1. Depression Frequency-dependent Function Connectivity Group Topological Changes 2. Depression Based On Resting FMRI Brain Functional Connectivity Abnormal Density

BackgroundMajor depressive disorder (MDD) is among the most common forms of mental disorder with a world-wide prevalence of 16%across the lifespan and 6.6%across a 12 month period. A recent review of MDD found replicable grey matter alterations in the frontal cortex, cingulate cortex, orbitalfrontal cortex, hippocampus and straitum. A meta-analytic review of diffusion tensor imaging (DTI) studies found consistent decreased fractional anisotropy in the bilateral frontal cortex, right fusiform gyrus and right occipital cortex. Evidence from functional magnetic resonance imaging (fMRI) studies also points to abnormal activity in the frontal lobe, insular cortex, temporal lobe, occipital lobe and subcortical structures. A possible and plausible interpretation of these wide regional alterations is that depression is associated with aberrant coupling between these anatomical regions, which is supported by functional connectivity studies of MDD. Major depressive disorder is associated with aberrant topological organizations of brain networks. However, whether this aberrance is shown in broader frequency bands or in a specific frequency band remains unknown. Given previous graph theory based studies of MDD, We hypothesized that the brain networks of MDD patients would be disrupted at both global and regional levels. A recent study showed that intelligence was mediated by the coupling of brain networks across several frequency bands. We thus also hypothesized that the aberrant brain networks of MDD patients may be manifestated across multiple frequency intervals. PurposeWe aim to examin the topological organization of the brain networks of MDD patients in R-fMRI data and to find the specific and most salient wavelet scale of topological alterations.Method50 patients diagnosed with major depressive disorder and 50 normal controls participated in this investigation. All images were acquired on a 3.0-T Siemens Trio MRI scanner. Data preprocessing was performed using DPARSF. Nodes were obtained by anatomically dividing the brain into 112 distinct regions according to the Harvard-Oxford atlas. The maximal overlap discrete wavelet transform (MODWT) method was used to decompose each regional mean R-fMRI time series into four successive scales or frequency intervals (Scale 1,0.12-0.25Hz; Scale 20.06-0.12Hz; Scale 3,0.03-0.06Hz; Scale 4,0.015-0.03Hz).Frequency dependent topological measures based on graph theory were calculated from wavelet decomposed resting state functional brain signals.Group comparisons of topological metrics (global and regional) were carried out by permutation tests (10000 permutations) while controlling for gender, age and education. Partial correlation analysis was employed to assess the relationships between topological metrics and clinical variables (HRSD scores and disease durations) while regressing out nuisance variables (i.e. gender, age, education).ResultsThe patient group featured less connections, weaker connections and shorter anatomical connections. Global topological metrics exhibited significant alterations in Scale 3 but not in the other Scales. In patients, the clustering coefficient and the global efficiency were reduced while the characteristic path length was increased. Patients had decreased degree centrality predominately in nodes relevant to executive function, emotion processing and basic sensory function. They also showed increased betweenness centrality in cortical midline structures (CMS), which are part of the default mode network and are a core component of self processing. None of the global topological metrics significantly covaried with HRSD score or disease duration. Among the regions showing significant group differences, the bilateral insular cortex and bilateral planum polare exhibited positive and significant correlations with HRSD scoresConclusionThe finding provides the first systematic evidence that depression is associated with frequency specific global and local topological disruptions and highlights the importance of frequency information in investigating major depressive disorders.BackgroundMajor depressive disorder (MDD) is among the most common forms of mental disorder with a world-wide prevalence of 16%across the lifespan and 6.6%across a 12 month period.Some neuroimaging studies have reported that MDD exhibits abnormal functional connectivity in specific brain networks. Thus, advanced neuroimaging technologies may aid to understand the pathophysiological mechanisms of MDD.Purposewe used voxel-based functional connectivity density (FCD) analyses to investigate the difference between patients with MDD and health controls in functional network.METHODSWe investigated changes in brain functional connectivity in 50 patients with MDD and 51 healthy controls. Functional connectivity density mapping (FCDM), a voxelwise data-driven technique, was employed to compute local and global FCD maps. Then long-range FCD values were calculated and group analyses performed between patents with MDD and healthy controls.RESULTS:We found that patients with MDD showed reduced lFCD and gFCD in the left occipital lobe. There is no significant difference in long-range FCD between MDD group and HC group. In the middle frontal gyrus showing significant correlations between lFCD and HRSD score.CONCLUSION:The present results support the hypothesis that patients with MDD are associated with reduced lFCD and gFCD. This might be a biomarker of MDD. This study adds new knowledge to our understanding of the pathophysiological mechanisms underlying MDD.