Journal
BEHAVIOUR RESEARCH AND THERAPY
Volume 124, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.brat.2019.103513
Keywords
Posttraumatic stress disorder; Fear-conditioning; Generalization; Threat expectancy; Nonparametric regression; Exposure therapy
Categories
Funding
- National Institutes of Health [R00MH080130]
- Congressionally Directed Medical Research Program
- Department of Defense [PT074550]
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One key conditioning abnormality in posttraumatic stress disorder (PTSD) is heightened generalization of fear from a conditioned danger-cue (CS+) to similarly appearing safe stimuli. The present work represents the first effort to track the time-course of heightened generalization in PTSD with the prediction of heightened PTSD-related over-generalization in earlier but not later trials. This prediction derives from past discriminative fear-conditioning studies providing incidental evidence that over-generalization in PTSD may be reduced with sufficient learning trials. In the current study, we re-analyzed previously published conditioned fear-generalization data (Kaczkurkin et al., 2017) including combat veterans with PTSD (n = 15) or subthreshold PTSD (SubPTSD: n = 18), and trauma controls (TC: n = 19). This re-analysis aimed to identify the trial-by-trial course of group differences in generalized perceived risk across three classes of safe generalization stimuli (GSs) parametrically varying in similarity to a CS + paired with shock. Those with PTSD and SubPTSD, relative to TC, displayed significantly elevated generalization to all GSs combined in early but not late generalization trials. Additionally, over-generalization in PTSD and SubPTSD persisted across trials to a greater extent for classes of GSs bearing higher resemblance to CS+ . Such results suggest that PTSD-related over-generalization of conditioned threat expectancies can be reduced with sufficient exposure to unreinforced GSs and accentuate the importance of analyzing trial-by-trial changes when assessing over-generalization in clinical populations.
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