Auditory Noise Leads to Increased Visual Brain-Computer Interface Performance: A Cross-Modal Study

  • Jun Xie
  • , Guozhi Cao
  • , Guanghua Xu
  • , Peng Fang
  • , Guiling Cui
  • , Yi Xiao
  • , Guanglin Li
  • , Min Li
  • , Tao Xue
  • , Yanjun Zhang
  • , Xingliang Han

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Noise has been proven to have a beneficial role in non-linear systems, including the human brain, based on the stochastic resonance (SR) theory. Several studies have been implemented on single-modal SR. Cross-modal SR phenomenon has been confirmed in different human sensory systems. In our study, a cross-modal SR enhanced brain–computer interface (BCI) was proposed by applying auditory noise to visual stimuli. Fast Fourier transform and canonical correlation analysis methods were used to evaluate the influence of noise, results of which indicated that a moderate amount of auditory noise could enhance periodic components in visual responses. Directed transfer function was applied to investigate the functional connectivity patterns, and the flow gain value was used to measure the degree of activation of specific brain regions in the information transmission process. The results of flow gain maps showed that moderate intensity of auditory noise activated the brain area to a greater extent. Further analysis by weighted phase-lag index (wPLI) revealed that the phase synchronization between visual and auditory regions under auditory noise was significantly enhanced. Our study confirms the existence of cross-modal SR between visual and auditory regions and achieves a higher accuracy for recognition, along with shorter time window length. Such findings can be used to improve the performance of visual BCIs to a certain extent.

Original languageEnglish
Article number590963
JournalFrontiers in Neuroscience
Volume14
DOIs
StatePublished - 22 Dec 2020

Keywords

  • auditory noise
  • brain–computer interface (BCI)
  • cross-modal stochastic resonance
  • functional connectivity
  • phase synchronization
  • steady-state motion visual evoked potential (SSMVEP)

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