Fiber-specific structural properties relate to reading skills in children and adolescents

Abstract
Data availability
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Abstract

Recent studies suggest that the cross-sectional relationship between reading skills and white matter microstructure, as indexed by fractional anisotropy, is not as robust as previously thought. Fixel-based analyses yield fiber-specific micro- and macrostructural measures, overcoming several shortcomings of the traditional diffusion tensor model. We ran a whole-brain analysis investigating whether the product of fiber density and cross-section (FDC) related to single-word reading skills in a large, open, quality-controlled data set of 983 children and adolescents ages 6-18. We also compared FDC between participants with (n = 102) and without (n = 570) reading disabilities. We found that FDC positively related to reading skills throughout the brain, especially in left temporoparietal and cerebellar white matter, but did not differ between reading proficiency groups. Exploratory analyses revealed that among metrics from other diffusion models - DTI, DKI, and NODDI - only the orientation dispersion and neurite density indexes from NODDI were associated (inversely) with reading skills. The present findings further support the importance of left-hemisphere dorsal temporoparietal white matter tracts in reading. Additionally, these results suggest future DWI studies of reading and dyslexia should be designed to benefit from advanced diffusion models, include cerebellar coverage, and consider continuous analyses that account for individual differences in reading skill.

Data availability

Raw and preprocessed neuroimaging data from the Healthy Brain Network are publicly available without restriction, and can be downloaded from Amazon Simple Storage Service (S3) following directions from the HBN-POD2 manuscript (Richie-Halford et al., 2022).Access to full phenotypic and behavioral data, which are stored at https://data.healthybrainnetwork.org/main.php, is restricted. For this reason, we cannot make our full study outputs publicly available. These data can be collected by any entity following directions on the Healthy Brain Network data portal (http://fcon_1000.projects.nitrc.org/indi/cmi_healthy_brain_network/index.html) after signing a data use agreement.Study-specific code and instructions for processing data and running the statistical models can be found at https://github.com/smeisler/Meisler_Reading_FBA. We share the population FOD template, tract segmentations, and model outputs (which only report data in the aggregate) at https://osf.io/3ady4/. These can all be viewed using MRview from MRtrix3.

The following previously published data sets were used

1. Richie-Halford A
2. et al
(2022) HBN-POD2
s3://fcp-indi/data/Projects/HBN/BIDS_curated/derivatives/qsiprep/.

https://www.nature.com/articles/s41597-022-01695-7
1. Alexander LM
2. et al
(2017) Healthy Brain Network
s3://fcp-indi/data/Projects/HBN/BIDS_curated/.

http://fcon_1000.projects.nitrc.org/indi/cmi_healthy_brain_network/

Article and author information

Author details

Steven Lee Meisler

Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, United States

For correspondence
smeisler@g.harvard.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-8888-1572
John Gabrieli

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States

Competing interests
The authors declare that no competing interests exist.

Funding

National Institute on Deafness and Other Communication Disorders (T32 Training Grant,5T32DC000038)

Steven Lee Meisler

Chan Zuckerberg Initiative

John Gabrieli

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The Healthy Brain Network project was approved by the Chesapeake Institutional Review Board (now called Advarra, Inc.; https://www.advarra.com/; protocol number: Pro00012309). Informed consent was obtained from all participants ages 18 or older. For younger participants, written informed consent was collected from their legal guardians, and written assent was obtained from the participants.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.