.

Anxiety and depression in school-age patients with spinal muscular atrophy: a cross-sectional study

BACKGROUND

Spinal muscular atrophy (SMA) is a rare neurogenetic disease which involves multisystem dysfunctions such as respiratory, digestive, and motor disorders. Anxiety, depression and other psychological disorders often accompany severe chronic physical diseases. The aim of this study was to investigate the prevalence of anxiety and depression along with their influencing factors among school-age patients with SMA.

METHODS

We conducted a cross-sectional study on school-age SMA patients in China. Patients aged 8-18 years with a genetic diagnosis of 5qSMA were invited to answer a questionnaire composed of sociodemographic and clinical questions, then to complete the Screen for Child Anxiety-Related Emotional Disorders and Depression Self-Rating Scale for depression and anxiety level evaluation. At the end of the questionnaire, further questions assessed the subjective anxiety and subjective depression of patients' caregivers and their expectations for their child's future.

RESULTS

Complete data were available for 155 patients. The sample included 45.8% boys and 54.2% girls; 65.2% were type II, 27.1% were type III, and the remainder were type I SMA. Rates of anxiety and depression in these school-age SMA patients were 40.0% and 25.2%, respectively. Gender, age, and disease type were not associated with anxiety or depression, but respiratory system dysfunction, digestive system dysfunction, skeletal deformity, rehabilitation exercise, academic delay, specialized support from school, household income level, caregivers' subjective anxiety, and caregivers' expectations were significantly related to both anxiety and depression.

CONCLUSIONS

There was a high prevalence of anxiety and depression in school-age SMA patients in China. Professional psychological care maybe included in the standard of care. These results also call for possible targets for intervention such as reducing complications, improving drug accessibility, retaining normal schooling, strengthening school support, and enhancing the ability of the caregivers of SMA patients to assist in the diagnosis and treatment of the disease, so improving the mental health of SMA patients.

A specific neural substrate predicting current and future impulsivity in young adults

Impulsivity (rash action with deleterious outcomes) is common to many psychiatric disorders. While some studies indicate altered amygdala and prefrontal cortical (PFC) activity associated with impulsivity, it remains unclear whether these patterns of neural activity are specific to impulsivity or common to a range of affective and anxiety symptoms. To elucidate neural markers specific to impulsivity, we aimed to differentiate patterns of amygdala-PFC activity and functional connectivity associated with impulsivity from those associated with affective and anxiety symptoms, and identify measures of this circuitry predicting future worsening of impulsivity. Using a face emotion processing task that reliably activates amygdala-PFC circuitry, neural activity and connectivity were assessed in a transdiagnostically-recruited sample of young adults, including healthy (N = 47) and treatment-seeking individuals (N = 67). Relationships were examined between neural measures and impulsivity, anhedonia, and affective and anxiety symptoms at baseline (N = 114), and at 6 months post scan (N = 30). Impulsivity, particularly negative urgency and lack of perseverance, was related to greater amygdala activity (beta = 0.82, p = 0.003; beta = 0.68, p = 0.004; respectively) and lower amygdala-medial PFC functional connectivity (voxels = 60, tpeak = 4.45, pFWE = 0.017; voxels = 335, tpeak = 5.26, pFWE = 0.001; respectively) to facial fear. Left vlPFC, but not amygdala, activity to facial anger was inversely associated with mania/hypomania (beta = -2.08, p = 0.018). Impulsivity 6 months later was predicted by amygdala activity to facial sadness (beta = 0.50, p = 0.017). There were no other significant relationships between neural activity and 6-month anhedonia, affective, and anxiety symptoms. Our findings are the first to associate amygdala-PFC activity and functional connectivity with impulsivity in a large, transdiagnostic sample, providing neural targets for future interventions to reduce predisposition to impulsivity and related future mental health problems in young adults.

