Finite element model predicts micromotion-induced strain profiles that correlate with the functional performance of Utah arrays in humans and non-human primates

有限元模型预测了微动引起的应变分布,该分布与犹他阵列在人类和非人灵长类动物中的功能性能相关。

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Abstract

Objective.Utah arrays are widely used in both humans and non-human primates (NHPs) for intracortical brain-computer interfaces, primarily for detecting electrical signals from cortical tissue to decode motor commands. Recently, these arrays have also been applied to deliver electrical stimulation aimed at restoring sensory functions. A key challenge limiting their longevity is the micromotion between the array and cortical tissue, which may induce mechanical strain in surrounding tissue and contribute to performance decline. This strain, due to mechanical mismatch, can exacerbate glial scarring around the implant, reducing the efficacy of Utah arrays in recording neuronal activity and delivering electrical stimulation.Approach.To investigate this, we employed a finite element model to predict tissue strains resulting from micromotion.Main results.Our findings indicated that strain profiles around edge and corner electrodes were greater than those around interior shanks, affecting both maximum and average strains within 50µm of the electrode tip. We then correlated these predicted tissue strains within-vivoelectrode performance metrics. We found negative correlations between 1 kHz impedance and tissue strains in human motor arrays and NHP area V4 arrays at 1 month, 1 year, and 2 years post-implantation. In human motor arrays, the peak-to-peak waveform voltage and signal-to-noise ratio (SNR) of spontaneous activity were also negatively correlated with strain. Conversely, we observed a positive correlation between the evoked SNR of multi-unit activity and strain in NHP area V4 arrays.Significance.This study establishes a spatial dependence of electrode performance in Utah arrays that correlates with tissue strain.

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