Evaluation of functional MRI-based human brain parcellation: a review

Author:

Moghimi Pantea1,Dang Anh The2,Do Quan2,Netoff Theoden I.3ORCID,Lim Kelvin O.4,Atluri Gowtham2ORCID

Affiliation:

1. Department of Neurobiology, University of Chicago, Chicago, Illinois

2. Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio

3. Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota

4. Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota

Abstract

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

Funder

HHS | NIH | National Institute of Biomedical Imaging and Bioengineering

HHS | NIH | National Institute of Mental Health

HHS | NIH | National Institute on Drug Abuse

HHS | NIH | NIH Office of the Director

National Science Foundation

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

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