Potential scalp stimulation targets for mental disorders: evidence from neuroimaging studies

Mental disorders widely contribute to the modern global disease burden, creating a significant need for improvement of treatments. Scalp stimulation methods (such as scalp acupuncture and transcranial electrical stimulation) have shown promising results in relieving psychiatric symptoms. However, neuroimaging findings haven’t been well-integrated into scalp stimulation treatments. Identifying surface brain regions associated with mental disorders would expand target selection and the potential for these interventions as treatments for mental disorders. In this study, we performed large-scale meta-analyses separately on eight common mental disorders: attention deficit hyperactivity disorder, anxiety disorder, autism spectrum disorder, bipolar disorder, compulsive disorder, major depression, post-traumatic stress disorder and schizophrenia; utilizing modern neuroimaging literature to summarize disorder-associated surface brain regions, and proposed neuroimaging-based target protocols. We found that the medial frontal gyrus, the supplementary motor area, and the dorsal lateral prefrontal cortex are commonly involved in the pathophysiology of mental disorders. The target protocols we proposed may provide new brain targets for scalp stimulation in the treatment of mental disorders, and facilitate its clinical application.

Subclinical depression and anxiety impact verbal memory functioning differently in men and women -an fMRI study

BACKGROUND

Depressive symptoms are known to affect memory efficiency in various populations. More specifically, several studies conducted in patients suffering from schizophrenia have indicated that memory efficiency is affected by depressed mood in female patients and by anxiety in male patients. We investigated, using neuroimaging techniques, whether similar gender-specific associations with subclinical depression and anxiety could be observed in a non-clinical sample.

METHOD

Forty-five healthy Spanish-speaking individuals (23 females) were administered a verbal memory task. Lists of high- and low-frequency words were presented. Immediate free recall was requested after the learning of each list, and a yes/no recognition task was completed during the acquisition of the fMRI data.

RESULTS

Regression analyses revealed that higher depression scores in women, and higher anxiety scores in men, were associated with poorer recall. In women, higher depression scores were further associated with decreased cerebral activity in the right temporoparietal junction, left inferior occipitotemporal gyrus, bilateral thalamus, and left anterior cingulate during correct recognition of target words. In men, anxiety scores were not associated with any cerebral activity.

CONCLUSIONS

Subclinical depression in women appears to affect memory efficiency by impacting cerebral regions specifically recruited for the cognitive demands of the task, as well as cerebral regions more generally involved in arousal, decision-making, and emotional regulation. Anxiety in men might impact the encoding memory processes. The results, although preliminary, suggest that gender differences may need to be taken into account when developing strategies for the cognitive and pharmacological remediation of memory impairment.

Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder

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.

Endocannabinoids, cannabinoids and the regulation of anxiety

Cannabis has been used for hundreds of years, with its ability to dampen feelings of anxiety often reported as a primary reason for use. Only recently has the specific role cannabinoids play in anxiety been thoroughly investigated. Here we discuss the body of evidence describing how endocannabinoids and exogenous cannabinoids are capable of regulating the generation and termination of anxiety states. Disruption of the endogenous cannabinoid (eCB) system following genetic manipulation, pharmacological intervention or stress exposure reliably leads to the generation of an anxiety state. On the other hand, upregulation of eCB signaling is capable of alleviating anxiety-like behaviors in multiple paradigms. When considering exogenous cannabinoid administration, cannabinoid receptor 1 (CB1) agonists have a biphasic, dose-dependent effect on anxiety such that low doses are anxiolytic while high doses are anxiogenic, a phenomenon that is evident in both rodent models and humans. Translational studies investigating a loss of function mutation in the gene for fatty acid amide hydrolase, the enzyme responsible for metabolizing AEA, have also shown that AEA signaling regulates anxiety in humans. Taken together, evidence reviewed here has outlined a convincing argument for cannabinoids being powerful regulators of both the manifestation and amelioration of anxiety symptoms, and highlights the therapeutic potential of targeting the eCB system for the development of novel classes of anxiolytics. This article is part of the special issue on 'Cannabinoids'.

