The synchronous neural interactions test as a functional neuromarker for post-traumatic stress disorder (PTSD): A robust classification method based on the bootstrap

A. P. Georgopoulos, H. R.M. Tan, S. M. Lewis, A. C. Leuthold, A. M. Winskowski, J. K. Lynch, B. Engdahl

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

Traumatic experiences can produce post-traumatic stress disorder (PTSD) which is a debilitating condition and for which no biomarker currently exists (Institute of Medicine (US) 2006 Posttraumatic Stress Disorder: Diagnosis and Assessment (Washington, DC: National Academies)). Here we show that the synchronous neural interactions (SNI) test which assesses the functional interactions among neural populations derived from magnetoencephalographic (MEG) recordings (Georgopoulos A P et al 2007 J. Neural Eng. 4 349-55) can successfully differentiate PTSD patients from healthy control subjects. Externally cross-validated, bootstrap-based analyses yielded >90% overall accuracy of classification. In addition, all but one of 18 patients who were not receiving medications for their disease were correctly classified. Altogether, these findings document robust differences in brain function between the PTSD and control groups that can be used for differential diagnosis and which possess the potential for assessing and monitoring disease progression and effects of therapy.

Original languageEnglish (US)
Article number016011
JournalJournal of neural engineering
Volume7
Issue number1
DOIs
StatePublished - Feb 19 2010

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