Functional and morphological alterations associated with working memory dysfunction in patients with generalized anxiety disorder

Identifying modifiable factors and their joint effect on brain health: an exposome-wide association study

Considerable uncertainty remains regarding the associations of multiple factors with brain health. We aimed to conduct an exposome-wide association study on neurodegenerative disease and neuropsychiatry disorders using data of participants from the UK Biobank. Multivariable Cox regression models with the least absolute shrinkage and selection operator technique as well as principal component analyses were used to evaluate the exposures in relation to common disorders of central nervous system (CNS). Restricted cubic splines were conducted to explore potential nonlinear correlations. Then, weighted standardized scores were generated based on the coefficients to calculate the joint effects of risk factors. We also estimated the potential impact of eliminating the unfavorable profiles of risk domains on CNS disorders using population attributable fraction (PAF). Finally, sensitivity analyses were performed to reduce the risk of reverse causality. The current study discovered the significantly associated exposures fell into six primary exposome categories. The joint effects of identified risk factors demonstrated higher risks for common disorders of CNS (HR = 1.278 ~ 3.743, p < 2e-16). The PAF varied by exposome categories, with lifestyle and medical history contributing to majority of disease cases. In total, we estimated that up to 3.7 ~ 64.1% of disease cases could be prevented.This study yielded modifiable variables of different categories and assessed their joint effects on common disorders of CNS. Targeting the identified exposures might help formulate effective strategies for maintaining brain health.

Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis

Anxiety disorders (ADs) are a group of prevalent and destructive mental illnesses, but the current understanding of their underlying neuropathology is still unclear. Employing voxel-based morphometry (VBM), previous studies have demonstrated several common brain regions showing grey matter volume (GMV) abnormalities. However, contradictory results have been reported among these studies. Considering that different subtypes of ADs exhibit common core symptoms despite different diagnostic criteria, and previous meta-analyses have found common core GMV-altered brain regions in ADs, the present research aimed to combine the results of individual studies to identify common GMV abnormalities in ADs. Therefore, we first performed a systematic search in PubMed, Embase, and Web of Science on studies investigating GMV differences between patients with ADs and healthy controls (HCs). Then, the anisotropic effect-size signed differential mapping (AES-SDM) was applied in this meta-analysis. A total of 24 studies (including 25 data sets) were included in the current study, and 906 patients with ADs and 1003 HCs were included. Compared with the HCs, the patients with ADs showed increased GMV in the left superior parietal gyrus, right angular gyrus, left precentral gyrus, and right lingual gyrus, and decreased GMV in the bilateral insula, bilateral thalamus, left caudate, and right putamen. In conclusion, the current study has identified some abnormal GMV brain regions that are related to the pathological mechanisms of anxiety disorders. These findings could contribute to a better understanding of the underlying neuropathology of ADs.

The role of dlPFC laterality in the expression and regulation of anxiety

Anxiety disorders are the most common mental health disorder. Therefore, elucidating brain mechanisms implicated in anxiety disorders is important avenue for developing novel treatments and improving care. The dorsolateral prefrontal cortex (dlPFC) is thought to be critically involved in working memory processes (i.e. maintenance, manipulation, suppression, etc.). In addition, there is evidence that this region is involved in anxiety regulation. However, it is unclear how working memory related dlPFC processes contribute to anxiety regulation. Furthermore, we know that laterality plays an important role in working memory related dlPFC processing, however there is no current model of dlPFC mediated anxiety regulation that accounts for potential laterality effects. To address this gap, we propose a potential framework where the dlPFC contributes to emotion regulation via working memory processing. According to this framework, working memory is a fundamental process executed by the dlPFC. However, the domain of content differs across the left and right dlPFC, with the left dlPFC sensitive to primarily verbal content, and the right dlPFC sensitive to primarily non-verbal (affective content). Critically, working memory processes allow for both the retention and suppression of affective information in working memory and the overall net effect of processing on mood will depend on the balance of retention and suppression, the valence of the information being processed (positive vs. negative), and the domain of the information (verbal vs. non-verbal). If accurate, the proposed framework predicts that effects of neuromodulation targeting the dlPFC may be dependent upon the context during which the stimulation is presented. This article is part of the Special Issue on 'Fear, Anxiety and PTSD'.

