Gray matter volume alterations in de novo Parkinson's disease: A mediational role in the interplay between sleep quality and anxiety.

OBJECTIVE: Parkinson's disease (PD) is increasingly recognized for its non-motor symptoms, among which emotional disturbances and sleep disorders frequently co-occur. The commonality of neuroanatomical underpinnings for these symptoms is not fully understood. This study is intended to investigate the differences in gray matter volume (GMV) between PD patients with anxiety (A-PD) and those without anxiety (NA-PD). Additionally, it seeks to uncover the interplay between GMV variations and the manifestations of anxiety and sleep quality. METHODS: A total of 37 A-PD patients, 43 NA-PD patients, and 36 healthy controls (HCs) were recruited, all of whom underwent voxel-based morphometry (VBM) analysis. Group differences in GMV were assessed using analysis of covariance (ANCOVA). Partial correlation between GMV, anxiety symptom, and sleep quality were analyzed. Mediation analysis explored the mediating role of the volume of GMV-distinct brain regions on the relationship between sleep quality and anxiety within the PD patient cohort. RESULTS: A-PD patients showed significantly lower GMV in the fusiform gyrus (FG) and right inferior temporal gyrus (ITG) compared to HCs and NA-PD patients. GMV in these regions correlated negatively with Hamilton Anxiety Rating Scale (HAMA) scores (right ITG: r = -0.690, p < 0.001; left FG: r = -0.509, p < 0.001; right FG: r = -0.576, p < 0.001) and positively with sleep quality in PD patients (right ITG: r = 0.592, p < 0.001; left FG: r = 0.356, p = 0.001; right FG: r = 0.470, p < 0.001). Mediation analysis revealed that GMV in the FG and right ITG mediated the relationship between sleep quality and anxiety symptoms, with substantial effect sizes accounted for by the right ITG (25.74%) and FG (left: 11.90%, right: 15.59%). CONCLUSION: This study has shed further light on the relationship between sleep disturbances and anxiety symptoms in PD patients. Given the pivotal roles of the FG and the ITG in facial recognition and the recognition of emotion-related facial expressions, our findings indicate that compromised sleep quality, under the pathological conditions of PD, may exacerbate the reduction in GMV within these regions, impairing the recognition of emotional facial expressions and thereby intensifying anxiety symptoms.

Sex and mental health are related to subcortical brain microstructure.

Some mental health problems such as depression and anxiety are more common in females, while others such as autism and attention deficit/hyperactivity (AD/H) are more common in males. However, the neurobiological origins of these sex differences are poorly understood. Animal studies have shown substantial sex differences in neuronal and glial cell structure, while human brain imaging studies have shown only small differences, which largely reflect overall body and brain size. Advanced diffusion MRI techniques can be used to examine intracellular, extracellular, and free water signal contributions and provide unique insights into microscopic cellular structure. However, the extent to which sex differences exist in these metrics of subcortical gray matter structures implicated in psychiatric disorders is not known. Here, we show large sex-related differences in microstructure in subcortical regions, including the hippocampus, thalamus, and nucleus accumbens in a large sample of young adults. Unlike conventional T1-weighted structural imaging, large sex differences remained after adjustment for age and brain volume. Further, diffusion metrics in the thalamus and amygdala were associated with depression, anxiety, AD/H, and antisocial personality problems. Diffusion MRI may provide mechanistic insights into the origin of sex differences in behavior and mental health over the life course and help to bridge the gap between findings from experimental, epidemiological, and clinical mental health research.

Exercise habits and mental health: Exploring the significance of multimodal imaging markers.

