Effective connectivity between resting-state networks in depression

DeMaster, Dana; Godlewska, Beata R.; Liang, Mingrui; Vannucci, Marina; Bockmann, Taya; Cao, Bo; Selvaraj, Sudhakar

doi:10.1016/j.jad.2022.03.041

Cited by 5 publications

(4 citation statements)

References 45 publications

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“…Racemic and S-ketamine were found to decrease cognitive symptoms [62] and increase cognitive performance [63,64]. Furthermore, in individuals with depression, the DMN shows a relative dominance over the CEN, with a stronger effective connectivity from the DMN to CEN than vice versa [65]. A ketamine-induced decrease of the rsFC between the DMN and CEN may therefore reestablish the balance between the two resting-state networks.…”

Section: Discussionmentioning

confidence: 99%

Association of the delayed changes in glutamate levels and functional connectivity with the immediate network effects of S-ketamine

et al. 2023

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Ketamine shows rapid antidepressant effects peaking 24 h after administration. The antidepressant effects may occur through changes in glutamatergic metabolite levels and resting-state functional connectivity (rsFC) within the default mode network (DMN). A multistage drug effect of ketamine has been suggested, inducing acute effects on dysfunctional network configuration and delayed effects on homeostatic synaptic plasticity. Whether the DMN-centered delayed antidepressant-related changes are associated with the immediate changes remains unknown. Thirty-five healthy male participants (25.1 ± 4.2 years) underwent 7 T magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (rsfMRI) before, during, and 24 h after a single S-ketamine or placebo infusion. Changes in glutamatergic measures and rsFC in the DMN node pregenual anterior cingulate cortex (pgACC) were examined. A delayed rsFC decrease of the pgACC to inferior parietal lobe (family-wise error corrected p (pFWEc) = 0.018) and dorsolateral prefrontal cortex (PFC; pFWEc = 0.002) was detected that was preceded by an immediate rsFC increase of the pgACC to medial PFC (pFWEc < 0.001) and dorsomedial PFC (pFWEc = 0.005). Additionally, the immediate rsFC reconfigurations correlated with the delayed pgACC glutamate (Glu) level increase (p = 0.024) after 24 h at trend level (p = 0.067). Baseline measures of rsFC and MRS were furthermore associated with the magnitude of the respective delayed changes (p’s < 0.05). In contrast, the delayed changes were not associated with acute psychotomimetic side effects or plasma concentrations of ketamine and its metabolites. This multimodal study suggests an association between immediate S-ketamine-induced network effects and delayed brain changes at a time point relevant in its clinical context.

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Section: Discussionmentioning

confidence: 99%

Association of the delayed changes in glutamate levels and functional connectivity with the immediate network effects of S-ketamine

et al. 2023

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“… Functional (cont.) DeMaster et al [ 11 ] 34 MDD -Escitalopram (SSRI) -6 weeks -EC: Bayesian multi-subject vector autoregressive model -Baseline MRI Higher FC strength in DMN, FPN, and SN was related to baseline depression severity and response to treatment. Fischer et al [ 25 ] 128 MDD, 58 HC -Sertraline (SSRI), Venlafaxine-XR (SNRI), or Escitalopram (SSRI) - 8 weeks -Randomized -Seed-based: NAcc -MRI before and after treatment Responders had an increase in NAcc-dACC FC, which was associated with an improvement in quality of life, and a decrease in NAcc-inferior parietal lobule (IPL) FC.…”

Section: Resultsmentioning

confidence: 99%

“…Ye et al (2022) reported increased baseline right angular gyrus FC within the DMN in the remitted group compared with the non-remitted group, which was positively correlated with the reduction of depressive scores [ 8 ]. In addition to the increased FC within the DMN that was associated with better treatment outcomes [ 9 – 11 ], increased FC between DMN and frontoparietal network (FPN) [ 9 , 10 , 12 ], and somatomotor network (SMN) [ 10 ] was also reported. Additionally, treatment response was associated with increased FC between the right FPN and the posterior DMN, SMN, and somatosensory association cortex (SAC) by Martens et al [ 13 ].…”

Section: Resultsmentioning

confidence: 99%

Brain connectivity in major depressive disorder: a precision component of treatment modalities?

Tura

Goya-Maldonado

2023

Transl Psychiatry

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Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an enormous burden on individuals, society, and health care systems. Most patients benefit from commonly used treatment methods such as pharmacotherapy, psychotherapy, electroconvulsive therapy (ECT), and repetitive transcranial magnetic stimulation (rTMS). However, the clinical decision on which treatment method to use remains generally informed and the individual clinical response is difficult to predict. Most likely, a combination of neural variability and heterogeneity in MDD still impedes a full understanding of the disorder, as well as influences treatment success in many cases. With the help of neuroimaging methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the brain can be understood as a modular set of functional and structural networks. In recent years, many studies have investigated baseline connectivity biomarkers of treatment response and the connectivity changes after successful treatment. Here, we systematically review the literature and summarize findings from longitudinal interventional studies investigating the functional and structural connectivity in MDD. By compiling and discussing these findings, we recommend the scientific and clinical community to deepen the systematization of findings to pave the way for future systems neuroscience roadmaps that include brain connectivity parameters as a possible precision component of the clinical evaluation and therapeutic decision.

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“…To identify patterns, discover anomalies, and interpret temporal dynamics, it is critical to understand the changes of effective connectivity as a biomarker of neurodegenerative and psychiatric disorders, connections between different brain areas, and how these connections develop over time ( Zhao et al, 2022 ). In DeMaster et al (2022) it is demonstrated how alterations in resting state effective connectivity can serve as biomarkers for depression, or another work ( Wang et al, 2022 ) highlights the changes in effective connectivity in schizophrenia, aiding in better diagnosis and understanding of the disorder. A study validates the use of dynamic causal modeling (DCM) for resting state effective connectivity, which can detect early connectivity changes in neurodegenerative diseases ( Razi et al, 2015 ).…”

Section: Discussionmentioning

confidence: 99%

The subcortical brain regions influence the cortical areas during resting-state: an fMRI study

Moazeni,

Northoff,

Batouli

2024

Front. Hum. Neurosci.

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IntroductionNumerous modes or patterns of neural activity can be seen in the brain of individuals during the resting state. However, those functions do not persist long, and they are continuously altering in the brain. We have hypothesized that the brain activations during the resting state should themselves be responsible for this alteration of the activities.MethodsUsing the resting-state fMRI data of 63 healthy young individuals, we estimated the causality effects of each resting-state activation map on all other networks. The resting-state networks were identified, their causality effects on the other components were extracted, the networks with the top 20% of the causality were chosen, and the networks which were under the influence of those causal networks were also identified.ResultsOur results showed that the influence of each activation component over other components is different. The brain areas which showed the highest causality coefficients were subcortical regions, such as the brain stem, thalamus, and amygdala. On the other hand, nearly all the areas which were mostly under the causal effects were cortical regions.DiscussionIn summary, our results suggest that subcortical brain areas exert a higher influence on cortical regions during the resting state, which could help in a better understanding the dynamic nature of brain functions.

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Effective connectivity between resting-state networks in depression

Cited by 5 publications

References 45 publications

Association of the delayed changes in glutamate levels and functional connectivity with the immediate network effects of S-ketamine

Association of the delayed changes in glutamate levels and functional connectivity with the immediate network effects of S-ketamine

Brain connectivity in major depressive disorder: a precision component of treatment modalities?

The subcortical brain regions influence the cortical areas during resting-state: an fMRI study

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