Out-of-step: brain-heart desynchronization in anxiety disorders

Imaging studies in anxiety disorders (AD) show abnormal functional connectivity primarily in the salience network (SN), somatomotor network (SMN), and default mode network (DMN). However, it is not clear how precisely these network changes occur including their relation to psychopathological symptoms. Here, we show that the functional networks affected in AD overlap with cortical regions that receive visceral inputs (the so-called central/visceral autonomic network). Focusing on cardiac afferents, we suggest that network changes in AD may be due to reduced phase synchronization between ongoing neural and cardiac activity. This neuro-cardiac desynchronization occurs due to the abnormal phase resetting of neural activity at the onset of each heartbeat, as measured by a lower intertrial coherence and heartbeat-evoked potential. Biochemically, cardiac afferents reach subcortical serotonergic raphe nuclei and noradrenergic locus coeruleus (among others) which, in turn, are known to reciprocally modulate the DMN and SMN/SN on the cortical level. Consistent with the network changes in AD, decreases in serotonergic and noradrenergic activity are known to increase connectivity in both SMN and SN while, at the same time, they decrease DMN connectivity. SMN and SN increases, in turn, lead to increased emotional arousal/anxiety and bodily awareness whereas decreased DMN connectivity leads to an unstable sense-of-self in AD. Finally, we integrate our proposal with interoceptive predictive processing models suggesting neuro-cardiac desynchronization as a mechanism for "noisy" bottom-up information leading to a persistently uncertain bodily state in top-down models. In sum, integrating theories on active interference and hyperarousal, we propose a precise neuro-cardiac and biochemically -driven mechanisms for key psychopathological symptoms of AD.

Examining longitudinal associations between self-reported depression, anxiety and stress symptoms and hair cortisol among mothers of young children

BACKGROUND

Maternal mental health is critically important given its impacts on both women's and children's outcomes. Hair cortisol concentrations (HCC) may provide insight into physiological processes underpinning mental health. This study investigated associations between mothers' self-reported mental health symptoms and their HCC at 1, 2 and 3 years postpartum.

METHODS

Longitudinal study of Australian mothers recruited for their experience of adversity in pregnancy ('right@home' trial, N=722). Mental health symptoms were self-reported using the Depression, Anxiety and Stress Scales (DASS). Associations between DASS total and subscale scores and HCC were estimated using linear regression and generalized estimating equation (GEE) models, examining associations: at each age; across all ages (multivariate GEE); and with persistence of high symptom severity. Missing data were addressed using multiple imputation.

RESULTS

546/722 (76%) women provided at least one hair sample (71% at 1, 61% at 2, 49% at 3 years). Associations between DASS total or subscale scores and HCC were not evident across time points. Only dichotomized high depression symptom severity was associated with higher HCC in the GEE models (β=0.12, p=0.04). There was no evidence of associations between persistence of high DASS symptom severity and HCC at 3 years.

LIMITATIONS

The DASS measured self-reported symptoms for the preceding week whereas HCC captured average cortisol over three months. Associations amongst mothers experiencing adversity may not represent patterns in the general population.

CONCLUSIONS

Considered in context with existing literature, these findings suggest that HCC provides limited insight into the mental health of mothers experiencing adversity across the early postpartum years.

tDCS as a treatment for anxiety and related cognitive deficits

INTRODUCTION

Anxiety is characterized by psychological, physiological, and cognitive complaints. Current treatments have significant limitations, and often overlook any potential benefits to common cognitive symptoms, notably attention and executive function issues. The current study aimed to investigate the use of transcranial direct current stimulation (tDCS) on both common anxiety symptoms and executive function abilities in a college aged sample.

METHOD

As this is one of the first large scale anxiety studies utilizing tDCS, participants were given a single session of tDCS (anodal, cathodal, or sham) for 20 min at 2 mA over the left dorsolateral prefrontal cortex (lDLPFC). Participants also completed a series of self-reported anxiety measures and measures of executive functioning (Rey-O Copy and Wisconsin Card Sorting Task).

RESULTS

While there were no differences in anxiety between tDCS groups, a trend was noted demonstrating better performance on Rey-O Copy for the cathodal group. Anxiety increased pre to post for all groups.

CONCLUSION

Overall, results suggest that while anodal stimulation of the lDLPFC may benefit cognitive abilities for this population, targeting psychological symptoms of anxiety likely requires stimulation over other cortex, possibly right DLPFC. Further, the use of tDCS, whether active or sham, may be distressing to patients.

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.

Neurovisceral integration in the executive control network: A resting state analysis

Neurovisceral integration models emphasize the role of frontal lobes in cognitive, behavioral, and emotional regulation. Two candidate hubs for the regulation of cardio-autonomic control, anxiety, and executive attention are the dorsolateral prefrontal cortex (DLPFC) and middle frontal gyrus (MFG). Two-hundred and seventy-one adults (62.9 % female) aged 18-85 years were selected from the NKI-Rockland Sample. Resting state functional imaging data was preprocessed, and seeds extracted from bilateral DLPFC and MFG to test 4 regression models predicting connectivity with high frequency HRV (HF-HRV), trait anxiety (TA), and reaction time on an executive attention task. After controlling for age, sex, body mass index and head motion, the right DLPFC-MFG seed pair provided strongest support for neurovisceral integration indexed by HF-HRV, low TA and shorter reaction time on the attention network task. This hemispheric effect may underlie the inhibitory role of right PFC in the regulation of cardio-autonomic function, emotion, and executive attention.