Engaging in regular physical activity and establishing exercise habits is known to have multifaceted benefits extending beyond physical health to cognitive and mental well-being. This study explores the intricate relationship between exercise habits, brain imaging markers, and mental health outcomes. While extensive evidence supports the positive impact of exercise on cognitive functions and mental health, recent advancements in multimodal imaging techniques provide a new dimension to this exploration. By using a cross-sectional multimodal brain-behavior statistic in participants with different exercise habits, we aim to unveil the intricate mechanisms underlying exercise's influence on cognition and mental health, including the status of depression, anxiety, and quality of life. This integration of exercise science and imaging promises to substantiate cognitive benefits on mental health and uncover functional and structural changes underpinning these effects. This study embarks on a journey to explore the significance of multimodal imaging metrics (i.e., structural and functional metrics) in deciphering the intricate interplay between exercise habits and mental health, enhancing the comprehension of how exercise profoundly shapes psychological well-being. Our analysis of group comparisons uncovered a strong association between regular exercise habits and improved mental well-being, encompassing factors such as depression, anxiety levels, and overall life satisfaction. Additionally, individuals who engaged in exercise displayed enhanced brain metrics across different modalities. These metrics encompassed greater gray matter volume within the left frontal regions and hippocampus, improved white matter integrity in the frontal-occipital fasciculus, as well as more robust functional network configurations in the anterior segments of the default mode network. The interplay between exercise habits, brain adaptations, and mental health outcomes underscores the pivotal role of an active lifestyle in nurturing a resilient and high-functioning brain, thus paving the way for tailored interventions and improved well-being.

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.

Susceptibility or resilience to childhood peer abuse can be explained by cortical thickness in brain regions involved in emotional regulation.

Experiencing peer abuse in childhood can damage mental health, but some people exhibit resilience against these negative outcomes. However, it remains uncertain which specific changes in brain structures are associated with this type of resilience. We categorized 217 participants into three groups: resilience group, susceptibility group, and healthy control group, based on their experiences of peer abuse and mental health problems. They underwent MRI scans to measure cortical thickness in various brain regions of the prefrontal cortex. We employed covariance analysis to compare cortical thickness among these groups. Individuals who resilient to anxiety exhibited smaller cortical thickness in the bilateral inferior frontal gyrus (IFG), and with larger thickness in the right medial orbitofrontal cortex (mOFC), while those resilient to stress was associated with smaller thickness in both the bilateral IFG and bilateral middle frontal gyrus (MFG). These findings deepen our understanding of the neural mechanisms underlying resilience and offer insight into improving individual resilience.

Mediating role of right superior corona microstructural changes in linking attentional control and trait anxiety among youth with childhood maltreatment.

This study explores the neural correlates between attentional control and trait anxiety among youth with a history of childhood maltreatment. Using diffusion tensor imaging, we investigated the microstructural integrity of brain white matter, particularly focusing on the right superior corona radiata (SCA-R). A total of 173 university students with experiences of childhood maltreatment underwent behavioral assessments using the Attentional Control Scale and trait anxiety measurements via the Spielberger State-Trait Anxiety Inventory. Our analysis found significant correlations between fractional anisotropy values in the SCA-R and trait anxiety levels, controlled for age and sex. Notably, SCA-R fractional anisotropy values partially mediated the relationship between attentional control and trait anxiety, suggesting a potential pathway through which attentional control could mitigate trait anxiety. These insights highlight attentional control as a potential mitigating factor against trait anxiety, particularly noting the partial mediation role of the SCA-R. Importantly, this study is descriptive and correlative, highlighting associations rather than causal relationships among the variables studied. These findings enhance our understanding of the neural mechanisms underlying anxiety in individuals with a history of childhood maltreatment.

Computed tomography myocardial perfusion imaging to detect myocardial ischemia in patients with anxiety and obstructive coronary heart disease post-exposure to mental stressors.

This study aims to measure myocardial blood flow (MBF) using dynamic CT- myocardial perfusion imaging (CT-MPI) combined with mental stressors in patients with obstructive coronary artery disease (OCAD) and in patients with anxiety and no obstructive coronary artery disease (ANOCAD). A total of 30 patients with OCAD with 30 patients with ANOCAD were included in this analysis. Using the 17-segment model, the rest and stress phase MBF of major coronary arteries in participants were recorded respectively. Compared with ANOCAD patients, OCAD patients were more likely to have localized reduction of MBF (p < 0.05). For patients with ANOCAD, both global MBF and MBF of the main coronary arteries in the stress phase were lower than those in the rest phase (all p < 0.05), but there was no significant difference in MBF among the main coronary arteries in the rest or stress phase (p = 0.25, p = 0.15). For patients with OCAD, the MBF of the target area was lower than that of the non-target area in both the rest and stress phase, and the MBF of the target area in the stress phase was lower than that in the rest phase (all p < 0.05). However, there was no significant difference in MBF between the rest or stress phase in the non-target area (p = 0.73). Under mental stress, the decrease in MBF in ANOCAD patients was diffuse, while the decrease in MBF in OCAD patients was localized. Dynamic CT-MPI combined with mental stressors can be used to detect MBF changes in anxiety patients.

