Towards predicting posttraumatic stress symptom severity using portable EEG-derived biomarkers

Abstract

Posttraumatic Stress Disorder (PTSD) is a heterogeneous mental health disorder that can develop following a traumatic experience. Understanding its neurobiological basis is crucial to advance early diagnosis and treatment. Electroencephalography (EEG) can be used to explore the neurobiological basis of PTSD. However, only limited research has explored mobile EEG, which is important for scalability. This proof-of-concept study delves into mobile EEG-derived biomarkers for posttraumatic stress (PTS) symptom severity and their potential implications. Participants with partial PTSD, defined as meeting for at least three out of four symptom clusters, including hyperarousal symptoms, were enrolled in the study. Over four weeks, we measured PTS symptom severity using the PTSD checklist for DSM-5 (PCL-5) at multiple timepoints, and we recorded multiple EEG sessions from 21 individuals using a mobile EEG device. In total, we captured 38 EEG sessions, each comprising two recordings (“Recording A” and “Recording B”) that lasted approximately 180 s, to evaluate reproducibility. Next, we extracted Shannon entropy, as a measure of the brain flexibility and complexity of the signal and spectral power for the fronto-temporal regions of interest, including electrodes at AF3, AF4, T7, and T8 for each EEG recording session. We calculated the partial correlation between the EEG variables and PCL- 5 measured closest to the EEG session, using age, sex, and the grouping variable ‘batch’ as covariates. We observed a significant negative correlation between Shannon entropy in fronto- temporal regions and PCL-5 scores. Specifically, this association was evident in the AF3 ( r = -0.456, FDR-corrected p = 0.01), AF4 ( r = -0.362, FDR-corrected p = 0.04), and T7 ( r = -0.472, FDR-corrected p = 0.01) regions. Additionally, we found a significant negative association between the alpha power estimated from AF4 and PCL-5 ( r = -0.429, FDR-corrected p = 0.04). Our findings suggest that EEG markers acquired using a mobile EEG device are associated with PTS symptom severity, offering valuable insights into the neurobiological mechanisms underlying PTSD and highlighting the potential benefits of this innovative technology in assessing and monitoring PTSD.