Dissociable salience and default mode network modulation in generalized anxiety disorder: a connectome-wide association study.

Generalized anxiety disorder (GAD) is a common anxiety disorder experiencing psychological and somatic symptoms. Here, we explored the link between the individual variation in functional connectome and anxiety symptoms, especially psychological and somatic dimensions, which remains unknown. In a sample of 118 GAD patients and matched 85 healthy controls (HCs), we used multivariate distance-based matrix regression to examine the relationship between resting-state functional connectivity (FC) and the severity of anxiety. We identified multiple hub regions belonging to salience network (SN) and default mode network (DMN) where dysconnectivity associated with anxiety symptoms (P < 0.05, false discovery rate [FDR]-corrected). Follow-up analyses revealed that patient's psychological anxiety was dominated by the hyper-connectivity within DMN, whereas the somatic anxiety could be modulated by hyper-connectivity within SN and DMN. Moreover, hypo-connectivity between SN and DMN were related to both anxiety dimensions. Furthermore, GAD patients showed significant network-level FC changes compared with HCs (P < 0.01, FDR-corrected). Finally, we found the connectivity of DMN could predict the individual psychological symptom in an independent GAD sample. Together, our work emphasizes the potential dissociable roles of SN and DMN in the pathophysiology of GAD's anxiety symptoms, which may be crucial in providing a promising neuroimaging biomarker for novel personalized treatment strategies.

Insular-associated causal network of structural covariance evaluating progressive gray matter changes in major depressive disorder.

BACKGROUND: Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD). OBJECTIVE: This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis. METHODS: The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information. RESULTS: With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum. CONCLUSIONS: This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.

Shared and distinct patterns of dynamic functional connectivity variability of thalamo-cortical circuit in bipolar depression and major depressive disorder.

Evidence has indicated abnormalities of thalamo-cortical functional connectivity (FC) in bipolar disorder during a depressive episode (BDD) and major depressive disorder (MDD). However, the dynamic FC (dFC) within this system is poorly understood. We explored the thalamo-cortical dFC pattern by dividing thalamus into 16 subregions and combining with a sliding-window approach. Correlation analysis was performed between altered dFC variability and clinical data. Classification analysis with a linear support vector machine model was conducted. Compared with healthy controls (HCs), both patients revealed increased dFC variability between thalamus subregions with hippocampus (HIP), angular gyrus and caudate, and only BDD showed increased dFC variability of the thalamus with superior frontal gyrus (SFG), HIP, insula, middle cingulate gyrus, and postcentral gyrus. Compared with MDD and HCs, only BDD exhibited enhanced dFC variability of the thalamus with SFG and superior temporal gyrus. Furthermore, the number of depressive episodes in MDD was significantly positively associated with altered dFC variability. Finally, the disrupted dFC variability could distinguish BDD from MDD with 83.44% classification accuracy. BDD and MDD shared common disrupted dFC variability in the thalamo-limbic and striatal-thalamic circuitries, whereas BDD exhibited more extensive and broader aberrant dFC variability, which may facilitate distinguish between these 2 mood disorders.

Individual variation in brain network topology is linked to course of illness in major depressive disorder.

Major depressive disorder (MDD) is a chronic and highly recurrent disorder. The functional connectivity in depression is affected by the cumulative effect of course of illness. However, previous neuroimaging studies on abnormal functional connection have not mainly focused on the disease duration, which is seen as a secondary factor. Here, we used a data-driven analysis (multivariate distance matrix regression) to examine the relationship between the course of illness and resting-state functional dysconnectivity in MDD. This method identified a region in the anterior cingulate cortex, which is most linked to course of illness. Specifically, follow-up seed analyses show this phenomenon resulted from the individual differences in the topological distribution of three networks. In individuals with short-duration MDD, the connection to the default mode network was strong. By contrast, individuals with long-duration MDD showed hyperconnectivity to the ventral attention network and the frontoparietal network. These results emphasized the centrality of the anterior cingulate cortex in the pathophysiology of the increased course of illness and implied critical links between network topography and pathological duration. Thus, dissociable patterns of connectivity of the anterior cingulate cortex is an important dimension feature of the disease process of depression.

