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Graphene-based microelectrodes with bidirectional functionality for next-generation retinal electronic interfaces.

Fikret Taygun DuvanMarina CunqueroEduard Masvidal-CodinaSteven T WalstonMaria MarsalJose Manuel de la CruzDamia VianaDiep NguyenJulie DegardinXavi IllaJulie Meng ZhangMaria Del Pilar BernícolaJosé Gabriel Macias-MonteroCarles PuigdengolesGustavo Castro-OlveraElena Del CorroSocrates DokosMokhtar ChmeissaniPablo Loza-AlvarezSerge PicaudJose A Garrido
Published in: Nanoscale horizons (2024)
Neuroelectronic prostheses are being developed for restoring vision at the retinal level in patients who have lost their sight due to photoreceptor loss. The core component of these devices is the electrode array, which enables interfacing with retinal neurons. Generating the perception of meaningful images requires high-density microelectrode arrays (MEAs) capable of precisely activating targeted retinal neurons. Achieving this precision necessitates the downscaling of electrodes to micrometer dimensions. However, miniaturization increases electrode impedance, which poses challenges by limiting the amount of current that can be delivered, thereby impairing the electrode's capability for effective neural modulation. Additionally, it elevates noise levels, reducing the signal quality of the recorded neural activity. This report focuses on evaluating reduced graphene oxide (rGO) based devices for interfacing with the retina, showcasing their potential in vision restoration. Our findings reveal low impedance and high charge injection limit for microscale rGO electrodes, confirming their suitability for developing next-generation high-density retinal devices. We successfully demonstrated bidirectional interfacing with cell cultures and explanted retinal tissue, enabling the identification and modulation of multiple cells' activity. Additionally, calcium imaging allowed real-time monitoring of retinal cell dynamics, demonstrating a significant reduction in activated areas with small-sized electrodes. Overall, this study lays the groundwork for developing advanced rGO-based MEAs for high-acuity visual prostheses.
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