Towards Assessing Subcortical “Deep Brain” Biomarkers of PTSD with Functional Near-Infrared Spectroscopy

Abstract

Assessment of brain function with functional near-infrared spectroscopy (fNIRS) is limited to the outer regions of the cortex. Previously, we demonstrated the feasibility of inferring activity in subcortical "deep brain" regions using cortical fMRI and fNIRS activity in healthy adults. Access to subcortical regions subserving emotion and arousal using affordable and portable fNIRS is likely to be transformative for clinical diagnostic and treatment planning. Here, we validate the feasibility of inferring activity in subcortical regions that are central to the pathophysiology of PTSD (i.e., amygdala and hippocampus) using cortical fMRI and simulated fNIRS activity in a sample of adolescents diagnosed with PTSD (N=20, mean age=15.3, SD=1.9 years) and age-matched healthy controls (N=20, mean age=14.5, SD=2.0 years) as they performed a facial expression task. We tested different prediction models, including linear regression, a multi-layer perceptron neural network, and a k-nearest neighbors model. Inference of subcortical fMRI activity with cortical fMRI showed high prediction performance for the amygdala (r>0.91) and hippocampus (r>0.95) in both groups. Using fNIRS simulated data, relatively high prediction performance for deep brain regions was maintained in healthy controls (r>0.79), as well as in youths with PTSD (r>0.75). The linear regression and neural network models provided the best predictions.