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Related Experiment Video

Updated: Jun 3, 2026

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
13:32

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Using the electrocorticographic speech network to control a brain-computer interface in humans.

Eric C Leuthardt1, Charles Gaona, Mohit Sharma

  • 1Department of Biomedical Engineering, Washington University in St. Louis, Campus Box 8057, 660 South Euclid, St Louis, MO 63130, USA. leuthardte@wudosis.wustl.edu

Journal of Neural Engineering
|April 8, 2011
PubMed
Summary

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Brain-computer interfaces (BCIs) can now use speech network signals for control. Electrocorticography (ECoG) from phoneme articulation allows patients to operate cursors, enhancing BCI capabilities beyond motor cortex signals.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Human-Computer Interaction

Background:

  • Electrocorticography (ECoG) is a key signal platform for brain-computer interface (BCI) systems.
  • Traditionally, sensorimotor cortex signals have been used for BCI control.
  • The potential of the speech network for BCI control remained unexplored.

Purpose of the Study:

  • To investigate if ECoG signals from the speech network can be used for BCI control.
  • To determine if speech-based BCI can complement or improve existing motor-based paradigms.
  • To assess the feasibility of using phoneme articulation signals for cursor control.

Main Methods:

  • Recorded ECoG signals during overt and imagined phoneme articulation in human patients.
  • Analyzed higher gamma frequency oscillations for phonetic content.

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Last Updated: Jun 3, 2026

Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
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Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

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Using an EEG-Based Brain-Computer Interface for Virtual Cursor Movement with BCI2000
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Published on: July 29, 2009

  • Evaluated cursor control performance (accuracy and speed) within a 15-minute timeframe.
  • Utilized a minimally invasive microarray with 1 mm spaced microwires for signal acquisition.

    • Main Results:

    • Demonstrated that ECoG signals from phoneme articulation can enable rapid and accurate cursor control.
    • Achieved final target accuracies ranging from 68% to 91% within 15 minutes.
    • Showcased robust control using a small, minimally invasive cortical array.

    Conclusions:

    • The speech network offers a viable neurophysiological substrate for BCI operation.
    • Phonetic ECoG signals can enhance or complement existing motor-based BCI control.
    • Effective BCI control is achievable with small, minimally invasive cortical arrays.