PPy/SWCNTs-modified microelectrode array for learning and memory model construction through electrical stimulation and detection of in vitro hippocampal neuronal network

The learning and memory functions of the brain remain unclear, which are in urgent need for the detection of both a single cell signal with high spatiotemporal resolution and network activities with high throughput. Here, an in vitro microelectrode array (MEA) was fabricated and further modified with polypyrrole/carboxylated single-walled carbon nanotubes (PPy/SWCNTs) nanocomposites as the interface between biological and electronic systems. The deposition of the nanocomposites significantly improved the performance of microelectrodes including low impedance (60.3 ± 28.8 k Ω), small phase delay (−32.8 ± 4.4°), and good biocompatibility. Then the modified MEA was used to apply learning training and test on hippocampal neuronal network cultured for 21 days through electrical stimulation, and multichannel electrophysiological signals were recorded simultaneously. During the process of learning training, the stimulus/response ratio of the hippocampal learning population gradually increased and the response time gradually decreased. After training, the mean spikes in burst, number of bursts, and mean burst duration increased by 53%, 191%, and 52%, respectively, and the correlation of neurons in the network was significantly enhanced from 0.45 ± 0.002 to 0.78 ± 0.002. In addition, the neuronal network basically retained these characteristics for at least 5 h. These results indicated that we have successfully constructed a learning and memory model of hippocampal neurons on the in vitro MEA, contributing to understanding learning and memory based on synaptic plasticity. The proposed PPy/SWCNTs-modified in vitro MEA will provide a promising platform for the exploration of learning and memory mechanism and their applications in vitro

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

Both the cellular- and population-level properties of involved neurons are essential for unveiling the learning and memory functions of the brain. To give equal attention to these two aspects, neural sensors based on microelectrode arrays (MEAs) have been in the limelight due to their noninvasive detection and regulation capabilities. Here, we fabricated a neural sensor using carboxylated graphene/3,4-ethylenedioxythiophene:polystyrenesulfonate (cGO/PEDOT:PSS), which is effective in sensing and monitoring neuronal electrophysiological activity in vitro for a long time. The cGO/PEDOT:PSS-modified microelectrodes exhibited a lower electrochemical impedance (7.26 ± 0.29 kΩ), higher charge storage capacity (7.53 ± 0.34 mC/cm2), and improved charge injection (3.11 ± 0.25 mC/cm2). In addition, their performance was maintained after 2 to 4 weeks of long-term cell culture and 50,000 stimulation pulses. During neural network training, the sensors were able to induce learning function in hippocampal neurons through precise electrical stimulation and simultaneously detect changes in neural activity at multiple levels. At the cellular level, not only were three kinds of transient responses to electrical stimulation sensed, but electrical stimulation was also found to affect inhibitory neurons more than excitatory neurons. As for the population level, changes in connectivity and firing synchrony were identified. The cGO/PEDOT:PSS-based neural sensor offers an excellent tool in brain function development and neurological disease treatment