Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder.
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ABSTRACT:
SUBMITTER: Demirtas M
PROVIDER: S-EPMC5074271 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Major depressive disorder (MDD) is a complex mood disorder characterized by persistent and overwhelming depression. Previous studies have identified abnormalities in large scale functional brain networks in MDD, yet most of them were based on static functional connectivity. In contrast, here we explored disrupted topological organization of dynamic functional network connectivity (dFNC) in MDD based on graph theory. One hundred and eighty-two MDD patients and 218 healthy controls were included in this study, all Chinese Han people. By applying group information guided independent component analysis (GIG-ICA) to resting-state functional magnetic resonance imaging (fMRI) data, the dFNCs of each subject were estimated using a sliding window method and k-means clustering. Network properties including global efficiency, local efficiency, node strength and harmonic centrality, were calculated for each subject. Five dynamic functional states were identified, three of which demonstrated significant group differences in their percentage of state occurrence. Interestingly, MDD patients spent much more time in a weakly-connected State 2, which includes regions previously associated with self-focused thinking, a representative feature of depression. In addition, the FNCs in MDD were connected differently in different states, especially among prefrontal, sensorimotor, and cerebellum networks. MDD patients exhibited significantly reduced harmonic centrality primarily involving parietal lobule, lingual gyrus and thalamus. Moreover, three dFNCs with disrupted node properties were commonly identified in different states, and also correlated with depressive symptom severity and cognitive performance. This study is the first attempt to investigate the dynamic functional abnormalities in MDD in a Chinese population using a relatively large sample size, which provides new evidence on aberrant time-varying brain activity and its network disruptions in MDD, which might underscore the impaired cognitive functions in this mental disorder.
| S-EPMC6080590 | biostudies-literature
Project description:Transcranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The effects of TMS on both brain physiology and therapeutic outcomes are known to be highly variable from subject to subject, however. Proposed reasons for this variability include individual differences in neurophysiology, in cortical geometry, and in brain connectivity. Standard approaches to TMS target site definition tend to focus on coordinates or landmarks within the individual brain regions implicated in MDD, such as the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC). Additionally considering the network connectivity of these sites (i.e., the wider set of brain regions that may be mono- or poly-synaptically activated by TMS stimulation) has the potential to improve subject-specificity of TMS targeting and, in turn, improve treatment outcomes. In this study, we looked at the functional connectivity (FC) of dlPFC and OFC TMS targets, based on induced electrical field (E-field) maps, estimated using the SimNIBS library. We hypothesized that individual differences in spontaneous functional brain dynamics would contribute more to downstream network engagement than individual differences in cortical geometry (i.e., E-field variability). We generated individualized E-field maps on the cortical surface for 121 subjects (67 female) from the Human Connectome Project database using tetrahedral head models generated from T1- and T2-weighted MR images. F3 and Fp1 electrode positions were used to target the left dlPFC and left OFC, respectively. We analyzed inter-subject variability in the shape and location of these TMS target E-field patterns, their FC, and the major functional networks to which they belong. Our results revealed the key differences in TMS target FC between the dlPFC and OFC, and also how this connectivity varies across subjects. Three major functional networks were targeted across the dlPFC and OFC: the ventral attention, fronto-parietal and default-mode networks in the dlPFC, and the fronto-parietal and default mode networks in the OFC. Inter-subject variability in cortical geometry and in FC was high. Our analyses showed that the use of normative neuroimaging reference data (group-average or representative FC and subject E-field) allows prediction of which networks are targeted, but fails to accurately quantify the relative loading of TMS targeting on each of the principal networks. Our results characterize the FC patterns of canonical therapeutic TMS targets, and the key dimensions of their variability across subjects. The high inter-individual variability in cortical geometry and FC, leading to high variability in distributions of targeted brain networks, may account for the high levels of variability in physiological and therapeutic TMS outcomes. These insights should, we hope, prove useful as part of the broader effort by the psychiatry, neurology, and neuroimaging communities to help improve and refine TMS therapy, through a better understanding of the technology and its neurophysiological effects.
| S-EPMC9260048 | biostudies-literature
Project description:Investigating the neurobiological mechanism of suicidal ideation (SI) in major depressive disorder (MDD) may be beneficial to prevent the suicidal behavior. Mounting evidence showed that habenula contributed to the etiology of MDD. The habenula is a key brain region that links the forebrain to midbrain, crucial for the processing of reward and aversion. The aim of the present study was to identify whether first-episode, drug-naive MDD patients with SI displayed altered habenula neural circuitry. Forty-three and 38 drug-naïve patients with first-episode MDD with or without SI (SI+/- group) and 35 healthy control subjects (HC) underwent resting-state functional magnetic resonance imaging. The whole-brain habenula static (sFC) and dynamic functional connectivity (dFC) were calculated to identify regions showing significant difference among these three groups followed by region of interest to region of interest post hoc analysis. For sFC, compared with SI- and HC groups, SI+ group showed decreased sFC from habenula to the precuneus and the inferior frontal gyrus. Patients with MDD displayed increased sFC from habenula to the putamen but decreased sFC to the precentral gyrus. For dFC, SI+ group showed increased dFC from habenula to the superior temporal gyrus, the precuneus, but decreased dFC to the lingual gyrus, the postcentral gyrus, when comparing with SI- and HC groups. Patients with MDD, regardless of SI, displayed decreased dFC from the habenula to the angular gyrus. These findings provide evidence that SI in first-episode, drug-naïve patients with MDD may be related to an abnormality in habenula neural circuitry, which may provide the theoretical basis of novel treatments.
