# Dissemination of Real-time Neural Decoding for Cellular imaging Laboratory

> **NIH NIH R01** · UNIVERSITY OF MARYLAND BALTIMORE · 2022 · $163,687

## Abstract

This supplement is for the parent grant, R01NS110421, which was a response to FOA NSF18501
Collaborative Research in Computational Neuroscience. Real-time neural decoding for cellular
imaging is becoming a central focus in neuroscience, leading to precise neuromodulation. In the
parent grant, we have developed a stable version of an open-source software system called RNDC-
Lab (Real-time Neural Decoding for Cellular imaging Laboratory). RNDC-Lab enables real-time
implementation of complex combinations of neural signal processing algorithms including motion
correction, cell identification, calcium trace extraction, and predictive modeling (support vector
machine-based and deep neural network-based design). RNDC-Lab offers the unprecedented
capability to jointly experiment with diverse models, methods, and devices for real-time
interrogation of neural circuit activity in behaving animals.
This project centers on the rapid dissemination of RNDC-Lab. The potential users of RNDC-Lab are
experimental neuroscientists who will use the software to analyze their calcium imaging data and
computational neuroscientists who may further improve the software by adding new functions.
Experimental neuroscientists often do not have extensive background or experience in software
engineering. Major barriers to dissemination of RNDC-Lab are 1) a steep learning curve for how to
use the software and 2) a non-trivial installation process. We will address these barriers in this
supplement. The Specific Aims are: 1) we will ease the learning curve by providing training materials,
workshops, and extensive documentation; 2) we will remove the installation barrier by containerization
with Docker.
This supplement project will address the following specific objective of NOT-NS-21-014:
“maintenance, minor enhancements, and distribution of open-source computational tools and software
packages”. A value to the intended user group is 1) a simplified installation process for easy
deployment and 2) comprehensive documentation and training materials.
The anticipated outcomes of our proposal are: (1) an enhanced version of RNDC-Lab that is equipped
with container technology to enable easy installation and utilization by users on their preferred
computing platforms, and also to facilitate its maintenance and extension by developers of RNDC-
Lab; (2) extensive documentation and training to accelerate adoption of RNDC-Lab; and (3) an initial
community of users outside of the RNDC-Lab development team, and feedback gained from this
community to inform future development and revision of RNDC-Lab.

## Key facts

- **NIH application ID:** 10496623
- **Project number:** 3R01NS110421-03S1
- **Recipient organization:** UNIVERSITY OF MARYLAND BALTIMORE
- **Principal Investigator:** SHUVRA S BHATTACHARYYA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $163,687
- **Award type:** 3
- **Project period:** 2022-01-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10496623

## Citation

> US National Institutes of Health, RePORTER application 10496623, Dissemination of Real-time Neural Decoding for Cellular imaging Laboratory (3R01NS110421-03S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10496623. Licensed CC0.

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