The Neural Networks Underlying Treatment-Resistant Depression

Abstract

Treatment-resistant depression (TRD) presents significant clinical challenges, characterized by persistent symptoms despite multiple antidepressant treatments. Understanding the TRD’s neurobiological mechanisms is essential for improving treatments. This thesis investigates functional connectivity (FC) alterations in key brain regions associated with TRD, focusing on the “default mode” network (DMN) of self-referential processing, the reward system, and the affective network. The aim of this project was to explore how FC differences between TRD and treatment sensitive depression (TSD) could inform the mechanisms underlying treatment-resistance. Using task-based and resting-state fMRI, we examined the connectivity of the habenula, rostral anterior cingulate cortex (rACC), and subgenual ACC (sgACC) with other brain regions from the networks above in patients with TRD, TSD, and healthy controls (HC). Results revealed that TRD patients, compared to TSD, exhibited hyperconnectivity of the habenula, part of the reward system, with the DMN, which may contribute to anhedonia, a core symptom of TRD. Altered DMN connectivity distinguished TRD from TSD and HC, reflecting self-referential and emotion regulation processes during rest. Additionally, TRD

patients showed abnormal rACC connectivity during emotional processing, particularly hypoconnectivity with the hippocampus during supraliminal processing of positive emotions. These findings advance our understanding of TRD by highlighting distinct patterns of FC, particularly within the default-mode, reward and affective networks, that differentiate TRD from TSD. These connectivity patterns suggest disruptions in self-referential processing, emotion regulation, and reward sensitivity, which may contribute to the persistence of symptoms in TRD. This research underscores the importance of a network-based approach to both diagnosis and treatment and offers insights into the neurobiological mechanisms of treatment resistance.