Decreased default mode network functional connectivity with visual processing regions as potential biomarkers for delayed neurocognitive recovery: A resting-state fMRI study and machine-learning analysis

Objectives

The abnormal functional connectivity (FC) pattern of default mode network (DMN) may be key markers for early identification of various cognitive disorders. However, the whole-brain FC changes of DMN in delayed neurocognitive recovery (DNR) are still unclear. Our study was aimed at exploring the whole-brain FC patterns of all regions in DMN and the potential features as biomarkers for the prediction of DNR using machine-learning algorithms.

Methods

Resting-state functional magnetic resonance imaging (fMRI) was conducted before surgery on 74 patients undergoing non-cardiac surgery. Seed-based whole-brain FC with 18 core regions located in the DMN was performed, and FC features that were statistically different between the DNR and non-DNR patients after false discovery correction were extracted. Afterward, based on the extracted FC features, machine-learning algorithms such as support vector machine, logistic regression, decision tree, and random forest were established to recognize DNR. The machine learning experiment procedure mainly included three following steps: feature standardization, parameter adjustment, and performance comparison. Finally, independent testing was conducted to validate the established prediction model. The algorithm performance was evaluated by a permutation test.

Results

We found significantly decreased DMN connectivity with the brain regions involved in visual processing in DNR patients than in non-DNR patients. The best result was obtained from the random forest algorithm based on the 20 decision trees (estimators). The random forest model achieved the accuracy, sensitivity, and specificity of 84.0, 63.1, and 89.5%, respectively. The area under the receiver operating characteristic curve of the classifier reached 86.4%. The feature that contributed the most to the random forest model was the FC between the left retrosplenial cortex/posterior cingulate cortex and left precuneus.

Conclusion

The decreased FC of DMN with regions involved in visual processing might be effective markers for the prediction of DNR and could provide new insights into the neural mechanisms of DNR.

Clinical Trial Registration

: Chinese Clinical Trial Registry, ChiCTR-DCD-15006096.

Muscle strength and incidence of depression and anxiety: findings from the UK Biobank prospective cohort study

BACKGROUND

Depression and anxiety are the leading mental health problems worldwide; depression is ranked as the leading cause of global disability with anxiety disorders ranked sixth. Preventive strategies based on the identification of modifiable factors merit exploration. The aim of the present study was to investigate the associations of handgrip strength (HGS) with incident depression and anxiety and to explore how these associations differ by socio-demographic, lifestyle, and health-related factors.

METHODS

The analytic sample comprised 162 167 participants (55% women), aged 38-70 years, from the UK Biobank prospective cohort study. HGS was assessed at baseline using dynamometry. Depression and anxiety were extracted from primary care and hospital admission records. Cox proportional models were applied, with a 2 year landmark analysis, to investigate the associations between HGS and incident depression and anxiety.

RESULTS

Of the 162 167 participants included, 5462 (3.4%) developed depression and 6614 (4.1%) anxiety, over a median follow-up period of 10.0 years (inter-quartile range: 9.3-10.8) for depression and 9.9 (inter-quartile range: 9.0-10.8) for anxiety. In the fully adjusted model, a 5 kg lower HGS was associated with a 7% (HR: 1.07 [95% CI: 1.05, 1.10]; P < 0.001) and 8% (HR: 1.08 [95% CI: 1.06, 1.10]; P < 0.001) higher risk of depression and anxiety, respectively. Compared with participants in the sex and age-specific highest tertiles of HGS, those in the medium and lowest tertiles had an 11% (HR: 1.11 [95% CI: 1.04, 1.19]; P = 0.002) and 24% (HR: 1.24 [95% CI: 1.16, 1.33]; P < 0.001) higher risk of depression and 13% (HR: 1.13 [95% CI: 1.06, 1.20]; P < 0.001) and 27% (HR: 1.27 [95% CI: 1.19, 1.35]; P < 0.001) higher risk of anxiety, respectively. The association of HGS with depression was stronger among participants with average or brisk walking pace (vs. slow walking pace; P_interaction  < 0.001). The association with anxiety was stronger in those participants aged ≥58 years (vs. ≤58 years; P_interaction  = 0.002) and those living in more affluent areas (vs. deprived; P_interaction  = 0.001).

