Dyslexia Data Consortium

Resources to enhance our understanding of reading disability

Data Access

The generous contributions from our Dyslexia Data Consortium members have made access to the data collected here possible. All work stemming from use of these data should be acknowledged in presentations and publications. For that reason, as well as to ensure the integrity of the data, we ask that you complete the data use agreement and select below the pattern of data that you would like to obtain. You will be contacted shortly after submitting this information about how to access the data.

Please see our Best Use Practice page when developing your project idea(s).

Please select age, gender etc. below.








Computer Aided Scientific Integrity

Under Development


Please contact Mark A. Eckert ( eckert@musc.edu ) to identify collaborators for your project idea(s).


Song, X., Wang, J., Wang, A., Meng, Q., Prescott, C., Tsu, L., Eckert, M.A. (2015). DeID–a data sharing tool for neuroimaging studies. Frontiers in Neuroscience, 9.

Eckert, M.A., Berninger, V.W., Hoeft, F., Vaden, K.I., Dyslexia Data Consortium. (2016). A case of Bilateral Perisylvian Syndrome with reading disability. Cortex, 76: 121-124. doi: 10.1016/j.cortex.2016.01.004.

Eckert, M.A., Berninger, V.W., Vaden, K.I., Gebregziabher, M., Tsu, L., for Dyslexia Data Consortium. (2016). Gray matter features of reading disability: A combined meta-analytic and direct data analysis approach. eNeuro, 3(1), doi: 10.1523/ENEURO.0103-15.2015.