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A Multi-Channel Neural Recording System With Neural Spike Scan and Adaptive Electrode Selection for High-Density Neural Interface

Han-Sol Lee, Kyeongho Eom, Minju Park, Seung-Beom Ku, Kwonhong Lee, Taewoo Kim, Tae-Kyung Kim, Young‐Min Shon, Hangue Park, Hyung‐Min Lee

2023IEEE Transactions on Circuits and Systems I Regular Papers16 citationsDOI

Abstract

There is an increasing demand for real-time neural signal monitoring from a large number of electrodes to provide adequate spatial and temporal resolution for high-density brain neural interfaces. This paper proposes an adaptive multi-channel neural recording system that can record neural signals from a large number of electrodes using a smaller number of recording channels. The system utilizes an adaptive electrode selection technique to automatically scan the electrodes where neural spikes occur and record those selected electrodes. A proposed 32-electrode neural recording prototype, including 12 recording channels and 8 scanning channels, was fabricated in a 180-nm CMOS process and tested <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> . With pre-recorded neural data, the system verified that the occurrence of neural spikes in specific electrodes could be detected and processed in real-time, enabling automatic electrode selection. Measured results showed that the proposed system could lead to over 40% reduction in silicon area compared to conventional works.

Topics & Concepts

ElectrodeComputer scienceChannel (broadcasting)Artificial neural networkBrain–computer interfaceSIGNAL (programming language)Interface (matter)Spike (software development)Artificial intelligenceMaterials scienceElectroencephalographyTelecommunicationsChemistryNeuroscienceProgramming languageMaximum bubble pressure methodBubblePhysical chemistryParallel computingSoftware engineeringBiologyNeuroscience and Neural EngineeringNeural dynamics and brain functionEEG and Brain-Computer Interfaces