Data Quality Influences Observed Links Between Functional Connectivity and Behavior

Abstract

A growing field of research explores links between behavioral measures and functional\nconnectivity (FC) assessed using resting-state functional magnetic resonance imaging.\nRecent studies suggest that measurement of these relationships may be corrupted by head\nmotion artifact. Using data from the Human Connectome Project (HCP), we find that a\nsurprising number of behavioral, demographic, and physiological measures (23 of 122),\nincluding fluid intelligence, reading ability, weight, and psychiatric diagnostic scales,\ncorrelate with head motion. We demonstrate that “trait” (across-subject) and\n“state” (across-day, within-subject) effects of motion on FC are remarkably\nsimilar in HCP data, suggesting that state effects of motion could potentially mimic trait\ncorrelates of behavior. Thus, head motion is a likely source of systematic errors (bias)\nin the measurement of FC:behavior relationships. Next, we show that data cleaning\nstrategies reduce the influence of head motion and substantially alter previously reported\nFC:behavior relationship. Our results suggest that spurious relationships mediated by head\nmotion may be widespread in studies linking FC to behavior.