Abstract Research using functional and structural magnetic resonance imaging has identified areas of reduced brain activation and gray matter volume in children and adults with reading disability, but associations between cortical structure and individual differences in reading in typically developing children remain underexplored. Furthermore, the majority of research linking gray matter structure to reading ability quantifies gray matter in terms of volume, and cannot specify unique contributions of cortical surface area and thickness to these relationships. Here, we applied a continuous analytic approach to investigate associations between distinct surface-based properties of cortical structure and individual differences in reading-related skills in a sample of typically developing young children. Correlations between cortical structure and reading-related skills were conducted using a surface-based vertex-wise approach. Cortical thickness in the left superior temporal cortex was positively correlated with word and pseudoword reading performance. The observed positive correlation between cortical thickness in the left superior temporal cortex and reading may have implications for the patterns of brain activation that support reading.
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Altered topological structure of the brain white matter in maltreated children through topological data analysis
Childhood maltreatment may adversely affect brain development and consequently influence behavioral, emotional, and psychological patterns during adulthood. In this study, we propose an analytical pipeline for modeling the altered topological structure of brain white matter in maltreated and typically developing children. We perform topological data analysis (TDA) to assess the alteration in the global topology of the brain white matter structural covariance network among children. We use persistent homology, an algebraic technique in TDA, to analyze topological features in the brain covariance networks constructed from structural magnetic resonance imaging and diffusion tensor imaging. We develop a novel framework for statistical inference based on the Wasserstein distance to assess the significance of the observed topological differences. Using these methods in comparing maltreated children with a typically developing control group, we find that maltreatment may increase homogeneity in white matter structures and thus induce higher correlations in the structural covariance; this is reflected in the topological profile. Our findings strongly suggest that TDA can be a valuable framework to model altered topological structures of the brain. The MATLAB codes and processed data used in this study can be found at https://github.com/laplcebeltrami/maltreated.
more » « less- NSF-PAR ID:
- 10480049
- Publisher / Repository:
- DOI PREFIX: 10.1162
- Date Published:
- Journal Name:
- Network Neuroscience
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2472-1751
- Format(s):
- Medium: X Size: p. 355-376
- Size(s):
- p. 355-376
- Sponsoring Org:
- National Science Foundation
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