# Scalable Electrode Technology for High Resolution Chronic Recording of Brain

> **NIH NIH R01** · UNIVERSITY OF TEXAS DALLAS · 2021 · $602,702

## Abstract

Abstract
Chronically implanted microelectrode arrays (MEAs) for recording extracellular neural activity are central to
scientific studies of neural circuit function in behaving animals. These studies seek to understand how neurons
encode information and how neural signals can be decoded to provide insights into brain learning and
dysfunction. The majority of microelectrode MEAs, and especially those available commercially, are fabricated
from silicon and leverage techniques associated with integrated circuit microfabrication and packaging. For
microelectrode MEAs, the major limitations for chronic neural recording are the reactive tissue response that
encapsulates electrodes and kills or damages neurons in the vicinity of the electrode and the degradation and
failure of materials used in MEA fabrication. An effective means of minimizing the foreign body response is the
use of ultramicroelectrode MEAs (UMEAs) with subcellular cross-sectional dimensions. In related work, we have
demonstrated that carbon-fiber ultramicroelectrodes substantially evade a foreign body response and have been
shown to provide stable chronic neural recordings in small-animal models. However, a scalable manufacturing
process for carbon-fiber ultramicroelectrodes has not emerged. The proposed effort is aimed at developing and
demonstrating the chronic stability and reliability of ultramicroelectrodes based on amorphous silicon carbide (a-
SiC) UMEAs that are fabricated by industry-standard thin-film processes. We aim to develop a fabrication
process for a-SiC UMEAs with 32 to 128 ultramicroelectrodes and demonstrate the stability of these UMEAs
through accelerated laboratory testing and their functionality by neural recording and histology using chronic
implants in rat cortex and in a 3-4 year non-human primate study. To facilitate dissemination of the a-SiC UMEA
technology, electrical interconnect hardware and implantation methods will also be developed. We anticipate the
proposed a-SiC UMEAs impacting the neuroscience community by providing a highly stable neural interface that
allows single-unit and ensemble recording for probing neuronal circuitry on a dimensional scale that is not
possible with current multielectrode recording devices. We expect a-SiC UMEAs will provide new insights into
the neural networks and changes in neural circuitry that may accompany behavior and adaption.

## Key facts

- **NIH application ID:** 10247033
- **Project number:** 5R01NS104344-04
- **Recipient organization:** UNIVERSITY OF TEXAS DALLAS
- **Principal Investigator:** Stuart F Cogan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $602,702
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10247033

## Citation

> US National Institutes of Health, RePORTER application 10247033, Scalable Electrode Technology for High Resolution Chronic Recording of Brain (5R01NS104344-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10247033. Licensed CC0.

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