Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity

2013 ◽  
Vol 44 (10) ◽  
pp. 2041-2051 ◽  
Author(s):  
F. Sambataro ◽  
N. D. Wolf ◽  
M. Pennuto ◽  
N. Vasic ◽  
R. C. Wolf
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Large Scale ◽  
Critical Role ◽  
Low Frequency ◽  
Network Connectivity ◽  
Brain Regions ◽  
Default Mode ◽  
Network Function ◽  
Functional Relevance

BackgroundMajor depressive disorder (MDD) is characterized by alterations in brain function that are identifiable also during the brain's ‘resting state’. One functional network that is disrupted in this disorder is the default mode network (DMN), a set of large-scale connected brain regions that oscillate with low-frequency fluctuations and are more active during rest relative to a goal-directed task. Recent studies support the idea that the DMN is not a unitary system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in depression, however, is unclear.MethodHere, we investigated the functional connectivity of distinct DMN subsystems and their interplay in depression using resting-state functional magnetic resonance imaging.ResultsWe show that patients with MDD exhibit increased within-network connectivity in posterior, ventral and core DMN subsystems along with reduced interplay from the anterior to the ventral DMN subsystems.ConclusionsThese data suggest that MDD is characterized by alterations of subsystems within the DMN as well as of their interactions. Our findings highlight a critical role of DMN circuitry in the pathophysiology of MDD, thus suggesting these subsystems as potential therapeutic targets.

scholarly journals Task-evoked Negative BOLD Response and Functional Connectivity in the Default Mode Network are Representative of Two Overlapping but Separate Neurophysiological Processes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
David B. Parker ◽  
Qolamreza R. Razlighi
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Low Frequency ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Bold Response ◽  
Default Mode ◽  
Macro Scale ◽  
Negative Bold

Abstract The topography of the default mode network (DMN) can be obtained with one of two different functional magnetic resonance imaging (fMRI) methods: either from the spontaneous but organized synchrony of the low-frequency fluctuations in resting-state fMRI (rs-fMRI), known as “functional connectivity”, or from the consistent and robust deactivations in task-based fMRI (tb-fMRI), here referred to as the “negative BOLD response” (NBR). These two methods are fundamentally different, but their results are often used interchangeably to describe the brain’s resting-state, baseline, or intrinsic activity. While the DMN was initially defined by consistent task-based decreases in blood flow in a set of specific brain regions using PET imaging, recently nearly all studies on the DMN employ functional connectivity in rs-fMRI. In this study, we first show the high level of spatial overlap between NBR and functional connectivity of the DMN extracted from the same tb-fMRI scan; then, we demonstrate that the NBR in putative DMN regions can be significantly altered without causing any change in their overlapping functional connectivity. Furthermore, we present evidence that in the DMN, the NBR is more closely related to task performance than the functional connectivity. We conclude that the NBR and functional connectivity of the DMN reflect two separate but overlapping neurophysiological processes, and thus should be differentiated in studies investigating brain-behavior relationships in both healthy and diseased populations. Our findings further raise the possibility that the macro-scale networks of the human brain might internally exhibit a hierarchical functional architecture.

A Classification Mechanism of Brain Functional fMRI in Resting State

2014 ◽  
Vol 687-691 ◽  
pp. 1087-1090
Author(s):  
Hui Zhou ◽  
Zhen Cheng Chen ◽  
Jian Ming Zhu ◽  
Dong Cui Wang ◽  
Biao Xu
Keyword(s):  
Hierarchical Clustering ◽  
Default Mode Network ◽  
Resting State ◽  
Low Frequency ◽  
Brain Regions ◽  
Default Mode ◽  
Complex Network Theory ◽  
Healthy Young People ◽  
Comparative Results ◽  
The Brain

To investigate the brain default mode network (DMN) of healthy young people, a novel hierarchical clustering method was proposed to detect similarities of low-frequency fluctuations between any two out of 160 regions of interest (ROI) all over the brain. Feature of these ROIs were firstextractedand analyzed the feature using hierarchical clustering approach.Combining with the strongest connected network node identified by network centric criterion, the default mode network which presented the strongest connectivity in resting state was then determined. The results demonstrated that cingulate had the highest value of average degree, making it the most suspectof where the centrality indices of DMN lay.The comparative results between nodes included by DMN returned by our method and these given by Dosenbach’s research showed quite high coincidence rates,indicating the proposed method of combining complex network theory and hierarchical clustering analysis feasible method to parse brain regions.

scholarly journals Altered insula–default mode network connectivity in fibromyalgia: a resting-state magnetoencephalographic study

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Fu-Jung Hsiao ◽  
Shuu-Jiun Wang ◽  
Yung-Yang Lin ◽  
Jong-Ling Fuh ◽  
Yu-Chieh Ko ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Network Connectivity ◽  
Default Mode

scholarly journals Symptoms of fatigue and depression is reflected in altered default mode network connectivity in multiple sclerosis

2018 ◽  
Author(s):  
Einar August Høgestøl ◽  
Gro Owren Nygaard ◽  
Dag Alnæs ◽  
Mona K. Beyer ◽  
Lars T. Westlye ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Default Mode Network ◽  
Symptom Burden ◽  
Network Connectivity ◽  
Principal Component ◽  
Brain Network ◽  
Common Symptom ◽  
Linear Regression Models ◽  
Default Mode ◽  
Network Function

Background: Fatigue and depression are frequent and often co-occurring symptoms in multiple sclerosis (MS). Resting-state functional magnetic resonance imaging (rs-fMRI) represents a promising tool for disentangling differential associations between depression and fatigue and brain network function and connectivity. In this study we tested for associations between symptoms of fatigue and depression and DMN connectivity in patients with MS. Materials and methods: Seventy-four MS patients were included on average 14 months after diagnosis. They underwent MRI scanning of the brain including rs-fMRI, and symptoms of fatigue and depression were assessed with Fatigue Severity Scale (FSS) and Beck Depression Inventory II (BDI). A principal component analysis (PCA) on FSS and BDI scores was performed, and the component scores were analysed using linear regression models to test for associations with default mode network (DMN) connectivity. Results: We observed higher DMN connectivity with higher scores on the primary principal component reflecting common symptom burden for fatigue and depression (Cohen's f2=0.075, t=2.17, p=0.03). The secondary principal component reflecting a pattern of low fatigue scores with high scores of depression was associated with lower DMN connectivity (Cohen's f2=0.067, t=-2.1, p=0.04). Using continuous mean scores of FSS we also observed higher DMN connectivity with higher symptom burden (t=3.1, p=0.003), but no significant associations between continuous sum scores of BDI and DMN connectivity (t=0.8, p=0.4). Conclusion: Multivariate decomposition of FSS and BDI data supported both overlapping and unique manifestation of fatigue and depression in MS patients. Rs-fMRI analyses showed that symptoms of fatigue and depression was reflected in altered DMN connectivity, and that higher DMN activity was seen in MS patients with fatigue even with low depression scores.

Sign in / Sign up

Export Citation Format

Share Document