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 in vitro. 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.
Original language | English |
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Pages (from-to) | 2844-2857 |
Number of pages | 14 |
Journal | IEEE Transactions on Circuits and Systems I: Regular Papers |
Volume | 70 |
Issue number | 7 |
DOIs | |
Publication status | Published - 2023 Jul 1 |
Bibliographical note
Publisher Copyright:© 2004-2012 IEEE.
Keywords
- Adaptive electrode selection
- implantable device
- multi-unit activity (MUA)
- neural interface
- neural recording
ASJC Scopus subject areas
- Hardware and Architecture
- Electrical and Electronic Engineering