Anxiety and Stress Alter Decision-Making Dynamics and Causal Amygdala-Dorsolateral Prefrontal Cortex Circuits During Emotion Regulation in Children

BACKGROUND

Anxiety and stress reactivity are risk factors for the development of affective disorders. However, the behavioral and neurocircuit mechanisms that potentiate maladaptive emotion regulation are poorly understood. Neuroimaging studies have implicated the amygdala and dorsolateral prefrontal cortex (DLPFC) in emotion regulation, but how anxiety and stress alter their context-specific causal circuit interactions is not known. Here, we use computational modeling to inform affective pathophysiology, etiology, and neurocircuit targets for early intervention.

METHODS

Forty-five children (10-11 years of age; 25 boys) reappraised aversive stimuli during functional magnetic resonance imaging scanning. Clinical measures of anxiety and stress were acquired for each child. Drift-diffusion modeling of behavioral data and causal circuit analysis of functional magnetic resonance imaging data, with a National Institute of Mental Health Research Domain Criteria approach, were used to characterize latent behavioral and neurocircuit decision-making dynamics driving emotion regulation.

RESULTS

Children successfully reappraised negative responses to aversive stimuli. Drift-diffusion modeling revealed that emotion regulation was characterized by increased initial bias toward positive reactivity during viewing of aversive stimuli and increased drift rate, which captured evidence accumulation during emotion evaluation. Crucially, anxiety and stress reactivity impaired latent behavioral dynamics associated with reappraisal and decision making. Anxiety and stress increased dynamic casual influences from the right amygdala to DLPFC. In contrast, DLPFC, but not amygdala, reactivity was correlated with evidence accumulation and decision making during emotion reappraisal.

CONCLUSIONS

Our findings provide new insights into how anxiety and stress in children impact decision making and amygdala-DLPFC signaling during emotion regulation, and uncover latent behavioral and neurocircuit mechanisms of early risk for psychopathology.

Neuroinflammation-Associated Alterations of the Brain as Potential Neural Biomarkers in Anxiety Disorders

Stress-induced changes in the immune system, which lead to neuroinflammation and consequent brain alterations, have been suggested as possible neurobiological substrates of anxiety disorders, with previous literature predominantly focusing on panic disorder, agoraphobia, and generalized anxiety disorder, among the anxiety disorders. Anxiety disorders have frequently been associated with chronic stress, with chronically stressful situations being reported to precipitate the onset of anxiety disorders. Also, chronic stress has been reported to lead to hypothalamic–pituitary–adrenal axis and autonomic nervous system disruption, which may in turn induce systemic proinflammatory conditions. Preliminary evidence suggests anxiety disorders are also associated with increased inflammation. Systemic inflammation can access the brain, and enhance pro-inflammatory cytokine levels that have been shown to precipitate direct and indirect neurotoxic effects. Prefrontal and limbic structures are widely reported to be influenced by neuroinflammatory conditions. In concordance with these findings, various imaging studies on panic disorder, agoraphobia, and generalized anxiety disorder have reported alterations in structure, function, and connectivity of prefrontal and limbic structures. Further research is needed on the use of inflammatory markers and brain imaging in the early diagnosis of anxiety disorders, along with the possible efficacy of anti-inflammatory interventions on the prevention and treatment of anxiety disorders.

Emotion reactivity-related brain network analysis in generalized anxiety disorder: a task fMRI study

BACKGROUND

Generalized anxiety disorder (GAD) is closely associated with emotional dysregulation. Patients with GAD tend to overreact to emotional stimuli and are impaired in emotional regulation. Using emotional regulation task, studies have found hypo-activation in prefrontal cortex (PFC) of GAD patients and concluded with inadequate top-down control. However, results remain inconsistent concerning PFC and limbic area's reactivity to emotional stimuli. What's more, only a few studies aim to identify how limbic area interacts with PFC in GAD patients. The current study aims to identify the difference in PFC-limbic circuitry response to emotional stimuli between GAD patients and healthy controls (HCs) from the perspective of brain network. Through brain network analysis, it revealed the connectivity between limbic area and PFC, and moreover, the orientation of connectivity, all of which gave a better test of inadequate top-down control hypothesis.

