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Rauschecker, J.

Publications and source records attributed to Rauschecker, J..

2 recordsLinked to original sources

Selective attention network in naturalistic auditory scenes is object and scene specific

Everyday auditory scenes often contain overlapping sound objects, requiring selective attention to isolate relevant objects from irrelevant background objects. This study examined how selective attention shapes neural representations of naturalistic sound scenes in the auditory cortex (AC). Using functional magnetic resonance imaging, we recorded brain activity from participants (n = 20) 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 consistently enhanced activations in lateral AC subfields, while attention to animal and instrument sounds preferentially modulated medial 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 the objects of the scene belonged to different categories, attended objects dominated fields processing higher-level category-specific features. In contrast, when all scene objects shared the same category, dominance shifted to fields processing low-level 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 several steps of auditory scene decomposition and analysis - influencing stream segregation and gating of higher-level processing in a contextual manner, adapting to specific auditory environments.

neuroscience↗

An energy costly architecture of neuromodulators for human brain evolution and cognition

Humans spend more energy on the brain than any other species. However, the high energy demand cannot be fully explained by brain size scaling alone. We hypothesized that energy-demanding signaling strategies may have contributed to human cognitive development. We measured the energy distribution along signaling pathways using multimodal brain imaging and found that evolutionarily novel connections have up to 67% higher energetic costs of signaling than sensory-motor pathways. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an upregulation of signaling at G-protein coupled receptors in energy-demanding regions. We found that neuromodulators are predominantly involved in complex cognition such as reading or memory processing. Our study suggests that the upregulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

neuroscience↗