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

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.

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Publication Details

Journal
Neuroinformatics
Published
2025-10-08
DOI
https://doi.org/10.1007/s12021-025-09747-0
Citations
1
Primary Topic
Reading and Literacy Development
Type
article
Field-Weighted Citation Impact
3.44

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article

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

Mark A. Eckert, Kenneth I. Vaden, Rishikesh V. Phatangare, Li Luo et al.
1 citations
Neuroinformatics
Reading and Literacy Development
3.44
article

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

Mark A. Eckert, Kenneth I. Vaden, Rishikesh V. Phatangare, Li Luo, James Z. Wang
article en
1 citations

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.

NeuroinformaticsVol. 23(4)
Medical University of South Carolina (US), Columbia University (US), Clemson University (US)
Clemson University, National Institute of Child Health and Human Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Openalex Percentile: Top 7%
Reading and Literacy Development
3.44
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Dyslexia Data Consortium: A Comprehensive Platform for Neuroimaging Data Sharing, Analysis, and Advanced Research in Dyslexia — Mark A. Eckert, Kenneth I. Vaden, et al. · Neuroinformatics (2025) | TGRS Research Map | TGRS