Converging Resting State Networks Unravels Potential Remote Effects of Transcranial Magnetic Stimulation for Major Depression

Abstract

Despite being a commonly used protocol to treat major depressive disorder (MDD), the underlying mechanism of repetitive transcranial magnetic stimulation (rTMS) on dorsolateral prefrontal cortex (DLPFC) remains unclear. In the current study, we investigated the resting-state fMRI data of 100 healthy subjects by exploring three overlapping functional networks associated with the psychopathologically MDD-related areas (the nucleus accumbens, amygdala, and ventromedial prefrontal cortex). Our results showed that these networks converged at the bilateral DLPFC, which suggested that rTMS over DLPFC might improve MDD by remotely modulating the MDD-related areas synergistically. Additionally, they functionally converged at the DMPFC and bilateral insula which are known to be associated with MDD. These two areas could also be potential targets for rTMS treatment. Dynamic causal modelling (DCM) and Granger causality analysis (GCA) revealed that all pairwise connections among bilateral DLPFC, DMPFC, bilateral insula, and three psychopathologically MDD-related areas contained significant causality. The DCM results also suggested that most of the functional interactions between MDD-related areas and bilateral DLPFC, DMPFC, and bilateral insula can predominantly be explained by the effective connectivity from the psychopathologically MDD-related areas to the rTMS stimulation sites. Finally, we found the conventional functional connectivity to be a more representative measure to obtain connectivity parameters compared to GCA and DCM analysis. Our research helped inspecting the convergence of the functional networks related to a psychiatry disorder. The results identified potential targets for brain stimulation treatment and contributed to the optimization of patient-specific brain stimulation protocols.

Amygdala connectivity related to subsequent stress responses during the COVID-19 outbreak

“…During processing of negative emotion, researchers found that the connectivity from the right amygdala to the dmPFC was significant in healthy controls using a method called Granger causality modeling (70,71). A recent study, which also used the spDCM as we did, found inhibitory connectivity from the right amygdala to the dmPFC and excitatory connectivity from the dmPFC to the right amygdala, as well as the self-connections in both of the two regions, in healthy volunteers during rest in a network including six other regions besides the amygdala and dmPFC (72). Our finding is consistent with these previous studies.…”

The thalamus is the causal hub of intervention in patients with major depressive disorder: Evidence from the Granger causality analysis

“…Compared with functional hubs, effective hubs reflect the regions with heavily directional influences on multiple regions ( Ishida et al, 2020 , Rao et al, 2018 ). Several causal models were put forward to measure effective connections among brain regions, such as the dynamic causal modeling (DCM) ( Friston et al, 2010 ), structural equation modeling (SEM) ( Anderson et al, 1988 ), and Granger causality model (GCM) ( Granger, 1969 ).…”

Amygdala connectivity as a predisposing neural feature of stress-induced behaviour during the COVID-2019 outbreak in Hubei

“…The copyright holder for this preprint this version posted July 30, 2021. ; https://doi.org/10.1101/2021.07.26.21261160 doi: medRxiv preprint we did, found inhibitory connectivity from the right amygdala to the dmPFC and the excitatory connectivity from the dmPFC to the right amygdala, as well as the self-connections in both of the two regions, in healthy volunteers during rest in a network including 6 other regions besides the amygdala and dmPFC (Ishida et al 2020).…”