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Updated: Sep 24, 2025

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
Published on: August 2, 2021
Effects of escitalopram therapy on functional brain controllability in major depressive disorder
Feng Fang1, Beata Godlewska2, Raymond Y Cho3
1Department of Biomedical Engineering, University of Houston, Houston, TX, USA.
Abstract:
Antidepressant drugs are the mainstay of treatment for patients with major depressive disorders (MDD). Given the critical role of the underlying neural control mechanism in the physiopathology of depression, this study aims to investigate the effects of escitalopram, a type of antidepressant drug, on the changes of functional brain controllability throughout the escitalopram treatment for MDD. We collected resting-state functional magnetic resonance imaging data from 20 unmedicated major depressive patients at baseline (visit 1, pre-treatment), one week (visit 2, 1-week after the onset of the treatment) and six weeks (visit 3, after the 6-week escitalopram treatment). Our results revealed that the global average and modal controllability of MDD patients were significantly larger and smaller, respectively, compared to healthy subjects (P < 0.01). Furthermore, the modal controllability rank of the frontoparietal network in depression patients was also significantly smaller than the healthy subjects (P < 0.01). However, throughout the escitalopram treatment, the global average and modal controllability, and the controllability of the default mode network and frontoparietal network of MDD patients were consistently changed to the healthy subjects' level. Our results also showed that the changes of global average and modal controllability measures can predict the improvements of clinical scores of the MDD patients as the escitalopram treatment advanced (P < 0.05). In conclusion, this study reveals promising brain controllability-based biomarkers to mechanistically understand and predict the effects of the escitalopram treatment for depression and maybe extended to predict and understand the effects of other interventions for other neurological and psychiatric diseases.
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