METHODS

During fMRI scanning, participants were required to complete an emotional face identification task (fearful, neutral, happy facial expression). 30 participants (16 GAD patients, 14 HCs) were included in the formal analysis. A Bayesian-network based method was used to identify the brain network consisting of several pre-hypothesized regions of interest (ROIs) under each condition (negative, positive, neutral). In total, six graphs were obtained. Each of them represented the brain network that was common to the group under corresponding condition.

RESULTS

Results revealed that GAD patients showed more bottom-up connection but less top-down connection regardless of condition, relative to HCs. Also, the insula was more connected but the amygdala was less connected regardless of condition, relative to HCs. the results also revealed a very different brain network response between GAD patients and HCs even under neutral condition.

CONCLUSIONS

More bottom-up connection but less top-down connection may indicate that GAD patients are insufficient in top-down control, in keeping with inadequate top-down control hypothesis. The more connected insula may indicate GAD patients' abnormality in interoception processing. Relative to HCs, distinct brain network response pattern in GAD patients under neutral condition suggests GAD patients' abnormality in distinguishing safety from threat and intolerance of uncertainty.

Parsing differences in amygdala volume among individuals with and without social and generalized anxiety disorders across the lifespan

Structural differences in the amygdala (AMG) are implicated in anxiety and observed among individuals with generalized (GAD) and social anxiety (SAD) disorders. Findings have been mixed, perhaps because studies rarely examine differences between GAD and SAD, test comorbidity, or examine age-related differences. We tested AMG volume differences among a sample of adults and youth with/without SAD and GAD. Participants (N = 242; ages 7-60 years) completed an MRI scan, diagnostic interviews, and anxiety symptom measures. Groups were formed from diagnostic interviews: 1) Typically developing (TD; n = 91); 2) GAD (n = 53); 3) SAD (n = 35); and 4) comorbid SAD/GAD (n = 63). We used analysis of covariance with a bonferroni correction to examine group differences in AMG volume. The SAD and comorbid SAD/GAD groups exhibited increased bilateral AMG volume compared to the TD group. GAD and TD groups did not differ from each other in AMG size. The SAD, but not the comorbid SAD/GAD group, displayed greater right AMG size relative to the GAD group. SAD and comorbid SAD/GAD groups did not differ from the GAD group in left AMG volume. SAD and SAD/GAD groups did not exhibit different bilateral AMG size. Linear regression analyses demonstrated that greater social anxiety but not generalized anxiety symptom severity was associated with enlarged AMG volume. Age was not associated with AMG volume and nor did age moderate any group or symptom effects. Future longitudinal studies should examine whether larger AMG volume is a unique biomarker for SAD across the lifespan.

Progressive brain structural alterations assessed via causal analysis in patients with generalized anxiety disorder

Accumulating neuroimaging studies implicate widespread brain structural alterations in patients with generalized anxiety disorder (GAD), but little is known regarding the temporal information of these changes and their causal relationships. In this study, a morphometric analysis was performed on T1-weighted structural images, and the progressive changes in the gray matter volume (GMV) in GAD were simulated by dividing the patients into different groups from low illness duration to high illness duration. The duration was defined as the interval between the onset of GAD and the time for magnetic resonance imaging collection. Then, a causal structural covariance network analysis was conducted to describe the causal relationships of the brain structural alterations in GAD. With increased illness duration, the GMV reduction in GAD originated from the subgenual anterior cingulate cortex (sgACC) and propagated to the bilateral ventromedial prefrontal cortex, right dorsomedial prefrontal cortex, left inferior temporal gyrus, and right insula. Intriguingly, the sgACC and the right insula had positive causal effects on each other. Moreover, both sgACC and right insula exhibited positive causal effects on the parietal cortex and negative effects on the posterior cingulate cortex, dorsolateral prefrontal cortex, visual cortex, and temporal lobe. The opposite causal effects were noted on the somatosensory and the ventrolateral prefrontal cortices. In conclusion, patients with GAD show gradual GMV reduction with increasing ilness duration. Furthermore, the causal effects of the sgACC and the right insula GMV reduction with shifts of duration may provide an important new avenue for understanding the pathological anomalies in GAD.

