scholarly journals Brain network connectivity in major depression: extending findings from a large public data set by meta-analysis across sites

2020 ◽  
Author(s):  
Leonardo Tozzi ◽  
Leanne Maree Williams
Keyword(s):  
Major Depression ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Meta Analysis ◽  
Network Connectivity ◽  
Strong Impact ◽  
Data Set ◽  
Default Mode ◽  
Depressed Patients ◽  
Public Data

In this short communication, we test whether patients with major depression and healthy individuals have different functional connectivity within established brain networks. To this end, we leverage a very large multi-site data set of resting state fMRI data (1,300 depressed patients and 1,128 controls) collected by 25 groups. A previous study conducted on this data set compared functional connectivity of the default mode network between the two groups. In our investigation, we performed a meta-analysis across sites quantifying the effects of depression and symptom severity on connectivity of several brain-wide networks beyond the default mode. Running a meta-analysis instead of a mega-analysis also allowed us to calculate effect sizes, heterogeneity and prediction intervals that will be valuable to inform future studies wishing to investigate network functional connectivity in depression. Our results indicate that network connectivity differences between depressed and healthy subjects are consistently small, with confidence intervals almost always encompassing zero, in line with the mixed findings from previous research. Default mode network connectivity differences between depressed patients and controls were exceptionally heterogeneous across sites, suggesting the existence of depression sub-types with normo- and hypo-connected default mode network or a strong impact of clinical confounds on default mode network connectivity. The only networks for which connectivity in depressed individuals was consistently lower than in controls were the somato-motor and visual networks, which could be promising understudied targets for future investigation. Overall, we highlight the need of minimizing heterogeneity in future multi-site studies on functional connectivity in depression and the need for more research on novel taxonomies of mental illness that are robustly anchored in brain function.

scholarly journals The Effect of Seed Location on Functional Connectivity: Evidence from an Image-Based Meta-Analysis

2021 ◽  
Author(s):  
Mengting Li ◽  
Jiawei Sun ◽  
Linlin Zhan ◽  
Yating Lv ◽  
Xize Jia ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Meta Analysis ◽  
Brain Diseases ◽  
Seed Selection ◽  
Resting State Functional Connectivity ◽  
Future Studies ◽  
Default Mode ◽  
Analytic Maps ◽  
Selection Of

Abstract Default mode network (DMN) is the most involved network in the study of brain development and brain diseases. Resting-state functional connectivity (rs-FC) is the most used method to study DMN, but different studies are inconsistent in the selection of seed. To evaluate the effect of different seed selection on rs-FC, we conducted an image-based meta-analysis (IBMA). We identified 59 coordinates of seed regions of interest (ROIs) within the default mode network (DMN) from 11 studies (retrieved from Web of Science and Pubmed) to calculate the functional connectivity; then, the uncorrected t maps were obtained from the statistical analyses. The IBMA was performed with the t maps. We demonstrate that the overlap of meta-analytic maps across different seeds’ ROIs within DMN is relatively low, which cautions us to be cautious with seeds’ selection. Future studies using the seed-based functional connectivity method should take the reproducibility of different seeds into account. The choice of seed may significantly affect the connectivity results.

scholarly journals Altered functional connectivity of cortical networks in semantic variant Primary Progressive Aphasia

2020 ◽  
Author(s):  
Haroon Popal ◽  
Megan Quimby ◽  
Daisy Hochberg ◽  
Bradford C. Dickerson ◽  
Jessica A. Collins
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Large Scale ◽  
Network Connectivity ◽  
Primary Progressive Aphasia ◽  
Cognitive Networks ◽  
Default Mode ◽  
Progressive Aphasia ◽  
Primary Progressive ◽  
Semantic Variant

AbstractAs their illness progresses, patients with the semantic variant of Primary Progressive Aphasia (svPPA) frequently exhibit peculiar behaviors indicative of altered visual attention or an increased interest in artistic endeavors. In the present study, we examined changes within and between large-scale functional brain networks that may explain this altered visual behavior. We first examined the connectivity of the visual association network, the dorsal attention network, and the default mode network in healthy young adults (n=89) to understand the typical architecture of these networks in the healthy brain. We then compared the large-scale functional connectivity of these networks in a group of svPPA patients (n=12) to a group of age-matched cognitively normal controls (n=30). Our results showed that the between-network connectivity of the dorsal attention and visual association networks was elevated in svPPA patients relative to controls. We further showed that this heightened between-network connectivity was associated with a decrease in the within-network connectivity of the default mode network, possibly due to progressive degeneration of the anterior temporal lobes in svPPA. These results suggest that focal neurodegeneration can lead to the reorganization of large-scale cognitive networks beyond the primarily affected network(s), possibly contributing to cognitive or behavioral changes that are commonly present as part of the clinical phenotype of svPPA.

scholarly journals Instability of default mode network connectivity in major depression: a two-sample confirmation study

2017 ◽  
Vol 7 (4) ◽  
pp. e1105-e1105 ◽  
Author(s):  
T Wise ◽  
L Marwood ◽  
A M Perkins ◽  
A Herane-Vives ◽  
R Joules ◽  
...  
Keyword(s):  
Major Depression ◽  
Default Mode Network ◽  
Network Connectivity ◽  
Default Mode

scholarly journals Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Silvia Ingala ◽  
Jori Tomassen ◽  
Lyduine E Collij ◽  
Naomi Prent ◽  
Dennis van ‘t Ent ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Amyloid Beta ◽  
Default Mode Network ◽  
Network Connectivity ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Binding Potential ◽  
Amyloid Burden ◽  
Default Mode ◽  
Posterior Cingulate

Abstract Cortical accumulation of amyloid beta is one of the first events of Alzheimer’s disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer’s disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer’s disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline.

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