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.

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.

Effects of rTMS Intervention on Functional Neuroimaging Activities in Adolescents with Major Depressive Disorder Measured Using Resting-State fMRI.

Repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) is commonly used for the clinical treatment of major depressive disorder (MDD). The neuroimaging biomarkers and mechanisms of rTMS are still not completely understood. This study aimed to explore the functional neuroimaging changes induced by rTMS in adolescents with MDD. A total of ten sessions of rTMS were administrated to the L-DLPFC in thirteen adolescents with MDD once a day for two weeks. All of them were scanned using resting-state functional magnetic resonance imaging at baseline and after rTMS treatment. The regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and the subgenual anterior cingulate cortex (sgACC)-based functional connectivity (FC) were computed as neuroimaging indicators. The correlation between changes in the sgACC-based FC and the improvement in depressive symptoms was also analyzed. After rTMS treatment, ReHo and ALFF were significantly increased in the L-DLPFC, the left medial prefrontal cortex, bilateral medial orbital frontal cortex, and the left ACC. ReHo and ALFF decreased mainly in the left middle occipital gyrus, the right middle cingulate cortex (MCC), bilateral calcarine, the left cuneus, and the left superior occipital gyrus. Furthermore, the FCs between the left sgACC and the L-DLPFC, the right IFGoper, the left MCC, the left precuneus, bilateral post-central gyrus, the left supplementary motor area, and the left superior marginal gyrus were enhanced after rTMS treatment. Moreover, the changes in the left sgACC-left MCC FC were associated with an improvement in depressive symptoms in early improvers. This study showed that rTMS treatment in adolescents with MDD causes changes in brain activities and sgACC-based FC, which may provide basic neural biomarkers for rTMS clinical trials.

Disrupted functional networks within white-matter served as neural features in adolescent patients with conduct disorder.

BACKGROUND: Conduct disorder (CD) has been conceptualized as a psychiatric disorder associated with white-matter (WM) structural abnormalities. Although diffusion tensor imaging could identify WM structural architecture changes, it cannot characterize functional connectivity (FC) within WM. Few studies have focused on disentangling the WM dysfunctions in CD patients by using functional magnetic resonance imaging (fMRI). METHODS: The resting-state fMRI data were first obtained from both adolescent CD and typically developing (TD) controls. A voxel-based clustering analysis was utilized to identify the large-scale WM FC networks. Then, we examined the disrupted WM network features in CD, and further investigated whether these features could predict the impulsive symptoms in CD using support vector regression prediction model. RESULTS: We identified 11 WM functional networks. Compared with TDs, CD patients showed increased FCs between occipital network (ON) and superior temporal network (STN), between orbitofrontal network (OFN) and corona radiate network (CRN), as well as between deep network and CRN. Further, the disrupted FCs between ON and STN and between OFN and CRN were significantly negatively associated with non-planning impulsivity scores in CD. Moreover, the disrupted WM networks could be served as features to predict the motor impulsivity scores in CD. CONCLUSIONS: Our results provided further support on the existence of WM functional networks and could extended our knowledge about the WM functional abnormalities related with emotional and perception processing in CD patients from the view of WM dysfunction.

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.

Effect of intermittent theta burst stimulation on suicidal ideation and depressive symptoms in adolescent depression with suicide attempt: A randomized sham-controlled study.

BACKGROUND: Suicidal ideation is a serious symptom of major depressive disorder (MDD). Intermittent theta burst stimulation (iTBS) is a safe, effective brain stimulation treatment for alleviating suicidal ideation in adults with MDD. This study aimed to examine the clinical efficacy of iTBS on reducing suicidal ideation in adolescent MDD with suicide attempt. METHODS: In a randomized, sham-controlled protocol, a total of 10 sessions of iTBS was administrated to the left dorsolateral prefrontal cortex (DLPFC) in patients once a day for two weeks. The suicidal ideation and depressive symptoms were assessed using Beck Scale for Suicide Ideation-Chinese Version (BSI-CV), Hamilton Rating Scale for Depression (HAMD-24), and Self-rating Depression Scale (SDS) at baseline and after 10 treatment sessions. RESULTS: Forty-five patients were randomized assigned to either active iTBS (n = 23) or sham group (n = 22). The suicidal ideation and depressive symptoms of the active iTBS group were significantly ameliorated over 2 weeks of treatment. Further, higher baseline SDS, HAMD-24 and BSI-CV scores in the active iTBS group were associated with greater reductions. LIMITATIONS: A larger sample size and double-blinded clinical trial should be conducted to verify the reliability and reproducibility. CONCLUSIONS: The current study suggested that daily iTBS of the left DLPFC for 2 weeks could effectively and safely alleviate suicidal ideation and mitigate depression in adolescent MDD, especially for individuals with relatively more severe symptoms. Although caution is warranted, the findings could provide further evidence for the effectiveness and safety of iTBS in clinical practice.

