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Selective auditory attention decoding in bilateral cochlear implant users to music instruments.

Jonas Althoff1,2, Waldo Nogueira1,2,3

  • 1Department of Otolaryngology, Hannover Medical School, Hanover, Germany.

Journal of Neural Engineering
|January 19, 2026
PubMed
Summary

Selective auditory attention decoding (SAAD) is possible for cochlear implant (CI) users listening to music. A new artifact reduction technique improved decoding accuracy, enhancing music perception for CI users.

Keywords:
brain computer interfacecochlear implantmusicselective auditory attention decoding

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Area of Science:

  • Neuroscience
  • Audiology
  • Biomedical Engineering

Background:

  • Electroencephalography (EEG) can decode attended sound in normal-hearing (NH) listeners, offering potential for cochlear implant (CI) users' music experience.
  • Decoding auditory attention could guide CI sound processing strategies for improved music perception.

Purpose of the Study:

  • To investigate the feasibility of selective auditory attention decoding (SAAD) for music stimuli in CI users.
  • To develop and evaluate a novel artifact rejection technique for EEG in CI users.

Main Methods:

  • Recorded high-density EEG from 8 NH and 8 CI users listening to dichotic clarinet and cello duets.
  • Trained a linear decoder to reconstruct attended instrument audio features from EEG.
  • Developed and applied ASICA, an automated artifact rejection method using Independent Component Analysis (ICA).

Main Results:

  • Achieved SAAD for music in CI users with decoding accuracies of 59.4% (NH) and 60% (CI).
  • The ASICA algorithm improved correlation coefficients between reconstructed and attended audio features, especially with dominant artifacts.
  • Demonstrated effective suppression of cochlear implant stimulation artifacts.

Conclusions:

  • Selective auditory attention to music can be decoded in CI users.
  • The ASICA algorithm enhances decoding accuracy in the presence of CI-induced artifacts.
  • SAAD in CI users may serve as an objective measure of music perception or inform brain-computer interfaces for music enjoyment.