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Dyslexia Data Consortium: A Comprehensive Platform for Neuroimaging Data Sharing, Analysis, and Advanced Research in Dyslexia

Rishikesh V. Phatangare; Mark A. Eckert; Li Luo; Kenneth I. Vaden; James Z. Wang
Neuroinformatics · Vol. 23, Issue 4 · 2025

Abstract

Neuroimaging studies have and continue to advance our understanding of the neurobiology of dyslexia. Integration of data from these studies has the potential to replicate findings, deepen understanding through theoretically focused research, and provide for unexpected discovery. This data integration can be important for questions where a sufficiently large and well-defined group of participants is necessary for sufficient experimental power, particularly for a complex disorder where age, language background, and cognitive profiles can impact imaging results. We have developed a data-sharing platform to provide a data repository, image processing resources, and data analysis tools, with an emphasis on data harmonization across retrospective datasets ( https://dyslexiadata.org ). Here, we summarize data sharing, download, imaging metrics, and quality and privacy considerations in the design of and resources available through this repository. By providing access to a relatively large multisite dataset, researchers can test hypotheses about reading development and disability, test novel data analysis methods, even within the platform, and advance understanding of dyslexia.

Bibliographic Information

JournalNeuroinformatics
PublisherSpringer
Publication Date2025-10-08
Publication Year2025
Volume23
Issue4
Document TypeJournal Article
eISSN1559-0089
DOI10.1007/s12021-025-09747-0

Access Information

NARA Access Coverage2003-01-01~Current
Journal Homepagehttps://www.springer.com/journal/12021
Publisher PageOpen Publisher Page
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