11β-hydroxysteroid dehydrogenase type 1 inhibitor use in human disease-a systematic review and narrative synthesis

INTRODUCTION

11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) is an intracellular enzyme that catalyses conversion of cortisone into cortisol; correspondingly, 11β-HSD1 inhibitors inhibit this conversion. This systematic review focuses on the use of 11β-HSD1 inhibitors in diseases known to be associated with abnormalities in hypothalamic pituitary adrenal (HPA) axis function.

METHODS

The databases screened for suitable papers were: MedLine, EMBASE, Web of Science, ClinicalTrials.gov, and Cochrane Central.

RESULTS

1925 papers were identified, of which 29 were included in the final narrative synthesis. 11β-HSD1 and its inhibitors have been studied in diabetes, obesity, metabolic syndrome (MetS), and Alzheimer's disease (AD). Higher expression of 11β-HSD1 is seen in obesity and MetS, but has not yet been described in obesity or AD. Genetic studies identify 11β-HSD1 SNPs of interest in populations with diabetes, MetS, and AD. One phase II trial successfully reduced HbA1c in a diabetic population, however trials in MetS, obesity, and AD have not met primary endpoints.

CONCLUSIONS

Translation of this research from preclinical studies has proved challenging so far, however this is a growing area of research and more studies should focus on understanding the complex relationships between 11β-HSD1 and disease pathology, especially given the therapeutic potential of 11β-HSD1 inhibitors in development.

Disrupted dynamic local brain functional connectivity patterns in generalized anxiety disorder

Previous studies have reported abnormalities in static brain activity and connectivity in patients with generalized anxiety disorder (GAD). However, the dynamic patterns of brain connectivity in patients with GAD have not been fully explored. In this study, we aimed to investigate the dynamic local brain functional connectivity in patients with GAD using dynamic regional phase synchrony (DRePS), a newly developed method for assessing intrinsic dynamic local functional connectivity. Seventy-four patients with GAD and 74 healthy controls (HCs) were enrolled and underwent resting-state functional magnetic resonance imaging. Compared to the HCs, patients with GAD exhibited decreased DRePS values in the bilateral caudate, left hippocampus, left anterior insula, left inferior frontal gyrus, and right fusiform gyrus extending to inferior temporal gyrus. The DRePS value of the left hippocampus was negatively correlated with the Hamilton Anxiety Rating Scale scores. Moreover, these abnormal DRePS patterns could be used to distinguish patients with GAD from HCs in an independent sample (18 patients with GAD and 21 HCs). Our findings provide further evidence on brain dysfunction in GAD from the perspective of the dynamic behaviour of local connections, suggesting that patients with GAD may have an insufficient brain adaptation. This study provides new insights into the neurocognitive mechanism of GAD and could potentially inform the diagnosis and treatment of this disease. Future studies on GAD could benefit from combining the DRePS method with task-related functional magnetic resonance imaging and non-invasive brain stimulation.

Prefrontal-amygdala connectivity in trait anxiety and generalized anxiety disorder: Testing the boundaries between healthy and pathological worries

BACKGROUND

Current brain-based theoretical models of generalized anxiety disorder (GAD) suggest a dysfunction of amygdala-ventromedial prefrontal cortex emotional regulatory mechanisms. These alterations might be reflected by an altered resting state functional connectivity between both areas and could extend to vulnerable non-clinical samples such as high worriers without a GAD diagnosis. However, there is a lack of information in this regard.

METHODS

We investigated differences in resting state functional connectivity between the basolateral amygdala and the ventromedial prefrontal cortex (amygdala-vmPFC) in 28 unmedicated participants with GAD, 28 high-worriers and 28 low-worriers. We additionally explored selected clinical variables as predictors of amygdala-vmPFC connectivity, including anxiety sensitivity.

RESULTS

GAD participants presented higher left amygdala-vmPFC connectivity compared to both groups of non-GAD participants, and there were no differences between the latter two groups. In our exploratory analyses, concerns about the cognitive consequences of anxiety (the cognitive dimension of anxiety sensitivity) were found to be a significant predictor of the left amygdala-vmPFC connectivity.

