RT Journal Article
SR Electronic
T1 Improving effect size and power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 017350
DO 10.1101/017350
A1 Michael V. Lombardo
A1 Bonnie Auyeung
A1 Rosie Holt
A1 Jack Waldman
A1 Amber Ruigrok
A1 Natasha Mooney
A1 Edward T Bullmore
A1 Simon Baron-Cohen
A1 Prantik Kundu
YR 2015
UL http://biorxiv.org/content/early/2015/03/31/017350.abstract
AB Functional magnetic resonance imaging (fMRI) research is routinely criticized for being underpowered due to characteristically small sample sizes. Additionally, fMRI signals inherently possess various sources of non-BOLD noise that further hampers ability to detect subtle effects. Here we demonstrate that multi-echo fMRI data acquisition and denoising can increase effect size and statistical power for block-design experiments, allowing for novel insights by detecting effects that are typically obscured in small sample size/underpowered studies. Application of this method on two different tasks within the social cognitive domain of mentalizing/theory of mind demonstrates that effect sizes are enhanced at a median rate of 25-32% in regions canonically associated with mentalizing. For non-canonical cerebellar areas that have been largely less focused on by the field, effect sizes boosts were much more substantial in the range of 43-108%. These cerebellar areas are highly functionally connected at rest with neural systems typically associated with mentalizing and the resting state connectivity maps largely recapitulate the topology observed in activation maps for mentalizing. Power simulations show that boosts in effect size enable ability to conduct high-powered studies at traditional sample sizes. However, cerebellar effects will remain underpowered at traditional sample sizes and without the multi-echo innovations we describe here. Thus, 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.