Joshua Cisler - US grants

DESCRIPTION (provided by applicant): This proposal for a NIMH Exploratory/Developmental Grant Award (R21) seeks to identify neural functional connectivity patterns associated with response to Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) among female adolescent assault victims. Adolescent assault exposure is a potent risk factor for persistent psychopathology, most notably PTSD. TF-CBT is the only treatment for adolescent PTSD victims with strong empirical support, yet response to TF-CBT is variable and many victims continue to exhibit clinically significant symptoms following treatment. The overall goal of this proposal is to use computational neuroscience tools to predict and understand treatment response among this vulnerable population. Based on human neuroimaging studies demonstrating altered activity and connectivity within neural networks mediating emotion reactivity and emotion regulation among PTSD victims, we hypothesize that patterns of functional connectivity within these neural networks can be used to predict and understand response to TF-CBT among adolescent assault victims. 45 adolescent assault victims aged 11-16 will be provided with a 12-week course of TF-CBT. Participants will undergo fMRI scanning while engaged in emotion reactivity and emotion regulation tasks before and after treatment. A combination of graph theory analyses and support vector classification and regression will be used to identify pre-treatment patterns of functional connectivity that predict subsequent response to TF-CBT (Aim 1). Graph theory analyses will similarly be used to identify changes in network organization from pre-to-post-treatment associated with successful (Aim 2) and unsuccessful (Aim 3) treatment response. This analytic approach to the clinical problem of understanding the variable response to TF-CBT will foster concrete algorithms to be used by a clinician to predict a child's treatment response, which is the first step towards personalizing treatments for this vulnerable population. Further, this analytic approach will identify the essential neural mechanism mediating treatment response and provide targets for the development of novel treatment components. This application proposes a novel approach towards understanding treatment response among a vulnerable adolescent population and will hopefully facilitate the development of more consistent interventions to ameliorate the high cost associated with adolescent assault exposure. PUBLIC HEALTH RELEVANCE: This proposal investigates neural network predictors of treatment outcome among assaulted adolescent girls. This research will lead to a better understanding of how treatment works and why some children do not respond to treatment.

? DESCRIPTION (provided by applicant): This proposal for a NIMH Exploratory/Developmental Grant Award (R21) seeks to critically evaluate and expand upon leading neurocircuitry models of trauma and PTSD among assaulted adolescent girls. Existing neurocircuitry models of trauma and PTSD focus almost exclusively on identifying the neural mechanisms that explain observed hypervigilance for threat and deficits in fear extinction learning. While these models have ample empirical support, they do not explain known deficits in risk perceptions of social situations and increased rates of revictimization among assault-exposed and PTSD populations. By contrast, our pilot study demonstrated that assaulted adolescent girls display both worse behavioral performance and decreased activation of anterior cingulate cortex and bilateral anterior insular cortex during a social learning task, which suggests a novel mechanism to explain known social functioning deficits in these populations. Based on these pilot data, we hypothesize that expanding existing neurorcircuitry models to include weakened brain and behavioral correlates of social prediction error encoding increases explanatory power for PTSD symptoms and functional deficits among assaulted adolescent girls. We propose to recruit control, assaulted without PTSD, and assaulted with PTSD adolescent girls and administer both a threat processing task and our previously used social learning task during fMRI. Participants would also complete a standardized risk perception task, in which they are presented with written vignettes depicting increasingly dangerous social situations. Aim 1 seeks to demonstrate that weakened encoding of social prediction errors among assaulted adolescent girls mediates decreased risk perceptions to the standardized risk social situation vignettes when controlling for variance explained by neural mechanisms on the threat processing task. Aim 2 seeks to demonstrate that weakened encoding of social prediction errors among assaulted adolescent girls predicts 3-month trajectories of PTSD symptoms when controlling for variance explained by neural mechanisms on the threat detection task. The overarching purpose of the proposed project is to demonstrate increased explanatory power of a neurocircuitry model that includes social processing deficits. Successful completion of the proposed project would stimulate new conceptualizations of the toxic effects of early life trauma and PTSD, and hopefully lead to improved prevention and treatment programs.

