Unconscious elevated bottom-up processing in depression: Insights from dynamic causal modeling with EEG and fMRI

MRI compatible EEG systems enable simultaneous EEG-fMRI data assessment, which provides high spatial and high temporal resolution of neural signaling data. Functional connectivity analyses suggest altered fronto-limbic emotion regulation in patients with major depressive disorder (MDD).

Sixty patients with MDD and 66 healthy controls (HC) performed a priming task using unconsciously and consciously presented emotional facial expressions (happy, sad, neutral) performed a priming task using unconsciously and consciously presented emotional facial expressions. Effective connectivity of simultaneously recorded EEG-fMRI data between cortical (bilateral dorsolateral prefrontal cortex and fusiform gyrus) and subcortical regions (bilateral amygdala) was captured using dynamic causal modeling (DCM). Delineate stimulus-related changes in bottom-up and top-down neurophysiological networks across both EEG and fMRI data were estimated in models of unconscious and conscious processing, defined for both groups.

Bayesian model selection favored a bottom-up processing model for both groups and input conditions (conscious and unconscious) in EEG-DCMs. Mixed top-down and bottom-up processing models best represented conscious and unconscious stimulus processing in HC fMRI-DCM, while bottom-up models were most representative for MDD fMRI data. Amygdala activity leads to higher DLPFC activity in conscious, and lower DLPFC activity in unconscious conditions in both groups.

This study demonstrates the distinct capabilities of EEG and fMRI data through showing that EEG captures early and fast processing (bottom-up) while fMRI reflects both, bottom-up and top-down regulation. Activity reduction of DLPFC through FFA bottom-up connectivity in early processing (EEG-DCM) might inhibit later top-down emotion regulation through the DLPFC in MDD (fMRI-DCM).