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Related Experiment Video

Updated: May 9, 2026

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy
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A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

Published on: November 13, 2016

Stimulus-artifact elimination in a multi-electrode system.

E A Brown, J D Ross, R A Blum

    IEEE Transactions on Biomedical Circuits and Systems
    |July 16, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a novel 16-channel system for neural recording that rapidly eliminates stimulation artifacts. This custom integrated circuit (IC) enables high-fidelity neural data acquisition with multi-electrode arrays.

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    A Method for Systematic Electrochemical and Electrophysiological Evaluation of Neural Recording Electrodes

    Published on: March 3, 2014

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Electrical Engineering

    Background:

    • Multi-electrode arrays are crucial for neural recording but are limited by stimulation-induced artifacts.
    • Residual charge from stimulation protocols obscures neural signals, hindering data analysis.

    Purpose of the Study:

    • To develop a scalable system for artifact elimination in multi-electrode array recordings.
    • To enable high-fidelity neural signal acquisition by minimizing stimulus artifacts.

    Main Methods:

    • A custom 16-channel integrated circuit (IC) designed for both stimulation and recording.
    • A novel feedback scheme for direct electrode discharge and optimized electrode behavior.
    • Development of a framework for artifact measurement, classification, and understanding.

    Main Results:

    • The system achieves artifact elimination within 3 ms on the stimulating channel and 500 µs on adjacent channels.
    • Characterization of system features enabling rapid and effective artifact removal.
    • Demonstration of the system's performance with biological data.

    Conclusions:

    • The presented system effectively eliminates stimulation artifacts, enhancing neural recording capabilities.
    • The developed artifact analysis framework aids in comparing and advancing artifact elimination techniques.
    • This technology is vital for fully utilizing current and future multi-electrode array systems.