Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics

Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges in developing durable, highly transparent electrodes while maintaining low interface impedance and prioritizing scalable processing and fabrication methods. To address these limitations, we introduce artifact-resistant transparent MXene microelectrode arrays optimized for high spatiotemporal resolution recording of neural activity. With 60% transmittance at 550 nm, these arrays enable simultaneous imaging and electrophysiology for multimodal neural mapping. Electrochemical characterization shows low impedance of 563 ± 99 kΩ at 1 kHz and a charge storage capacity of 58 mC cm⁻² without chemical doping. In vivo experiments in rodent models demonstrate the transparent arrays' functionality and performance. In a rodent model of chemically-induced epileptiform activity, we tracked ictal wavefronts via calcium imaging while simultaneously recording seizure onset. In the rat barrel cortex, we recorded multi-unit activity across cortical depths, showing the feasibility of recording high-frequency electrophysiological activity. The transparency and optical absorption properties of Ti₃C₂Tx MXene microelectrodes enable high-quality recordings and simultaneous light-based stimulation and imaging without contamination from light-induced artifacts.

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Publication Details

Journal
Advanced Healthcare Materials
Published
2024-09-27
DOI
https://doi.org/10.1002/adhm.202402576
Citations
19
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
3.96

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article

Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics

Yuzhang Chen, Brendan B. Murphy, Hajime Takano, Nicolette Driscoll et al.
19 citations
Advanced Healthcare Materials
Advanced Memory and Neural Computing
3.96
article

Transparent MXene Microelectrode Arrays for Multimodal Mapping of Neural Dynamics

Yuzhang Chen, Brendan B. Murphy, Hajime Takano, Nicolette Driscoll, Mikhail Shekhirev, Flavia Vitale, Yury G. Gogotsi, Andrew G. Richardson, Quincy Hendricks, Benjamin I Ferleger, Spencer R. Averbeck, Sneha Shankar
article en
19 citations

Abstract

Transparent microelectrode arrays have proven useful in neural sensing, offering a clear interface for monitoring brain activity without compromising high spatial and temporal resolution. The current landscape of transparent electrode technology faces challenges in developing durable, highly transparent electrodes while maintaining low interface impedance and prioritizing scalable processing and fabrication methods. To address these limitations, we introduce artifact-resistant transparent MXene microelectrode arrays optimized for high spatiotemporal resolution recording of neural activity. With 60% transmittance at 550 nm, these arrays enable simultaneous imaging and electrophysiology for multimodal neural mapping. Electrochemical characterization shows low impedance of 563 ± 99 kΩ at 1 kHz and a charge storage capacity of 58 mC cm⁻² without chemical doping. In vivo experiments in rodent models demonstrate the transparent arrays' functionality and performance. In a rodent model of chemically-induced epileptiform activity, we tracked ictal wavefronts via calcium imaging while simultaneously recording seizure onset. In the rat barrel cortex, we recorded multi-unit activity across cortical depths, showing the feasibility of recording high-frequency electrophysiological activity. The transparency and optical absorption properties of Ti₃C₂Tx MXene microelectrodes enable high-quality recordings and simultaneous light-based stimulation and imaging without contamination from light-induced artifacts.

Advanced Healthcare MaterialsVol. 14(4)
Children's Hospital of Philadelphia (US), Translational Therapeutics (United States) (US), Drexel University (US), University of Pennsylvania (US)
National Science Foundation, University of Pennsylvania, Drexel University, National Institutes of Health
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Advanced Memory and Neural Computing
3.96
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