Understanding Anxiety in Cervical Dystonia: An Imaging Study.

BACKGROUND: Anxiety may precede motor symptoms in cervical dystonia (CD) and is associated with an earlier onset of dystonia. Our understanding of anxiety in CD is inadequate. OBJECTIVE: To investigate brain networks associated with anxiety in CD. METHODS: Twenty-six subjects with idiopathic CD underwent MRI Brain without contrast. Correlational tractography was derived using Diffusion MRI connectometry. Quantitative Anisotropy (QA) was used in deterministic diffusion fiber tracking. Correlational tractography was then used to correlate QA with State-Trait Anxiety Inventory (STAI) state (STAI-S) and trait (STAI-T) subscales. RESULTS: Connectometry analysis showed direct correlation between state anxiety and QA in tracts from amygdala to thalamus/ pulvinar bilaterally, and trait anxiety and QA in tracts from amygdala to motor cortex, sensorimotor cortex and parietal association area bilaterally (FDR ≤0.05). CONCLUSION: Our efforts to map anxiety to brain networks in CD highlight the role of the amygdala in the pathophysiology of anxiety in CD.

Mapping structural covariance networks of emotional withdrawal symptoms in males with methamphetamine use disorder during abstinence.

Individuals with methamphetamine use disorder (MUD) often experience anxiety and depressive symptoms during abstinence, which can worsen the likelihood of relapse. Thus, it is essential to understand the neuro-mechanism behind methamphetamine use and its associated emotional withdrawal symptoms in order to develop effective clinical strategies. This study aimed to evaluate associations between emotional withdrawal symptoms and structural covariance networks (SCNs) based on cortical thickness (CTh) across the brain. The CTh measures were obtained from Tl-weighted MRI data from a sample of 48 males with MUD during abstinence and 48 male healthy controls. The severity of anxiety and depressive symptoms was assessed by the Hamilton Anxiety Scale (HAMA) and depression (HAMD) scales. Two important nodes belonging to the brain reward system, the right rostral anterior cingulate cortex (rACC) and medial prefrontal cortex (medPFC), were selected as seeds to conduct SCNs and modulation analysis by emotional symptoms. MUDs showed higher structural covariance between the right rACC and regions in the dorsal attention, right frontoparietal, auditory, visual and limbic networks. They also displayed higher structural covariance between the right medPFC and regions in the limbic network. Moreover, the modulation analysis showed that higher scores on HAMA were associated with increased covariance between the right rACC and the left parahippocampal and isthmus cingulate cortex in the default mode network. These outcomes shed light on the complex neurobiological mechanisms underlying methamphetamine use and its associated emotional withdrawal symptoms and may provide new insights into the development of effective treatments for MUD.

Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

Transcranial focused ultrasound of the amygdala modulates fear network activation and connectivity.

BACKGROUND: Current noninvasive brain stimulation methods are incapable of directly modulating subcortical brain regions critically involved in psychiatric disorders. Transcranial Focused Ultrasound (tFUS) is a newer form of noninvasive stimulation that could modulate the amygdala, a subcortical region implicated in fear. OBJECTIVE: We investigated the effects of active and sham tFUS of the amygdala on fear circuit activation, skin conductance responses (SCR), and self-reported anxiety during a fear-inducing task. We also investigated amygdala tFUS' effects on amygdala-fear circuit resting-state functional connectivity. METHODS: Thirty healthy individuals were randomized in this double-blinded study to active or sham tFUS of the left amygdala. We collected fMRI scans, SCR, and self-reported anxiety during a fear-inducing task (participants viewed red or green circles which indicated the risk of receiving an aversive stimulus), as well as resting-state scans, before and after tFUS. RESULTS: Compared to sham tFUS, active tFUS was associated with decreased (pre to post tFUS) blood-oxygen-level-dependent fMRI activation in the amygdala (F(1,25) = 4.86, p = 0.04, η2 = 0.16) during the fear task, and lower hippocampal (F(1,27) = 4.41, p = 0.05, η2 = 0.14), and dorsal anterior cingulate cortex (F(1,27) = 6.26, p = 0.02; η2 = 0.19) activation during the post tFUS fear task. The decrease in amygdala activation was correlated with decreased subjective anxiety (r = 0.62, p = 0.03). There was no group effect in SCR changes from pre to post tFUS (F(1,23) = 0.85, p = 0.37). The active tFUS group also showed decreased amygdala-insula (F(1,28) = 4.98, p = 0.03) and amygdala-hippocampal (F(1,28) = 7.14, p = 0.01) rsFC, and increased amygdala-ventromedial prefrontal cortex (F(1,28) = 3.52, p = 0.05) resting-state functional connectivity. CONCLUSIONS: tFUS can change functional connectivity and brain region activation associated with decreased anxiety. Future studies should investigate tFUS' therapeutic potential for individuals with clinical levels of anxiety.

