State-independent alterations of intrinsic brain network in current and remitted depression

Dong, Daifeng; Ming, Qingsen; Zhong, Xue; Pu, Weidan; Zhang, Xiaocui; Jiang, Yali; Gao, Yidian; Sun, Xiaoqiang; Wang, Xiang; Yao, Shuqiao

doi:10.1016/j.pnpbp.2018.08.031

Cited by 38 publications

(20 citation statements)

References 45 publications

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“…The DMN and CEN can co-active with each other to perform particular mental tasks (Angst et al ., 2010). The abnormal stationary FC between DMN and CEN has been reported in BD and MDD patients in depressive state (Sheline et al ., 2010; Ye et al ., 2012; de Almeida and Phillips, 2013; Manoliu et al ., 2014 a ; Dong et al ., 2018) and remitted state (Dong et al ., 2018). Thus, the decreased dFNC variability between DMN and CEN may indicate a state-independent impairment in information processing in BD and MDD patients.…”

Section: Discussionmentioning

confidence: 99%

“…For depressed and remitted MDD patients, Dong et al . (2018) found that both had decreased FC within the CEN, increased FC between the SN and CEN, and decreased FC between the DMN and CEN compared with controls, suggesting the state-independent FC alterations within the triple networks in MDD patients. Further, by including both depressed BD and MDD patients, Goya-Maldonado et al .…”

Section: Introductionmentioning

confidence: 99%

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Abnormal dynamic functional network connectivity in unmedicated bipolar and major depressive disorders based on the triple-network model

Wang

Huang

et al. 2019

Psychol. Med.

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BackgroundPrevious studies have analyzed brain functional connectivity to reveal the neural physiopathology of bipolar disorder (BD) and major depressive disorder (MDD) based on the triple-network model [involving the salience network, default mode network (DMN), and central executive network (CEN)]. However, most studies assumed that the brain intrinsic fluctuations throughout the entire scan are static. Thus, we aimed to reveal the dynamic functional network connectivity (dFNC) in the triple networks of BD and MDD.MethodsWe collected resting state fMRI data from 51 unmedicated depressed BD II patients, 51 unmedicated depressed MDD patients, and 52 healthy controls. We analyzed the dFNC by using an independent component analysis, sliding window correlation and k-means clustering, and used the parameters of dFNC state properties and dFNC variability for group comparisons.ResultsThe dFNC within the triple networks could be clustered into four configuration states, three of them showing dense connections (States 1, 2, and 4) and the other one showing sparse connections (State 3). Both BD and MDD patients spent more time in State 3 and showed decreased dFNC variability between posterior DMN and right CEN (rCEN) compared with controls. The MDD patients showed specific decreased dFNC variability between anterior DMN and rCEN compared with controls.ConclusionsThis study revealed more common but less specific dFNC alterations within the triple networks in unmedicated depressed BD II and MDD patients, which indicated their decreased information processing and communication ability and may help us to understand their abnormal affective and cognitive functions clinically.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Abnormal dynamic functional network connectivity in unmedicated bipolar and major depressive disorders based on the triple-network model

Wang

Huang

et al. 2019

Psychol. Med.

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“…Resting-state fMRI studies, wherein subjects are not performing an explicit task during the scan, can complement task fMRI studies (Su et al, 2010; Biswal, 2012). Resting-state data can be analyzed by multifarious approaches, such as seed-based approaches, independent component analysis, graph methods, clustering algorithms, neural networks, and pattern classifier (Lee et al, 2013; Dong et al, 2018). In recent years, a resting-state fMRI analytical method named amplitude of low-frequency fluctuation (ALFF) was developed to assess the spontaneous low frequency (0.01–0.08 Hz) fluctuations (LFF) in the BOLD fMRI signal at rest, which could reflect the intensity of brain regional spontaneous neural activity (Zang et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

State-Related Alterations of Spontaneous Neural Activity in Current and Remitted Depression Revealed by Resting-State fMRI

et al. 2019

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Purpose: Although efforts have been made to identify neurobiological characteristic of major depressive disorder (MDD) in recent years, trait- and state-related biological characteristics of MDD still remains unclear. Using functional magnetic resonance imaging (fMRI), the aim of this study was to explore whether altered spontaneous neural activities in MDD are trait- or state- related.Materials and Methods: Resting-state fMRI data were analyzed for 72 current MDD (cMDD) patients (first-episode, medication-naïve), 49 remitted MDD (rMDD) patients, and 78 age- and sex- matched healthy control (HC) subjects. The values of amplitude of low-frequency fluctuation (ALFF) were compared between groups.Results: Compared with the cMDD group, the rMDD group had increased ALFF values in the left middle occipital gyrus, left middle temporal gyrus and right cerebellum anterior lobe. Besides, compared with the HC group, the cMDD group had decreased ALFF values in the left middle occipital gyrus. Further analysis explored that the mean ALFF values in the left middle occipital gyrus, left middle temporal gyrus and right cerebellum anterior lobe were correlated positively with BDI scores in rMDD patients.Conclusion: Abnormal activity in the left middle occipital gyrus, left middle temporal gyrus and right cerebellum anterior lobe may be state-specific in current (first-episode, medication-naïve) and remitted (medication-naïve) depression patients. Furthermore, the state-related compensatory effect was found in these brain areas.

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“…According to the "kindling theory," subsequent episodes of MDD are correlated with a high number of previous episodes, even with milder stressors [2]. Individuals prone to recurrence may experience residual symptoms, including persistent subclinical depressive symptoms, rumination, impaired attentional control, and cognitive decline from the previous depressive episode [1,3]. As a result, people with recurrent remitted MDD experience difficulty recovering from negative emotions and exhibit a persistent reduction in positive affect, resulting in a sustained depressed mood [4].…”

Section: Introductionmentioning

confidence: 99%

Neural networks and the anti-inflammatory effect of transcutaneous auricular vagus nerve stimulation in depression

Liu

Yang

Zhang

et al. 2020

J Neuroinflammation

100

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Transcutaneous auricular vagus nerve stimulation (taVNS) is a relatively non-invasive alternative treatment for patients suffering from major depressive disorder (MDD). It has been postulated that acupuncture may achieve its treatment effects on MDD through suppression of vagal nerve inflammatory responses. Our previous research established that taVNS significantly increases amygdala-dorsolateral prefrontal cortex connectivity, which is associated with a reduction in depression severity. However, the relationship between taVNS and the central/ peripheral functional state of the immune system, as well as changes in brain neural circuits, have not as yet been elucidated. In the present paper, we outline the anatomic foundation of taVNS and emphasize that it significantly modulates the activity and connectivity of a wide range of neural networks, including the default mode network, executive network, and networks involved in emotional and reward circuits. In addition, we present the inflammatory mechanism of MDD and describe how taVNS inhibits central and peripheral inflammation, which is possibly related to the effectiveness of taVNS in reducing depression severity. Our review suggests a link between the suppression of inflammation and changes in brain regions/circuits post taVNS.

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State-independent alterations of intrinsic brain network in current and remitted depression

Cited by 38 publications

References 45 publications

Abnormal dynamic functional network connectivity in unmedicated bipolar and major depressive disorders based on the triple-network model

Abnormal dynamic functional network connectivity in unmedicated bipolar and major depressive disorders based on the triple-network model

State-Related Alterations of Spontaneous Neural Activity in Current and Remitted Depression Revealed by Resting-State fMRI

Neural networks and the anti-inflammatory effect of transcutaneous auricular vagus nerve stimulation in depression

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