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.

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.

Disorder-specific impaired neurocognitive function in major depression and generalized anxiety disorder.

BACKGROUND: Generalized anxiety disorder (GAD) and major depressive disorder (MDD) are both highly prevalent and comorbid psychiatric disorders. Neurocognitive dysfunction has been commonly found in MDD, but the findings in GAD are inconsistent. Few studies have directly compared cognitive performance between GAD and MDD. Therefore, the present study aimed to reveal the similar and distinct cognitive impairments between both disorders. METHODS: Three non-overlapping and non-comorbid groups were enrolled in the current study including patients with GAD (n = 37), MDD (n = 107) and healthy controls (n = 74). Levels of anxiety and depression were assessed using the Hamilton Anxiety Rating Scale (HAMA) and the Hamilton Depression Rating Scale (HAMD) respectively. The Cambridge Neuropsychological Test Automated Battery (CANTAB) was used to compare the cognitive performance, including sustained attention, visual memory, executive functions and learning. RESULTS: Both MDD and GAD groups demonstrated common significant deficits in sustained attention, visual memory, working memory and learning when compared to healthy controls. Despite the similarities, the MDD group had significantly greater impairment in learning, particularly generalization, while the GAD group demonstrated more pronounced deficits in visual memory. LIMITATIONS: Patients involved were medicated and the sample size for GAD was relatively small. CONCLUSIONS: The significant differences in visual memory and learning between MDD and GAD groups might be indicators to distinguishing both disorders. These results confirm that cognitive function is of great importance as a future target for treatment in order to improve wellbeing, quality of life and functionality in both GAD and MDD.

Neural mechanisms of aberrant self-referential processing in patients with generalized anxiety disorder.

Massive theoretical studies in clinical psychology have implicated the self in understanding internalizing disorders (i.e., anxiety and mood disorders), in which self-related tasks were frequently used to investigate internalizing psychopathology. As one of the most frequently seen internalizing disorder in primary care, patients with generalized anxiety disorder (GAD) are characterized by inappropriate self-related processing such as negative self-referential thinking. However, relevant neural mechanisms remain unknown. In this study, participants underwent a self-related task which they were presented with several positive and negative trait words and were required to judge the extent to which these traits matched themselves when compared to their average peers. Aberrant brain activation and functional connectivity of GAD were detected during processing positive and negative traits. Compared to healthy controls (HCs), patients with GAD exhibited abnormal self-processing which manifested as lower biased self-rating scores particularly for negative traits and weaker brain activity in the left dorsomedial prefrontal cortex, inferior frontal gyrus, superior temporal sulcus (STS), and bilateral lingual gyrus when processing trait words. Abnormal functional connections between these hypoactive regions and regions associated with reward, emotion, and theory of mind were observed in subsequent psychophysiological interaction analysis. An attenuation of connectivity between the left insula and left STS was associated with greater severity of anxiety symptom in GAD patients. These findings provide insight into the abnormal neurocognitive mechanisms of biased self-related processing in GAD patients, which involves distorted self-schema accompanied by abnormal activation and functional connections of regions implicated in self-related and social cognition processing.

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.

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.

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.

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.

Prefrontal-limbic-striatum dysconnectivity associated with negative emotional endophenotypes in bipolar disorder during depressive episodes.