Lower cerebrovascular reactivity in prefrontal cortex and weaker negative functional connectivity between prefrontal cortex and insula contribute to white matter hyperintensity-related anxiety or depression.

BACKGROUND: White matter hyperintensities (WMHs) are associated with higher anxiety or depression (A/D) incidence. We investigated associations of WMHs with A/D, cerebrovascular reactivity (CVR), and functional connectivity (FC) to identify potential pathomechanisms. METHODS: Participants with WMH (n = 239) and normal controls (NCs, n = 327) were assessed for A/D using the Hamilton Anxiety Rating Scale (HAMA) and Hamilton Depression Rating Scale (HAMD). The CVR and FC maps were constructed from resting-state functional MRI. Two-way analysis of covariance with fixed factors A/D and WMH was performed to identify regional CVR abnormalities. Seed-based FC analyses were then conducted on regions with WMH × A/D interaction effects on CVR. Logistic regression models were constructed to examine the utility of these measurements for identifying WMH-related A/D. RESULTS: Participants with WMH related A/D exhibited significantly greater CVR in left insula and lower CVR in right superior frontal gyrus (SFG.R), and HAMA scores were negatively correlated with CVR in SFG.R (r = -0.156, P = 0.016). Insula-SFG.R negative FC was significantly weaker in WMH patients with suspected or definite A/D. A model including CVR plus FC changes identified WMH-associated A/D with highest sensitivity and specificity. In contrast, NCs with A/D exhibited greater CVR in prefrontal cortex and stronger FC within the default mode network (DMN) and between the DMN and executive control network. LIMITATIONS: This cross-sectional study requires validation by longitudinal and laboratory studies. CONCLUSIONS: Impaired CVR in SFG.R and weaker negative FC between prefrontal cortex and insula may contribute to WMH-related A/D, providing potential diagnostic imaging markers and therapeutic targets.

Reduced GM-WM concentration inside the Default Mode Network in individuals with high emotional intelligence and low anxiety: a data fusion mCCA+jICA approach.

The concept of emotional intelligence (EI) refers to the ability to recognize and regulate emotions to appropriately guide cognition and behaviour. Unfortunately, studies on the neural bases of EI are scant, and no study so far has exhaustively investigated grey matter (GM) and white matter (WM) contributions to it. To fill this gap, we analysed trait measure of EI and structural MRI data from 128 healthy participants to shed new light on where and how EI is encoded in the brain. In addition, we explored the relationship between the neural substrates of trait EI and trait anxiety. A data fusion unsupervised machine learning approach (mCCA + jICA) was used to decompose the brain into covarying GM-WM networks and to assess their association with trait-EI. Results showed that high levels trait-EI are associated with decrease in GM-WM concentration in a network spanning from frontal to parietal and temporal regions, among which insula, cingulate, parahippocampal gyrus, cuneus and precuneus. Interestingly, we also found that the higher the GM-WM concentration in the same network, the higher the trait anxiety. These findings encouragingly highlight the neural substrates of trait EI and their relationship with anxiety. The network is discussed considering its overlaps with the Default Mode Network.

Molecular basis underlying default mode network functional abnormalities in postpartum depression with and without anxiety.