LIMITATIONS

The cross-sectional nature of our study preclude us from assessing if functional connectivity measures and anxiety sensitivity scores entail an increased risk of GAD.

CONCLUSIONS

These results suggest a neurobiological qualitative distinction at the level of the amygdala-vmPFC emotional-regulatory system in GAD compared to non-GAD participants, either high- or low-worriers. At this neural level, they question previous hypotheses of continuity between high worries and GAD development. Instead, other anxiety traits such as anxiety sensitivity might confer a greater proneness to the amygdala-vmPFC connectivity alterations observed in GAD.

Threat bias and resting state functional connectivity of the amygdala and bed nucleus stria terminalis

BACKGROUND

Previous research has distinguished the activations of the amygdala and bed nucleus of stria terminalis (BNST) during threat-related contingencies. However, how intrinsic connectivities of the amygdala and BNST relate to threat bias remains unclear. Here, we investigated how resting state functional connectivity (rsFC) of the amygdala and BNST in healthy controls (HC) and patients with anxiety-related disorders (PAD) associate with threat bias in a dot-probe task.

METHODS

Imaging and behavioral data of 30 PAD and 83 HC were obtained from the Nathan Kline Institute - Rockland sample and processed according to published routines. All imaging results were evaluated at voxel p < 0.001 and cluster p < 0.05, FWE corrected in SPM.

RESULTS

PAD and HC did not show differences in whole brain rsFC with either the amygdala or BNST. In linear regressions threat bias was positively correlated with amygdala-thalamus/anterior cingulate cortex (ACC) rsFC in HC but not PAD, and with BNST-caudate rsFC in PAD but not HC. Slope tests confirmed group differences in the correlations between threat bias and amygdala-thalamus/ACC as well as BNST-caudate rsFC.

LIMITATIONS

As only half of the patients included were diagnosed with comorbid anxiety, the current findings need to be considered with the clinical heterogeneity and require replication in populations specifically with anxiety disorders.

CONCLUSIONS

Together, these results suggest amygdala and BNST connectivities as new neural markers of anxiety disorders. Whereas amygdala-thalamus/ACC rsFC support adaptive regulation of threat response in the HC, BNST-caudate rsFC may reflect maladaptive neural processes that are dominated by anticipatory anxiety.

The salivary-α-amylase level after stroop test in anxious patients can predict the severity of anxiety

Individuals with anxiety disorder often exhibit as imbalance in response to stressors. We sought to explore the relationship between physiological as well as psychological responses under acute mental stress and the severity of the disease. 20 Generalized Anxiety Disorder (GAD) patients (14 males, mean age 46 ± 10 years) were confronted with the stroop test, during which salivary-α-amylase (sAA), salivary cortisol, and heart rate variability (HRV) were assessed. The results showed that stroop test as a stressor induced autonomic nervous response in GAD patients, which was mainly manifested as the increase in HRV representing sympathetic nervous system and the decrease in HRV representing vagal nerve activity. Moreover, the basic function of sympathetic-adrenal medulla system was hyperfunctional in GAD patients while theirs reactivity was limited, which showed the more serious the lesion was, the higher the baseline value of sAA was, and the less sAA secretion increase would be, or even decrease after mental stress. The change of sAA after stroop test in GAD patients can predict the severity of anxiety, but subjective psychological perception can not.

Anxiety Disorders and the Brain's Resting State Networks: From Altered Spatiotemporal Synchronization to Psychopathological Symptoms

