Benchmarking common preprocessing strategies in early childhood functional connectivity and intersubject correlation fMRI

Kirk Graff; Ryann Tansey; Amanda Ip; Christiane Rohr; Dennis Dimond; Deborah Dewey; Signe Bray

doi:10.1016/j.dcn.2022.101087

Benchmarking common preprocessing strategies in early childhood functional connectivity and intersubject correlation fMRI

Dev Cogn Neurosci. 2022 Apr:54:101087. doi: 10.1016/j.dcn.2022.101087. Epub 2022 Feb 18.

Authors

Kirk Graff¹, Ryann Tansey², Amanda Ip², Christiane Rohr², Dennis Dimond², Deborah Dewey³, Signe Bray⁴

Affiliations

¹ Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada. Electronic address: kirk.graff@ucalgary.ca.
² Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Neuroscience, University of Calgary, Calgary, AB, Canada.
³ Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Department of Pediatrics, University of Calgary, Calgary, AB, Canada; Community Health Science, University of Calgary, Calgary, AB, Canada.
⁴ Child and Adolescent Imaging Research Program, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Department of Radiology, University of Calgary, Calgary, AB, Canada.

Abstract

Preprocessing choices present a particular challenge for researchers working with functional magnetic resonance imaging (fMRI) data from young children. Steps which have been shown to be important for mitigating head motion, such as censoring and global signal regression (GSR), remain controversial, and benchmarking studies comparing preprocessing pipelines have been conducted using resting data from older participants who tend to move less than young children. Here, we conducted benchmarking of fMRI preprocessing steps in a population with high head-motion, children aged 4-8 years, leveraging a unique longitudinal, passive viewing fMRI dataset. We systematically investigated combinations of global signal regression (GSR), volume censoring, and ICA-AROMA. Pipelines were compared using previously established metrics of noise removal as well as metrics sensitive to recovery of individual differences (i.e., connectome fingerprinting), and stimulus-evoked responses (i.e., intersubject correlations; ISC). We found that: 1) the most efficacious pipeline for both noise removal and information recovery included censoring, GSR, bandpass filtering, and head motion parameter (HMP) regression, 2) ICA-AROMA performed similarly to HMP regression and did not obviate the need for censoring, 3) GSR had a minimal impact on connectome fingerprinting but improved ISC, and 4) the strictest censoring approaches reduced motion correlated edges but negatively impacted identifiability.

Keywords: Connectome fingerprinting; Early childhood; FMRI; Functional connectivity; Motion; Preprocessing.

Publication types

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

MeSH terms

Artifacts
Benchmarking*
Brain / physiology
Child
Child, Preschool
Connectome* / methods
Humans
Image Processing, Computer-Assisted / methods
Magnetic Resonance Imaging / methods