Functional connectivity analyses using emulated and conventional resting-state data: parts versus the whole story

Abstract

Continuous resting-state (RS) functional magnetic resonance imaging (fMRI) has become particularly useful to identify changes in functional connectivity (FC) in CNS disorders. Fair et al. proposed a method of volume extraction to emulate RS fMRI from block-design experiments. Whether the validity of this approach holds true in multiple sclerosis (MS) patients has not been tested formally so far. Twelve MS patients and 18 controls underwent conventional RS fMRI and a cognitive block-design fMRI. The total amount of volumes as well as the truncated set of volumes of both functional datasets was separately analyzed using a seed-based approach. Overall, seed-based analyses of FC from the anterior cingulated cortex allowed identification of the same key-network constituents using different analytical approaches, whereas higher-level within-group analyses of emulated RS versus continuous RS also revealed significant distinct differences in FC networks. Using the emulated RS approach, a general identification of connectivity networks similar to those obtained using conventional RS data also appears feasible in diseased brains. Higher-level contrasts, however, yielded different results attesting to a significant impact of employed methodology.

Keywords: emulated resting state; functional connectivity; multiple sclerosis; resting-state functional MRI; seed-based correlation analysis; validity.