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Enhanced Performance of Novel Amorphous Silicon Carbide Microelectrode Arrays in Rat Motor Cortex
Pegah Haghighi1, Eleanor N Jeakle1, Brandon S Sturgill1
1Department of Bioengineering, The University of Texas at Dallas, Richardson, TX 75080, USA.
Micromachines
|March 6, 2025
Summary
Amorphous silicon carbide (a-SiC) microelectrode arrays (MEAs) offer superior long-term neural recording stability compared to traditional silicon-based MEAs. These a-SiC devices show reduced brain tissue inflammation and gliosis, improving chronic implantation performance.
Area of Science:
- Neuroscience
- Biomaterials Engineering
- Implantable Medical Devices
Background:
- Implantable microelectrode arrays (MEAs) are crucial for brain-machine interfaces but suffer from reduced performance due to the brain's foreign body response, including neuroinflammation and gliosis.
- Developing MEAs with reduced tissue response is essential for stable, long-term neural recordings.
Purpose of the Study:
- To compare the chronic performance of amorphous silicon carbide (a-SiC) MEAs with smaller cross-sectional areas against silicon-based MEAs.
- To evaluate the inflammatory response and recording stability of these different MEA types over 16 weeks.
Main Methods:
- Implantation of multi-shank planar silicon-based MEAs and low-flexural-rigidity a-SiC MEAs into the motor cortex of Sprague-Dawley rats.
- Weekly neural recordings for 16 weeks to assess single unit activity metrics.
- Immunohistochemical analysis to quantify neuroinflammation and gliosis.
Main Results:
- a-SiC MEAs demonstrated significantly higher expression of single units compared to silicon-based MEAs throughout the 16-week implantation period.
- Immunohistochemistry revealed reduced neuroinflammation and gliosis around the a-SiC MEAs.
- a-SiC MEAs with smaller shank cross-sectional areas provided more stable single unit activity recording.
Conclusions:
- a-SiC MEAs exhibit superior chronic performance for neural recording compared to silicon-based devices.
- The reduced inflammatory response and enhanced stability of a-SiC MEAs make them a promising alternative for long-term brain-machine interface applications.