BACKGROUND: The prefrontal-limbic-subcortical network has been suggested as an important circuitry in the pathophysiology underlying bipolar disorder during depressive episodes (BDD). However, the relationships between disrupted prefrontal-limbic-subcortical connection and the emotional endophenotypes in BDD patients remain largely unclear. METHODS: Forty-three BDD patients and 63 matched healthy controls (HCs) underwent the resting-state functional magnetic resonance imaging scan. The altered clusters were first identified by using a spatial pairwise clustering method and then were extracted as regions of interest to calculate the functional connectivity (FC). Group comparisons were conducted to identify the abnormal FCs. Classification analysis was employed to examine whether the altered FCs could distinguish BDD from HCs. The relationships between FC alterations and the emotional endophenotypes as measured by the Affective Neuroscience Personality Scales (ANPS) were further detected in BDD. RESULTS: Compared with HCs, BDD patients showed abnormal FCs in the prefrontal-limbic-striatum circuit. Importantly, the altered FCs yielded 84.91% accuracy (p< 1/5000) with 93.65% sensitivity and 72.09% specificity in differentiating between BDD and HCs. Moreover, the decreased FCs in the prefrontal-striatum and prefrontal-limbic systems were positively correlated with negative emotional endophenotypes of Sadness and Fear scores. CONCLUSIONS: The findings demonstrated that prefrontal-limbic-striatum disconnection may be identified as a potential effective biomarker for BDD, which could help further explain the neurobiological mechanisms underlying BDD.

Anomalous neurovascular coupling in patients with generalized anxiety disorder evaluated by combining cerebral blood flow and functional connectivity strength.

Coupling between neuronal activity and blood perfusion is termed neurovascular coupling, and it provides a new mechanistic perspective into understanding numerous brain diseases. Although abnormal brain activity and blood supply have been separately reported in generalized anxiety disorder (GAD), whether anomalous neurovascular coupling would still be presented in such disease is hitherto unknown. In this study, the neuronal activity and blood supply were measured using the functional connectivity strength (FCS) and cerebral blood flow (CBF). The voxel-wise CBF-FCS correlations and CBF/FCS ratio were separately used to assess global and local neurovascular coupling in participants. Patients with GAD showed decreased voxel-wise CBF-FCS correlation, implicating global neurovascular decoupling. They also exhibited increased CBF/FCS ratio in the right superior parietal gyrus (SPG), and the enhanced CBF/FCS ratio in this region was negatively correlated with the self-esteem scores of GAD. The abnormal neurovascular coupling of GAD may indicate the disrupted balance between the intrinsic functional organization of the brain and corresponding blood perfusion of patients, and the abnormally increased local neurovascular coupling of the right SPG may be correlated with the abnormal self in GAD. These findings provide new information in understanding the brain dysfunction and abnormal cognition of GAD from the perspective of neurovascular coupling.

Superficial white-matter functional networks changes in bipolar disorder patients during depressive episodes.

BACKGROUND: Bipolar disorder is a common psychiatric disorder characterized by insufficient or ineffective connections associated with white-matter (WM) abnormalities. Previous studies have detected the structural attributes of WM using magnetic resonance imaging (MRI) or diffusion tensor imaging, however, they failed to disentangle the dysfunctional organization within the WM. METHODS: This study aimed to uncover the WM functional connectivity (FC) in 45 bipolar disorder patients during depressive episodes (BDD) and 45 healthy controls based on resting-state functional MRI. Eight WM functional networks were identified by using a clustering analysis of voxel-based correlation profiles, which were further classified into superficial, middle and deep layers of networks. RESULTS: Group comparisons on the FCs among 8 WM networks showed that the superficial tempofrontal network (TFN) in BDD patients had increased FC with the superficial cerebellar network (CN) and with the superficial pre/post-central network (PCN). Further, support vector regression prediction analysis results revealed that the increased FCs of CN-TFN and PCN-TFN could be served as features to predict the numbers of depressive episode in BDD patients. CONCLUSIONS: The current study extended our knowledge about the impaired WM functional connections associated with emotional and sensory-motor perception processing in BDD, which may facilitate the interpretation of the pathophysiology mechanisms underlying BDD.