High-Throughput PEDOT:PSS/PtNPs-Modified Microelectrode Array for Simultaneous Recording and Stimulation of Hippocampal Neuronal Networks in Gradual Learning Process

Abstract

When it comes to mechanisms of brain functions such as learning and memory mediated by neural networks, existing multichannel electrophysiological detection and regulation technology at the cellular level does not suffice. To address this challenge, a 128-channel microelectrode array (MEA) was fabricated for electrical stimulation (ES) training and electrophysiological recording of the hippocampal neurons in vitro. The PEDOT:PSS/PtNPs-coated microelectrodes dramatically promote the recording and electrical stimulation performance. The MEA exhibited low impedance (10.94 ± 0.49 kohm), small phase delay (−12.54 ± 0.51°), high charge storage capacity (14.84 ± 2.72 mC/cm2), and high maximum safe injection charge density (4.37 ± 0.22 mC/cm2), meeting the specific requirements for training neural networks in vitro. A series of ESs at various frequencies was applied to the neuronal cultures in vitro, seeking the optimum training mode that enables the neuron to display the most obvious plasticity, and 1 Hz ES was determined. The network learning process, including three consecutive trainings, affected the original random spontaneous activity. Along with that, the firing pattern gradually changed to burst and the correlation and synchrony of the neuronal activity in the network have progressively improved, increasing by 314% and 240%, respectively. The neurons remembered these changes for at least 4 h. Collectively, ES activates the learning and memory functions of neurons, which is manifested in transformations in the discharge pattern and the improvement of network correlation and synchrony. This study offers a high-performance MEA revealing the underlying learning and memory functions of the brain and therefore serves as a useful tool for the development of brain functions in the future.

Nanomaterial-based microelectrode arrays for in vitro bidirectional brain–computer interfaces: a review

“…Comprehensive and feasible characterizations of MEA are necessary, ensuring that the devices meet the demands for recording and stimulation 38 . To quantify the performance of the electrodes, typically, the impedance, charge storage capacity (CSC), charge injection capacity (CIC) or charge injection limits (CIL), water reduction potential and oxidation potential (water window) and stability should be determined 39 – 41 .…”

Neuron devices: emerging prospects in neural interfaces and recognition

“…A high-performance electronic device was designed to train hippocampal neurons to learn by activating their memory function through electrical stimulation (Fig. 7a, b ) 103 . Correlation and synchrony of the hippocampal neuronal networks with training were examined by a heatmap, which showed that the synchrony index increased with increasing training time (Fig.…”

“… a Scheme of high-throughput MEA for recording and stimulation. b The process of dynamic changes in the synchrony index of the network 103 . Copyright 2022 American Chemical Society.…”

A Neural Sensor with a Nanocomposite Interface for the Study of Spike Characteristics of Hippocampal Neurons under Learning Training

“…In the past ten years, conductive polymers including polypyrrole (PPy) [ 22 ] and poly(3,4-ethylenedioxythiophene) (PEDOT) have attracted much attention as interface materials. In particular, PEDOT has been widely used in neural interfaces due to its biocompatibility and chemical stability [ 23 , 24 , 25 , 26 ]. The electrochemical deposition of PEDOT forms a positively charged framework, which provides accommodation for negatively charged dopants to reach charge balance.…”