Assessing functional interactions among neural populations provided 90% accuracy of detection, as reported in the Journal of Neural Engineering.

A group of researchers report that differences in brain function between PTSD and control groups can be used to diagnose the disease. Their studies suggest that it can also be used to assess and monitor PTSD progression and effects of therapy.

The findings are published January 20 in the Journal of Neural Engineering in a paper titled “The synchronous neural interactions test as a functional neuromarker for post-traumatic stress disorder (PTSD): a robust classification method based on the bootstrap.” The research was led by Apostolos Georgopoulos, M.D., Ph.D., and Brian Engdahl, Ph.D., both members of the Brain Sciences Center at the Minneapolis VA Medical Center and University of Minnesota.

A group of 74 U.S. veterans and 250 healthy controls were involved in the study and were evaluated using magnetoencephalography (MEG), a noninvasive measurement of magnetic fields in the brain. The MEG has 248 sensors that record the interactions in the brain on a millisecond by millisecond basis, much faster than current methods of evaluation such as fMRI, which takes seconds to record.

The scientists demonstrated that the synchronous neural interactions test, which assesses the functional interactions among neural populations derived from MEG recordings, could successfully differentiate PTSD patients from healthy control subjects. Externally cross-validated analyses yielded a greater than 90% overall accuracy of classification. In addition, all but one of 18 patients who were not receiving medications were correctly classified.

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