Resting-State Functional Connectivity in Major Depression: Abnormally Increased Contributions from Subgenual Cingulate Cortex and Thalamus

Department of Neurology and Neurological Sciences, Stanford University Medical Center, Stanford, California 94305-5235, USA.
Biological Psychiatry (Impact Factor: 10.26). 10/2007; 62(5):429-37. DOI: 10.1016/j.biopsych.2006.09.020
Source: PubMed


Positron emission tomography (PET) studies of major depression have revealed resting-state abnormalities in the prefrontal and cingulate cortices. Recently, fMRI has been adapted to examine connectivity within a specific resting-state neural network--the default-mode network--that includes medial prefrontal and anterior cingulate cortices. The goal of this study was to examine resting-state, default-mode network functional connectivity in subjects with major depression and in healthy controls.
Twenty-eight subjects with major depression and 20 healthy controls underwent 5-min fMRI scans while resting quietly. Independent component analysis was used to isolate the default-mode network in each subject. Group maps of the default-mode network were compared. A within-group analysis was performed in the depressed group to explore effects of depression refractoriness on functional connectivity.
Resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network were significantly greater in the depressed subjects. Within the depressed group, the length of the current depressive episode correlated positively with functional connectivity in the subgenual cingulate.
This is the first study to explore default-mode functional connectivity in major depression. The findings provide cross-modality confirmation of PET studies demonstrating increased thalamic and subgenual cingulate activity in major depression. Further, the within-subject connectivity analysis employed here brings these previously isolated regions of hypermetabolism into the context of a disordered neural network. The correlation between refractoriness and subgenual cingulate functional connectivity within the network suggests that a quantitative, resting-state fMRI measure could be used to guide therapy in individual subjects.