? DESCRIPTION (provided by applicant): This R21/R33 application in response to RFA-MH-15-300 seeks to demonstrate target engagement and clinical viability for a novel combination therapy for Posttraumatic Stress Disorder. PTSD is associated with poor quality of life and comorbidity with both physical and mental illness. While exposure-based psychological treatments have proven efficacious, up to 40% retain PTSD diagnoses following treatment. Thus, new protocols to boost treatment efficacy can have a significant public health impact. Recent basic research suggests that consolidation of fear extinction learning memories is at least partly dopamine-mediated and that boosting dopamine signaling in the consolidation window can decrease fear responding during subsequent exposure to fear cues. The overall goal of the proposed project is to demonstrate the viability of boosting dopamine signaling in the post-learning consolidation window as a novel means of boosting therapy outcomes among adult women with PTSD related to assaultive violence (physical or sexual assault). In the R21 target engagement phase, we will test the impact of endogenous and exogenous manipulations of dopamine neurotransmission on 1) acute functional organization of dopaminergic resting-state networks, and 2) the consolidation of generic (i.e., laboratory-induced) fear extinction learning using concurrent neuroimaging, psychophysiological, and self-report assessments among women with PTSD (Aim 1). In the R33 clinical phase, we seek to replicate and extend target engagement to the clinical context of fear extinction learning for ideographic trauma memories and emotional responding to trauma cues among women with PTSD using concurrent neuroimaging, psychophysiological, and self-report assessments (Aim 2). Successful demonstration of target engagement (Aim 1) and efficacy for the clinical target of trauma memories and emotional responding to trauma cues (Aim 2) would provide critical scientific support of the viability of combining exposure-based therapy with pharmacological agents that boost dopamine signaling as a means to improve treatment outcomes for PTSD.

Project Summary The goal of this proposal is to characterize novel computational biases in learning and decision-making in PTSD. The dominant understanding of PTSD emphasizes heightened fear learning and threat detection, and weakened fear extinction / inhibition. While this model explains many aspects of PTSD, there is a growing gap between our models of PTSD and the emerging literature defining the normative computational mechanisms of learning and decision-making. This proposal aims to bridge this gap by defining computational biases in two clinically-relevant domains of learning and decision-making in PTSD. First, the mechanisms by which individuals with PTSD prefer avoiding threat at the expense of losing potential reward is not understood. This bias in approach-avoidance conflict resolution is an essential feature of the clinical presentation of PTSD, and though threat processing and reward processing have separately been characterized in PTSD, how threat and reward processing interact to result in biases towards avoidance has never been investigated. Second, dysregulation of context-depending (i.e., latent state) learning has clear clinical implications in PTSD: generalization of threat learning outside the trauma context is related to the development of PTSD; generalization of extinction learning outside of the clinical context is related to the treatment of PTSD. However, computational models of context-modulated learning have not been used to understand these processes in PTSD. The current project proposes to use computational modeling of learning and decision- making in novel tasks that probe the behavioral and brain mechanisms of approach-avoidance biases (Specific Aim 1) and context-modulated (i.e., latent state) learning (Specific Aim 2). A case-controlled design would be used, in which healthy adults, trauma-exposed adults without PTSD, trauma-exposed adults with PTSD, and adults with non-PTSD anxiety disorders would undergo novel learning and decision-making tasks during fMRI with concurrent psychophysiological assessment. By defining novel computational biases in learning and decision-making in PTSD, the project 1) would bridge the gap between our understanding of PTSD and our the growing science of computational mechanisms of learning, 2) has the potential to explain clinically-relevant features of dysfunction in PTSD, and 3) would provide targets for tracking trajectories of PTSD development and treatment, and stimulate novel methods for treating PTSD that go beyond the traditional fear conditioning and extinction models.