TNSRE presents

3-D Flexible Nano-Textured High-Density Microelectrode Arrays for High-Performance Neuro-Monitoring and Neuro-Stimulation

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Gabran, S.R.I. ; Salam, M. ; Dian, J. ; El-Hayek, Y. ; Perez Velazquez, J.L. ; Genov, R. ; Carlen, P. ; Salama, M.M.A. ; Mansour, R.
3-D Flexible Nano-Textured High-Density Microelectrode Arrays for High-Performance Neuro-Monitoring and Neuro-Stimulation

Abstract

We introduce a new 3-D flexible microelectrode array for high performance electrographic neural signal recording and stimulation. The microelectrode architecture maximizes the number of channels on each shank and minimizes its footprint. The electrode was implemented on flexible polyimide substrate using microfabrication and thin-film processing. The electrode has a planar layout and comprises multiple shanks. Each shank is three mm in length and carries six gold pads representing the neuro-interfacing channels. The channels are used in recording important precursors with potential clinical relevance and consequent electrical stimulation to perturb the clinical condition. The polyimide structure satisfied the mechanical characteristics required for the proper electrode implantation and operation. Pad postprocessing technique was developed to improve the electrode electrical performance. The planar electrodes were used for creating 3-D “Waterloo Array” microelectrode with controlled gaps using custom designed stackers. Electrode characterization and benchmarking against commercial equivalents demonstrated the superiority of the Flex electrodes. The Flex and commercial electrodes were associated with low-power implantable responsive neuro-stimulation system. The electrodes performance in recording and stimulation application was quantified through in vitro and in vivo acute and chronic experiments on human brain slices and freely-moving rodents. The Flex electrodes exhibited remarkable drop in the electric impedance (100 times at 100 Hz), improved electrode–electrolyte interface noise (dropped by four times) and higher signal-to-noise ratio (3.3 times).

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