Darius Rountree-Harrison
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About
Darius Rountree-Harrison is the QEEG analyst at STARTTS and ANFI, and a board member of the Applied Neuroscience Society of Australasia (ANSA). He studied psychology and neuroscience at the University of Sydney and Monash University and is an IQCB-certified QEEG-Diplomat. Darius has published on PTSD biomarker identification, COVID-19’s neurological impact and developmental working memory. He worked on the Royal Commission into Institutional Responses to Child Sexual Abuse and has presented on mindfulness, HRV-biofeedback and trauma at multiple conferences.
Darius was responsible for implementing biofeedback stress management programs for lawyers working in offshore detention centres. He also provided training for the Ukrainian Ministry of Health’s National Biofeedback program, which is currently running across nine hospitals in Ukraine. Since 2013, Darius has been practising a wide array of neurofeedback and biofeedback modalities and co-delivers BCIA didactic neurofeedback training at ANFI. Darius is presently exploring neuronal and cardiovascular biomarkers of stress responses in PTSD with machine learning as a PhD candidate at Macquarie University. His broader interests include the interplay between arousal, mindfulness, emotion processing, language, and psychophysics.
Presenting at the 2025 ANSA Conference
Comparison of EEGs from Traumatised Refugees to Age and gender matched Normative data and machine learning symptom associations
My presentation explores EEG biomarkers for posttraumatic stress disorder derived from comparing clinical data to the iSyncBrain normative database. The analyses revealed distinct biomarkers associated with the eyes open and closed conditions, gender differences and limited differences between clinical and sub-clinical groups. I will discuss the diversity of PTSD presentations, highlight limitations of the current data and conceptual understanding of PTSD, and provide details of my plans for more detailed analyses using phenotypic clusters and machine learning methods. This presentation will help clinicians better understand clinical presentations and their treatment implications.
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