A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Kim, Jung-Woo; Andrews‐Hanna, Jessica R.; Eisenbarth, Hedwig; Lux, Byeol Kim; Kim, Hong Ji; Lee, Eunjin; Lindquist, Martin A.; Losin, Elizabeth A. Reynolds; Wager, Tor D.; Woo, Choong‐Wan

doi:10.1038/s41467-023-39142-9

Cited by 23 publications

(12 citation statements)

References 94 publications

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“…Dynamic time-varying FC is a promising avenue to elucidate intricate time-sensitive neuronal mechanisms underlying various states of cognition, disease and consciousness, with greater potential to characterize psychiatric biomarkers compared to traditional static FC alone (Calhoun et al, 2008, 2014; Cohen, 2018; Ganesan et al, 2022; Hutchison et al, 2013). Notably, dynamic FC can outperform static FC in predicting individual differences in rumination using diverse clinical and subclinical datasets (Kim et al, 2023). Our present work demonstrates the utility of dynamic FC in characterizing the time-varying behavior of a whole-brain FC state associated with brooding, a critical symptom and prognostic factor of MDD.…”

Section: Discussionmentioning

confidence: 99%

“…Studies investigating dynamic FC in rumination and MDD have observed links to disrupted FC dynamics of the DMN, CEN and other networks, suggesting impaired neural communications associated with cognitive control, flexibility and self-referential processing. High variability (and low stability) of FC dynamics in DMN regions such as mPFC, hippocampus and PCC (Chen (••) & Yan (•超•), 2021; Kaiser et al, 2016; Kim et al, 2023; Kucyi & Davis, 2014) was associated with increased rumination and mind-wandering across MDD and healthy samples, and dynamic FC of dorsal mPFC was found to strongly predict rumination in MDD (Kim et al, 2023). Similarly, lower stability and shorter dwelling in dynamic FC states with positive FC of DMN, sensorimotor areas and subcortical regions have been associated with MDD pathology (Long et al, 2020; Wu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Functional brain network dynamics of brooding in depression: insights from real-time fMRI neurofeedback

Ganesan,

Misaki,

Zalesky

et al. 2024

Preprint

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Background: Brooding is a critical symptom and prognostic factor of major depressive disorder (MDD), which involves passively dwelling on self-referential dysphoria and related abstractions. The neurobiology of brooding remains under characterized. We aimed to elucidate neural dynamics underlying brooding, and explore their responses to neurofeedback intervention in MDD. Methods: We investigated functional MRI (fMRI) dynamic functional network connectivity (dFNC) in 36 MDD subjects and 26 healthy controls (HCs) during rest and brooding. Rest was measured before and after fMRI neurofeedback (MDD-active/sham: n=18/18, HC-active/sham: n=13/13). Baseline brooding severity was recorded using Ruminative Response Scale - Brooding subscale (RRS-B). Results: Four recurrent dFNC states were identified. Measures of time spent were not significantly different between MDD and HC for any of these states during brooding or rest. RRS-B scores in MDD showed significant negative correlation with measures of time spent in dFNC state 3 during brooding (r=-0.5, p= 1.7E-3, FDR-significant). This state comprises strong connections spanning several brain systems involved in sensory, attentional and cognitive processing. Time spent in this anti-brooding dFNC state significantly increased following neurofeedback only in the MDD active group (z=-2.09, p=0.037). Limitations: The sample size was small and imbalanced between groups. Brooding condition was not examined post-neurofeedback. Conclusion: We identified a densely connected anti-brooding dFNC brain state in MDD. MDD subjects spent significantly longer time in this state after active neurofeedback intervention, highlighting neurofeedback`s potential for modulating dysfunctional brain dynamics to treat MDD.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Functional brain network dynamics of brooding in depression: insights from real-time fMRI neurofeedback

Ganesan,

Misaki,

Zalesky

et al. 2024

Preprint

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“…This disruption may move the overall of the state from one that supports healthy introspection to one that produces maladaptive rumination. Of the subnetworks highlighted in Figure 3B, the default-mode and fronto-parietal networks have been extensively studied in MDD, with functional and structural alterations reported in areas of each (Kim et al, 2023; Menon, 2011; Sheline et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

“…A connection between sensory network properties and MDD has also been reported (Furey et al, 2013; Zhang et al, 2023), including changes to structure, function, and biochemical properties (Song et al, 2021; Wu et al, 2023). Notably, the visual system has been connected to rumination in some studies (Burkhouse et al, 2017; Kim et al, 2023; Piguet et al, 2014), where activation may reflect memory-related processes (Dijkstra et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Structural alterations in a rumination-related network in patients with major depressive disorder

Cheng,

Lee,

Lane

et al. 2023

Preprint

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Rumination is a common symptom in major depressive disorder (MDD) and has been linked to risk for that disorder, its prognosis, and relapse likelihood. Previous work has linked individual differences in rumination to structural properties in a variety of brain regions. Some of these regions, such as the dorsolateral prefrontal cortex (dlPFC), have also been highlighted as being altered in MDD, suggesting a connection between structural changes and ruminative symptoms. Although informative, such localised relations have some limitations in the context of a network view of the brain. To further investigate rumination-related structural changes in depression and to situate these within potential functional networks, we acquired structural data from patients with MDD (n = 32) and controls (n = 69). Analysis of cortical grey-matter identified group differences in the dlPFC that were, however, not related to rumination. Instead, rumination was correlated with grey-matter properties in the right precuneus. Using normative functional connectivity analysis on a large independent sample, we show that these two regions are interconnected. It was further shown that the rumination-related precuneus region is highly connected with networks associated with processes such as executive function, autobiographical memory, and visual perception. Notably, each of these processes has been connected to rumination. These results suggest that rumination in depression may be linked to focal structural changes that disrupt a distributed functional network.

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“…16 A resting-state fMRI model of trait rumination predicted depression scores in adults with major depressive disorder. 82 However, such model predictions do not succeed in all individuals, and population-derived predictive models are most likely to fail in individuals who defy sample stereotypes (e.g. due to sociodemographic and/or clinical factors).…”

Section: Implications For Interpreting Spontaneous Brain Activitymentioning

confidence: 99%

Individual variability in neural representations of mind-wandering

Kucyi,

Anderson,

Bounyarith

et al. 2024

Preprint

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Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population-rather than individual-based inferences due to limited within-individual sampling. Here, three densely-sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely-sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously-unrecognized inter-individual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

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A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Cited by 23 publications

References 94 publications

Functional brain network dynamics of brooding in depression: insights from real-time fMRI neurofeedback

Functional brain network dynamics of brooding in depression: insights from real-time fMRI neurofeedback

Structural alterations in a rumination-related network in patients with major depressive disorder

Individual variability in neural representations of mind-wandering

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