James Lisa M, Enghdal Brian E, Leuthold Arthur C, Georgopoulos Apostolos P
The PTSD Research Group, Brain Sciences Center, Department of Veterans Affairs Health Care System, Minneapolis, MN, USA.
Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, USA.
J Neurol Neuromedicine. 2021;6(1):13-20. doi: 10.29245/2572.942x/2021/1.1279.
Previous research has demonstrated highly accurate classification of veterans with posttraumatic stress disorder (PTSD) and controls based on synchronous neural interactions (SNI), highlighting the utility of SNI as a biomarker of PTSD. Here we extend that research to classify additional trauma-related outcomes including subthreshold PTSD, partial recovery, and full recovery according to SNI. A total of 219 U.S. veterans completed diagnostic interviews and underwent a magnetoencephalography (MEG) scan from which SNI was computed. Linear discriminant analysis was used to classify the PTSD and control brains, achieving 100% accuracy. That discriminant function was then used to classify each brain in the subthreshold PTSD, partial recovery, and full recovery diagnostic groups as PTSD or Control. All of the subthreshold PTSD diagnostic group were classified as PTSD, as were three-quarters of the partial recovery group. Findings regarding the full recovery group were mixed, documenting variability in the functional brain status of PTSD recovery. The results of the present study add to the literature supporting the discriminatory power of MEG SNI and demonstrate the utility of SNI as a biomarker of various PTSD-related trajectories.
先前的研究表明,基于同步神经交互作用(SNI),能够对患有创伤后应激障碍(PTSD)的退伍军人和对照组进行高度准确的分类,这突出了SNI作为PTSD生物标志物的效用。在此,我们将该研究扩展至根据SNI对包括阈下PTSD、部分恢复和完全恢复在内的其他创伤相关结果进行分类。共有219名美国退伍军人完成了诊断访谈并接受了脑磁图(MEG)扫描,从中计算出SNI。采用线性判别分析对PTSD患者和对照组的大脑进行分类,准确率达到100%。然后使用该判别函数将阈下PTSD、部分恢复和完全恢复诊断组中的每个大脑分类为PTSD或对照组。所有阈下PTSD诊断组均被分类为PTSD,部分恢复组中也有四分之三被分类为PTSD。关于完全恢复组的研究结果不一,记录了PTSD恢复过程中大脑功能状态的变异性。本研究结果补充了支持MEG SNI判别能力的文献,并证明了SNI作为各种PTSD相关轨迹生物标志物的效用。