Browsing by Subject "graph theory metrics"
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Item Open Access Effect of Repetitive Transcranial Magnetic Stimulation on the Structural and Functional Connectome in Patients with Major Depressive Disorder(2017-05-08) Asturias, GabrielaThrough this whole-brain exploratory analysis, our aim is to study the effect of repetitive transcranial magnetic stimulation (rTMS) on the structural and functional connectivity of patients with major depressive disorder. Twenty-five currently depressed patients (age 21–68) participated in the study. Patients received daily 10-Hz rTMS over the left dlPFC five days/week for five weeks. Treatment response was assessed using the 24-item Hamilton Rating Scale for Depression (HAMD-24) at baseline and after the course of TMS. MRIs were acquired within seven days prior to starting rTMS and within three days after the end of treatment. Using diffusion tensor images and resting-state fMRI data we computed the whole-brain functional and structural connectomes. We used graph theory techniques to characterize brain architecture to identify potential biomarkers for depression severity and response to treatment. The frontal pole, part of the midline core in the default mode network (DMN) and the exteroception compartment of the depression network (DN), was identified as a potential biomarker for depression severity. The intracalcarine cortex and lateral occipital cortex, neither part of the default mode network and depression network, were defined as potential biomarkers for treatment response. The subcallosal cortex, orbitofrontal cortex, and supramarginal gyrus were identified as potential biomarkers for treatment response and their change across the treatment protocol could explain the simultaneous effect of rTMS on structural and functional connectivity. Ultimately, the goal is to articulate specific hypotheses that will inform treatment strategies for patients with major depressive disorder.