| S-EPMC7772142 | biostudies-literature
Project description:BackgroundAbnormalities of the striatum and frontal cortex have been reported consistently in studies of neural structure and function in major depressive disorder (MDD). Despite speculation that compromised connectivity between these regions may underlie symptoms of MDD, little work has investigated the integrity of frontostriatal circuits in this disorder.MethodsFunctional magnetic resonance images were acquired from 21 currently depressed and 19 never-disordered women during wakeful rest. Using four predefined striatal regions-of-interest, seed-to-whole brain correlations were computed and compared between groups.ResultsCompared to controls, depressed participants exhibited attenuated functional connectivity between the ventral striatum and both ventromedial prefrontal cortex and subgenual anterior cingulate cortex. Depressed participants also exhibited stronger connectivity between the dorsal caudate and dorsal prefrontal cortex, which was positively correlated with severity of the disorder.ConclusionsDepressed individuals are characterized by aberrant connectivity in frontostriatal circuits that are posited to support affective and cognitive processing. Further research is required to examine more explicitly the link between patterns of disrupted connectivity and specific symptoms of depression, and the extent to which these patterns precede the onset of depression and normalize with recovery from depressive illness.
| S-EPMC3384258 | biostudies-literature
Project description:Background: Major depressive disorder (MDD) has demonstrated abnormalities of static intrinsic brain activity measured by amplitude of low-frequency fluctuation (ALFF). Recent studies regarding the resting-state functional magnetic resonance imaging (rs-fMRI) have found the brain activity is inherently dynamic over time. Little is known, however, regarding the temporal dynamics of local neural activity in MDD. Here, we investigated whether temporal dynamic changes in spontaneous neural activity are influenced by MDD. Methods: We recruited 81 first-episode, drug-naive MDD patients and 64 age-, gender-, and education-matched healthy controls who underwent rs-fMRI. A sliding-window approach was then adopted for the estimation of dynamic ALFF (dALFF), which was used to measure time-varying brain activity and then compared between the two groups. The relationship between altered dALFF variability and clinical variables in MDD patients was also analyzed. Results: MDD patients showed increased temporal variability (dALFF) mainly focused on the bilateral thalamus, the bilateral superior frontal gyrus, the right middle frontal gyrus, the bilateral cerebellum posterior lobe, and the vermis. Furthermore, increased dALFF variability values in the right thalamus and right cerebellum posterior lobe were positively correlated with MDD symptom severity. Conclusions: The overall results suggest that altered temporal variability in corticocerebellar-thalamic-cortical circuit (CCTCC), involved in emotional, executive, and cognitive, is associated with drug-naive, first-episode MDD patients. Moreover, our study highlights the vital role of abnormal dynamic brain activity in the cerebellar hemisphere associated with CCTCC in MDD patients. These findings may provide novel insights into the pathophysiological mechanisms of MDD.
| S-EPMC8328277 | biostudies-literature
Project description:Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.
| S-EPMC6500168 | biostudies-literature
Project description:Posttraumatic stress disorder (PTSD) is an anxiety disorder that is often diagnosed with comorbid depressive disorder. Therefore, neuroimaging studies investigating PTSD typically include both patients with and without comorbid depression. Differences in activity of the anterior cingulate cortex (ACC) and insula have been shown to differentiate PTSD patients with and without major depressive disorder (MDD). Whether or not comorbid MDD affects resting state functional connectivity of PTSD patients has not been investigated to our knowledge. Here, resting state functional connectivity of PTSD patients with (PTSD+MDD; n=27) and without (PTSD-MDD; n=23) comorbid MDD was investigated. The subgenual ACC and insula were investigated as seed regions. Connectivity between the subgenual ACC and perigenual parts of the ACC was increased in PTSD+MDD versus PTSD-MDD, which may reflect the presence of depressive specific symptoms such as rumination. Functional connectivity of the subgenual ACC with the thalamus was reduced, potentially related to more severe deficits in executive functioning in the PTSD+MDD group versus the PTSD-MDD group. In addition, the PTSD+MDD group showed reduced functional connectivity of the insula with the hippocampus compared to the PTSD-MDD group. However, this cluster was no longer significantly different when PTSD patients that were using medication were excluded from analyses. Thus, resting state functional connectivity of the subgenual ACC can distinguish PTSD+MDD from PTSD-MDD, and this may therefore be used as a neurobiological marker for comorbid MDD in the presence of PTSD. As PTSD+MDD are more treatment resistant, these findings can also guide treatment development, for example by targeting the subgenual ACC network with treatment.
