ArticleNature human behaviour2026
Optimized feature gains explain and predict successes and failures of human selective listening.
Article in Nature human behaviour, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Human perception of avian biodiversity in naturalistic auditory scenes.PLoS computational biology · 2026Article
- Optimized feature gains explain and predict successes and failures of human selective listening.Nature human behaviour · 2026Article
- From sound to source: Human and model recognition of environmental sounds.bioRxiv : the preprint server for biology · 2026Article
- Task-optimized models of sensory uncertainty reproduce human confidence judgments.bioRxiv : the preprint server for biology · 2025Article
- A deep learning framework for understanding cochlear implants.bioRxiv : the preprint server for biology · 2025Article
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Abstract
Attention facilitates communication by enabling selective listening to sound sources of interest. However, little is known about why attentional selection succeeds in some conditions but fails in others. While neurophysiology implicates multiplicative feature gains in selective attention, it is unclear whether such gains can explain real-world attention-driven behaviour. Here we optimized an artificial neural network with stimulus-computable feature gains to recognize a cued talker's speech from binaural audio in 'cocktail party' scenarios. Though not trained to mimic humans, the model produced human-like performance across diverse real-world conditions, exhibiting selection based both on voice qualities and on spatial location as well as selection failures in conditions where humans tended to fail. It also predicted novel attentional effects that we confirmed in human experiments, and exhibited signatures of 'late selection' like those seen in human auditory cortex. The results suggest that human-like attentional strategies naturally arise from the optimization of feature gains for selective listening.
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