# Administrative Core

> **NIH NIH P30** · DUKE UNIVERSITY · 2020 · $21,727

## Abstract

Administrative Core 
Abstract 
The functions of Administrative Core Component are to provide strategic supervision to the core facilities for 
vision research at Duke University and to oversee the routine operation of four resource Modules supported 
by this grant. All major decisions regarding the scope of services supported by this grant and investments in 
new technologies and methodologies will be made by the Core Grant Advisory Committee, which includes the 
PI, the Module Directors, and rotating NEI-funded investigators. Periodic (usually biannually) meetings of this 
Committee are typically open to the entire community of visual scientists and used as forums to discuss core 
usage and optimization, pressing needs and future plans. The daily operation of service Modules will be 
conducted by highly skilled personnel reporting to Module Directors. The accounting and financial reporting 
for this grant will be performed by the Office of Grants Administration. This office will provide monthly 
account statements to the PI, who will discuss them with Module Directors. In addition to open meetings of 
the Core Grant Advisory Committee, communication with members of the vision science community will be 
conducted through periodic emails summarizing major technical developments, equipment repairs and 
updates, and introduction of new commonly used services.

## Key facts

- **NIH application ID:** 10006545
- **Project number:** 5P30EY005722-35
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Vadim Y Arshavsky
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $21,727
- **Award type:** 5
- **Project period:** 1997-07-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10006545

## Citation

> US National Institutes of Health, RePORTER application 10006545, Administrative Core (5P30EY005722-35). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10006545. Licensed CC0.

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