Decoding dynamic auditory attention during naturalistic experience

Abstract

Equipped with selective auditory attention (SAA), people are able to rapidly shift their attention to auditory events of interest. Although abstract neuroimaging paradigms are fundamental for exploring the neural basis of SAA, whether those findings are valid in a more naturalistic condition and how the types of auditory stimuli affect SAA are largely unknown. Here we propose a brain decoding study to explore SAA using naturalistic auditory excerpts in three categories (pop music, classical music and speech) as stimuli for functional magnetic resonance imaging (fMRI). We adopted a computational auditory attention model to estimate attentional allocation for the excerpts. We then extracted brain activity features from fMRI data via sparse representation and used them to decode the auditory attention allocation. Our experimental results showed that the primary auditory cortex was commonly involved in the attentional processing of the three categories and the contribution of distinct brain networks to the decoding model in each group. Our study on the one hand provides novel insights into neural SAA in naturalistic experience, on the other hand shows the possibility of leveraging neuroimaging studies by integrating naturalistic stimuli and computational auditory information processing approaches.