Enhanced Response of ZnO Nanorod-Based Flexible MEAs for Recording Ischemia-Induced Neural Activity in Acute Brain Slices

TL;DR

A new flexible microelectrode array using zinc oxide nanorods improves detection of brain activity during ischemia, offering better sensitivity and signal quality.

Contribution

The study introduces a flexible nano-fMEA with gold-coated ZnO nanorods that enhances electrophysiological recording during ischemic conditions.

Findings

The nano-fMEA showed higher event detection rates and captured subtle neural signal fluctuations better than flat fMEAs.

The improved performance is due to an optimized electrode-tissue interface that reduces impedance and enhances charge transfer.

The nano-fMEA effectively detected weak electrophysiological events under ischemic models like oxygen–glucose deprivation and hyperkalemia.

Abstract

Brain ischemia is a severe condition caused by reduced cerebral blood flow, leading to the disruption of ion gradients in brain tissue. This imbalance triggers spreading depolarizations, which are waves of neuronal and glial depolarization propagating through the gray matter. Microelectrode arrays (MEAs) are essential for real-time monitoring of these electrophysiological processes both in vivo and in vitro, but their sensitivity and signal quality are critical for accurate detection of extracellular brain activity. In this study, we evaluate the performance of a flexible microelectrode array based on gold-coated zinc oxide nanorods (ZnO NRs), referred to as nano-fMEA, specifically for high-fidelity electrophysiological recording under pathological conditions. Acute mouse brain slices were tested under two ischemic models: oxygen–glucose deprivation (OGD) and hyperkalemia. The nano-fMEA demonstrated significant improvements in event detection rates and in capturing subtle fluctuations in neural signals compared to flat fMEAs. This enhanced performance is primarily attributed to an optimized electrode–tissue interface that reduces impedance and improves charge transfer. These features enabled the nano-fMEA to detect weak or transient electrophysiological events more effectively, making it a valuable platform for investigating neural dynamics during metabolic stress. Overall, the results underscore the promise of ZnO NRs in advancing electrophysiological tools for neuroscience research.

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