# Instrumentation Module

> **NIH NIH P30** · BAYLOR COLLEGE OF MEDICINE · 2022 · $132,869

## Abstract

ABSTRACT
Instrumentation Module
The Instrumentation Module provides design, fabrication and modification capabilities for project-specific,
customized and software-flexible vision research apparatuses that are not commercially available. During the
past five years, the Module fabricated many in-house, tailor-fitted and specially-designed devices that have
played crucial roles in generating many high-impact and innovative vision research results. In the next grant
period, this Module will continue its indispensable role in supporting vision research projects by providing new
mechanical, electronic, optic and computer-based design and fabrication services and to develop highly
innovative, high-impact research tools, such as the chronically implanted recording chambers, the customized
in-house construction of a 8-patch-electrode micromanipulator/recording system, two-photon microscope
systems, LED white-noise stimulating system, and the forced-choice, optokinetic reflex machine. All these
devices will be constructed and repeatedly modified, fitted and adjusted before and during experiments by the
in-house machine shop and electronic/optics/computer shop. Therefore the Instrumentation Module is not only
a necessity of many Vision Core labs, but also an integrated part of the research process and scientific
progress.

## Key facts

- **NIH application ID:** 10462676
- **Project number:** 5P30EY002520-43
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Samuel M Wu
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $132,869
- **Award type:** 5
- **Project period:** 1997-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10462676

## Citation

> US National Institutes of Health, RePORTER application 10462676, Instrumentation Module (5P30EY002520-43). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10462676. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*