Abstract
Despite the widespread use of the Research Domain Criteria (RDoC) framework in psychiatry and neuroscience, recent studies suggest that the RDoC is insufficiently specific or excessively broad relative to the underlying brain circuitry it seeks to elucidate. To address these concerns, we employed a latent variable approach using bifactor analysis. We examined 84 whole-brain task-based fMRI (tfMRI) activation maps from 19 studies with 6,192 participants. A curated subset of 37 maps with a balanced representation of RDoC domains constituted the training set, and the remaining held-out maps formed the internal validation set. External validation was conducted using 36 peak coordinate activation maps from Neurosynth, using terms of RDoC constructs as seeds for topic meta-analysis. Here, we show that a bifactor model incorporating a task-general domain and splitting the cognitive systems domain better fits the examined corpus of tfMRI data than the current RDoC framework. We also identify the domain of arousal and regulatory systems as underrepresented. Our data-driven validation supports revising the RDoC framework to reflect underlying brain circuitry more accurately.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
The manuscript has been revised based on reviewer comments. Changes have primarily been made to the discussion to acknowledge the limitations of the study. The results remain the same, but the internal validation step now compares all four models instead of just the data-driven bifactor model and RDoC specific factor model. Correlation between brain factor maps in Figure 4B have also been corrected for spatial autocorrelation.
Data availability
The whole-brain task fMRI contrast maps used in this study are publicly available at the neurovault.org website. The coordinate activation maps used are available at neurosynth.org.
