Carbon Cybernetics Array: a miniaturized carbon-based microelectrode array for intracortical recording

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Authors: Simon J. Higham, Young Jun Jung, Sorel E. De León, Wei Tong, Shun Long Cyril Au, Yidan Shang, H Wang, Mauhak Kalra, Andrew P. Morokoff, Matias I. Maturana, Rob Hilkes, Michael R. Ibbotson
+2 more David J. Garrett, Steven Prawer
Cited by: 0
References: 48

Abstract

ABSTRACT Implantable brain-machine interfaces, capable of capturing high-resolution neural signals, hold great promise for treating neurological conditions and advancing neuroscience research. As the field moves toward chronic, fully implantable systems, ensuring the long-term safety and stability of the microelectrode arrays, the core component of these interfaces, remains a significant challenge. Hermetic sealing, which prevents moisture and contaminants from entering the device, is a critical yet often overlooked factor in array designs. This study reports the Carbon Cybernetics Array, a hermetically sealed, carbon-based microelectrode array for neural interfacing. Carbon fiber electrodes are anchored on a diamond substrate via a hermetic feedthrough structure, with hermeticity validated through helium leak testing. These ultrathin and flexible carbon fibers require minimal insertion force, cause little tissue damage after six months of implantation in rats and enable single-unit neural recordings. Furthermore, a low-cost, manually controllable insertion toolset is developed for precise array implantation in the sheep brain through a small burr hole, demonstrating a step toward clinical translation. Finally, the scalability of the fabrication approach is exemplified by arrays with over 1000 fibers. Together, this hermetically sealed feedthrough structure will lay the foundation for a future fully implantable device with wireless capabilities.

Fields of Study & Subjects

Neuroscience and Neural Engineering Photoreceptor and optogenetics research Neurological disorders and treatments

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
7 January 2026
Document type
Preprint