Negative bias effects during audiovisual emotional processing in major depression disorder.

Aberrant affective neural processing and negative emotional bias are trait-marks of major depression disorders (MDDs). However, most research on biased emotional perception in depression has only focused on unimodal experimental stimuli, the neural basis of potentially biased emotional processing of multimodal inputs remains unclear. Here, we addressed this issue by implementing an audiovisual emotional task during functional MRI scanning sessions with 37 patients with MDD and 37 gender-, age- and education-matched healthy controls. Participants were asked to distinguish laughing and crying sounds while being exposed to faces with different emotional valences as background. We combined general linear model and psychophysiological interaction analyses to identify abnormal local functional activity and integrative processes during audiovisual emotional processing in MDD patients. At the local neural level, MDD patients showed increased bias activity in the ventromedial prefrontal cortex (vmPFC) while listening to negative auditory stimuli and concurrently processing visual facial expressions, along with decreased dorsolateral prefrontal cortex (dlPFC) activity in both the positive and negative visual facial conditions. At the network level, MDD exhibited significantly decreased connectivity in areas involved in automatic emotional processes and voluntary control systems during perception of negative stimuli, including the vmPFC, dlPFC, insula, as well as the subcortical regions of posterior cingulate cortex and striatum. These findings support a multimodal emotion dysregulation hypothesis for MDD by demonstrating that negative bias effects may be facilitated by the excessive ventral bottom-up negative emotional influences along with incapability in dorsal prefrontal top-down control system.

Neural correlates of acceptance and rejection in online speed dating: An electroencephalography study.

Pursuing dating relationships is important for many people's well-being, because it helps them fulfill the need for stable social relationships. However, the neural underpinnings of decision-making processes during the pursuit of dating interactions are unclear. In the present study, we used a novel online speed dating paradigm where participants (undergraduate students, N = 25, aged 18-25 years, 52% female) received direct information about acceptance or rejection of their various speed dates. We recorded EEG measurements during speed dating feedback anticipation and feedback processing stages to examine the stimulus preceding negativity (SPN) and feedback-related brain activity (Reward Positivity, RewP, and theta oscillatory power). The results indicated that the SPN was larger when participants anticipated interest versus disinterest from their speed dates. A larger RewP was observed when participants received interest from their speed dates. Theta power was increased when participants received rejection from their speed dates. This theta response could be source-localized to brain areas that overlap with the physical pain matrix (anterior cingulate cortex, dorsolateral prefrontal cortex, and the supplementary motor area). This study demonstrates that decision-making processes-as evident in a speed date experiment-are characterized by distinct neurophysiological responses during anticipating an evaluation and processing thereof. Our results corroborate the involvement of the SPN in reward anticipation, RewP in reward processing and mid-frontal theta power in processing of negative social-evaluative feedback. These findings contribute to a better understanding of the neurocognitive mechanisms implicated in decision-making processes when pursuing dating relationships.

Integrating Multilevel Functional Characteristics Reveals Aberrant Neural Patterns during Audiovisual Emotional Processing in Depression.

Emotion dysregulation is one of the core features of major depressive disorder (MDD). However, most studies in depression have focused on unimodal emotion processing, whereas emotional perception in daily life is highly dependent on multimodal sensory inputs. Here, we proposed a novel multilevel discriminative framework to identify the altered neural patterns in processing audiovisual emotion in MDD. Seventy-four participants underwent an audiovisual emotional task functional magnetic resonance imaging scanning. Three levels of whole-brain functional features were extracted for each subject, including the task-evoked activation, task-modulated connectivity, combined activation and connectivity. Support vector machine classification and prediction models were built to identify MDD from controls and evaluate clinical relevance. We revealed that complex neural networks including the emotion regulation network (prefrontal areas and limbic-subcortical regions) and the multisensory integration network (lateral temporal cortex and motor areas) had the discriminative power. Moreover, by integrating comprehensive information of local and interactive processes, multilevel models could lead to a substantial increase in classification accuracy and depression severity prediction. Together, we highlight the high representational capacity of machine learning algorithms to characterize the complex network abnormalities associated with emotional regulation and multisensory integration in MDD. These findings provide novel evidence for the neural mechanisms underlying multimodal emotion dysregulation of depression.

