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Individual Functional ROI Optimization Via Maximization of Group-Wise Consistency of Structural and Functional Profiles

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Abstract

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain.

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Acknowledgement

K Li was supported by the NWPU Foundation for Fundamental Research. T Liu was supported by the NIH Career Award EB 006878, NIH R01 HL087923-03S2, and The University of Georgia start-up research funding. We would like to thank the anonymous reviewers whose comments helped to significantly improve this paper.

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Authors and Affiliations

  1. School of Automation, Northwestern Polytechnical University, Xi’an, China

    Kaiming Li, Lei Guo, Xintao Hu & Junwei Han

  2. Department of Computer Science & Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA

    Kaiming Li, Dajiang Zhu & Tianming Liu

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  1. Kaiming Li
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Correspondence to Tianming Liu.

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Li, K., Guo, L., Zhu, D. et al. Individual Functional ROI Optimization Via Maximization of Group-Wise Consistency of Structural and Functional Profiles. Neuroinform 10, 225–242 (2012). https://doi.org/10.1007/s12021-012-9142-5

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