Abstract
Previous studies have demonstrated relations between spontaneous neural activity evaluated by resting-state functional magnetic resonance imaging (fMRI) and symptom severity in post-traumatic stress disorder. However, few studies have used brain-based measures to identify imaging associations with illness severity at the level of individual patients. This study applied connectome-based predictive modeling (CPM), a recently developed data-driven and subject-level method, to identify brain function features that are related to symptom severity of trauma survivors. Resting-state fMRI scans and clinical ratings were obtained 10–15 months after the earthquake from 122 earthquake survivors. Symptom severity of post-traumatic stress disorder features for each survivor was evaluated using the Clinician Administered Post-traumatic Stress Disorder Scale (CAPS-IV). A functionally pre-defined atlas was applied to divide the human brain into 268 regions. Each individual’s functional connectivity 268 × 268 matrix was created to reflect correlations of functional time series data across each pair of nodes. The relationship between CAPS-IV scores and brain functional connectivity was explored in a CPM linear model. Using a leave-one-out cross-validation (LOOCV) procedure, findings showed that the positive network model predicted the left-out individual’s CAPS-IV scores from resting-state functional connectivity. CPM predicted CAPS-IV scores, as indicated by a significant correspondence between predicted and actual values (r = 0.30, P = 0.001) utilizing primarily functional connectivity between visual cortex, subcortical-cerebellum, limbic, and motor systems. The current study provides data-driven evidence regarding the functional brain features that predict symptom severity based on the organization of intrinsic brain networks and highlights its potential application in making clinical evaluation of symptom severity at the individual level.
Highlights
There is a high risk for trauma survivors to develop post-traumatic stress disorder (PTSD; Yehuda and Flory, 2007), a highly debilitating psychiatric disorder characterized by symptoms including avoidance of trauma-related stimuli, re-experiencing of the trauma, hyperarousal, and altered cognition and mood (American Psychiatric Association, 2013)
Exclusion criteria included history of any neurological or psychiatric disorder other than PTSD, psychiatric comorbidities evaluated by the structured clinical interview for DSM IV diagnosis (SCID), pregnancy, history of drug or alcohol abuse, and recent medication that might have an effect on brain function
The relations between connection strength of the positive/negative network and ClinicianAdministered PTSD Scale (CAPS)-IV scores in individual trauma survivors were examined by implementing a leave-one-out cross-validation (LOOCV) approach
Summary
There is a high risk for trauma survivors to develop post-traumatic stress disorder (PTSD; Yehuda and Flory, 2007), a highly debilitating psychiatric disorder characterized by symptoms including avoidance of trauma-related stimuli, re-experiencing of the trauma, hyperarousal, and altered cognition and mood (American Psychiatric Association, 2013). Previous studies have identified brain connectivity network alterations in trauma survivors who develop PTSD compared with those who do not (Patel et al, 2012; Lei et al, 2015; Kennis et al, 2016; Akiki et al, 2018; Niu et al, 2018). These alterations were based on group-level comparisons. Modeling the associations between phenotypic measures (e.g., ratings of illness severity) and functional brain organization can provide a basis for establishing the clinical utility of imaging data (Gao et al, 2019)
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