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Available from: Heather A Kenna, Oct 04, 2015
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    • "thy controls , depressed patients showed increased resting state functional connectivity of the DMN areas , such as the subgenual cingulate cortex and thalamus , especially increased medial PFC ( mPFC ) functional connectivity with other resting - state brain networks , including the cognitive control network , affective network , and DMN itself ( Greicius et al . , 2007 ; Sheline et al . , 2010 ) . Other researchers found that part of the DMN areas showed decreased resting state functional connectivity , such as the PCC / PCu and caudate , cerebellar regions and other DMN areas ( e . g . , mPFC and PCC / PCu ; Bluhm et al . , 2009 ; Liu et al . , 2012 ) . Zhu et al . ( 2012 ) observed increased anterio"
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    ABSTRACT: Previous studies have focused on resting-state default mode network (DMN) alterations in the development and maintenance of depression; however, only a few studies have addressed DMN changes during task-related processing and their results are inconsistent. Therefore, we explored DMN patterns in young adult patients with first-episode, treatment-naïve major depressive disorder (MDD) performing an implicit emotional processing task. Patients with MDD (N = 29) and healthy controls (N = 33) were subjected to functional magnetic resonance imaging (fMRI) at rest and while performing a gender judgment task. Group independent component analysis (ICA) was used to identify DMN component under task state for both groups. The DMN of participants with MDD had decreased functional connectivity in bilateral prefrontal areas compared to controls. Right prefrontal gyrus connectivity for MDD patients correlated negatively with scores on maladaptive scales of the Cognitive Emotion Regulation Questionnaire (CERQ). Our findings suggest that depressed people have altered DMN patterns during implicit emotional processing, which might be related to impaired internal monitoring and emotional regulation ability.
    Frontiers in Psychology 08/2015; 6:1198. DOI:10.3389/fpsyg.2015.01198 · 2.80 Impact Factor
    • "llosal and subgenual cingulate respectively ( Bijanki et al . , 2014 ) . Converging evidence from an array of neuroimaging modalities and participant groups has implicated the vAC in depressive symptom manifestation ( Mayberg , 2009 ) . For example , elevated blood flow in the vAC gray matter is noted in antidepressant treatment non - responders ( Greicius et al . , 2007 ) , currently depressed ( Dougherty et al . , 2003 ; Mayberg et al . , 2005 ; Kennedy et al . , 2007 ) , and transiently sad healthy normal participants ( Mayberg et al . , 1999 ; Zald et al . , 2002 ) . Changes in blood flow or glucose metabolism in the vAC gray matter are also noted in response to various interventions , such as antid"
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    ABSTRACT: We sought to characterize the relationship between integrity of the white matter underlying the ventral anterior cingulate (vAC) and depressive symptoms in older adults with atherosclerotic vascular disease (AVD), a condition associated with preferential degeneration of the white matter. The ventral anterior cingulate was defined as including white matter underlying ventral Brodmann Area 24 and Brodmann Area 25, corresponding with the “subcallosal” and “subgenual” cingulate respectively. This region of interest was chosen based on the preponderance of evidence that the white matter in the region plays a critical role in the manifestation of depressive symptoms. Participants had current unequivocal diagnoses of AVD and were between 55 and 90 years old. Fractional anisotropy (FA) was used as an index of white matter integrity and organization. Whole-brain mean diffusivity (MD) was used as an index of global white matter lesion burden. Depressive symptoms were measured using the Symptom Checklist-90-Revised (SCL-90-R) Depression Scale. Depressive symptoms were significantly related to low FA in the right vAC (r=-.356, DF=30, p=.045) but not the left vAC (r=.024, DF=30, p=.896) after controlling for total brain MD (a statistical control for global white matter lesion burden). Further, depressive symptoms were significantly related to low FA in the right vAC (r=-0.361, DF=31, p=.039), but not the left vAC (r=.259, DF=31, p=.145) when controlled for the contralateral vAC FA. The correlation coefficients for this follow-up analysis were found to be significantly different between left and right vAC (Z=2.310, p=.021). Poor white matter health in the vAC may be a biological mechanism for depressive symptoms in older adults with vascular disease. Further studies may corroborate that the right vAC plays a unique role in depressive symptom manifestation in cases where the white matter is preferentially affected, as is the case in AVD. This could lead to future targeting of
    Frontiers in Human Neuroscience 07/2015; 9. DOI:10.3389/fnhum.2015.00408 · 2.99 Impact Factor
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    • "Notably, neuroimaging studies have implicated network dysfunction in MDD. In MDD, increased connectivity between the DMN and both the subgenual anterior cingulate cortex (sgACC) and thalamus has been observed (Davey et al., 2012; Greicius et al., 2007; Li et al., 2013; Posner et al., 2013). Decreased connectivity between the DMN and the cerebellum and prefrontal cortex, and increased connectivity between the DMN and the visual system and parahippocampal gyrus (Guo et al., 2013) have also been noted. "
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    ABSTRACT: Functional magnetic resonance imaging (fMRI) studies have revealed the existence of robust, interconnected brain networks exhibiting correlated low frequency fluctuations during rest, which can be derived by examining inherent spatio-temporal patterns in functional scans independent of any a priori model. In order to explore the electrophysiological underpinnings of these networks, analogous techniques have recently been applied to magnetoencephalography (MEG) data, revealing similar networks that exhibit correlated low frequency fluctuations in the power envelope of beta band (14-30Hz) power. However, studies to date using this technique have concentrated on healthy subjects, and no method has yet been presented for group comparisons. We extended the ICA resting state MEG method to enable group comparisons, and demonstrate the technique in a sample of subjects with major depressive disorder (MDD). We found that the intrinsic resting state networks evident in fMRI appeared to be disrupted in individuals with MDD compared to healthy participants, particularly in the subgenual cingulate, although the electrophysiological correlates of this are unknown. Networks extracted from a combined group of healthy and MDD participants were examined for differences between groups. Individuals with MDD showed reduced correlations between the subgenual anterior cingulate (sgACC) and hippocampus in a network with primary nodes in the precentral and middle frontal gyri. Individuals with MDD also showed increased correlations between insulo-temporal nodes and amygdala compared to healthy controls. To further support our methods and findings, we present test/re-test reliability on independent recordings acquired within the same session. Our results demonstrate that group analyses are possible with the resting state MEG-independent components analysis (ICA) technique, highlighting a new pathway for analysis and discovery. This study also provides the first evidence of altered sgACC connectivity with a motor network. This finding, reliable across multiple sessions, suggests that the sgACC may partially mediate the psychomotor symptoms of MDD via synchronized changes in beta-band power, and expands the idea of the sgACC as a hub region mediating cognitive and emotional symptomatic domains in MDD. Findings of increased connectivity between the amygdala and cortical nodes further supports the role of amygdalar networks in mediated depressive symptomatology. NCT00024635 (ZIA-MH002927-04). Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 05/2015; 118. DOI:10.1016/j.neuroimage.2015.05.051 · 6.36 Impact Factor
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