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Construction of Microdrive Arrays for Chronic Neural Recordings in Awake Behaving Mice
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A 32-Channel Time-Multiplexed Artifact-Aware Neural Recording System.

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    |August 30, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a low-power, low-noise microsystem for recording neural signals like local field potentials (LFPs) and intracranial electroencephalography (iEEG). The system enhances dynamic range and preserves neural data using novel signal processing techniques.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Integrated Circuits

    Background:

    • Accurate recording of neural signals is crucial for understanding brain function and diagnosing neurological disorders.
    • Existing systems often face challenges with power consumption, noise, and limited dynamic range, hindering long-term or in-vivo applications.

    Purpose of the Study:

    • To develop and validate a low-power, low-noise microsystem for high-fidelity recording of neural local field potentials (LFPs) and intracranial electroencephalography (iEEG) signals.
    • To enhance the system's dynamic range and robustness against artifacts using advanced signal processing techniques.

    Main Methods:

    • A 32-channel time-multiplexed microsystem was designed and fabricated using a 180 nm CMOS process.
    • Implementation of a spatial delta encoding scheme to leverage signal correlation between adjacent channels.
    • Integration of a mixed-signal voltage-triggered auto-ranging algorithm for artifact attenuation and dynamic range extension.

    Main Results:

    • The system achieved an integrated input-referred noise of 1.4 μVrms in the 0.5-200 Hz band, with a spot noise of 85 nV/√Hz.
    • Demonstrated a power consumption of 1.5 μW per channel from a 1.2 V supply.
    • Achieved a dynamic range of 71 dB + 26 dB with the auto-ranging mechanism, maintaining excellent channel isolation and rejection ratios.

    Conclusions:

    • The developed microsystem offers a significant advancement in neural signal recording technology, balancing low power, low noise, and high dynamic range.
    • Experimental validation in-vitro with primary cortical neurons confirms the system's capability for accurate neural data acquisition.
    • This technology holds promise for improved diagnostics and research in neuroscience and clinical neurology.