Objective. Neural interfaces are an essential tool to enable the human body to directly communicate with machines such as computers or prosthetic robotic arms. Since invasive electrodes can be located closer to target neurons, they have advantages such as precision in stimulation and high signal-to-noise ratio (SNR) in recording, while they often exhibit unstable performance in long-termin-vivoimplantation because of the tissue damage caused by the electrodes insertion. In the present study, we investigated the electrical functionality of flexible penetrating microelectrode arrays (FPMAs) up to 3 months inin-vivoconditions.Approach. Thein-vivoexperiment was performed by implanting FPMAs in five rats. Thein-vivoimpedance as well as the action potential (AP) amplitude and SNR were analyzed over weeks. Additionally, APs were tracked over time to investigate the possibility of single neuron recording.Main results. It was observed that the FPMAs exhibited dramatic increases in impedance for the first 4 weeks after implantation, accompanied by decreases in AP amplitude. However, the increase/decrease in AP amplitude was always accompanied by the increase/decrease in background noise, resulting in quite consistently maintained SNRs. After 4 weeks of implantation, we observed two distinctive issues regarding long-term implantation, each caused by chronic tissue responses or by the delamination of insulation layer. The results demonstrate that the FPMAs successfully recorded neuronal signals up to 12 weeks, with very stably maintained SNRs, reduced by only 16.1% on average compared to the first recordings, although biological tissue reactions or physical degradation of the FPMA were present.Significance. The fabricated FPMAs successfully recorded intracortical signals for 3 months. The SNR was maintained up to 3 months and the chronic function of FPMA was comparable with other silicon based implantable electrodes.
Keywords: flexible penetrating microelectrode array (FPMA); long-term recording; neural interface; signal-to-noise ratio (SNR).
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