Anxiety disorders include a variety of different disorders including panic disorder (PD), social anxiety disorder (SAD), generalized anxiety disorder (GAD), and phobias. We here focus our review on GAD, SAD, and PD and put a specific emphasis on resting state networks and the coupling between the brain and the heart as all anxiety disorders exhibit abnormal perception of their own heartbeat in some way or the other. Resting state functional connectivity (rsFC) studies demonstrate abnormalities in default-mode network (DMN) in all anxiety disorders, e.g., mostly decreases in rsFC of DMN. In contrast, resting state fMRI shows increased rsFC in salience network (SN) (SAD, GAD) and/or somato-motor/sensory network (SMN) (PD). Since rsFC is coherence- or phase-based operating in the infraslow frequency domain (0.01-0.1 Hz), these data suggest spatiotemporal hypo- or hyper-synchronization in DMN and SMN/SN, respectively. These abnormalities in the neural network's spatiotemporal synchronization may, in turn, impact phase-based temporal synchronization of neural and cardiac activities resulting in decreased (DMN) or increased (SMN/SN) neuro-cardiac coupling in anxiety disorders. That, in turn, may be related to the various psychopathological symptoms like unstable sense of self (as based on unstable DMN showing spatiotemporal hypo-synchronization), increased emotions and specifically anxiety (as related to increased SN showing spatiotemporal hyper-synchronization), and increased bodily awareness (mediated by increased SMN with spatiotemporal hyper-synchronization) in anxiety disorders. Taken together, we here suggest altered spatiotemporal synchronization of neural and cardiac activity within the brain's resting state to underlie various psychopathological symptoms in anxiety disorders. Such spatiotemporal basis of psychopathological symptoms is well compatible with the recently suggested "Spatiotemporal Psychopathology."

Systematic review and meta-analyses of neural structural and functional differences in generalized anxiety disorder and healthy controls using magnetic resonance imaging

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PFC-amygdala FC is altered in GAD, indicating top-down processing deficits.

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GAD had reduced activity for emotion regulation and working memory in the culmen.

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Salience, default, and central executive nodes have altered structure and function.

Objective

To compare structure, functional connectivity (FC) and task-based neural differences in subjects with generalized anxiety disorder (GAD) compared to healthy controls (HC).

Methods

The Embase, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched from inception until March 12, 2018. Two reviewers independently screened titles, abstracts, and full-text articles. Data were extracted from records directly contrasting GAD and HC that included structure (connectivity and local indices such as volume, etc.), FC, or task-based magnetic resonance imaging data. Meta-analyses were conducted, as applicable, using AES-SDM software.

Results

The literature search produced 4,645 total records, of which 85 met the inclusion criteria for the systematic review. Records included structural (n = 35), FC (n = 33), and task-based (n = 42) findings. Meta-analyses were conducted on voxel-based morphometry and task-based results.

Discussion

The systematic review confirms and extends findings from previous reviews. Although few whole-brain resting state studies were conducted, key nodes of resting state networks have altered physiology: the hippocampus (default network), ACC and amygdala (salience network), have reduced volume, and the dlPFC (central executive network) and ACC have reduced FC with the amygdala in GAD. Nodes in the sensorimotor network are also altered with greater pre- and postcentral volume, reduced supplementary motor area volume, and reduced FC in anterior and increased FC in posterior cerebellum.

Conclusions

Despite limitations due to sample size, the meta-analyses highly agree with the systematic review and provide evidence of widely distributed neural differences in subjects with GAD, compared to HC. Further research optimized for meta-analyses would greatly improve large-scale comparisons.

When worry may be good for you: Worry severity and limbic-prefrontal functional connectivity in late-life generalized anxiety disorder

BACKGROUND

Late-life generalized anxiety disorder (GAD) is one of the most common anxiety disorders in older adults. However, its neural markers have received relatively little attention. In this study, we explored the association between worry severity and limbic-prefrontal connectivity during emotional reactivity in late-life GAD.

METHODS

We recruited 16 anxious (GAD) and 20 non-anxious (HC) older adults to perform the faces/shapes emotional reactivity task during functional magnetic resonance imaging (fMRI). We investigated the functional connectivity of both the amygdala and the bed nucleus of stria terminalis (BNST) with the prefrontal cortex (PFC) using generalized psychophysiological interaction (gPPI) analysis. We tested for (1) group differences in connectivity, (2) association between worry severity and connectivity, and (3) interaction between group and worry severity and its association with connectivity.

RESULTS

Amygdala-PFC and BNST-PFC functional connectivity were associated with worry severity in an inverse U-shape, and was independent of depression severity, global anxiety, neuroticism, and general cognitive function.

LIMITATIONS

Our limitations include slightly skewed PSWQ distributions, lack of non-anxious individuals with high worry, small sample size, and low depression comorbidity in a sample of late-life GAD that may not generalize to GAD in younger populations.

CONCLUSIONS

This suggests that moderate worry is associated with maximum engagement of the limbic-PFC connectivity, while severe worry is associated with failure of the limbic-PFC emotional regulation circuit. This may explain the aberrant and exaggerated responses to negative stimuli observed in participants with pathological worry.