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

Area of Science:

• Neuroscience
• Psychiatry
• Biomedical Engineering

Background:

• Posttraumatic Stress Disorder (PTSD) is a complex mental health condition requiring better diagnostic and monitoring tools.
• Understanding the neurobiological underpinnings of PTSD is critical for advancing treatment.
• Mobile electroencephalography (EEG) offers a scalable approach to investigate brain activity but has been underutilized in PTSD research.

Purpose of the Study:

• To explore mobile EEG-derived biomarkers for assessing posttraumatic stress (PTS) symptom severity.
• To investigate the potential of mobile EEG for scalable and accessible PTSD assessment.

Main Methods:

• A proof-of-concept study involving 21 individuals with partial PTSD over four weeks.
• Utilized a mobile EEG device to record brain activity (Shannon entropy and spectral power) from fronto-temporal regions.
• Correlated EEG measures with PTSD symptom severity assessed via the PTSD Checklist for DSM-5 (PCL-5), controlling for age, sex, and batch.

Main Results:

• A significant negative correlation was found between Shannon entropy in fronto-temporal regions (AF3, AF4, T7) and PCL-5 scores, indicating reduced brain signal complexity with increased symptom severity.
• Alpha power in the AF4 region also showed a significant negative association with PCL-5 scores.
• These findings demonstrate the association between mobile EEG markers and PTS symptom severity.

Conclusions:

• Mobile EEG-derived biomarkers, specifically Shannon entropy and alpha power, are associated with PTS symptom severity.
• This technology holds potential for innovative, scalable methods to assess and monitor PTSD.
• Further research can leverage mobile EEG to gain deeper insights into PTSD neurobiology and facilitate early diagnosis and treatment.