Neurocomputational Changes in Inhibitory Control Associated With Prolonged Exposure Therapy

Abstract

Posttraumatic stress disorder (PTSD) is associated with inhibitory control dysfunction that extends beyond difficulties inhibiting trauma-related intrusions. Inhibitory learning has been proposed as a potential mechanism of change underlying the effectiveness of extinction-based therapies such as prolonged exposure (PE), a first-line treatment for PTSD. To identify neurocognitive markers of change in inhibitory learning associated with PE, we applied a Bayesian learning model to the analysis of neuroimaging data collected during an inhibitory control task, both before and after PE treatment. Veterans (N = 20) with combat-related PTSD completed a stop-signal task (SST) while undergoing fMRI at time points immediately before and after PE treatment. Participants exhibited a small, significant improvement in performance on the SST, as demonstrated by longer reaction times and improved inhibition accuracy. Amplitude of neural activation associated with a signed prediction error (SPE; i.e., the discrepancy between actual outcome and model-based expectation of needing to stop) in the right caudate decreased from baseline to posttreatment assessment. Change in model-based activation was modulated by performance accuracy, with a decrease in positive SPE activation observed on successful trials, d = 0.79, and a reduction in negative SPE activation on error trials, d = 0.74. The decrease in SPE-related activation on successful stop trials was correlated with PTSD symptom reduction. These results are consistent with the notion that PE may help broadly strengthen inhibitory learning and the development of more accurate model-based predictions, which may thus facilitate change in cognitions in response to trauma-related cues and help reduce PTSD symptoms.