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Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning

2019-10-11 psychiatry and clinical psychology Title + abstract only
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Given the subjective nature of conventional diagnostic methods for post-traumatic stress disorder (PTSD), an objectively measurable biomarker is highly desirable. Macroscopic neural circuits measured using magnetoencephalography (MEG) has previously been shown to be indicative of the PTSD phenotype and severity. In the present study, we employed a machine learning-based classification framework using MEG neural synchrony to distinguish combat-related PTSD from trauma-exposed controls. Support ve...

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