| Literature DB >> 28317230 |
Tristram A Lett1, Lea Waller1, Heike Tost2,3, Ilya M Veer1, Arash Nazeri4, Susanne Erk1, Eva J Brandl1, Katrin Charlet1, Anne Beck1, Sabine Vollstädt-Klein5, Anne Jorde5, Falk Kiefer5, Andreas Heinz1, Andreas Meyer-Lindenberg2,3, M Mallar Chakravarty6,7,8, Henrik Walter1.
Abstract
Threshold-free cluster enhancement (TFCE) is a sensitive means to incorporate spatial neighborhood information in neuroimaging studies without using arbitrary thresholds. The majority of methods have applied TFCE to voxelwise data. The need to understand the relationship among multiple variables and imaging modalities has become critical. We propose a new method of applying TFCE to vertexwise statistical images as well as cortexwise (either voxel- or vertexwise) mediation analysis. Here we present TFCE_mediation, a toolbox that can be used for cortexwise multiple regression analysis with TFCE, and additionally cortexwise mediation using TFCE. The toolbox is open source and publicly available (https://github.com/trislett/TFCE_mediation). We validated TFCE_mediation in healthy controls from two independent multimodal neuroimaging samples (N = 199 and N = 183). We found a consistent structure-function relationship between surface area and the first independent component (IC1) of the N-back task, that white matter fractional anisotropy is strongly associated with IC1 N-back, and that our voxel-based results are essentially identical to FSL randomise using TFCE (all PFWE <0.05). Using cortexwise mediation, we showed that the relationship between white matter FA and IC1 N-back is mediated by surface area in the right superior frontal cortex (PFWE < 0.05). We also demonstrated that the same mediation model is present using vertexwise mediation (PFWE < 0.05). In conclusion, cortexwise analysis with TFCE provides an effective analysis of multimodal neuroimaging data. Furthermore, cortexwise mediation analysis may identify or explain a mechanism that underlies an observed relationship among a predictor, intermediary, and dependent variables in which one of these variables is assessed at a whole-brain scale. Hum Brain Mapp 38:2795-2807, 2017.Entities:
Keywords: TFCE_mediation; cortical thickness; diffusion magnetic resonance imaging; magnetic resonance imaging; mediation; nonparametric statistics; statistical data interpretation; surface area
Mesh:
Year: 2017 PMID: 28317230 PMCID: PMC6866989 DOI: 10.1002/hbm.23563
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038