Connectivity In Major Depression Research Articles

Fronto-cingulate effective connectivity in major depression: A study with fMRI and dynamic causal modeling

Functional imaging studies are indicating disrupted error monitoring and executive control in a fronto-cingulate network in major depression. However, univariate statistical analyses allow only for a limited assessment of directed neuronal interactions. Therefore, the present study used dynamic causal modeling (DCM) of a fronto-cingulate network to re-analyze the data from a preceding fMRI study in 16 drug-free patients with major depression and 16 healthy controls using the Stroop Color-Word Test (Wagner et al., 2006).In both groups, a significant reciprocal interregional connectivity was found in a cognitive control network including prefrontal cortex (PFC) and dorsal anterior cingulate cortex (ACC). With regard to intrinsic connections we detected a significant difference for dorsal to rostral ACC connectivity between depressive patients and controls in terms of higher connectivity in patients. Additionally, a task by group interaction was observed for the bilinear interaction signaling enhanced task-related input from the dorsal to rostral ACC in subjects with depression. This could be related to the inability of patients to down-regulate rostral ACC activation as observed in the previous univariate analysis.The correlation between interference scores and intrinsic connections from dorsal ACC to dorsolateral PFC (DLPFC) was significant for both groups together, but no significant group differences in correlations could be detected. Thus, the observed relationship between control functions of the dorsal ACC exerted over DLPFC and interference scores appears to be valid in both patients with depression and controls. The findings are consistent with current models of a differential involvement of the fronto-cingulate system in the pathophysiology of major depression.

Impaired functional connectivity at EEG alpha and theta frequency bands in major depression.

Recent reports on functional brain imaging in major depression have lead to an assumption that observed psychopathology might be related to an altered brain functional connectivity. Our hypothesis was that an increase in brain functional connectivity occurs in major depression. As a measure of functional connectivity, the electroencephalogram (EEG) structural synchrony approach was used in 12 medication-free depressive outpatients and 10 control subjects. Differences in the number and strength of structurally synchronized EEG patterns were compared between groups. In depressive patients the number and strength of short cortex functional connections were significantly larger for the left than for the right hemisphere, while the number and strength of long functional connections were significantly larger for the right than for the left hemisphere. Some of the functional connections were positively correlated with the severity of depression, thus being predictive. These were short-range anterior, posterior, and left hemisphere functional connections for the alpha frequency band and short-range anterior functional connections for the theta frequency band. The topology of the most representative functional connections among all patients with major depression indicated that the right anterior and left posterior brain parts may discriminate depressive patients from healthy controls. The obtained data support our hypothesis that there is an increase in brain functional connectivity in major depression. This finding was interpreted within the semantic framework, where different specialization of left (monosemantic context) and right (polysemantic context) hemispheres is functionally insufficient in patients with depression.

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

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.

Limbic–frontal circuitry in major depression: a path modeling metanalysis

This paper reports the results of an across lab metanalysis of effective connectivity in major depression (MDD). Using FDG PET data and Structural Equation Modeling, a formal depression model was created to explicitly test current theories of limbic–cortical dysfunction in MDD and to characterize at the path level potential sources of baseline variability reported in this patient population. A 7-region model consisting of lateral prefrontal cortex (latF9), anterior thalamus (aTh), anterior cingulate (Cg24), subgenual cingulate (Cg25), orbital frontal cortex (OF11), hippocampus (Hc), and medial frontal cortex (mF10) was tested in scans of 119 depressed patients and 42 healthy control subjects acquired during three separate studies at two different institutions. A single model, based on previous theory and supported by anatomical connectivity literature, was stable for the three groups of depressed patients. Within the context of this model, path differences among groups as a function of treatment response characteristics were also identified. First, limbic–cortical connections (latF9-Cg25-OF11-Hc) differentiated drug treatment responders from nonresponders. Second, nonresponders showed additional abnormalities in limbic–subcortical pathways (aTh-Cg24-Cg25-OF11-Hc). Lastly, more limited limbic–cortical (Hc-latF9) and cortical–cortical (OF11-mF10) path differences differentiated responders to cognitive behavioral therapy (CBT) from responders to pharmacotherapy. We conclude that the creation of such models is a first step toward full characterization of the depression phenotype at the neural systems level, with implications for the future development of brain-based algorithms to determine optimal treatment selection for individual patients.