Aims
This project aims at examining the hierarchical structure of the NIH Research Domain Criteria (RDoC) framework using large-scale data-driven computational approaches. The RDoC framework, currently only for research, ultimately aims at facilitating the development of psychiatric nosology (disorder-classification system) based upon primary behavioral functions and their associated biological features that the brain has evolved to carry out. In this project, using large-scale fMRI datasets (e.g., ABCD study), we specifically aim to examine whether (and to what degree): (1) RDoC constructs overlap across domains (2) within-domain constructs relate to similar dimensions of psychopathology; and (3) task-free paradigms (e.g., resting-state) can be mined to extract similar domain-specific information that is usually extracted using specific task-based paradigms. By addressing these three key questions, our central goal is to provide the much-needed bottom-up examination of the RDoC framework to pave a pathway for its refinement and translation.
Highlights
- Evaluating hierarchical structure of RDoC framework using circuit and behavioral data
- Examining relations between RDoC domains and dimensions of psychopathology
- Predicting domain-specific information using task-free paradigms
Presentations/Papers
- Quah, S.K.L., Booil, J., Uddin, L.Q., Mumford, J., Barch, D., Fair, D., Golib, I.H., Poldrack, R.A., Saggar, M. (2023). A data-driven latent variable approach to validate the RDoC framework. OHBM Annual Meeting, Montreal, Canada
Funding
NIMH R01