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The purpose of this study is to decode different thinking states from the brain activation patterns and identify the neural circuits that disengage from these thinking patterns using functional magnetic resonance imaging (fMRI) measurement in individuals with major depressive disorder.
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This study aims to identify brain activation patterns associated with successful disengagement from negative thinking for MDD-affected participants. The investigators will use a machine learning classifier to decode thinking states from participants' fMRI signals. The decoder is utilized to trace the thinking state's time course as a measure of regulation performance. Investigating the brain activation correlated with the time course of the regulation success can indicate the neural circuits contributing to disengaging from negative thinking. The investigators will also explore the most effective regulation strategy for individual participants. Participants will be instructed to use three regulation strategies: mindfulness by focusing on breathing, distraction with positive thinking, and reinterpretation of a negative thing in a positive way. The investigators expect that the effective strategy could vary across participants, which could be associated with the variability of brain activation patterns in negative thinking.
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