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Brain Regions Identified as Being Associated With Verbal Reasoning Through the Use of Imaging Regression via Internal Variation

Version 4 2022-12-08, 16:47
Version 3 2021-09-22, 16:23
Version 2 2020-06-08, 19:09
Version 1 2020-05-15, 16:20
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posted on 2022-12-08, 16:47 authored by Long Feng, Xuan Bi, Heping Zhang

Abstract–Brain-imaging data have been increasingly used to understand intellectual disabilities. Despite significant progress in biomedical research, the mechanisms for most of the intellectual disabilities remain unknown. Finding the underlying neurological mechanisms has proved difficult, especially in children due to the rapid development of their brains. We investigate verbal reasoning, which is a reliable measure of an individual’s general intellectual abilities, and develop a class of high-order imaging regression models to identify brain subregions which might be associated with this specific intellectual ability. A key novelty of our method is to take advantage of spatial brain structures, and specifically the piecewise smooth nature of most imaging coefficients in the form of high-order tensors. Our approach provides an effective and urgently needed method for identifying brain subregions potentially underlying certain intellectual disabilities. The idea behind our approach is a carefully constructed concept called internal variation (IV). The IV employs tensor decomposition and provides a computationally feasible substitution for total variation, which has been considered suitable to deal with similar problems but may not be scalable to high-order tensor regression. Before applying our method to analyze the real data, we conduct comprehensive simulation studies to demonstrate the validity of our method in imaging signal identification. Next, we present our results from the analysis of a dataset based on the Philadelphia Neurodevelopmental Cohort for which we preprocessed the data including reorienting, bias-field correcting, extracting, normalizing, and registering the magnetic resonance images from 978 individuals. Our analysis identified a subregion across the cingulate cortex and the corpus callosum as being associated with individuals’ verbal reasoning ability, which, to the best of our knowledge, is a novel region that has not been reported in the literature. This finding is useful in further investigation of functional mechanisms for verbal reasoning. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Funding

This research was partially supported by grants R01 DA016750, R01 MH116527, and R01 HG010171 from the U.S. National Institutes of Health, and DMS1722544 from the National Science Foundation. Support for the collection of the PNC datasets was provided by NIH grant RC2MH089983 awarded to Raquel Gur and RC2MH089924 awarded to Hakon Hakonarson. All PNC participants were recruited through the Center for Applied Genomics at The Children’s Hospital in Philadelphia. The PNC datasets were obtained from dbGaP at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000607.v1.p1 through dbGaP accession: phs000607.v1.p1.

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