Selective attention shapes neural representations of complex auditory scenes: The Roles of Object Identity and Scene Composition

Everyday auditory scenes contain overlapping sound objects, requiring attention to isolate relevant objects from irrelevant background objects. This study examined how selective attention shapes neural representations of complex sound scenes in the auditory cortex (AC). Using functional magnetic resonance imaging, we recorded brain activity from participants (12 males, 8 females) as they attended to a designated object in scenes comprising three overlapping sounds. Scenes were constructed in two manners: one where each object belonged to a different category (speech, animal, instrument) and another where all objects were from the same category. Attending to speech enhanced activations in lateral AC subfields, while attention to animal and instrument sounds preferentially modulated medial AC subfields, supporting models where attention modulates feature-selective neural gain in AC. Remarkably, however, spatial pattern analysis revealed that the attended object dominated the AC activation patterns of the entire scene in a manner depending on both object type and scene composition: When scene objects belonged to different categories, attention effects were dominated by category-level processing. In contrast, when all scene objects shared the same category, dominance shifted to exemplar level processing in fields processing acoustic features. Thus, attention seems to dynamically prioritize the features offering maximal contrast within a given context, emphasizing object-specific patterns in feature-similar scenes and category-level patterns in feature-diverse scenes. Our results support models where top-down signals not only modulate gain but also affect scene decomposition and analysis – influencing stream segregation and gating of higher-level processing in a contextual manner, adapting to specific auditory environments. Significance statement Selective attention is essential for filtering behaviorally relevant sounds from complex auditory environments, yet the underlying neural mechanisms remain obscure. We combined fMRI with spatial activation pattern analysis to determine how the auditory cortex attentionally filters different types of sounds (speech, animal, instrument) in complex scenes composed of three sounds, either from different or the same categories. Attentional filtering depended both on the object type and on scene composition. Our data suggest that in the auditory cortex attentional filtering operates on category-level features in multi-category scenes, while exemplar-level features prevail in same-category scenes. Thus, top-down attention not only modulates neural gain but also affects scene decomposition and gating of higher-level processing in a contextual manner, adapting to specific auditory environments.