| S-EPMC4184309 | biostudies-literature
Project description:Reward deficits and associated striatal circuitry disturbances have been implicated in the onset and progression of major depressive disorder (MDD). However, no studies have been conducted to investigate how the striatal circuitry changes during standard antidepressant, which is important for development of novel and targeted treatments for MDD. We examined the seed-to-whole-brain functional connectivity (FC) for six striatal subregions based on resting-state fMRI data of 23 MDD patients before and after 8-week duloxetine, a serotonin, and noradrenaline reuptake inhibitor. Twenty-three healthy controls (HCs) were also scanned twice with an 8-week interval. After the analysis of covariance, we observed significant group-by-time interaction on FC of the dorsal caudate (DC), ventral striatum (VS), and putamen seeds. Post hoc analyses revealed that the FC between several right striatal seeds and left superior frontal gyrus (SFG), between right DC and left precuneus, between right superior VS and left inferior parietal lobe, were significantly higher in MDD patients compared to HCs at baseline and were reduced after treatment. Conversely, the FC between right inferior VS and left cerebellum was lower in MDD patients and was increased after treatment. Patients with larger reduction in right superior VS-left SFG FC exhibited larger alleviation of rumination. These findings suggest that duloxetine modulates the striatal FC with dorsolateral prefrontal cortex, posterior default mode network, and cerebellum, and partly, these changes underlie symptomatic improvement. This study adds to our understanding of antidepressant mechanism and future therapeutic development might benefit from considering these striatal circuitry as potential targets.
| S-EPMC6865564 | biostudies-literature
Project description:Major depressive disorder (MDD) is a mental disorder characterized by at least 2 weeks of low mood, which is present across most situations. Diagnosis of MDD using rest-state functional magnetic resonance imaging (fMRI) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability. To our best knowledge, no studies aim at classification with effective connectivity and functional connectivity measures between MDD patients and healthy controls. In this study, we performed a data-driving classification analysis using the whole brain connectivity measures which included the functional connectivity from two brain templates and effective connectivity measures created by the default mode network (DMN), dorsal attention network (DAN), frontal-parietal network (FPN), and silence network (SN). Effective connectivity measures were extracted using spectral Dynamic Causal Modeling (spDCM) and transformed into a vectorial feature space. Linear Support Vector Machine (linear SVM), non-linear SVM, k-Nearest Neighbor (KNN), and Logistic Regression (LR) were used as the classifiers to identify the differences between MDD patients and healthy controls. Our results showed that the highest accuracy achieved 91.67% (p < 0.0001) when using 19 effective connections and 89.36% when using 6,650 functional connections. The functional connections with high discriminative power were mainly located within or across the whole brain resting-state networks while the discriminative effective connections located in several specific regions, such as posterior cingulate cortex (PCC), ventromedial prefrontal cortex (vmPFC), dorsal cingulate cortex (dACC), and inferior parietal lobes (IPL). To further compare the discriminative power of functional connections and effective connections, a classification analysis only using the functional connections from those four networks was conducted and the highest accuracy achieved 78.33% (p < 0.0001). Our study demonstrated that the effective connectivity measures might play a more important role than functional connectivity in exploring the alterations between patients and health controls and afford a better mechanistic interpretability. Moreover, our results showed a diagnostic potential of the effective connectivity for the diagnosis of MDD patients with high accuracies allowing for earlier prevention or intervention.
| S-EPMC5825897 | biostudies-literature
Project description:Objective: Clinically, it is very difficult to distinguish between major depressive disorder (MDD) and bipolar disorder (BD) in the period of depression. Increasing evidence shows that the insula plays an important role in depression. We aimed to compare the resting-state functional connectivity (rsFC) of insular subregions in patients with MDD and BD in depressive episodes (BDD), who had never experienced manic or hypomanic episodes when they were scanned to identify biomarkers for the identification of two diseases. Methods: We recruited 21 BDD patients, 40 MDD patients and 70 healthy controls (HC). Resting-state functional magnetic resonance imaging (rs-fMRI) was performed. BDD patients had never had manic or hypomanic episodes when they were scanned, and the diagnoses were determined by follow-up. We divided the insula into three parts including the ventral anterior insular cortex (v-AIN), dorsal anterior insular cortex (d-AIN), and posterior insula (PI). The insular-based rsFC was compared among the three groups, and an analysis of the correlation between the rsFC value and Hamilton depression and anxiety scales was carried out. Results: BDD and MDD patients demonstrated decreased rsFC from the v-AIN to the left superior/middle frontal gyrus compared with the HC group. Versus MDD and HC groups, BDD patients exhibited decreased rsFC from the v-AIN to the area in the left orbital frontal gyrus and left superior temporal gyrus (included temporal pole), from the PI to the right lateral postcentral gyrus and from all three insular subregions to the somatosensory and motor cortex. Meanwhile, a correlation between the rsFC value of the PI-right lateral postcentral gyrus and anxiety score was observed in patients. Conclusion: Our findings show BDD and MDD patients have similar decreases in insular connectivity in the dorsal lateral frontal regions, and BDD patients have specific decreased insular connectivity, especially in the somatosensory and motor cortex, which may be used as imaging evidence for clinical identification.
| S-EPMC6246657 | biostudies-literature