Yale High-Resolution Controls Dataset

Overview

The Yale High-Resolution Controls (Yale Hires) comprises 120 healthy individuals and was collected with the purpose of assessing the intrinsic organization of the human brain at rest. For each subject, six functional scans (36 min total) and two anatomical scans (MPRAGE and FLASH) were acquired. The complete dataset includes:

The complete dataset includes:

717 functional scans (120 subjects x 6 runs/subject - 3 missing runs)
- missing functional scans: ta5368 S007, ta5368 S008, ta4825 S006
240 anatomical scans (120 subjects x 2 scans/subject)

Click here (pdf) for scan parameters.

Experimental Protocol

Subjects were instructed to keep their eyes open, stay awake, remain still, try to relax, and try not to think about anything in particular. No visual stimulation was provided; subjects were shown a black screen.

Data Release Download

Click here to get the demographics.

Click here to access the compressed Yale High-Resolution Controls Dataset.

Data are also available for download as files in an Amazon Web Services S3 bucket.

Each file in the S3 bucket can only be accessed using HTTP (i.e., no ftp or scp ). You can obtain a URL for each desired file and then download it using an HTTP client such as a web browser, wget, or curl. Each file can only be accessed using its literal name - wildcards (i.e. "*") will not work.

There are file transfer programs that can handle S3 natively and will allow you to navigate through the data using a file browser. Cyberduck is one such program that works with Windows and Mac OS X (New Cyberduck version might not work, please try version 5.03.). Cyberduck also has a command line version that works with Windows, Mac OS X, and Linux. Instructions for using the Cyberduck program are as follows:

Open Cyberduck and click on Open Connection.
Set the application protocol in the dropdown menu to S3 (Amazon Simple Storage Service).
Set the server to s3.amazonaws.com.
Check the box labelled Anonymous Login.
Expand the More Options tab and set Path to fcp-indi/data/Projects/INDI/YALE/folder/highres.
Click Connect.

Personnel

Fuyuze Tokoglu¹
Maolin Qiu¹
Xilin Shen^1*
Dustin Scheinost¹
R. Todd Constable^1,2,3

^*please send any correspondence to Xilin Shen (xilin[dot]shen[at]yale[dot]edu)

¹Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA.
²Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520, USA.
³Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06520, 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.

Acknowledgments

We would additionally like to acknowledge our MR technicians—Hedwig Sarofin, Terry Hickey, Karen Martin, and Cheryl McMurray—for their tireless work and our subjects, without whom this work would not be possible.

Publications

Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., ... & Constable, R. T. (2015). Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nature neuroscience, 18(11), 1664.