Wayne State Study 11 Dataset

Overview

The Wayne State longitudinal data set (collected on 4T Bruker scanner, with Siemens user interface) for the Brain Aging in Detroit Longitudinal Study, comprises 200 healthy individuals. The overarching aim of the Brain Aging in Detroit Longitudinal Study, is understanding the mechanisms driving human brain changes over the adult lifespan, identifying the risk factors and protective influences that modify the rate of change, and elucidating the relationships between changes in brain properties and cognitive performance. All participants were screened at baseline via a health questionnaire for the following conditions: presence of cardiovascular, neurological, or psychiatric disease, use of centrally acting medications, the habit of having three or more alcoholic drinks per day, as well as being minimally high school educated, native English speakers.

All participants underwent cognitive testing, and although the composition of testing batteries varied across cohorts, some tests are common to all: Cattell Culture Fair Intelligence Test, various forms of multiple-choice vocabulary tests (Educational Testing Service), tests of episodic memory and working memory. Cognitive variables are available to qualified investigators upon request.

302 total anatomical scans (200 subjects at baseline x 2 sessions/subject x 1 T1 MPRAGE scan/session) over 2 waves of data collection. The number of participants (after attrition) per wave are as follows:

• Wave 1: N=200
• Wave 2: N=102

Click here (pdf) for scan parameters.

Experimental Protocol

Participants were instructed to remain still in the scanner, with eyes closed.

Data Release Download

Click here to get the demographics.

Click here to access the compressed Wayne State Study 11 dataset.

NITRC Download Instructions
In order to access the data, you must first register for an account with NITRC. After you have done so, click here to request access to the 1000 Functional Connectomes Project on NITRC. Users will be approved within 1 business day.

Personnel

Principal Investigator:

• Raz, N., Ph.D^{1, 2, 3}

Senior Personnel and Collaborators (Alphabetical order):

• Bender, A.R., Ph.D
• Dahle, C.L., Ph.D.^{1, 2}
• Daugherty, A.M., Ph.D.
• Ghisletta, P., Ph.D.
• Haacke, E.M., Ph.D.
• Kennedy, K.M., Ph.D.
• Lindenberger, U., Ph.D.
• Rodrigue, K.M., Ph.D.
• Stanley, J.A., Ph.D.⁴
• Yang, Y., Ph.D.
• Yuan, P., Ph.D.

^*please send correspondence to Naftali Raz (nraz@wayne.edu)

¹Institute of Gerontology, Wayne State University, Detroit MI, USA
²Department of Psychology, Wayne State University, Detroit MI, USA
³Max Planck Institute for Human Development, Berlin, Germany
⁴Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit MI, USA

Data Sharing License

Creative Commons – Attribution-NonCommercial Share Alike (CC-BY-NC-SA): Standard INDI data sharing policy. Prohibits use of the data for commercial purposes.

Publications

• Burgmans, S., van Boxtel, M.P.J, Gronenschild, E.H.B.M., Vuurman, E.F.P.M., Hofman, P., Uylings, H.B.M., Jolles, J., Raz, N. (2010). Multiple indicators of age-related differences in cerebral white matter and the modifying effects of hypertension. NeuroImage, 49, 2083-2093.
• Burgmans, S., Gronenschild, E.H.B.M., Fandakova, Y., Shing, Y.L., van Boxtel, M.P.J., Vuurman, E.F.P.M., Uylings, H.B.M., Jolles, J., Raz, N. (2011). Age differences in speed of processing are partially mediated by differences in axonal integrity. NeuroImage, 55, 1287-1297.
• Raz, N., Yang, Y., Dahle, C.L., Land, S. (2012). Volume of white matter hyperintensities in healthy adults: Contribution of age, vascular risk factors, and inflammation-related genetic variants. BBA: Biochimica et Biophyisica Acta, Section: Molecular Basis of Disease, 1822, 361-369.
• Bender, A.R., Raz, N. (2012). Age-related differences in memory and executive functions in healthy APOE 4 carriers: The contribution of individual differences in prefrontal volumes and systolic blood pressure. Neuropsychologia, 50, 704-714.
• Yuan, P., Daugherty, A.M., Raz, N. (2014). Turning bias in virtual spatial navigation: Age-related differences and neuroanatomical correlates. Biological Psychology, 96, 8-19.
• Persson, N., Ghisletta, P., Dahle, C.L., Bender, A.R., Yang, Y., Yuan, P., Daugherty, A.M., Raz, N. (2014). Regional brain shrinkage over two years: Individual differences and effects of pro-inflammatory genetic polymorphisms. NeuroImage, 103, 334-348.
• Daugherty, A.M., Haacke, E.M., Raz, N. (2015). Striatal iron content predicts its shrinkage and changes in verbal working memory after two years in healthy adults. Journal of Neuroscience, 35, 6731-6743.
• Bender, A.R., Raz, N. (2015). Normal-appearing cerebral white matter in healthy adults: Mean change over two years and individual differences in change. Neurobiology of Aging, 36, 1834-1848.
• Daugherty, A.M., Yuan, P., Dahle, C., Bender, A.R., Yang, Y., Raz, N. (2015). Path complexity in virtual water maze navigation: Differential associations with age, sex, and regional brain volume. Cerebral Cortex, 25, 3122-3131.
• Persson, N., Ghisletta, P., Dahle, C.L., Bender, A.R., Daugherty, A.M., Yang, Y., Yuan, P., Raz, N. (2016). Regional brain shrinkage and change in cognitive performance over two years: The bidirectional influences of the brain and cognitive reserve factors. NeuroImage, 126, 15-26.
• Bender, A.R., Prindle, J.J., Brandmaier, A.M., Raz, N. (2016). White matter and memory in healthy adults: Coupled changes over two years. NeuroImage, 131, 193-204.
• Daugherty, A.M., Raz, N. (2017). A virtual water maze revisited: Two-year changes in navigation performance and their neural correlates in healthy adults. NeuroImage, 146, 492-506.

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