A Transdiagnostic fMRI Dataset With 300+ Deeply Phenotyped Subjects Across Resting and Task States

YaleNeuroConnect is a human functional MRI (fMRI) dataset collected at Yale University that includes functional MRI data (and the respective functional connectomes) obtained under resting-state and six task conditions. There are 302 diagnostically and demographically diverse subjects, each with extensive neuropsychological testing and symptom inventories obtained outside of the MRI. Prior studies have shown that stronger predictive models relating the brain to external measures can be built with connectivity data obtained during continuous performance tasks instead of the more common resting-state. The tasks here were selected to exercise the brain across various cognitive domains. For each subject, 48 minutes of fMRI data and high-resolution 3D brain volumes were obtained. The fMRI data, along with the deep phenotyping data in a diverse subject pool, allow studies of brain parcellation under different conditions, the relationship between cognitive and clinical measures, identification of circuits supporting external measures, and data for the development of brain-based tests. The transdiagnostic nature of the sample allows a sufficient range of symptom scores to test the principles of the Research Domain Criteria framework.