Although Postpartum depression (PPD) and PPD with anxiety (PPD-A) have been well characterized as functional disruptions within or between multiple brain systems, however, how to quantitatively delineate brain functional system irregularity and the molecular basis of functional abnormalities in PPD and PPD-A remains unclear. Here, brain sample entropy (SampEn), resting-state functional connectivity (RSFC), transcriptomic and neurotransmitter density data were used to investigate brain functional system irregularity, functional connectivity abnormalities and associated molecular basis for PPD and PPD-A. PPD-A exhibited higher SampEn in medial prefrontal cortex (MPFC) and posterior cingulate cortex (PPC) than healthy postnatal women (HPW) and PPD while PPD showed lower SampEn in PPC compared to HPW and PPD-A. The functional connectivity analysis with MPFC and PPC as seed areas revealed decreased functional couplings between PCC and paracentral lobule and between MPFC and angular gyrus in PPD compared to both PPD-A and HPW. Moreover, abnormal SampEn and functional connectivity were associated with estrogenic level and clinical symptoms load. Importantly, spatial association analyses between functional changes and transcriptome and neurotransmitter density maps revealed that these functional changes were primarily associated with synaptic signaling, neuron projection, neurotransmitter level regulation, amino acid metabolism, cyclic adenosine monophosphate (cAMP) signaling pathways, and neurotransmitters of 5-hydroxytryptamine (5-HT), norepinephrine, glutamate, dopamine and so on. These results reveal abnormal brain entropy and functional connectivities primarily in default mode network (DMN) and link these changes to transcriptome and neurotransmitters to establish the molecular basis for PPD and PPD-A for the first time. Our findings highlight the important role of DMN in neuropathology of PPD and PPD-A.

Differential role of fusiform gyrus coupling in depressive and anxiety symptoms during emotion perception.

Anxiety and depression co-occur; the neural substrates of shared and unique components of these symptoms are not understood. Given emotional alterations in internalizing disorders, we hypothesized that function of regions associated with emotion processing/regulation, including the anterior cingulate cortex (ACC), amygdala and fusiform gyrus (FG), would differentiate these symptoms. Forty-three adults with depression completed an emotional functional magnetic resonance imaging task and the Hamilton Depression and Anxiety Scales. We transformed these scales to examine two orthogonal components, one representing internalizing symptom severity and the other the type of internalizing symptoms (anxiety vs depression). We extracted blood oxygen level dependent signal from FG subregions, ACC, and amygdala and performed generalized psychophysiological interaction analyses to assess relationships between symptoms and brain function. Type of internalizing symptoms was associated with FG3-FG1 coupling (F = 8.14, P = 0.007). More coupling was associated with a higher concentration of depression, demonstrating that intra-fusiform coupling is differentially associated with internalizing symptom type (anxiety vs depression). We found an interaction between task condition and internalizing symptoms and dorsal (F = 4.51, P = 0.014) and rostral ACC activity (F = 4.27, P = 0.012). Post hoc comparisons revealed that less activity was associated with greater symptom severity during emotional regulation. Functional coupling differences during emotional processing are associated with depressive relative to anxiety symptoms and internalizing symptom severity. These findings could inform future treatments for depression.

Transdiagnostic symptom of depression and anxiety associated with reduced gray matter volume in prefrontal cortex.

Dimensional models of psychopathology may provide insight into mechanisms underlying comorbid depression and anxiety and improve specificity and sensitivity of neuroanatomical findings. The present study is the first to examine neural structure alterations using the empirically derived Tri-level Model. Depression and anxiety symptoms of 269 young adults were assessed using the Tri-level Model dimensions: General Distress (transdiagnostic depression and anxiety symptoms), Anhedonia-Apprehension (relatively specific depression symptoms), and Fears (specific anxiety symptoms). Using structural MRI, gray matter volumes were extracted for emotion generation (amygdala, nucleus accumbens) and regulation (orbitofrontal, ventrolateral, and dorsolateral prefrontal cortex) regions, often implicated in depression and anxiety. Each Tri-level symptom was regressed onto each region of interest, separately, adjusting for relevant covariates. General Distress was significantly associated with smaller gray matter volumes in bilateral orbitofrontal cortex and ventrolateral prefrontal cortex, independent of Anhedonia-Apprehension and Fears symptom dimensions. These results suggests that prefrontal alterations are associated with transdiagnostic dysphoric mood common across depression and anxiety, rather than unique symptoms of these disorders. Additionally, no regions of interest were associated with Anhedonia-Apprehension or Fears, highlighting the importance of studying transdiagnostic features of depression and anxiety. This has implications for understanding mechanisms of and interventions for depression and anxiety.

