TY - JOUR T1 - Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing JF - bioRxiv DO - 10.1101/017350 SP - 017350 AU - Michael V. Lombardo AU - Bonnie Auyeung AU - Rosemary J. Holt AU - Jack Waldman AU - Amber N. V. Ruigrok AU - Natasha Mooney AU - Edward T. Bullmore AU - Simon Baron-Cohen AU - Prantik Kundu Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/05/09/017350.abstract N2 - Functional magnetic resonance imaging (fMRI) research is routinely criticized for being underpowered due to characteristically small sample sizes. fMRI signals also inherently possess various sources of non-BOLD noise that further hampers ability to detect subtle effects. Here we take a bottom-up approach to addressing these problems via implementing multi-echo fMRI data acquisition and denoising innovations that can substantially improve effect size estimation and statistical power. We show that effect sizes on two different tasks within the social cognitive domain of mentalizing/theory of mind were enhanced at a median rate of 27% in regions canonically associated with mentalizing, while much more substantial boosts (43-130%) were observed in non-canonical cerebellar areas. This effect size boosting is primarily a consequence of reduction of non-BOLD noise at the subject level, which then translates into consequent reductions in between-subject variance. Power simulations demonstrate that enhanced effect size enables highly-powered studies at traditional sample sizes. Moreover, the cerebellar effects observed after applying our multi-echo innovations may be unobservable with conventional imaging at traditional sample sizes. The adoption of multi-echo fMRI innovations can help address key criticisms regarding statistical power and non-BOLD noise and enable potential for novel discovery of aspects of brain organization that are currently under-appreciated and not well understood. ER -