The positive-negative mode link between brain connectivity, demographics, and behavior: A pre-registered replication of Smith et al. 2015

In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to mental health disorders. Recently, a family of data-driven analyses have provided such reliable measures when applied to large, population-level datasets. In the current pre-registered replication study, we show that the canonical correlation analysis (CCA) methods previously developed using resting-state MRI functional connectivity and subject measures of cognition and behavior from healthy adults are also effective in measuring well-being (a "positive-negative axis") in an independent developmental dataset. Our replication was successful in two out of three of our pre-registered criteria, such that a primary CCA mode's weights displayed a significant positive relationship and explained a significant amount of variance in both functional connectivity and subject measures. The only criteria that was not successful was that compared to other modes the magnitude of variance explained by the primary CCA mode was smaller than predicted, a result which could indicate a developmental trajectory of a primary mode. This replication establishes a signature neurotypical relationship between connectivity and phenotype, opening new avenues of research in neuroscience with clear clinical applications.