CONCLUSIONS

Handgrip strength was inversely associated with incident depression and anxiety. Because HGS is a simple, non-invasive, and inexpensive measure, it could be easily used in clinical practice to stratify patients and identify those at elevated risk of mental health problems. However, future research should assess if resistance training aimed at increasing HGS can prevent the occurrence of mental health conditions.

Disorder- and cognitive demand-specific neurofunctional alterations during social emotional working memory in generalized anxiety disorder and major depressive disorder

BACKGROUND

Generalized Anxiety Disorder (GAD) and Major Depressive Disorder (MDD) are both characterized by cognitive and social impairments. Determining disorder-specific neurobiological alterations in GAD and MDD by means of functional magnetic resonance imaging (fMRI) may promote determination of precise diagnostic markers.

METHODS

This study aimed to examine disorder-specific behavioral and neural alterations at the intersection of social and cognitive processing in treatment-naïve first-episode GAD (n = 35) and MDD (n = 37) patients compared to healthy controls (n = 35) by employing a social-emotional n-back fMRI paradigm.

RESULTS

No behavioral differences between patients and healthy controls were observed. However, GAD patients exhibited decreased bilateral dorsomedial prefrontal cortex (dmPFC) engagement during the 0-back condition yet increased dmPFC engagement during the 1-back condition compared to MDD and healthy participants. In contrast, MDD patients exhibited increased dmPFC-insula coupling during 0-back, yet decreased coupling during 1-back, compared to GAD and healthy participants. Dimensional symptom-load analysis confirmed that increased dmPFC-insula connectivity during 0-back was positively associated with depressive symptom load.

LIMITATIONS

The moderate sample size in the present study did not allow us to further explore gender differences. In addition, some patients exhibited GAD and MDD comorbidity according to the M.I.N.I. interview. Finally, the paradigm we used did not allow to further disentangle emotion-specific effects on working memory.

CONCLUSIONS

These findings suggest that the dmPFC engaged in integrating affective and cognitive components and self-other processing exhibits GAD-specific neurofunctional dysregulations whereas functional dmPFC communication with the insula, a region involved in salience processing, may represent an MDD-specific neurofunctional deficit.

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.

Predicting Delayed Neurocognitive Recovery After Non-cardiac Surgery Using Resting-State Brain Network Patterns Combined With Machine Learning

Delayed neurocognitive recovery (DNR) is a common subtype of postoperative neurocognitive disorders. An objective approach for identifying subjects at high risk of DNR is yet lacking. The present study aimed to predict DNR using the machine learning method based on multiple cognitive-related brain network features. A total of 74 elderly patients (≥ 60-years-old) undergoing non-cardiac surgery were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) before the surgery. Seed-based whole-brain functional connectivity (FC) was analyzed with 18 regions of interest (ROIs) located in the default mode network (DMN), limbic network, salience network (SN), and central executive network (CEN). Multiple machine learning models (support vector machine, decision tree, and random forest) were constructed to recognize the DNR based on FC network features. The experiment has three parts, including performance comparison, feature screening, and parameter adjustment. Then, the model with the best predictive efficacy for DNR was identified. Finally, independent testing was conducted to validate the established predictive model. Compared to the non-DNR group, the DNR group exhibited aberrant whole-brain FC in seven ROIs, including the right posterior cingulate cortex, right medial prefrontal cortex, and left lateral parietal cortex in the DMN, the right insula in the SN, the left anterior prefrontal cortex in the CEN, and the left ventral hippocampus and left amygdala in the limbic network. The machine learning experimental results identified a random forest model combined with FC features of DMN and CEN as the best prediction model. The area under the curve was 0.958 (accuracy = 0.935, precision = 0.899, recall = 0.900, F1 = 0.890) on the test set. Thus, the current study indicated that the random forest machine learning model based on rs-FC features of DMN and CEN predicts the DNR following non-cardiac surgery, which could be beneficial to the early prevention of DNR. Clinical Trial Registration: The study was registered at the Chinese Clinical Trial Registry (Identification number: ChiCTR-DCD-15006096).

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.

