scholarly journals Abnormal resting state effective connectivity within the default mode network in major depressive disorder: A spectral dynamic causal modeling study

2017 ◽  
Vol 7 (7) ◽  
pp. e00732 ◽  
Author(s):  
Liang Li ◽  
Baojuan Li ◽  
Yuanhan Bai ◽  
Wenlei Liu ◽  
Huaning Wang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Effective Connectivity ◽  
Causal Modeling ◽  
Dynamic Causal Modeling ◽  
Major Depressive ◽  
Default Mode ◽  
Modeling Study

scholarly journals Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns

2020 ◽  
Vol 28 ◽  
pp. 102514
Author(s):  
Sugai Liang ◽  
Wei Deng ◽  
Xiaojing Li ◽  
Andrew J. Greenshaw ◽  
Qiang Wang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Major Depressive ◽  
Default Mode ◽  
Network Patterns

scholarly journals Reduced Default Mode Network Functional Connectivity in Patients with Recurrent Major Depressive Disorder

2018 ◽  
Author(s):  
Chao-Gan Yan ◽  
Xiao Chen ◽  
Le Li ◽  
Francisco Xavier Castellanos ◽  
Tong-Jian Bai ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Research Groups ◽  
Major Depressive ◽  
Default Mode ◽  
Normal Controls

ABSTRACTMajor Depressive Disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol prior to aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. Finally, all resting-state fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.SIGNIFICANCE STATEMENTFunctional connectivity within the default mode network in major depressive disorder patients has been frequently reported abnormal but with contradicting directions in previous small sample size studies. In creating the REST-meta-MDD consortium containing neuroimaging data of 1,300 depressed patients and 1,128 normal controls from 25 research groups in China, we found decreased default mode network functional connectivity in depressed patients, driven by patients with recurrent depression, and associated with current medication treatment but not with disease duration. These findings suggest that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments.

scholarly journals Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

2016 ◽  
Vol 10 ◽  
Author(s):  
Maksim G. Sharaev ◽  
Viktoria V. Zavyalova ◽  
Vadim L. Ushakov ◽  
Sergey I. Kartashov ◽  
Boris M. Velichkovsky
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Effective Connectivity ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Fmri Data ◽  
Network Dynamic ◽  
Dynamic Causal Modeling ◽  
Default Mode

scholarly journals Multiscale Neural Modeling of Resting-state fMRI Reveals Executive-Limbic Malfunction as a Core Mechanism in Major Depressive Disorder

2020 ◽  
Author(s):  
Guoshi Li ◽  
Yujie Liu ◽  
Yanting Zheng ◽  
Ye Wu ◽  
Danian Li ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Resting State ◽  
Effective Connectivity ◽  
Strong Support ◽  
Resting State Fmri ◽  
Salience Network ◽  
Large Sample Size ◽  
Major Depressive ◽  
Default Mode

Computational neuroimaging has played a central role in characterizing functional abnormalities in major depressive disorder (MDD). However, most of existing non-invasive analysis tools based on functional magnetic resonance imaging (fMRI) are largely descriptive and superficial, thus cannot offer a deep mechanistic understanding of neural circuit dysfunction in MDD. To overcome this limitation, we significantly improved a previously developed Multiscale Neural Model Inversion (MNMI) framework that can link mesoscopic neural interaction with macroscale network dynamics and enable the estimation of both intra-regional and inter-regional effective connectivity. We applied the improved MNMI approach to test two well-established competing hypotheses of MDD pathophysiology (default mode-salience network disruption vs. executive-limbic network malfunction) based on resting-state fMRI with a relatively large sample size. Results indicate that MDD is primarily characterized by aberrant circuit interactions within the executive-limbic network, rather than the default mode-salience network. Specifically, we observed reduced frontoparietal effective connectivity that potentially contributes to hypoactivity in the dorsolateral prefrontal cortex (dlPFC), and decreased intrinsic inhibition combined with increased excitation from the superior parietal cortex (SPC) that potentially leads to amygdala hyperactivity, together resulting in connectivity imbalance in the PFC-amygdala circuit that pervades in MDD. Moreover, the model unravels reduced PFC-to-hippocampus excitation but decreased SPC-to-thalamus inhibition in MDD population that potentially leads to hypoactivity in hippocampus and hyperactivity in thalamus, consistent with previous experimental data. Overall, our findings provide strong support for the long-standing limbic-cortical dysregulation model in major depression but also offer novel insights into the multi-scale pathophysiology of this deliberating disease.

scholarly journals Effects of escitalopram therapy on resting-state functional connectivity of subsystems of the default mode network in unmedicated patients with major depressive disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian Cui ◽  
Yun Wang ◽  
Rui Liu ◽  
Xiongying Chen ◽  
Zhifang Zhang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Fmri Data ◽  
Healthy Controls ◽  
Resting State Functional Connectivity ◽  
Major Depressive ◽  
Default Mode

AbstractAntidepressants are often the first-line medications prescribed for patients with major depressive disorder (MDD). Given the critical role of the default mode network (DMN) in the physiopathology of MDD, the current study aimed to investigate the effects of antidepressants on the resting-state functional connectivity (rsFC) within and between the DMN subsystems. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 36 unmedicated MDD patients at baseline and after escitalopram treatment for 12 weeks. The rs-fMRI data were also collected from 61 matched healthy controls at the time point with the same interval. Then, we decomposed the DMN into three subsystems based on a template from previous studies and computed the rsFC within and between the three subsystems. Finally, repeated measures analysis of covariance was conducted to identify the main effect of group and time and their interaction effect. We found that the significantly reduced within-subsystem rsFC in the DMN core subsystem in patients with MDD at baseline was increased after escitalopram treatment and became comparable with that in the healthy controls, whereas the reduced within-subsystem rsFC persisted in the DMN dorsal medial prefrontal cortex (dMPFC) and medial temporal subsystems in patients with MDD following escitalopram treatment. In addition, the reduced between-subsystem rsFC between the core and dMPFC subsystem showed a similar trend of change after treatment in patients with MDD. Moreover, our main results were confirmed using the DMN regions from another brain atlas. In the current study, we found different effects of escitalopram on the rsFC of the DMN subsystems. These findings deepened our understanding of the neuronal basis of antidepressants’ effect on brain function in patients with MDD. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377. Registration number: ChiCTR-OOC-17012566.

scholarly journals All roads lead to the default-mode network—global source of DMN abnormalities in major depressive disorder

2020 ◽  
Vol 45 (12) ◽  
pp. 2058-2069 ◽  
Author(s):  
Andrea Scalabrini ◽  
Benedetta Vai ◽  
Sara Poletti ◽  
Stefano Damiani ◽  
Clara Mucci ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Major Depressive ◽  
Default Mode ◽  
Global Source
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