The qualitative analysis of characteristic of callers to a psychological hotline at the early stage of COVID-19 in China.

BACKGROUND: As the outbreak of COVID-19, traditional face-to-face psychological intervention are difficult to achieve, so hotline becomes available and recommended strategies. The callers' characteristic could help us to study their experiences of emotional distress, as well as the reasons for calling during the pandemic, which can be used to inform future service design and delivery. METHODS: The information of 1558 callers called our hospital' s hotline for help from February 3, 2020, to March 16, 2020 were collected in the form of Tick-box and Free text, and the inductive content analysis was undertaken focusing on the reasons for caller engagement. RESULTS: It was indicated that more than half of the callers are female (59.7%), mostly between the age of 18-59 (76.5%). The average age was 37.13 ± 13.76 years old. The average duration of a call to the hotline was 10.03 ± 9.84 min. The most frequent description emotional state were anxious (45.1%) and calm (30.3%), with the sub-sequence of scared (18.2%), sad (11.9%), and angry (6.9%). All callers displayed a wide range of reasons for calling, with needing support around their emotion (64.6%), seeking practical help (44.0%), and sleep problems (20.3%) constituting the majority of calls. Among the subthemes, 314 callers thought the epidemic has made them upset, 198 asked questions about the epidemic, and 119 reported their life routines were disrupted. The prevalence of key reasons does not appear to differ over time. Through their feedback, 79.1% agreed that they felt emotionally better after calling, and 95.0% agreed that hotline had helped them. CONCLUSIONS: During the epidemic, the most concern of the public is still related to epidemics and its adverse effects. Fortunately, the hotline can be an active and effective rescue measure after an emergency happened.

Resting state functional network switching rate is differently altered in bipolar disorder and major depressive disorder.

The clinical misdiagnosis ratio of bipolar disorder (BD) patients to major depressive disorder (MDD) patients is high. Recent findings hypothesize that the ability to flexibly recruit functional neural networks is differently altered in BD and MDD patients. This study aimed to explore distinct aberrance of network flexibility during dynamic networks configuration in BD and MDD patients. Resting state functional magnetic resonance imaging of 40 BD patients, 61 MDD patients, and 61 matched healthy controls were recruited. Dynamic functional connectivity matrices for each subject were constructed with a sliding window method. Then, network switching rate of each node was calculated and compared among the three groups. BD and MDD patients shared decreased network switching rate of regions including left precuneus, bilateral parahippocampal gyrus, and bilateral dorsal medial prefrontal cortex. Apart from these regions, MDD patients presented specially decreased network switching rate in the bilateral anterior insula, left amygdala, and left striatum. Taken together, BD and MDD patients shared decreased network switching rate of key hubs in default mode network and MDD patients presented specially decreased switching rate in salience network and striatum. We found shared and distinct aberrance of network flexibility which revealed altered adaptive functions during dynamic networks configuration of BD and MDD.

Dynamic changes of amplitude of low-frequency fluctuations in patients with generalized anxiety disorder.

Previous neuroimaging studies have mainly focused on alterations of static and dynamic functional connectivity in patients with generalized anxiety disorder (GAD). However, the characteristics of local brain activity over time in GAD are poorly understood. This study aimed to investigate the abnormal time-varying local brain activity of GAD by using the amplitude of low-frequency fluctuation (ALFF) method combined with sliding-window approach. Group comparison results showed that compared with healthy controls (HCs), patients with GAD exhibited increased dynamic ALFF (dALFF) variability in widespread regions, including the bilateral dorsomedial prefrontal cortex, hippocampus, thalamus, striatum; and left orbital frontal gyrus, inferior parietal lobule, temporal pole, inferior temporal gyrus, and fusiform gyrus. The abnormal dALFF could be used to distinguish between patients with GAD and HCs. Increased dALFF variability values in the striatum were positively correlated with GAD symptom severity. These findings suggest that GAD patients are associated with abnormal temporal variability of local brain activity in regions implicated in executive, emotional, and social function. This study provides insight into the brain dysfunction of GAD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding neurophysiological mechanisms and potentially informing the diagnosis of GAD.