Multi-Order Brain Functional Connectivity Network-Based Machine Learning Method for Recognition of Delayed Neurocognitive Recovery in Older Adults Undergoing Non-cardiac Surgery

Objectives: Delayed neurocognitive recovery (DNR) seriously affects the post-operative recovery of elderly surgical patients, but there is still a lack of effective methods to recognize high-risk patients with DNR. This study proposed a machine learning method based on a multi-order brain functional connectivity (FC) network to recognize DNR.

Method: Seventy-four patients who completed assessments were included in this study, in which 16/74 (21.6%) had DNR following surgery. Based on resting-state functional magnetic resonance imaging (rs-fMRI), we first constructed low-order FC networks of 90 brain regions by calculating the correlation of brain region signal changing in the time dimension. Then, we established high-order FC networks by calculating correlations among each pair of brain regions. Afterward, we built sparse representation-based machine learning model to recognize DNR on the extracted multi-order FC network features. Finally, an independent testing was conducted to validate the established recognition model.

Results: Three hundred ninety features of FC networks were finally extracted to identify DNR. After performing the independent-sample T test between these features and the categories, 15 features showed statistical differences (P < 0.05) and 3 features had significant statistical differences (P < 0.01). By comparing DNR and non-DNR patients’ brain region connection matrices, it is found that there are more connections among brain regions in DNR patients than in non-DNR patients. For the machine learning recognition model based on multi-feature combination, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the classifier reached 95.61, 92.00, 66.67, and 100.00%, respectively.

Conclusion: This study not only reveals the significance of preoperative rs-fMRI in recognizing post-operative DNR in elderly patients but also establishes a promising machine learning method to recognize DNR.

Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder

Generalized anxiety disorder (GAD) is marked by uncontrollable, persistent worry and exaggerated response to uncertainty. Here, we review and summarize the findings from the GAD literature that employs functional neuroimaging methods. In particular, the present review focuses on task-based blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. We find that select brain regions often regarded as a part of a corticolimbic circuit (e.g., amygdala, anterior cingulate cortex, prefrontal cortex) are consistently targeted for a priori hypothesis-driven analyses, which, in turn, shows varying degrees of abnormal BOLD responsivity in GAD. Data-driven whole-brain analyses show the insula and the hippocampus, among other regions, to be affected by GAD, depending on the task used in each individual study. Overall, while the heterogeneity of the tasks and sample size limits the generalizability of the findings thus far, some promising convergence can be observed in the form of the altered BOLD responsivity of the corticolimbic circuitry in GAD.

Patients with anxiety disorders rely on bilateral dlPFC activation during verbal working memory

One of the hallmarks of anxiety disorders is impaired cognitive control, affecting working memory (WM). The dorsolateral prefrontal cortex (dlPFC) is critical for WM; however, it is still unclear how dlPFC activity relates to WM impairments in patients. Forty-one healthy volunteers and 32 anxiety (general and/or social anxiety disorder) patients completed the Sternberg WM paradigm during safety and unpredictable shock threat. On each trial, a series of letters was presented, followed by brief retention and response intervals. On low- and high-load trials, subjects retained the series (five and eight letters, respectively) in the original order, while on sort trials, subjects rearranged the series (five letters) in alphabetical order. We sampled the blood oxygenation level-dependent activity during retention using a bilateral anatomical dlPFC mask. Compared to controls, patients showed increased reaction time during high-load trials, greater right dlPFC activity and reduced dlPFC activity during threat. These results suggest that WM performance for patients and controls may rely on distinct patterns of dlPFC activity with patients requiring bilateral dlPFC activity. These results are consistent with reduced efficiency of WM in anxiety patients. This reduced efficiency may be due to an inefficient allocation of dlPFC resources across hemispheres or a decreased overall dlPFC capacity.

Altered resting-state fMRI signals and network topological properties of bipolar depression patients with anxiety symptoms

BACKGROUND

This study aims to explore the changes in functional neuroimaging in bipolar depression patients with anxiety symptoms (BDP-A).

METHODS

Forty-five BDP-A patients, 22 bipolar depression patients without anxiety symptoms (BDP-NA), and 48 healthy controls (HC) were finally involved. The low-frequency oscillation characteristics, functional connectivity (FC), and network properties among the three groups of participants were analyzed.

