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Related Experiment Video

Updated: May 9, 2026

Assessment and Communication for People with Disorders of Consciousness
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Brain-computer interfaces increase whole-brain signal to noise.

T Dorina Papageorgiou1, Jonathan M Lisinski, Monica A McHenry

  • 1Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA.

Proceedings of the National Academy of Sciences of the United States of America
|August 1, 2013
PubMed
Summary

Controlling devices with brain-computer interfaces (BCIs) enhances cognitive task performance and signal quality. Real-time fMRI reveals BCI control recruits specific brain networks, improving task classification.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Biomedical Engineering

Background:

  • Brain-computer interfaces (BCIs) translate mental states into device control.
  • The cognitive impact of BCI control on covert tasks remains unclear.
  • Measuring covert task performance quality is challenging.

Purpose of the Study:

  • To investigate if covert task performance differs with and without BCI control.
  • To quantify the quality of covert task performance during BCI use.
  • To examine the neural correlates of BCI control.

Main Methods:

  • Utilized whole-brain, classifier-based real-time functional MRI (rt-fMRI).
  • Subjects performed covert counting tasks (fast and slow rates) to control a visual interface.
Keywords:
multi-voxel pattern analysisneurofeedbackspeech motor imagerysupport vector machine

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Last Updated: May 9, 2026

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  • Compared neural activity and classification accuracy during BCI control versus passive viewing.

    • Main Results:

    • BCI control improved classification accuracy for both fast and slow covert counting tasks.
    • Active BCI control increased whole-brain signal-to-noise ratio compared to passive viewing.
    • Identified distinct neural networks associated with BCI control, including frontal, parietal, and insula regions.

    Conclusions:

    • Real-time fMRI is a viable platform for studying BCI-related cognitive processes.
    • BCI control modulates neural activity and enhances task-specific signal detection.
    • Frontoparietal and insula networks play a key role in regulating brain activity during BCI use.