The enclosed ward management strategies in psychiatric hospitals during COVID-19 outbreak.

During the COVID-19 pandemic, as a large city located in Southwest China, Chengdu was mainly affected by imported cases. For a psychiatric hospital, the enclosed management model, the crowded wards and the uncooperative patients are the risk factors of nosocomial infection. Admitting new patients while preventing the COVID-19 outbreak within the institutions was a crucial challenge. The Mental Health Centre of Chengdu proposed a series of effective management strategies to deal with the rapidly evolving situation during the COVID-19 pandemic which included regulation for the inpatients, their families and staff, and achieved Zero infection in our hospital.

Combined static and dynamic functional connectivity signatures differentiating bipolar depression from major depressive disorder.

OBJECTIVE: Bipolar disorder in the depressive phase (BDd) may be misdiagnosed as major depressive disorder (MDD), resulting in poor treatment outcomes. To identify biomarkers distinguishing BDd from MDD is of substantial clinical significance. This study aimed to characterize specific alterations in intrinsic functional connectivity (FC) patterns in BDd and MDD by combining whole-brain static and dynamic FC. METHODS: A total of 40 MDD and 38 BDd patients, and 50 age-, sex-, education-, and handedness-matched healthy controls (HCs) were included in this study. Static and dynamic FC strengths (FCSs) were analyzed using complete time-series correlations and sliding window correlations, respectively. One-way analysis of variance was performed to test group effects. The combined static and dynamic FCSs were then used to distinguish BDd from MDD and to predict clinical symptom severity. RESULTS: Compared with HCs, BDd patients showed lower static FCS in the medial orbitofrontal cortex and greater static FCS in the caudate, while MDD patients exhibited greater static FCS in the medial orbitofrontal cortex. BDd patients also demonstrated greater static and dynamic FCSs in the thalamus compared with both MDD patients and HCs, while MDD patients exhibited greater dynamic FCS in the precentral gyrus compared with both BDd patients and HCs. Combined static and dynamic FCSs yielded higher accuracy than either static or dynamic FCS analysis alone, and also predicted anhedonia severity in BDd patients and negative mood severity in MDD patients. CONCLUSION: Altered FC within frontal-striatal-thalamic circuits of BDd patients and within the default mode network/sensorimotor network of MDD patients accurately distinguishes between these disorders. These unique FC patterns may serve as biomarkers for differential diagnosis and provide clues to the pathogenesis of mood disorders.

Functional dysconnectivity within the emotion-regulating system is associated with affective symptoms in major depressive disorder: A resting-state fMRI study.

OBJECTIVE: Major depressive disorder (MDD) can be characterized as a multidimensional and system-level disorder. The neuropathophysiological abnormalities have been reported to be distributed in emotion regulation system, involving the prefrontal cortex (PFC), limbic and striatum in convergent studies. Decrease of positive affect and increase of negative affect are recognized as a hallmark of MDD. However, the dysfunctions in affective processing in MDD within the emotion regulation system remains largely unclear. In this study, our goals are to characterize the dysconnectivity pattern within this system and explore the relationships between this kind of dysconnectivity pattern and affective symptoms, which might help us better look into the neuropathophysiological mechanisms underlying MDD. METHODS: A total of 34 MDD and 34 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rsfMRI). The alterations in functional connectivity (FC) within the emotion regulation system and their relationships with affective symptoms were explored. RESULTS: Compared with HCs, MDD patients showed aberrant FC within this system. Importantly, deceased FC was mainly involved in the prefrontal-limbic system, while elevated FC was observed in the prefrontal-striatum system. In the MDD group, decreased FC of right posterior hippocampus-left dorsolateral prefrontal cortex (dlPFC) was negatively associated with the negative affect scores and Hamilton Depression Rating Scale scores and the FC of left ventral striatum-left dlPFC was significantly negatively related with the positive affect scores. CONCLUSIONS: These findings demonstrated that MDD showed characteristic pathological alterations of the emotion regulation system. Dysconnectivity within prefrontal-limbic system might be more related to the dysregulation of negative affect, whereas dysconnectivity within prefrontal-striatum system might influence more on positive affect processing. The decrease in positive affect and increase in negative affect in MDD might have different pathological basis. These results could help better understand the dysconnectivity pattern in the emotion-regulating system underlying depression.

