Decoding Object-Based Auditory Attention from Source-Reconstructed MEG Alpha Oscillations

How do we attend to relevant auditory information in complex naturalistic scenes? Much research has focused on detecting which information is attended, without regarding underlying top-down control mechanisms. Studies investigating attentional control generally manipulate and cue specific features in simple stimuli. However, in naturalistic scenes it is impossible to dissociate relevant from irrelevant information based on low-level features. Instead, the brain has to parse and select auditory objects of interest. The neural underpinnings of object-based auditory attention remain not well understood. Here we recorded MEG while 15 healthy human subjects (9 female) prepared for the repetition of an auditory object presented in one of two overlapping naturalistic auditory streams. The stream containing the repetition was prospectively cued with 70% validity. Crucially, this task could not be solved by attending low-level features, but only by processing the objects fully. We trained a linear classifier on the cortical distribution of source-reconstructed oscillatory activity to distinguish which auditory stream was attended. We could successfully classify the attended stream from alpha (8–14 Hz) activity in anticipation of repetition onset. Importantly, attention could only be classified from trials in which subjects subsequently detected the repetition, but not from miss trials. Behavioral relevance was further supported by a correlation between classification accuracy and detection performance. Decodability was not sustained throughout stimulus presentation, but peaked shortly before repetition onset, suggesting that attention acted transiently according to temporal expectations. We thus demonstrate anticipatory alpha oscillations to underlie top-down control of object-based auditory attention in complex naturalistic scenes.SIGNIFICANCE STATEMENT In everyday life, we often find ourselves bombarded with auditory information, from which we need to select what is relevant to our current goals. Previous research has highlighted how we attend to specific highly controlled aspects of the auditory input. Although invaluable, it is still unclear how this relates to attentional control in naturalistic auditory scenes. Here we used the high precision of magnetoencephalography in space and time to investigate the brain mechanisms underlying top-down control of object-based attention in ecologically valid sound scenes. We show that rhythmic activity in auditory association cortex at a frequency of ∼10 Hz (alpha waves) controls attention to currently relevant segments within the auditory scene and predicts whether these segments are subsequently detected.