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ERAASR: an algorithm for removing electrical stimulation artifacts from multielectrode array recordings.

Daniel J O'Shea1, Krishna V Shenoy

  • 1Neurosciences Program, Stanford University, Stanford, CA 94305, United States of America. Department of Electrical Engineering, Stanford University, Stanford, CA 94305, United States of America.

Journal of Neural Engineering
|December 22, 2017
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Summary
This summary is machine-generated.

A new algorithm, ERAASR, effectively removes electrical stimulation artifacts from neural recordings. This enables clear detection of neural spiking activity, advancing systems neuroscience and neural prosthetics research.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Electrical stimulation is crucial in neuroscience and neural prosthetics.
  • Electrical artifacts from stimulation obscure neural activity detection on recording electrodes.
  • Understanding neural population responses during stimulation is challenging due to artifacts.

Purpose of the Study:

  • Develop a method to clean artifact-corrupted signals from multielectrode arrays.
  • Recover underlying neural spiking activity obscured by electrical stimulation artifacts.
  • Enable simultaneous electrical stimulation and neural recording.

Main Methods:

  • Developed an algorithm: Estimation and Removal of Array Artifacts via Sequential Principal Components Regression (ERAASR).
  • ERAASR leverages artifact transient similarity across channels, pulses, and trials.
  • Employs straightforward linear methods with intuitive parameters, requiring no special hardware.

Main Results:

  • Demonstrated ERAASR effectiveness in macaque dorsal premotor cortex recordings.
  • ERAASR successfully removed large electrical artifacts present during stimulation.
  • Cleaned signals revealed quiescent channels and evoked spikes resembling spontaneous activity.

Conclusions:

  • ERAASR enables simultaneous electrical stimulation and multielectrode array recording.
  • This facilitates the study of causal links between neural activity and cognition.
  • Aids in the development of naturalistic sensory prostheses.