TY - JOUR
T1 - Characterizing the Time-Varying Brain Networks of Audiovisual Integration across Frequency Bands
AU - Xi, Yang
AU - Li, Qi
AU - Zhang, Mengchao
AU - Liu, Lin
AU - Wu, Jinglong
N1 - Funding Information:
This work was financially supported by the National Natural Science Foundation of China (grant numbers 61773076 and 61806025) and Jilin Scientific and Technological Development Program (grant numbers 20190302072GX and 20200802004GH). Acknowledgments
Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/11
Y1 - 2020/11
N2 - 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.
AB - 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.
KW - Attention
KW - Audiovisual integration
KW - Brain network
KW - Frequency band
KW - Graph theory
KW - Time varying
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U2 - 10.1007/s12559-020-09783-9
DO - 10.1007/s12559-020-09783-9
M3 - Article
AN - SCOPUS:85095412063
SN - 1866-9956
VL - 12
SP - 1154
EP - 1169
JO - Cognitive Computation
JF - Cognitive Computation
IS - 6
ER -