Characterizing the Time-Varying Brain Networks of Audiovisual Integration across Frequency Bands

Yang Xi, Qi Li, Mengchao Zhang, Lin Liu, Jinglong Wu

Research output: Contribution to journalArticlepeer-review

Abstract

Multisensory integration involves multiple cortical regions and occurs at multiple stages with attentional modulation. The structure of network formed by the interactive cortical regions reflects the state of working on a current task and changes continuously with the task processing. In addition, the neural oscillatory responses in various frequency bands are associated with different cognitive functions. Thus, studying topological characteristics of time-varying networks across multiple frequency bands helps to elucidate the mechanism of multisensory integration. Here, we designed an event-related experiment using auditory, visual, and audiovisual stimuli to record electroencephalographic data in both attended and unattended conditions and constructed delta-, theta-, alpha-, and beta-band networks at eight time points post-stimulus. We used graph theory to calculate global properties, nodal out-degree, and their correlation with behavioral performance. The increasing clustering coefficient and global efficiency and decreasing characteristic path length indicated that the brain had optimized the configuration across multiple frequency bands over time to efficiently process audiovisual integration. The differences in global properties and hub distributions showed that each frequency band–specificity system in the brain had a different topological structure, indicating that the networks on each frequency band contributed to various cognitive functions and involved in different stages of audiovisual integration. Our results suggest that differences in cognitive function are, at least partly, due to the different network structures across frequency bands and that the frequency band–specificity systems with different distribution are involved in various stages of audiovisual integration and attention modulation.

Original languageEnglish
Pages (from-to)1154-1169
Number of pages16
JournalCognitive Computation
Volume12
Issue number6
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Attention
  • Audiovisual integration
  • Brain network
  • Frequency band
  • Graph theory
  • Time varying

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Cognitive Neuroscience

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