Effect of exogenous methanol on glycolate oxidase and photorespiratory intermediates in cotton.

Application of methanol (MeOH) inhibits photorespiration and enhances growth and yield in C3 plants. However, the underlying cellular and molecular mechanisms are not clear. In this study, we investigated the effects of foliar application of MeOH (30%, v/v) on glycolate oxidase (GO) activity and photorespiratory intermediates in cotton leaves in a field experiment. MeOH treatment significantly inhibited GO activity (by 30% compared with the controls). We also found that endogenous glyoxylate, a photorespiratory intermediate, increased and glycine decreased significantly in MeOH-treated plants. Serine increased significantly in MeOH-treated plants. These results thus demonstrated that exogenous MeOH can modulate GO activity and the production of photorespiratory intermediates, and sheds new lights on our current understanding of how exogenous MeOH inhibits photorespiration and enhances the growth and yield of C3 plants such as cotton.

Cortical thickness reductions associate with brain network architecture in major depressive disorder.

BACKGROUND: Cortical thickness reductions in major depressive disorder are distributed across multiple regions. Research has indicated that cortical atrophy is influenced by connectome architecture on a range of neurological and psychiatric diseases. However, whether connectome architecture contributes to changes in cortical thickness in the same manner as it does in depression is unclear. This study aims to explain the distribution of cortical thickness reductions across the cortex in depression by brain connectome architecture. METHODS: Here, we calculated a differential map of cortical thickness between 110 depression patients and 88 age-, gender-, and education level-matched healthy controls by using T1-weighted images and a structural network reconstructed through the diffusion tensor imaging of control group. We then used a neighborhood deformation model to explore how cortical thickness change in an area is influenced by areas structurally connected to it. RESULTS: We found that cortical thickness in the frontoparietal and default networks decreased in depression, regional cortical thickness changes were related to reductions in their neighbors and were mainly limited by the frontoparietal and default networks, and the epicenter was in the prefrontal lobe. CONCLUSION: Current findings suggest that connectome architecture contributes to the irregular topographic distribution of cortical thickness reductions in depression and cortical atrophy is restricted by and dependent on structural foundation.

Research on the Mechanism and Propagation Characteristics of Combustion and Explosion of Natural Gas/Ammonia/Hydrogen Mixed Gas Fuel.

The addition of ammonia and hydrogen into natural gas fuel is an effective method to reduce carbon emissions. This study aims to investigate the effect of adding ammonia and hydrogen on the mechanism of natural gas combustion and emission characteristics. Based on a self-developed mixed gas deflagrate experimental platform, the deflagrate characteristics, emission characteristics, and chemical reaction kinetics mechanism of mixed gas fuels under different composition ratios (natural gas 0-100%, hydrogen 10-85%, and ammonia 0-100%) were studied. The results indicate that the propagation of the deflagration shock wave can be categorized into an initial stage (L < 3 m) and a development stage (L > 3 m) based on the observed trend of shock wave intensity variation with distance. The intensity of the deflagration shock wave for the mixed gases increases monotonically as the hydrogen content ratio rises. In contrast, the impact of the ammonia content ratio on the shock wave intensity exhibits a distinct pattern that varies with changes in the equivalence ratio and hydrogen content ratio. In terms of carbon emissions per unit of heat value produced by the fuel, adding hydrogen to natural gas proves to be more effective at reducing carbon emissions than adding ammonia. When the ammonia content ratio is 50% and the hydrogen content ratio is 40%, the combustion performance of the mixed gas fuel is similar to that of natural gas, but its carbon emissions are lower than 30% of natural gas, making it a new type of mixed fuel with potential application value; the interaction between reflected pressure waves and flames is the main reason for the fluctuation of deflagrate shock wave pressure; ammonia lowers the temperature of the reaction system by reducing the concentration of OH radicals.

