1 Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

2 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

3 Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, China

4 University of Chinese Academy of Sciences, Beijing 100049, China

Abstract 

Cross-modal selective attention enhances the processing of sensory inputs that are most relevant to the task at hand. Such differential processing could be mediated by a swift network reconfiguration on the macroscopic level, but this remains a poorly understood process. To tackle this issue, we used a behavioral paradigm to introduce a shift of selective attention between the visual and auditory domains, and recorded scalp electroencephalographic signals from eight healthy participants. The changes in effective connectivity caused by the cross-modal attentional shift were delineated by analyzing spectral Granger Causality (GC), a metric of frequency-specific effective connectivity. Using data-driven methods of pattern-classification and feature-analysis, we found that a change in the α band (12 Hz–15 Hz) of GC is a stable feature across different individuals that can be used to decode the attentional shift. Specifically, auditory attention induces more pronounced information flow in the α band, especially from the parietal–occipital areas to the temporal–parietal areas, compared to the case of visual attention, reflecting a reconfiguration of interaction in the macroscopic brain network accompanying different processing. Our results support the role of α oscillation in organizing the information flow across spatially-separated brain areas and, thereby, mediating cross-modal selective attention.

Keywords

Human EEG; Audiovisual selective attention; Granger Causality; Pattern classification 

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