Current first-line treatments for clinical anxiety exhibit a 50-70% response plateau, with high rates of relapse, low rates of remission, and little evidence to suggest which patients may benefit from which treatment options. Barriers to progress towards a more efficient and effective approach to psychiatric care may include inadequate focus on theory-driven, mechanistic predictors of treatment outcome;the use of heterogeneous treatment protocols that require expert administration and have multiple likely mechanisms;and the current diagnostic nosology of psychiatry, which may obscure critical, transdiagnostic dimensions of biobehavioral functioning. The candidate's long-term ambition is to improve outcomes in clinical anxiety treatment through an increased focus on transdiagnostic dimensions of neurocognition. Such work has the potential to 1) guide refinement and development of novel mechanistic, """"""""neurobehavioral"""""""" treatment approaches, or treatments that target brain mechanisms through behavioral methods, and 2) fine-tune the clinical indications of specific approaches, e.g., by characterizing the specific aspects of anxiety pathophysiology that are (and are not) targeted by specific neurobehavioral treatments. The candidate's immediate focus is to study neural mechanisms of excessive attention to threat and target these mechanisms directly using a computer-based training intervention, attention bias modification (ABM). Excessive attention to threat is theorized to be a critical contributor to chronic anxiety symptoms and related negative health consequences. ABM, which directly targets this mechanism, is a highly cost-effective intervention with rapidly growing empirical support for its efficacy in clinically anxious populations. The candidate seeks to bridge basic and applied research domains by investigating neural mechanisms of threat processing in anxiety and relating these neural dimensions to ABM outcome. The current Mentored Patient Oriented Career Development Award will uniquely position the candidate to advance her long-term research agenda. Her background includes specialized training in neural mechanisms of attention to threat in anxiety, basic fMRI methods, and preliminary exposure to neurobehavioral treatment research, in addition to broad training in clinical psychology, statistics, research methods, and cognitive- affective neuroscience. She seeks to deepen, extend, and integrate across her previous training, receiving additional training in 1) neural circuitry of threat processing;2) advanced fMRI methods;and 3) clinical trials research-including basic methods for testing efficacy and advanced methods for testing neural mechanisms and predictors of outcome. The University of Pittsburgh is an outstanding environment in which to engage in the interdisciplinary training required to achieve these training goals. The candidate's mentors-Greg Siegle (University of Pittsburgh), David Brent (University of Pittsburgh), and Nader Amir (San Diego State University)-have combined expertise in advanced fMRI methods, neural and attentional mechanisms of anxiety and threat processing, clinical trials research, neurobehavioral treatments, and neural predictors and mechanisms of treatment outcome. The team's collective record of individual productivity, strong mentorship histories, and interdisciplinary collaboration makes them ideally suited to guide the candidate's trajectory. The proposed project draws on this training and expertise to examine two dimensions of attention to threat: initial vigilance and sustained bias towards threat. The proposed study will examine the neural correlates of each form of threat processing using an individual differences, transdiagnostic approach. 65 individuals with clinically disabling trait anxiety will complete fMRI tasks designed to capture these dissociable dimensions, as well as behavioral, self-report, and diagnostic measures. Participants will be randomly allocated to receive ABM (n=45), which is specifically designed to ameliorate initial vigilance to threat, or a sham intervention (n=20). A subset of ABM completers (n=20) will repeat fMRI assessments post-intervention. Data will be used to test a neural mechanistic model of ABM efficacy which posits that initial, but not sustained, neural processing of threat will be specifically targeted by ABM. Accordingly, the candidate will examine 1) neural mechanisms correlated with behavioral manifestations of initial and sustained attention to threat at baseline;2) ABM effects on symptom-level, behavioral, and neural dimensions of initial and sustained threat processing;and 3) associations between baseline neural dimensions and ABM outcomes. These analyses will give the applicant valuable experience using an individual differences approach to understand anxiety pathophysiology and outcomes following a mechanistic treatment. They will also provide pilot data for future work in programmatic neurobehavioral treatment research. Future large-scale R01 studies will be designed to, e.g., further validate identified neural dimensions of threat processing as moderators and mediators of treatment outcome, translate fMRI predictors into clinically available forms, and develop new neurobehavioral approaches designed to target predictors of ABM non-response. Consistent with NIMH's Strategic Plan Strategy 1.4 and proposed Research Domain Criteria, the ultimate goal of this work is to promote a neurocognitive process-based framework for more effective patient classification and treatment.

Public Health Relevance

This project seeks to identify neural mechanisms underlying the tendency for anxious individuals to pay more attention to threatening information than to other types of information. A computerized treatment designed to train individuals to reduce their attention towards threat will be tested, with a focus on understanding the aspects of brain function that are involved in response to the treatment. This work could ultimately lead to the ability to treat anxiety more effectively by directly targeting the aspects of brain function that re altered in a given patient.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
1K23MH100259-01
Application #
8485272
Study Section
Interventions Committee for Adult Disorders (ITVA)
Program Officer
Wynne, Debra K
Project Start
2013-04-01
Project End
2017-12-31
Budget Start
2013-04-01
Budget End
2013-12-31
Support Year
1
Fiscal Year
2013
Total Cost
$155,011
Indirect Cost
$11,379
Name
University of Pittsburgh
Department
Psychiatry
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Price, Rebecca B; Cummings, Logan; Gilchrist, Danielle et al. (2018) Towards personalized, brain-based behavioral intervention for transdiagnostic anxiety: Transient neural responses to negative images predict outcomes following a targeted computer-based intervention. J Consult Clin Psychol 86:1031-1045
Carpenter, Joseph K; Andrews, Leigh A; Witcraft, Sara M et al. (2018) Cognitive behavioral therapy for anxiety and related disorders: A meta-analysis of randomized placebo-controlled trials. Depress Anxiety 35:502-514
Price, Rebecca B; Brown, Vanessa; Siegle, Greg J (2018) Computational Modeling Applied to the Dot-Probe Task Yields Improved Reliability and Mechanistic Insights. Biol Psychiatry :
Fang, Angela; Treadway, Michael T; Hofmann, Stefan G (2017) Working hard for oneself or others: Effects of oxytocin on reward motivation in social anxiety disorder. Biol Psychol 127:157-162
Price, Rebecca B; Kuckertz, Jennie M; Amir, Nader et al. (2017) Less is more: Patient-level meta-analysis reveals paradoxical dose-response effects of a computer-based social anxiety intervention targeting attentional bias. Depress Anxiety 34:1106-1115
Price, Rebecca B; Lane, Stephanie; Gates, Kathleen et al. (2017) Parsing Heterogeneity in the Brain Connectivity of Depressed and Healthy Adults During Positive Mood. Biol Psychiatry 81:347-357
Hofmann, Stefan G; Curtiss, Joshua; Carpenter, Joseph K et al. (2017) Effect of treatments for depression on quality of life: a meta-analysis. Cogn Behav Ther 46:265-286
Price, Rebecca B; Gates, Kathleen; Kraynak, Thomas E et al. (2017) Data-Driven Subgroups in Depression Derived from Directed Functional Connectivity Paths at Rest. Neuropsychopharmacology 42:2623-2632
Furukawa, Toshi A; Weitz, Erica S; Tanaka, Shiro et al. (2017) Initial severity of depression and efficacy of cognitive-behavioural therapy: individual-participant data meta-analysis of pill-placebo-controlled trials. Br J Psychiatry 210:190-196
Hofmann, Stefan G; Curtiss, Joshua; McNally, Richard J (2016) A Complex Network Perspective on Clinical Science. Perspect Psychol Sci 11:597-605

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