A cell-electrode interface signal-to-noise ratio model for 3D micro-nano electrode.

Abstract

3D Micro-nano electrodes (MNE) with the vertical nanopillar array distributed on the surface play an increasingly important role in neural science research. The geometric parameters of the nanopillar array and the cell adhesion state on the nanopillar array are the factors that may affect the MNE recording. However, the quantified relationship between these parameters and the signal-to-noise ratio (SNR) is still unclear. This paper establishes a cell-MNE interface SNR model and obtains the mathematical relationship between the above parameters and SNR. The equivalent electrical circuit and numerical simulation are used to study the sensing performance of the cell-electrode interface. The adhesion state of cells on MNE is quantified as engulfment percentage, and an equivalent cleft width is proposed to describe the signal loss caused by clefts between the cell membrane and the electrode surface. Whether the planar substrate is insulated or not, the SNR of MNE is greater than planar microelectrode (PME) only when the engulfment percentage is greater than a certain value. Under the premise of maximum engulfment percentage, the spacing and height of nanopillars should be minimized, and the radius of the nanopillar should be maximized for better signal quality. The model can clarify the mechanism of improving SNR by nanopillar arrays and provides the theoretical basis for the design of such nanopillar neural electrodes.