Transdiagnostic and diagnosis-specific dynamic functional connectivity anchored in the right anterior insula in major depressive disorder and bipolar depression

2018 ◽  
Vol 85 ◽  
pp. 7-15 ◽  
Author(s):  
Yajing Pang ◽  
Heng Chen ◽  
Yifeng Wang ◽  
Zhiliang Long ◽  
Zongling He ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Bipolar Depression ◽  
Anterior Insula ◽  
Major Depressive ◽  
Dynamic Functional Connectivity ◽  
The Right

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

2020 ◽  
Vol 54 (8) ◽  
pp. 832-842 ◽  
Author(s):  
Yajing Pang ◽  
Huangbin Zhang ◽  
Qian Cui ◽  
Qi Yang ◽  
Fengmei Lu ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Sex Education ◽  
Orbitofrontal Cortex ◽  
Bipolar Depression ◽  
Test Group ◽  
Precentral Gyrus ◽  
Major Depressive ◽  
Sensorimotor Network

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.

Altered dynamic functional connectivity in weakly-connected state in major depressive disorder

2019 ◽  
Vol 130 (11) ◽  
pp. 2096-2104 ◽  
Author(s):  
Zhijun Yao ◽  
Jie Shi ◽  
Zhe Zhang ◽  
Weihao Zheng ◽  
Tao Hu ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Major Depressive ◽  
Dynamic Functional Connectivity

scholarly journals Disruption of Neural Activity and Functional Connectivity in Adolescents With Major Depressive Disorder Who Engage in Non-suicidal Self-Injury: A Resting-State fMRI Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Qian Huang ◽  
Muni Xiao ◽  
Ming Ai ◽  
Jianmei Chen ◽  
Wo Wang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Neural Activity ◽  
Resting State ◽  
Brain Regions ◽  
Major Depressive ◽  
Superior Frontal Gyrus ◽  
Self Injury ◽  
The Right

Background: Non-suicidal self-injury (NSSI), which commonly occurs during adolescence, often co-occurs with major depressive disorder (MDD). However, the underlying neurobiological mechanisms in adolescents with MDD who engage in NSSI remain unclear. The current study examined the aberrant local neural activity in certain areas of the visual regions and the default mode network (DMN) and the resting-state functional connectivity (rs-FC) in changed brain regions in adolescents with MDD who engage in NSSI and adolescents with MDD only.Methods: A total of 67 adolescents with MDD were divided into two groups based on their NSSI behavior: the NSSI group (n = 31) and an age-, gender-, and education-matched MDD group (n = 36). The Hamilton Depression Rating Scale (HAMD) was used to assess the severity of MDD. Amplitude of low-frequency fluctuation (ALFF) analysis was used to detect alterations in local neural activity. Brain regions with aberrant neural activity were considered regions of interest (ROI). ALFF-based rs-FC analysis was used to further explore the underlying changes in connectivity between ROI and other areas in the NSSI group. Correlation analyses were performed to examine the relationship between neural changes and clinical characteristics.Results: There was no significant difference in HAMD scores between the two groups. ALFF analysis revealed that, compared to adolescents with MDD only, adolescents with MDD who engaged in NSSI displayed significantly enhanced neural activity in the right fusiform gyrus (FFG. R) and the right median cingulate and paracingulate gyri (DCG. R). Significantly reduced rs-FC of the FFG. R-bilateral medial orbital of the superior frontal gyrus (ORBsupmed. L/R)/bilateral medial superior frontal gyrus (SFGmed. L/R), FFG. R-bilateral posterior cingulate gyrus (PCG. L/R), DCG. R-left pallidum (PAL. L), DCG. R-right superior temporal gyrus (STG. R), and DCG. R-right postcentral gyrus (PoCG. R)/right inferior parietal lobule (IPL. R) was found in adolescents with MDD who were engaged in NSSI. Additionally, no significant correlations were observed between ALFF or rs-FC values and the HAMD scores between the two groups.Limitations: Owing to the cross-sectional design, the alterations in ALFF and rs-FC values in the FFG. R and DCG. R could not demonstrate that it was a state or feature in adolescents with MDD who engaged in NSSI. Additionally, the sample size was relatively small.Conclusions: This study highlights changes in regional brain activity and remote connectivity in the FFG. R and DCG. R in adolescents with MDD who engage in NSSI. This could provide a new perspective for further studies on the neurobiological mechanism of NSSI behavior in adolescents with MDD.

scholarly journals Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder

2016 ◽  
Vol 37 (8) ◽  
pp. 2918-2930 ◽  
Author(s):  
Murat Demirtaş ◽  
Cristian Tornador ◽  
Carles Falcón ◽  
Marina López‐Solà ◽  
Rosa Hernández‐Ribas ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Major Depressive ◽  
Dynamic Functional Connectivity

Cerebellar-cerebral dynamic functional connectivity alterations in major depressive disorder

2020 ◽  
Vol 275 ◽  
pp. 319-328 ◽  
Author(s):  
Dao-min Zhu ◽  
Ying Yang ◽  
Yu Zhang ◽  
Chunli Wang ◽  
Yajun Wang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Major Depressive ◽  
Dynamic Functional Connectivity

scholarly journals Shared dynamic functional connectivity across schizophrenia, bipolar disorder and major depressive disorder

2019 ◽  
Author(s):  
Chao Li ◽  
Ke Xu ◽  
Mengshi Dong ◽  
Yange Wei ◽  
Jia Duan ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Major Depressive ◽  
Dynamic Functional Connectivity ◽  
State Dependent ◽  
Window Method ◽  
Assessment And Treatment ◽  
Post Hoc

AbstractDynamic functional connectivity (DFC) analysis can capture time-varying properties of connectivity and may provide further information about transdiagnostic psychopathology across major psychiatric disorders. In this study, we used resting state functional MRI and a sliding-window method to study DFC in 150 schizophrenia (SZ), 100 bipolar disorder(BD), 150 major depressive disorder (MDD), and 210 healthy controls (HC). DFC were clustered into two functional connectivity states. Significant 4-group differences in DFC were found only in state 2. Post hoc analyses showed that transdiagnostic dysconnectivity among there disorders featured decreased connectivity within visual, somatomotor, salience and frontoparietal networks. Our results suggest that decreased connectivity within both lower-order (visual and somatomotor) and higher-order (salience and frontoparietal) networks may serve as transdiagnostic marker of these disorders, and that these dysconnectivity is state-dependent. Targeting these dysconnectivity may improve assessment and treatment for patients that having more than one of these disorders at the same time.

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