# Advanced Dynamic Clamp for Neuroscience

> **NIH NIH R44** · CYTOCYBERNETICS, INC. · 2022 · $860,834

## Abstract

Project Summary
 The goal of this Phase II proposal is to develop a commercial “plug and play”, user-friendly, powerful and
reliable dynamic clamp system specifically designed for neuronal applications. Our product will enable all
neuronal electrophysiologists to be able to perform sophisticated dynamic clamp experiments, without any
requirement for programming, engineering, or mathematical modeling skills. Our product is an integrated
package of hardware and software specifically for neuroscience applications, focusing on the specific stability
and reliability needed for routine neuronal electrophysiology and the large array of ion channels found in the
nervous system. In Phase I, we developed the critical combination of software, operating system, and hardware
to achieve high speeds, and, most importantly, the high reliability needed for this product. The hardware and
software innovations that make this system reliable and stable include a digitally modulated conductance clamp
mode. This new innovation greatly expands the stability of the system during the rapid voltage changes that
occur during neuronal action potentials. Our advances are made possible by proprietary software containing
trade secrets, novel patented and patent pending instrumentation and the unique skill set of our team. Our
system is also the first dynamic clamp system capable of using Ca2+ (and other fluorometric signals) to interact
with current amplitudes and gating behavior. In Phase I, we found that the main limitation to introducing optical
signals into dynamic clamp was bandwidth. In Phase II, we have a matched a patent-pending custom low-latency
photodetector system that we developed explicitly for use in dynamic clamp. The three aims of this project are:
 1) Develop Graphically Oriented Validated Model Channel Libraries. This aim is strongly customer driven,
based on feedback from our I-Corps interviews. The biggest barrier to using dynamic clamp in the laboratory is
difficulty implementing models. We will make dynamic clamp as easy to use as an app on your phone.
 2) Develop and validate an advanced version of the Cybersolver for intuitive model building. We will build an
intuitive interface that matches how electrophysiologists actually analyze their data. Machine intelligence will
help guide users through the process and avoid common errors. They will be able to produce custom models
that run, without problem, on the Cybercyte.
 3) Develop & Optimize Hardware for Customer-driven Features. This includes the need for more than just
membrane voltage as an input. We will incorporate optical input signals. We will also include frequently requested
features to improve the ease of use, speed of response, and an alternate “synthetic cell” mode of operation.
 Completion of these aims will result in an advanced commercial neuronal dynamic clamp system, which is
powerful, reliable, but plug and play to install, and simple to use.

## Key facts

- **NIH application ID:** 10483575
- **Project number:** 2R44MH119842-02A1
- **Recipient organization:** CYTOCYBERNETICS, INC.
- **Principal Investigator:** Mark W Nowak
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $860,834
- **Award type:** 2
- **Project period:** 2018-09-19 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10483575

## Citation

> US National Institutes of Health, RePORTER application 10483575, Advanced Dynamic Clamp for Neuroscience (2R44MH119842-02A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10483575. Licensed CC0.

---

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