RESULTS

Compared with the BDP-NA group, BDP-A patients exhibited significantly decreased amplitude of low-frequency fluctuation (ALFF) in the left middle frontal gyrus (MFG), superior occipital gyrus, and inferior parietal, but supramarginal and angular gyri (IPL). Enhanced FC from left IPL to middle temporal gyrus, from left precentral gyrus (PreCG) to bilateral angular gyri, medial superior frontal gyrus, and left superior frontal gyrus (SFG)/MFG were also revealed. Compared with HC, the BDP-A group showed remarkably increased ALFF in the left MFG/PreCG, right superior parietal gyrus, while decreased ALFF in the left inferior frontal gyrus, opercular part, and SFG. In addition, higher regional homogeneity in the left MFG/PreCG was found.

LIMITATIONS

The limitations are as follows: (1) relatively small sample size; (2) not all the patients were drug-naive; (3) lack of pure anxiety disorder patients as a controlled group; (4) mental health conditions of HC were not systemic evaluated.

CONCLUSIONS

BDP-A patients showed significant differences in resting-state fMRI properties when compared with BDP-NA or HC group. These results may infer the dysfunction of the dorsal attention network, the default network, and the fronto-limbic system as well as disrupted brain network efficiency in BDP-A patients.

Altered Cerebellar-Cerebral Circuits in Patients With Type 2 Diabetes Mellitus

The role of the cerebellum in type 2 diabetes mellitus (T2DM) has been receiving increased attention. However, the functional connectivity (FC) between the cerebellar subregions and the cerebral cortex has not been investigated in T2DM. Therefore, the purpose of this study was to investigate cerebellar-cerebral FC and the relationship between FC and clinical/cognitive variables in patients with T2DM. A total of 34 patients with T2DM and 30 healthy controls were recruited for this study to receive a neuropsychological assessment and undergo resting-state FC. We selected four subregions of the cerebellum (bilateral lobules IX, right and left Crus I/II, and left lobule VI) as regions of interest (ROIs) to examine the differences in cerebellar-cerebral circuits in patients with T2DM compared to healthy controls. Correlation analysis was performed to examine the relationship between FC and clinical/cognitive variables in the patients. Compared to healthy controls, patients with T2DM showed significantly decreased cerebellar-cerebral FC in the default-mode network (DMN), executive control network (ECN), and visuospatial network (VSN). In the T2DM group, the FC between the left cerebellar lobule VI and the right precuneus was negatively correlated with the Trail Making Test A (TMT-A) score (r = −0.430, P = 0.013), after a Bonferroni correction. In conclusion, patients with T2DM have altered FC between the cerebellar subregions and the cerebral networks involved in cognitive and emotional processing. This suggests that a range of cerebellar-cerebral circuits may be involved in the neuropathology of T2DM cognitive dysfunction.

Preoperative Altered Spontaneous Brain Activity and Functional Connectivity Were Independent Risk Factors for Delayed Neurocognitive Recovery in Older Adults Undergoing Noncardiac Surgery

Objectives

Recently, it has been demonstrated that patients with subtle preexisting cognitive impairment were susceptible to delayed neurocognitive recovery (DNR). This present study investigated whether preoperative alterations in gray matter volume, spontaneous activity, or functional connectivity (FC) were associated with DNR.

Methods

This was a nested case-control study of older adults (≥60 years) undergoing noncardiac surgery. All patients received MRI scan at least 1 day prior to surgery. Cognitive function was assessed prior to surgery and at 7-14 days postsurgery. Preoperative gray matter volume, amplitude of low-frequency fluctuation (ALFF), and FC were compared between the DNR patients and non-DNR patients. The independent risk factors associated with DNR were identified using a multivariate logistic regression model.

Results

Of the 74 patients who completed assessments, 16/74 (21.6%) had DNR following surgery. There were no differences in gray matter volume between the two groups. However, the DNR patients exhibited higher preoperative ALFF in the bilateral middle cingulate cortex (MCC) and left fusiform gyrus and lower preoperative FC between the bilateral MCC and left calcarine than the non-DNR patients. The multivariate logistic regression analysis showed that higher preoperative spontaneous activity in the bilateral MCC was independently associated with a higher risk of DNR (OR = 3.11, 95% CI, 1.30-7.45; P = 0.011). A longer education duration (OR = 0.57, 95% CI, 0.41-0.81; P = 0.001) and higher preoperative FC between the bilateral MCC and left calcarine (OR = 0.40, 95% CI, 0.18-0.92; P = 0.031) were independently correlated with a lower risk of DNR.