Irritable Bowel Syndrome Is Associated With Brain Health by Neuroimaging, Behavioral, Biochemical, and Genetic Analyses.

BACKGROUND: Irritable bowel syndrome (IBS) interacts with psychopathology in a complex way; however, little is known about the underlying brain, biochemical, and genetic mechanisms. METHODS: To clarify the phenotypic and genetic associations between IBS and brain health, we performed a comprehensive retrospective cohort study on a large population. Our study included 171,104 participants from the UK Biobank who underwent a thorough assessment of IBS, with the majority also providing neuroimaging, behavioral, biochemical, and genetic information. Multistage linked analyses were conducted, including phenome-wide association analysis, polygenic risk score calculation, and 2-sample Mendelian randomization analysis. RESULTS: The phenome-wide association analysis showed that IBS was linked to brain health problems, including anxiety and depression, and poor cognitive performance. Significantly lower brain volumes associated with more severe IBS were found in key areas related to emotional regulation and higher-order cognition, including the medial orbitofrontal cortex/ventromedial prefrontal cortex, anterior insula, anterior and mid-cingulate cortices, dorsolateral prefrontal cortex, and hippocampus. Higher triglycerides, lower high-intensity lipoprotein, and lower platelets were also related (p < 1 × 10-10) to more severe IBS. Finally, Mendelian randomization analyses demonstrated potential causal relationships between IBS and brain health and indicated possible mediating effects of dyslipidemia and inflammation. CONCLUSIONS: For the first time, this study provides a comprehensive understanding of the relationship between IBS and brain health phenotypes, integrating perspectives from neuroimaging, behavioral performance, biochemical factors, and genetics, which is of great significance for clinical applications to potentially address brain health impairments in patients with IBS.

Exploring the central mechanism of mind-regulation electroacupuncture in treatment of chronic fatigue syndrome with anxiety and depression comorbidity based on functional magnetic resonance imaging. / åŸºäºŽåŠŸèƒ½ç£å ±æŒ¯æŽ¢è®¨è°ƒç¥žæ³•ç”µé’ˆæ²»ç–—æ ¢æ€§ç–²åŠ³ç»¼åˆå¾ä¼´ç„¦è™‘æŠ‘éƒå ±ç— çš„ä¸­æž¢æœºåˆ¶.

OBJECTIVES: To observe the changes in the regional homogeneity (ReHo) and functional brain network in treatment of chronic fatigue syndrome (CFS) with anxiety and depression comorbidity with the mind-regulation electroacupuncture (EA), using resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: Thirty CFS patients with anxiety and depression comorbidity were enrolled from medical staffs as the observation group. The other 30 healthy subjects were recruited from medical university students as the control group, matching gender, age and education years with the observation group. No any acupuncture intervention was delivered in the control group, and EA for regulating the mind was operated in the observation group. Main points were the emotional area of Sun's scalp acupuncture, the regions 1 and 8 of Sun's abdominal acupuncture. Supplementary acupoints included Baihui (GV 20), Guanyuan (CV 4) and bilateral. RESULTS: The scores of the five domains in MFI-20 (i.e. general fatigue, physical fatigue, mental fatigue, reduced motivation and reduced activity), the total score of MFI-20, and the scores of SDS, SAS and PSQI in the observation group before treatment were higher than those of the control group (P<0.05). Except the score of reduced motivation in MFI-20, the scores of the other domains and the total score of MFI-20, as well as the scores of SDS, SAS and PSQI after treatment were lower than those before treatment in the observation group (P<0.05). Compared with the values before treatment, ReHo value was increased in the the right precuneus and decreased in the left inferior temporal gyrus and the left angular gyrus of the brain in the observation group after treatment. In the observation group, when compared with the control group, ReHo values were increased in the left inferior cerebral lobe, the interhemispheric region, the right occipital lobe and the thalamus; and it was reduced in the left middle temporal gyrus, the right posterior central gyrus, the right middle temporal gyrus, the right orbital middle frontal gyrus, the paracentral lobule and the right fusiform gyrus before treatment. In the observation group, the functional connectivity was decreased between the right thalamus and the left posterior central gyrus, the right hippocampus and the right fusiform gyrus before treatment, respectively; it was re-constructed after treatment between the right thalamus and the left posterior central gyrus, and the right fusiform gyrus. Compared with the control group, the functional connectivity between the right thalamus and the left posterior central gyrus, the right hippocampus, and the right fusiform gyrus was reduced before treatment; while after treatment, the functional connectivity was reduced between the right thalamus and the hippocampus in the observation group. With Spearman correlation analysis between the differential brain regions and the scores of MFI-20, SAS, SDS and PSQI, it was found that the left middle temporal gyrus, the paracentral lobule, the right precuneus, and the left inferior temporal gyrus had a partial positive correlation with the above clinical scales; and the interhemispheric region, the thalamus, the right fusiform gyrus, and the right middle temporal gyrus showed a partial negative correlation. CONCLUSIONS: There is the decrease of ReHo in many brain regions and the numbers of the local brain functional network connectivity in CFS patients with anxiety and depression comorbidity. The mind-regulation electroacupuncture therapy may relieve the clinical symptoms of the patients through adjusting the abnormal brain regions and activating emotion-related brain regions.

