A four-shank 32-channel microelectrode array integrated with FPGA-based online processing for multichannel neural recording

Multichannel neural recording requires not only microelectrode arrays (MEAs) with sufficient spatial coverage but also stable front-end acquisition and online signal processing hardware. In this work, a four-shank 32-channel MEA and a field-programmable gate array (FPGA)-based online processing module are developed for multichannel neural recording. The four-shank structure is designed to provide broader spatial coverage while maintaining a compact probe footprint. Platinum nanoparticles (PtNPs) are modified on the electrode surfaces to improve the electrical interface of the recording sites. Electrochemical measurements demonstrate that PtNPs modification significantly improves the interfacial properties of the electrodes. An FPGA-based module is employed to enable communication with the front-end chip and perform online signal processing. Post-implementation verification further demonstrates that the FPGA design satisfies the timing constraints while maintaining acceptable power consumption. The end-to-end performance of the electrophysiological recording chain is evaluated through gain/bandwidth testing and simulated neural signal detection. The system exhibits an average gain of 45.57 dB within the main passband, with a bandwidth ranging from 4.28 to 2.36 kHz. In addition, simulated spike tests demonstrate stable online detection and waveform extraction. In addition, in vivo recordings from the hippocampal CA1 region demonstrate that the proposed system simultaneously acquires clear spike and local field potential signals from multiple channels, with representative spike waveforms exhibiting good consistency. The combination of a four-shank MEA with PtNPs-modified recording sites and FPGA-based online processing supports stable neural signal acquisition both in vitro and in vivo and provides a useful foundation for future neural interface applications.