The Child Mind Institute has released a paper detailing their pioneering study in the journal Nature Human Behaviour titled, "Moving Beyond Processing and Analysis-Related Variation in Resting State Functional Brain Imaging." The research identifies significant challenges in the reproducibility and standardization of functional magnetic resonance imaging (fMRI) used to understand brain function and behavior -; and proposes concrete solutions to move the field towards results that translate into real world impact. Along with a diverse team of international collaborators, the study was led by Michael P.
Milham, MD, PhD, Child Mind Institute chief science officer, and Gregory Kiar, PhD, research scientist and director of the Center for Data Analytics, Innovation, and Rigor at the Child Mind Institute. The paper critically evaluates preprocessing pipelines in fMRI data analysis, widely used software tools that have increased participation in the field of fMRI research by automating basic analytical tasks. The study found only moderate agreement between five popular pipelines -; Adolescent Brain Cognitive Development fMRI Pipeline (ABCD-BIDS); Connectome Computational System (CCS); Configurable Pipeline for the Analysis of Connectomes default pipeline (C-PAC:Default), developed by the Child Mind Institute; Data Processing Assistant for Resting-State fMRI (DPARSF); and fMRIPrep Long-Term Support version (fMRIPrep-LTS) -; when given identical data.
This variability significantly aff.