The Research Domain Criteria (RDoC) project initiated a framework for developing research classifications based on functional dimensions emerging from translational research on genes, behaviors, circuits, and other cognitive-biological parameters. Almost a decade later, RDoC has grown into a matrix consisting of functional domains (e.g., cognitive systems), domain-specific constructs (e.g., attention, perception), and units of analysis for measuring each construct (e.g., physiology, behavior, genes, etc.). Numerous studies have contributed to defining each construct in terms of cognitive-biological parameters, and while these efforts have been broadly successful, the dimensional RDoC constructs themselves remain largely unvalidated. This lack of adequate validation is central to RFA-MH-19-242, which requests proposals that ?perform unbiased data-driven validation of existing constructs that may involve merging, subdividing, or hierarchically organizing them by integrating data between and within constructs.? Specifically, the RFA calls for studies that use ?multiple behavioral tasks and levels of analysis per construct,? ?multimodal data fusion ? to unbiasedly classify and compare constructs,? and ?data-driven definitions of constructs that involve structural and functional data on how brain states, networks, circuit dynamics, and hierarchies in the signals relate to outputs from task-based assays.? The RFA also encourages the use of ?accelerated longitudinal designs, with a particular emphasis on development ? and cutting-edge computational approaches to classify, predict, and explain developmental trajectories.? The Developmental Multimodal Imaging of Neurocognitive and (Epi)genomic Dynamics (Dev- MIND) Consortium responds to this call with an innovative, large-scale developmental multimodal neuroimaging study that will leverage previously-developed longitudinal pediatric cohorts and data fusion algorithms that this team established through the NSF-supported Dev-Cog project. Specifically, Dev-MIND will evaluate the unitarity and potential hierarchical structure of three constructs within the cognitive systems domain (i.e., attention, cognitive control, and working memory) using a battery of custom cognitive tasks, multimodal imaging, (epi)genomic analysis, an accelerated longitudinal design, and data-driven similarity metrics for construct validation testing. Our neuroimaging approach will include dynamic functional mapping based on magnetoencephalography (MEG), high-resolution volumetric MRI analyses based on multimodal parcellation, and functional MRI (fMRI) for whole-brain dynamic functional connectivity. These neuroimaging and behavioral performance metrics will also be combined with (epi)genetic data to identify covariance between genomic, cognitive, and neural activity patterns. Such data-driven approaches will enable classification and prediction of developmental trajectories per construct, and are central to the goals of computational psychiatry. In sum, this project brings together leading investigative teams, an array of state-of-the-art neuroimaging technology, and cutting-edge analytical methods to perform unbiased, data-driven validation of existing RDoC constructs.
The Research Domain Criteria (RDoC) framework is an emerging approach to classifying mental disorders based on dimensions of observable behavior and neurobiological measures. While the RDoC approach has been successful and seen relatively wide use, many of the central constructs that comprise the framework have not been validated, and the applicability of the framework to the developing brain is not well understood. The Developmental Multimodal Imaging of Neurocognitive and (epi)genomic Dynamics (Dev-MIND) Consortium will use a battery of custom cognitive tasks, advanced dynamic functional brain mapping methods, the latest in structural and diffusion MRI, (epi)genomic analyses, a unique longitudinal study design focused on development, and data-driven analyses to validate and/or amend cognitive constructs in the RDoC framework.
