# Computational Analysis of Neural Effects of Methylphenidate in Posttraumatic Stress Disorder

> **NIH VA IK2** · VA SAN DIEGO HEALTHCARE SYSTEM · 2023 · —

## Abstract

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...

## Key facts

- **NIH application ID:** 10663062
- **Project number:** 5IK2CX001887-05
- **Recipient organization:** VA SAN DIEGO HEALTHCARE SYSTEM
- **Principal Investigator:** Jonathon R Howlett
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2023
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2020-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10663062

## Citation

> US National Institutes of Health, RePORTER application 10663062, Computational Analysis of Neural Effects of Methylphenidate in Posttraumatic Stress Disorder (5IK2CX001887-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10663062. Licensed CC0.

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