The NIMH research domain criteria (RDoC) reconceptualizes mental health research along a series of key
cross-disorder dimensional constructs. However, these dimensions were determined in a top-down fashion by
relatively small groups of researchers. We propose a data-driven approach that tests the validity of the key RDoC
constructs of attention, cognitive control, and working memory. We will evaluate these constructs using multiple
cognitive tasks per construct to examine their relationship to brain networks and their ability to predict real-world
behaviors that are relevant to mental health. Finally, we propose an augmentation to the RDoC framework by
adding new units of analysis: contrasts and practice.
The current RDoC matrix maps directly from task paradigms to constructs and subconstructs, which is
problematic because supposedly distinct constructs can sometimes map to exactly the same set of tasks. To
address this, we propose a new RDoC unit of analysis called a “contrast”, which better reflects the usual logic of
experimental design. We will identify mappings between cognitive systems constructs and contrasts through
consultation with domain experts. We will then acquire a large-scale dataset to test both exploratory and
confirmatory models for RDoC cognitive system constructs. Finally, we will evaluate whether these RDoC
cognitive systems constructs are predictive of related real-world outcomes.
The RDoC matrix links constructs to both behavioral measures and neural circuits, but the present mappings
between cognitive systems constructs and brain systems are sparse and inconsistent. We will use a dense-
sampling fMRI acquisition of 65 subjects each completing 10 scanning sessions on the same battery of tasks as
the behavioral study, to develop a precise data-driven atlas of neural engagement at each level of the matrix,
from contrasts to subconstructs to constructs. We will then validate the behaviorally-derived models using neural
data, both between subjects and within subjects. We will also perform fully exploratory analyses to identify
whether the data-driven neural circuit structure on these tasks diverges from the RDoC matrix.
A long history of research in both and animals has shown that repeated practice on a task changes the way
that the task is performed and the brain systems that support performance. We will leverage our behavioral and
brain imaging samples to evaluate whether the structure of the cognitive systems domain remains constant with
practice. In parallel we will also apply exploratory methods to assess the consistency of structural models
estimated either early in training or after extensive practice.
Overall, this project expands the RDoC matrix with two new units of analysis (contrasts and practice), and
validates the constructs of attention, cognitive control, and working memory across both behavior and neural