Conclusions

Preoperative higher ALFF in the bilateral MCC and lower FC between the bilateral MCC and left calcarine were independently associated with the occurrence of DNR. The present fMRI study identified possible preoperative neuroimaging risk factors for DNR. This trial is registered with Chinese Clinical Trial Registry ChiCTR-DCD-15006096.

The anterior limb of the internal capsule: Anatomy, function, and dysfunction

The last two decades have seen a re-emergence of neurosurgery for severe, refractory psychiatric diseases, largely due to the advent of more precise and safe operative techniques. Nevertheless, the optimal targets for these surgeries remain a matter of debate, and are often grandfathered from experiences in the late 20th century. To better explore the rationale for one target in particular - the anterior limb of the internal capsule (ALIC) - we comprehensively reviewed all available literature on its role in the pathophysiology and treatment of mental illness. We first provide an overview of its functional anatomy, followed by a discussion on its role in several prevalent psychiatric diseases. Given its structural integration into the limbic system and involvement in a number of cognitive and emotional processes, the ALIC is a robust target for surgical treatment of refractory psychiatric diseases. The advent of novel neuroimaging techniques, coupled with image-guided therapeutics and neuromodulatory treatments, will continue to enable study on the ALIC in mental illness.

Altered heartbeat perception sensitivity associated with brain structural alterations in generalised anxiety disorder

Background

Palpitation is a common complaint in generalised anxiety disorder (GAD). Brain imaging studies have investigated the neural mechanism of heartbeat perception in healthy volunteers. This study explored the neuroanatomical differences of altered heartbeat perception in patients with GAD using structural MRI.

Aims

Based on the strong somatic-interoceptive symptoms in GAD, we explored the regional structural brain abnormalities involved in heartbeat perception in patients with GAD.

Methods

This study was applied to the a priori regions using neuroanatomical theories of heartbeat perception, including the insula, anterior cingulate cortex, supplementary motor area and prefrontal cortex. A total of 19 patients with GAD and 19 healthy control subjects were enrolled. We used the FMRIB Software Library voxel-based morphometry software for estimating the grey matter volume of these regions of interest and analysed the correlation between heartbeat perception sensitivity and the volume of abnormal grey matter.

Results

Patients with GAD showed a significantly decreased volume of grey matter in their left medial prefrontal cortex, right orbital frontal cortex and anterior cingulate cortex. The grey matter volume of the left medial prefrontal cortex negatively correlated with heartbeat perception sensitivity in patients with GAD.

Conclusions

It should be the first study that shows heartbeat perception is associated with brain structure in GAD. Our findings suggest that the frontal region may play an important role in aberrant heartbeat perception processing in patients with GAD, and this may be an underlying mechanism resulting in the abnormal cardiovascular complaints in GAD. This is hypothesised as a ‘top-down’ deficiency, especially in the medial prefrontal cortex. This will provide the foundation for a more targeted region for neuromodulation intervention in the future.

Cerebral functional abnormalities in patients with nasopharyngeal carcinoma after radiotherapy: an observational magnetic resonance resting-state study

BACKGROUND

Nasopharyngeal carcinoma (NPC) is sensitive to radiotherapy (RT). However, neurocognitive complications such as memory loss and learning and attention deficits emerge in the survivors of NPC who received RT. It remains unclear how radiation affects patient brain function. This pilot study aimed at finding cerebral functional alterations in NPC patients who have received RT.

METHODS

From September 2014 to December 2016, 42 individuals, including 22 NPC patients and 20 normal volunteer controls in National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, were recruited in this study. All patients received resting-state functional magnetic resonance imaging scans and neurocognitive tests 1 day before the initiation of RT (baseline) and 1 day after the completion of RT; the 20 normal controls were also subjected to the same scans and tests. The amplitude of the low-frequency fluctuations (ALFF) in blood oxygen level-dependent signals and functional connectivity (FC) were used to characterize cerebral functional changes. Independent t test, paired t test, and analysis of variances were used to obtain statistical significance across groups.

