Ten Simple Rules for Predictive Modeling of Individual Differences in Neuroimaging

Overview

Journal Neuroimage

Specialty Radiology

Date 2019 Mar 5

PMID 30831310

Citations 176

Authors

Dustin Scheinost

Stephanie Noble

Corey Horien

Abigail S Greene

Evelyn Mr Lake

Mehraveh Salehi

Siyuan Gao

Xilin Shen

David OConnor

Daniel S Barron

Sarah W Yip

Monica D Rosenberg

R Todd Constable

Affiliations

Soon will be listed here.

Abstract

Establishing brain-behavior associations that map brain organization to phenotypic measures and generalize to novel individuals remains a challenge in neuroimaging. Predictive modeling approaches that define and validate models with independent datasets offer a solution to this problem. While these methods can detect novel and generalizable brain-behavior associations, they can be daunting, which has limited their use by the wider connectivity community. Here, we offer practical advice and examples based on functional magnetic resonance imaging (fMRI) functional connectivity data for implementing these approaches. We hope these ten rules will increase the use of predictive models with neuroimaging data.

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