Project Details
Projekt
Linking Latent Transdiagnostic Anxiety Dimensions to Neural Functioning
Applicant
Professorin Dr. Anja Riesel
Subject Area
Personality Psychology, Clinical and Medical Psychology, Methodology
Term
since 2018
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 390963431
Background: Anxiety disorders are the most prevalent mental disorders and pose a significant burden of disease. To improve interventions, it is essential to broaden the understanding of the underlying pathophysiological mechanisms involved in the development and maintenance of anxiety. It is hoped that focusing on transdiagnostic dimensions of anxiety might advance the research. The goal of the first funding period of the DFG project was to examine psychophysiological mechanisms related to two core transdiagnostic dimensions of anxiety (i.e., anxious apprehension and anxious arousal). Four processes were examined: 1) error-processing, 2) the processing of predictable and unpredictable threat, 3) resting state brain activity, and 4) habituation processes to aversive stimuli. The results of the first funding phase refined our understanding of the neural processes associated with transdiagnostic dimensions of anxiety, pointed to boundary conditions, and have enriched and stimulated the related areas of research. Yet, only a restricted spectrum of patients with anxiety disorders was included, which limits the generalizability of the results.Aims and objectives: This renewal proposal aims at increasing our understanding of the neural mechanisms underlying transdiagnostic anxiety dimensions by increasing the spectrum of included anxiety patients. The same tasks will be used to facilitate collapsing the data and to enable data-driven analyses in a large sample. The project has three sub-aims:1. Examine transdiagnostic versus disorder-specific differences in neural mechanisms that have been closely linked to anxiety symptom dimensions (top-down approach).2. Apply machine learning techniques to differentiate clinical groups based on quantitative EEG parameters during rest.3. Data-driven clustering and forming of neural profiles using the psychophysiological markers and linking them to anxiety symptom dimensions (bottom-up approach).Planned method: We aim at recruiting 120 participants with anxiety disorders, 40 each with generalized anxiety disorder, panic disorder, and agoraphobia (with and without comorbid panic disorder), and 80 healthy participants, matched for gender and educational level. Participants will perform a resting state measure, the flanker task, the NPU-threat task and a picture viewing task while there EEG and peripherphysiology (startle and skin conductance) is recorded, following the same procedure as in the first funding period. For data-driven analyses (sub-aims 2 and 3), data of both funding periods will be collapsed adding up to ca. 500 participants to examine associations between data-driven subtypes and anxiety dimensions and traits.Expected impact: The proposed project contributes to identifying transdiagnostic and/or disorder-specific psychopathological mechanisms relevant to anxiety disorders. A better mechanistic understanding has the potential to inform novel and adapt existing interventions and prevention strategies.
DFG Programme
Research Grants