RESULTS

After RT, NPC patients showed significantly decreased ALFF values in the calcarine sulcus, lingual gyrus, cuneus, and superior occipital gyrus and showed significantly reduced FC mainly in the default mode network (P < 0.05, corrected by AlphaSim). Relative to the controls, ALFF was decreased in the lingual gyrus, calcarine sulcus, cingulate cortex, medial prefrontal gyrus (P < 0.05, corrected by AlphaSim), and FC reduction was found in multiple cerebellar-cerebral regions, including the cerebellum, parahippocampus, hippocampus, fusiform gyrus, inferior frontal gyrus, inferior occipital gyrus, precuneus, and cingulate cortex (P < 0.001, corrected by AlphaSim).

CONCLUSIONS

Cerebral functional alterations occur immediately after RT. This study may provide an explanation for the cognitive deficits in the morphologically normal-appearing brains of NPC patients after RT and may contribute to the understanding of the complex mechanism of RT.

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

•

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

•

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

•

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.

A review of neuroimaging studies in generalized anxiety disorder: "So where do we stand?"

Generalized anxiety disorder (GAD) is a prevalent anxiety disorder, but is still poorly recognized in clinical practice. The aim of this review is to provide a coherent understanding of the functional neuroanatomy of GAD; second, to discuss the current theoretical cognitive models surrounding GAD; and finally to discuss the discrepancy between fundamental research and clinical practice and highlight several potential directions for future research in this domain. A systematic review of original papers investigating the neural correlates of DSM-IV and DSM-5 defined GAD samples was undertaken in Ovid literature search, PubMed, Medline, EMbase, PsycINFO, Google Scholar, and TRIP databases. Articles published between 2007 and 2018 were included. First, GAD seems to be characterized by limbic and (pre)frontal abnormalities. More specifically, GAD patients show difficulties in engaging the prefrontal cortex (PFC) and anterior cingulate cortex (ACC) during emotional regulation tasks. Second, the involved brain areas appear to be characterized by heterogeneity possibly due to a variety of experimental designs and test subjects. Third, regarding the discrimination between GAD and other anxiety disorders via fMRI, results appear to be mixed. Studies report both GAD-specific activity and an inability to differentiate between GAD and other anxiety or mood disorders. The usage of different experimental tasks, test subjects, outcome measures and experimental designs limits the possibilities of generalizing results as well as conducting meta-analytical research. Certain theoretical models of GAD describe our understanding of this disorder and form the basis for treatment interventions. However, fMRI research thus far has failed to validate these models. To bridge the gap between fundamental research and clinical practice in GAD, we propose that fMRI researchers make an effort to validate the existing cognitive model of GAD. An alternative approach could be that new models would be based on current neuroimaging research as well as convergent research methods such as Heart Rate Variability (a bottom up approach).

Structural and functional neuroimaging studies in generalized anxiety disorder: a systematic review

OBJECTIVES

Brain imaging studies carried out in patients suffering from generalized anxiety disorder (GAD) have contributed to better characterize the pathophysiological mechanisms underlying this disorder. The present study reviews the available functional and structural brain imaging evidence on GAD, and suggests further strategies for investigations in this field.

METHODS

A systematic literature review was performed in PubMed, PsycINFO, and Google Scholar, aiming to identify original research evaluating GAD patients with the use of structural and functional magnetic resonance imaging as well as diffusion tensor imaging.

RESULTS

The available studies have shown impairments in ventrolateral and dorsolateral prefrontal cortex, anterior cingulate, posterior parietal regions, and amygdala in both pediatric and adult GAD patients, mostly in the right hemisphere. However, the literature is often tentative, given that most studies have employed small samples and included patients with comorbidities or in current use of various medications. Finally, different methodological aspects, such as the type of imaging equipment used, also complicate the generalizability of the findings.

CONCLUSIONS

Longitudinal neuroimaging studies with larger samples of both juvenile and adult GAD patients, as well as at risk individuals and unaffected relatives, should be carried out in order to shed light on the specific biological signature of GAD.