An investigation into the abnormal dynamic connection mechanism of generalized anxiety disorders based on non-homogeneous Markov models.

BACKGROUND: The dynamic and hierarchical nature of the functional brain network. The neural dynamical systems tend to converge to multiple attractors (stable fixed points or dynamical states) in long run. Little is known about how the changes in this brain dynamic "long-term" behavior of the connectivity flow of brain network in generalized anxiety disorder (GAD). METHODS: This study recruited 92 patients with GAD and 77 healthy controls (HC). We applied a reachable probability approach combining a Non-homogeneous Markov model with transition probability to quantify all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level and the stationary probability vector (10-step transition probabilities) to describe the steady state of the system in the long run. A random forest algorithm was conducted to predict the severity of anxiety. RESULTS: The dynamic functional patterns in distributed brain networks had larger possibility to converge in bilateral thalamus, posterior cingulate cortex (PCC), right superior occipital gyrus (SOG) and smaller possibility to converge in bilateral superior temporal gyrus (STG) and right parahippocampal gyrus (PHG) in patients with GAD compared to HC. The abnormal transition probability pattern could predict anxiety severity in patients with GAD. LIMITATIONS: Small samples and subjects taking medications may have influenced our results. Future studies are expected to rule out the potential confounding effects. CONCLUSION: Our results have revealed abnormal dynamic neural communication and integration in emotion regulation in patients with GAD, which give new insights to understand the dynamics of brain function of patients with GAD.

[Relationship between body mass index and volume ratio of brain gray matter in patients with first-episode schizophrenia].

OBJECTIVE: To analyze the relationship between psychotic symptoms and body mass index (BMI) and brain mass index in patients with first-episode schizophrenia. METHODS: We identified 97 patients with first-episode and drug-free schizophrenia and compared their BMI and scare MRI results with 97 healthy participants. RESULTS: There were no statistically significant differences in BMI, volume of white matter and volume of grey matter between the patients with schizophrenia and healthy participants. BMI was positively correlated with age and negatively correlated with gray matter volume and the ratio of gray matter volume in the healthy participants. No such correlations were found in the patients with schizophrenia. BMI were not correlated with the total score of PANSS, nor with the factor score of PANSS. CONCLUSION: BMI is positive correlated with age, but negatively correlated with gray matter volume and the ratio of gray matter volume in healthy adult. But such correlations disappear in patients with schizophrenia. BMI is not associated with the seriousness of psychotic symptoms.

Effects of depressive symptoms on regulating emotional goals: Preferences for distinct facial emotions.

BACKGROUND: Although many studies of emotion regulation in depression have focused on regulatory strategies, few have explored the goals of regulation. Regulatory strategies refer to methods of adjusting emotions, while regulatory goals refer to the desired states of emotion. According to situational selection strategy, individuals choose situations to regulate their emotions, and also selectively approach or avoid certain people. METHODS: We used the Beck Depression Inventory-II scale to classify healthy individuals into two groups: those with either high or low levels of depressive symptoms. We then explored the influence of these symptoms on individual goals for emotion regulation. Event-related potentials in the brain were recorded as participants viewed and selected images of happy, neutral, sad, and fearful faces. Participants also provided subjective emotional preferences. RESULTS: Late positive potential (LPP) amplitudes for all faces were smaller in the high depressive-symptom group than those in the low depressive-symptom group. Additionally, participants in the high depressive-symptom group chose to look at sad and fearful faces more often than they chose to view happy or neutral faces, and showed a stronger preference for sad and fearful emotions and a weaker preference for happy emotions. CONCLUSION: The results suggest that the more individuals exhibit depressive symptoms, the less likely that they will be motivated to approach happy faces and avoid sad and fearful faces. The result of this emotional regulation goal is an increase in the experience of negative emotions, which likely contributes to their depressive state.