Abstract
IntroductionResting state functional magnetic resonance imaging (rsfMRI) studies demonstrate that individuals with posttraumatic stress disorder (PTSD) exhibit atypical functional connectivity (FC) between the amygdala, involved in the generation of emotion, and regions responsible for emotional appraisal (e.g., insula, orbitofrontal cortex [OFC]) and regulation (prefrontal cortex [PFC], anterior cingulate cortex). Consequently, atypical amygdala FC within an emotional processing and regulation network may be a defining feature of PTSD, although altered FC does not seem constrained to one brain region. Instead, altered amygdala FC involves a large, distributed brain network in those with PTSD. The present study used a machine‐learning data‐driven approach, multi‐voxel pattern analysis (MVPA), to predict PTSD severity based on whole‐brain patterns of amygdala FC.MethodsTrauma‐exposed adults (N = 90) completed the PTSD Checklist‐Civilian Version to assess symptoms and a 5‐min rsfMRI. Whole‐brain FC values to bilateral amygdala were extracted and used in a relevance vector regression analysis with a leave‐one‐out approach for cross‐validation with permutation testing (1,000) to obtain significance values.ResultsResults demonstrated that amygdala FC predicted PCL‐C scores with statistically significant accuracy (r = .46, p = .001; mean sum of squares = 130.46, p = .001; R 2 = 0.21, p = .001). Prediction was based on whole‐brain amygdala FC, although regions that informed prediction (top 10%) included the OFC, amygdala, and dorsolateral PFC.ConclusionFindings demonstrate the utility of MVPA based on amygdala FC to predict individual severity of PTSD symptoms and that amygdala FC within a fear acquisition and regulation network contributed to accurate prediction.
Highlights
Resting state functional magnetic resonance imaging studies demonstrate that individuals with posttraumatic stress disorder (PTSD) exhibit atypical functional connectivity (FC) between the amygdala, involved in the generation of emotion, and regions responsible for emotional appraisal and regulation
Several insights emerged from this investigation: First, whole-brain patterns of amygdala FC did significantly predict severity of Posttraumatic stress disorder (PTSD) symptoms, indicating that whole-brain patterns of amygdala connectivity are meaningfully related to variability in PTSD outcomes in trauma-exposed individuals
We demonstrated that multi-voxel pattern analysis (MVPA) in the context of amygdala FC is a valid approach for predicting severity of PTSD symptoms at the individual level
Summary
Resting state functional magnetic resonance imaging (rsfMRI) studies demonstrate that individuals with posttraumatic stress disorder (PTSD) exhibit atypical functional connectivity (FC) between the amygdala, involved in the generation of emotion, and regions responsible for emotional appraisal (e.g., insula, orbitofrontal cortex [OFC]) and regulation (prefrontal cortex [PFC], anterior cingulate cortex). Atypical amygdala FC within an emotional processing and regulation network may be a defining feature of PTSD, altered FC does not seem constrained to one brain region. Conclusion: Findings demonstrate the utility of MVPA based on amygdala FC to predict individual severity of PTSD symptoms and that amygdala FC within a fear acquisition and regulation network contributed to accurate prediction. As interest in precision medicine grows (Collins & Varmus, 2015), more research is needed on the amygdala and its broader connectivity across the brain in those with PTSD in order to assess whether this may be meaningfully related to the disorder and provide insight into treatment can lead to remediation of symptoms
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