Abstract
Posttraumatic growth (PTG) is the advantageous change some people report following the struggle to overcome traumatic life circumstances. As neural understanding of PTG is limited, debate persists regarding whether PTG represents “real” or “illusory” change. This study presents a novel supervised machine learning examination, predicting high versus low PTG from electroencephalographic (EEG) data collected from 66 trauma-exposed individuals. Alpha and gamma EEG frequency power accurately classified PTG and demonstrated the disruptive neural influence of posttraumatic stress disorder. Results provide objectively measurable neural evidence of the existence of PTG and the first whole-brain, high-density EEG scalp topographies of PTG in known literature.
Acknowledgements
The authors are grateful to Nicholas Roots for data collection; Catherine Kennon and Dr Jonathan Robinson for early coding support; and the Australian Government Research Training Program for supporting the first author. This research was enabled by use of equipment and facilities in the School of Psychology and Counseling at Queensland University of Technology.
Author contributions
Conceptualization–AG, PJ, JS; data curation–AG; formal analysis–AG, PJ, JM, JS; investigation–AG; methodology–PJ, AG, JM, JS; project administration–AG; resources–PJ, JS, JM; software–PJ, AG, JM; supervision–JM, JS, PJ; validation–JM, PJ, JS; visualization–AG, PJ, JM; writing: original draft–AG; writing: review and editing–AG, JS, JM, PJ.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
Data supporting the findings of this study are available from the corresponding author on request.
Additional information
Notes on contributors
Ammanda-Jane Glazebrook
Ammanda-Jane Glazebrook is a final-year doctoral candidate in the School of Psychology and Counseling at Queensland University of Technology, Brisbane, Australia. AJ’s primary focus is the promotion of psychological health following adversity, including using applied neuroscientific approaches. AJ is also a sessional academic with Central Queensland University, Australia, and has received national recognition for her work in industry applying psychological neuroscience and strategy to workplace health, safety, and well-being.
Jane Shakespeare-Finch
Jane Shakespeare-Finch is professor in the School of Psychology and Counseling at Queensland University of Technology, Brisbane, Australia. Jane’s primary area of teaching and research is psychological trauma, specializing in posttraumatic growth. Professor Shakespeare-Finch has published widely in the area, is a regular presenter at national and international conferences, and is a Scientific Advisory Board member for the Bouldercrest Institute for Posttraumatic Growth, USA.
Patrick Johnston
Patrick Johnston is science advisor with the Defence Science and Technology Group, Eagle Farm, Australia. His primary expertise is in human perception and cognition and in understanding brain signals using neuroimaging techniques such as EEG, MEG, and fMRI. He also is active in the areas of machine learning and AI.
Johan van der Meer
Johan van der Meer is a postdoctoral researcher in the School of Information Systems at Queensland University of Technology, Brisbane, Australia. His major interest lies in the closed-loop systems, especially in how long-term training of brain signals corresponds to electrophysiological or behavioral change. He designs and uses open-source EEG technology that is portable to allow electrophysiological research to also take place in remote areas.