Cortical surface-based threshold-free cluster enhancement and cortexwise mediation

Tristram A Lett; Lea Waller; Heike Tost; Ilya M Veer; Arash Nazeri; Susanne Erk; Eva J Brandl; Katrin Charlet; Anne Beck; Sabine Vollstädt-Klein; Anne Jorde; Falk Kiefer; Andreas Heinz; Andreas Meyer-Lindenberg; M Mallar Chakravarty; Henrik Walter

doi:10.1002/hbm.23563

Cortical surface-based threshold-free cluster enhancement and cortexwise mediation

Hum Brain Mapp. 2017 Jun;38(6):2795-2807. doi: 10.1002/hbm.23563. Epub 2017 Mar 20.

Authors

Tristram A Lett¹, Lea Waller¹, Heike Tost^{2

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-Lindenberg^{2

3}, M Mallar Chakravarty^{6

7

8}, Henrik Walter¹

Affiliations

¹ Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Charité Campus Mitte, Berlin, Germany.
² Department of Psychiatry, University of Heidelberg, Heidelberg, Germany.
³ Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany.
⁴ Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Canada.
⁵ Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Germany.
⁶ Cerebral Imaging Centre, Douglas Hospital Mental Health University Institute, Verdun, Canada.
⁷ Departments of Psychiatry, McGill University, Montreal, Canada.
⁸ Department of Biomedical Engineering, McGill University, Montreal, Canada.

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 P_FWE <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 (P_FWE < 0.05). We also demonstrated that the same mediation model is present using vertexwise mediation (P_FWE < 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. © 2017 Wiley Periodicals, Inc.

Keywords: TFCE_mediation; cortical thickness; diffusion magnetic resonance imaging; magnetic resonance imaging; mediation; nonparametric statistics; statistical data interpretation; surface area.

Publication types

Technical Report
Research Support, Non-U.S. Gov't

MeSH terms

Adult
Brain Mapping / methods*
Cerebral Cortex / diagnostic imaging*
Computer Simulation
Female
Humans
Image Interpretation, Computer-Assisted*
Male
Middle Aged
Multimodal Imaging
Regression Analysis
Reproducibility of Results
White Matter / diagnostic imaging