Today, the key methodology to study in vitro or in vivo electrical activity in a population of electrogenic cells, under physiological or pathological conditions, is by using microelectrode array (MEA). While significant efforts have been devoted to develop nanostructured MEAs for improving the electrophysiological investigation in neurons and cardiomyocytes, data on the recording of the electrical activity from neuroendocrine cells with MEA technology are scarce owing to their weaker electrical signals. Disordered silicon nanowires (SiNWs) for developing a MEA that, combined with a customized acquisition board, successfully capture the electrical signals generated by the corticotrope AtT‐20 cells as a function of the extracellular calcium (Ca²⁺) concentration are reported. The recorded signals show a shape that clearly resembles the action potential waveform by suggesting a natural membrane penetration of the SiNWs. Additionally, the generation of synchronous signals observed under high Ca²⁺ content indicates the occurrence of a collective behavior in the AtT‐20 cell population. This study extends the usefulness of MEA technology to the investigation of the electrical communication in cells of the pituitary gland, crucial in controlling several essential human functions, and provides new perspectives in recording with MEA the electrical activity of excitable cells.

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.

Brain ischemia is a serious condition caused by reduced cerebral blood flow, causing disruption of ion gradients in brain tissue. This ionic imbalance induces spreading depolarization—waves of neuronal and glial depolarization propagating through the gray matter. Microelectrode arrays (MEAs) enable real-time monitoring of these dynamics in vivo and in vitro, but their sensitivity and signal quality is critical for detecting extracellular brain activity. This study investigates the response of flexible MEA based on gold-coated Zinc Oxide nanorods (ZnO NRs) - called nano-fMEA, for monitoring neural activity under pathological conditions. Nano-fMEA electromechanical properties are shown and discussed to highlight the superior performance of this platform. Conventional MEAs and nano-fMEAs are evaluated on acute mouse brain slices in two ischemic models: oxygen-glucose deprivation (OGD) and hyperkalemia. The findings reveal that the nano-fMEA significantly improves event detection rates and captures subtle fluctuations in neural activity compared to conventional rigid MEAs. This enhanced sensitivity is attributed to the optimized electrode-tissue interface, which reduces impedance and improves charge transfer. The results indicate that the nano-fMEA is particularly effective in detecting weak or transient signals, making it a valuable tool for studying neural dynamics during metabolic stress. Overall, the research underscores the promise of ZnO NRs in advancing electrophysiological tools for neuroscience applications.