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Video s3
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    Author(s)
    Display Name
    Jiajia Wu
    Affiliation
    Affiliation
    University of California, San Diego
    Display Name
    Abraham Akinin
    Affiliation
    Affiliation
    Lawrence Livermore National Laboratory
    Display Name
    Min Lee
    Affiliation
    Affiliation
    University of California, San Diego
    Display Name
    Akshay Paul
    Affiliation
    Affiliation
    University of California, San Diego
    Display Name
    Hongyu Lu
    Affiliation
    Affiliation
    University of California, San Diego
    Display Name
    Yongjae Park
    Affiliation
    Affiliation
    Ulsan National Institute of Science and Technology
    Display Name
    Preston Fowler
    Affiliation
    Affiliation
    University of California, San Diego
    Display Name
    Seong-Jin Kim
    Affiliation
    Affiliation
    Ulsan National Institute of Science and Technology
    Display Name
    Patrick Mercier
    Affiliation
    Affiliation
    University of California, San Diego
    Display Name
    Gert Cauwenberghs
    Affiliation
    Affiliation
    University of California, San Diego
    Abstract

    A 16-channel low-noise low-power neural recording system-on-chip is presented in this article. A low NEF of 2.93 is achieved with a chopping-based delta-sigma ADC topology to resolve the 1 Hz to 1 kHz frequency band in a continuous operation mode. Sample-level duty-cycling mode is proposed to scale down system power consumption by 98.4% for the 0.001 Hz to 1 Hz bandwidth while maintaining the same effective LSB and a high input impedance of 435 MOhm. The combination of these two operation modes expands the system's bandwidth coverage and enables versatile electrophysiological recordings on a single chip.