Individual differences in intrinsic connectivity Networks I: retest and validation in resting state.

Abstract

Connectivity of the resting brain can be empirically parsed into distinct networks which closely resemble patterns of evoked task-based brain activity, and have a biological and genetic basis. Recently, these intrinsic connectivity networks (ICNs) have become a popular method for investigating brain functioning and brain-behavior relationships with external variables such as personality or psychiatric symptoms. However, replication studies are needed to test the correspondence, neurometrics, and associations observed for these networks across independent samples. Using a meta-level independent component analysis (ICA), we produced ICNs from three datasets collected from two samples of healthy adults, and demonstrate robust and independent replication of twelve ICNs. In each dataset, the ICNs were found to reflect sixteen task-based networks. Networks involved in executive functions, speech and audition, default mode processing, vision, and interoception showed the greatest spatial reliability and reproducibility; whereas, only the networks associated with the right-lateralized executive functions and speech-audition demonstrated at least fair within-subject reliability over time. We also demonstrated regions with the highest connectivity were disjointed from regions with the highest reliability. Additionally, we tested the ability for connectivity to reliably predict cognitive performance, which showed a trend-level finding implicating the default-mode network in attention and concentration. Take as a whole, our findings agree with current hypotheses which postulate that intrinsic connectivity sustains, at rest, representations and modes of functioning from which task-evoked patterns of activation and connectivity are produced.