Posttraumatic stress disorder (PTSD) is one of the most common service-related mental health conditions among all treatment-seeking Veterans, and the critical lack of advancement in pharmacological treatment of this disorder has recently been termed an urgent crisis by leaders in the field. The absence of progress in developing more effective treatments targeting PTSD stems from an inability to objectively characterize behavioral dysfunction related to PTSD symptoms and link it directly to underlying neural process dysfunction that can be targeted with medications. One of the most encouraging recent developments in the psychopharmacology of PTSD was a randomized controlled trial (RCT) showing that the norepinephrine (NE) and dopamine (DA) reuptake inhibitor methylphenidate (MPH) was associated with a remarkably robust reduction in PTSD symptoms, but the effects of MPH on complex behaviors remains poorly understood, and improved understanding of its mechanism in PTSD will be crucial for individualized patient selection and for development of new interventions targeting similar mechanisms. This application seeks to integrate (a) a computational psychiatry approach with (b) pharmacological intervention with MPH and (c) functional neuroimaging to characterize a complex pharmacologic mechanism in PTSD and assist the development of process- and neural circuit-specific interventions for Veterans with this disabling condition. A core feature across multiple PTSD symptom clusters is a failure to appropriately modulate the salience of cues according to environmental context. MPH, via its NE and DA actions, is known to improve modulation of salience according to context in attention deficit hyperactivity disorder (ADHD), suggesting a similar mechanism may underlie its efficacy in PTSD. The failure of contextual salience regulation in PTSD spans multiple symptom domains, indicating the value of a unifying computational psychopharmacology approach to salience that can go beyond description of disparate symptoms and measure a core underlying process dysfunction and its improvement with MPH. Accumulating evidence indicates that a computational surprise- driven learning paradigm can quantitatively operationalize the deficit in salience modulation as a failure to scale surprise according to environmental volatility (rate of change): (1) In healthy subjects, environmental volatility scales surprise-driven learning via brain NE and DA; this process is impaired in anxious individuals. (2) Our own preliminary data indicate that individuals with PTSD exhibit exaggerated surprise-driven learning in a stable environment. (3) Our own preliminary data indicate that MPH enhances the influence of environmental volatility on surprise-driven learning in healthy subjects. (4) Our own preliminary fMRI data in a sample of combat Veterans indicates that PTSD symptoms are associated with exaggerated activation to surprise in a salience-sensitive region in the posterior parietal c...