Visible to the public Verification of a Rapidly Multiplexed Circuit for Scalable Action Potential Recording

TitleVerification of a Rapidly Multiplexed Circuit for Scalable Action Potential Recording
Publication TypeConference Paper
Year of Publication2020
AuthorsSharma, Mohit, Strathman, Hunter J., Walker, Ross M.
Conference Name2020 IEEE International Symposium on Circuits and Systems (ISCAS)
Date Publishedoct
KeywordsAction potential, Action potentials, analog design, Biomedical engineering, compositionality, Electric potential, electrode, electrode array, Electrodes, In vivo, Multiplexing, neural amplifier, neural engineering, neural recording, neuroscience, Predictive Metrics, pubcrawl, Resiliency, Scalability, scalable verification, Urban areas, windowed integrator sampling
AbstractThis report presents characterizations of in vivo neural recordings performed with a CMOS multichannel chip that uses rapid multiplexing directly at the electrodes, without any pre-amplification or buffering. Neural recordings were taken from a 16-channel microwire array implanted in rodent cortex, with comparison to a gold-standard commercial bench-top recording system. We were able to record well-isolated threshold crossings from 10 multiplexed electrodes and typical local field potential waveforms from 16, with strong agreement with the standard system (average SNR = 2.59 and 3.07 respectively). For 10 electrodes, the circuit achieves an effective area per channel of 0.0077 mm2, which is \textbackslashtextgreater5x smaller than typical multichannel chips. Extensive characterizations of noise and signal quality are presented and compared to fundamental theory, as well as results from in vivo and in vitro experiments. By demonstrating the validation of rapid multiplexing directly at the electrodes, this report confirms it as a promising approach for reducing circuit area in massively-multichannel neural recording systems, which is crucial for scaling recording site density and achieving large-scale sensing of brain activity with high spatiotemporal resolution.
Citation Keysharma_verification_2020