# Data Science Core

> **NIH NIH U19** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $345,330

## Abstract

Project Summary: Data Science Core
Our team for this NIH BRAIN Initiative U19 proposal on Oxytocin Modulation of Neural Circuit Function and
Behavior is located at NYU Grossman School of Medicine, and staff for the Data Science Core are located in
the NYU Health Sciences Library and Neuroscience Institute. This proximity facilitates their interactions, which
has produced 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 faculty
member in the Health Sciences Library with a background in computational and experimental neuroscience, in
collaboration with Dr. Karen Adolph, Dr. Peter Petersen, and Nicole Contaxis (leaders in repositories for
behavioral and neural data and data discovery, respectively).
 The 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 build a
pipeline for annotating, storing, and sharing behavioral video data. This project will involve a collaboration with
Drs. Mar (Behavior Core), Froemke (Project 1 PI), and Lin (Project 2 PI) and Dr. Karen Adolph, director of the
Databrary video repository to add functionality and metadata to Databrary to popularize a “Zoobrary” for animal
video data. Aim 2 is to further develop and disseminate the BrainSTEM tool as a low barrier means to achieve
FAIR data sharing. Dr. Surkis will continue her work with Dr. Peter Petersen to refine and disseminate this
experimental neuroscience metadata collection tool as a low barrier means to FAIR data sharing. Aim 3 is to
develop a blueprint for a sustainable system to maximize discoverability of BRAIN Initiative data. Dr. Surkis will
work with Nicole Contaxis, lead of the NYU Data Catalog to develop functionality that will provide a blueprint for
means to improve discovery of datasets within a fragmented and evolving data repository landscape. We will
also continue to work with extramural collaborators and other BRAIN Initiative U19 groups to discuss best
practices for data sharing, e.g., under the FAIR principles, and leverage Dr. Surkis’s position as Director of the
National Center for Data Services of the Network of the National Library of Medicine to disseminate best practices
developed within the OXT U19 and across the BRAIN Initiative.

## Key facts

- **NIH application ID:** 10912594
- **Project number:** 5U19NS107616-07
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Alisa Surkis
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $345,330
- **Award type:** 5
- **Project period:** 2018-09-15 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10912594

## Citation

> US National Institutes of Health, RePORTER application 10912594, Data Science Core (5U19NS107616-07). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10912594. Licensed CC0.

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