Network Neurofeedback Using 7-Tesla MRI to Reduce Rumination Levels in Depression

Major Depressive Disorder Clinical Trial

Official title: Network-based Real-time Neurofeedback Using Ultra-high Field MRI to Reduce Rumination Levels in Depression

Status Recruiting

Clinical Trial Summary

Patients with major depressive disorder (MDD) exhibit increased levels of rumination (i.e. repetitive thinking and focus on negative mood states) which have been found to increase the risk of depressive relapse. The ability to reduce rumination levels among these patients is greatly needed. Rumination is known to be associated with the default mode network (DMN) region activity. Implementing the Dependency Network Analysis (DEPNA), a recently developed method by the research team to quantify the connectivity influence of network nodes, found that rumination was significantly associated with lower connectivity influence of the left medial orbitofrontal cortex (MOFC) on the right precuneus, both key regions within the DMN. This study implements the first real-time fMRI neurofeedback (Rt-fMRI-NF) network-based protocol for up-regulation of the MOFC influence on the precuneus in patients with MDD to reduce rumination levels. This will allow for more accurate explicit brain connections modulation than the standard single brain region activity; creating a larger opportunity for target clinical neuromodulation treatment in individuals with MDD.

Clinical Trial Description

Major depressive disorder (MDD) is the world's largest health problem, and current available treatments fail at relieving symptoms for many patients. Rumination, which is conceptualized as repetitive thinking and focus on one's distress and negative mood states is a core feature of MDD. Patients with MDD exhibit increased levels of rumination which have been found to increase the risk of depressive relapse in remitted patients. The ability to reduce rumination levels among these patients is greatly needed.

Neurofeedback (NF) is a technique that feeds back information about brain signals to the individual in real-time, to allow for implicit modulation of the brain signal in order to improve performance. Yet, classic real-time fMRI-NF protocols focus on single region activity neglecting to consider the neural network dynamics, accounting for direct influences between regions.

Implementing the Dependency Network Analysis (DEPNA), a method developed by the research team, tested whether network connectivity influences during resting-state functional MRI (fMRI) are associated with rumination in patients with MDD. The research team found that rumination was significantly associated with lower connectivity influence of the left medial orbito-frontal cortex (MOFC) on the right precuneus, both key regions within the DMN. This is in line with intracranial recordings studies showing that MOFC activity precedes the precuneus in response to emotional stimuli.

The research team intend to extend this work by conducting the first real-time fMRI neurofeedback (Rt-fMRINF) protocol for up-regulation of the MOFC influence on the precuneus in patients with MDD and healthy controls to reduce rumination levels. The research team aims to develop an advanced ultra-high field MRI protocol that will allow for rt-fMRI-NF derived from networks' connectivity features as constructed by the DEPNA, and thus training the subject to control explicit brain connections. Specifically, the research team aims to train MDD patients to better regulate rumination levels by upregulating the influence of the MOFC on the precuneus. ;

Related Conditions & MeSH terms

• Depressive Disorder
• Depressive Disorder, Major
• Major Depressive Disorder

• NCT number: NCT05933148
• Study type: Interventional
• Source: Icahn School of Medicine at Mount Sinai
• Contact: Grace S. Butler, BA
• Phone: (212) 585-4623
• Email: grace.butler@mssm.edu
• Status: Recruiting
• Phase: N/A
• Start date: July 12, 2023
• Completion date: April 2025