Data Science Core Our team for this BRAIN Initiative proposal on Oxytocin Modulation of Neural Circuit Function and Behavior is located at NYU School of Medicine, and staff for the Data Science Core are located in the NYU Health Sciences Library and Division of Biostatistics. This proximity facilitates their interactions, already leading to a number of collaborations and efforts to promote data sharing, standardization, and archiving that form a solid foundation for this proposed Data Science Core. The Core Director is Dr. Alisa Surkis, a computational neuroscientist and data archivist, together with other Core staff members Mr. Kevin Read (an informationist) and Dr. Andrea Troxel, head of Biostatistics at NYU School of Medicine. This Data Science Core will help ensure the management and stewardship of the datasets to be collected in our Projects and by the other Cores, including behavioral data (short episodes and weeks-long movies), physiological recordings (in vivo and in vitro, whole-cell and extracellular recordings), imaging (2-photon, confocal, and fiber photometry), and gene expression profiling.
Aim 1 of the Data Science Core is to standardize data collection formats across Project team labs, in formats adopted from consortium sites such as Neurodata Without Borders and CRCNS.
Aim 2 is to archive these data for perpetuity, ensuring an enduring lifetime of raw data, annotations, and analyses, in formats amenable to easy sharing between investigators.
Aim 3 is to coordinate and communicate with other investigators and BRAIN Initiative teams, including other Data Science Cores for consensus building and sharing techniques for troubleshooting.
In Aim 5 we will provide rigorous training and practices in statistical analysis, incorporating faculty from the division of biostatistics at NYU into the Data Science Core.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19NS107616-03
Application #
9968472
Study Section
Special Emphasis Panel (ZNS1)
Project Start
Project End
Budget Start
2020-07-01
Budget End
2021-06-30
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
New York University
Department
Type
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016
Eyring, Katherine W; Tsien, Richard W (2018) Direct Visualization of Wide Fusion-Fission Pores and Their Highly Varied Dynamics. Cell 173:819-821