Multivariate patterns of brain functional connectome associated with COVID-19-related negative affect symptoms.

Severe mental health problems with the representation of negative affect symptoms (NAS) have been increasingly reported during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore the multivariate patterns of brain functional connectome predicting COVID-19-related NAS. This cohort study encompassed a group of university students to undergo neuroimaging scans before the pandemic, and we re-contacted participants for 1-year follow-up COVID-related NAS evaluations during the pandemic. Regularized canonical correlation analysis was used to identify connectome-based dimensions of NAS to compute pairs of canonical variates. The predictive ability of identified functional connectome to NAS dimensional scores was examined with a nested cross-validation. Two dimensions (i.e. mode stress and mode anxiety) were related to distinct patterns of brain functional connectome (r2 = 0.911, PFDR = 0.048; r2 = 0.901, PFDR = 0.037, respectively). Mode anxiety was characterized by high loadings in connectivity between affective network (AFN) and visual network (VN), while connectivity of the default mode network with dorsal attention network (DAN) were remarkably prominent in mode stress. Connectivity patterns within the DAN and between DAN and VN, ventral attention network, and AFN was common for both dimensions. The identified functional connectome can reliably predict mode stress (r = 0.37, MAE = 5.1, p < 0.001) and mode anxiety (r = 0.28, MAE = 5.4, p = 0.005) in the cross-validation. Our findings provide new insight into multivariate dimensions of COVID-related NAS, which may have implications for developing network-based biomarkers in psychological interventions for vulnerable individuals in the pandemic.

Responding to threat: Associations between neural reactivity to and behavioral avoidance of threat in pediatric anxiety.

BACKGROUND: Despite broad recognition of the central role of avoidance in anxiety, a lack of specificity in its operationalization has hindered progress in understanding this clinically significant construct. The current study uses a multimodal approach to investigate how specific measures of avoidance relate to neural reactivity to threat in youth with anxiety disorders. METHODS: Children with anxiety disorders (ages 6-12 years; n = 65 for primary analyses) completed laboratory task- and clinician-based measures of avoidance, as well as a functional magnetic resonance imaging task probing neural reactivity to threat. Primary analyses examined the ventral anterior insula (vAI), amygdala, and ventromedial prefrontal cortex (vmPFC). RESULTS: Significant but distinct patterns of association with task- versus clinician-based measures of avoidance emerged. Clinician-rated avoidance was negatively associated with right and left vAI reactivity to threat, whereas laboratory-based avoidance was positively associated with right vAI reactivity to threat. Moreover, left vAI-right amygdala and bilateral vmPFC-right amygdala functional connectivity were negatively associated with clinician-rated avoidance but not laboratory-based avoidance. LIMITATIONS: These results should be considered in the context of the restricted range of our treatment-seeking sample, which limits the ability to draw conclusions about these associations across children with a broader range of symptomatology. In addition, the limited racial and ethnic diversity of our sample may limit the generalizability of findings. CONCLUSION: These findings mark an important step towards bridging neural findings and behavioral patterns using a multimodal approach. Advancing understanding of behavioral avoidance in pediatric anxiety may guide future treatment optimization by identifying individual-specific targets for treatment.