Learning to localise weakly-informative sound spectra with and without feedback

How the human auditory system learns to map complex pinna-induced spectral-shape cues onto veridical estimates of sound-source elevation in the median plane is still unclear. Earlier studies demonstrated considerable sound-localisation plasticity after applying pinna moulds, and to altered vision. Several factors may contribute to auditory spatial learning, like visual or motor feedback, or updated priors. We here induced perceptual learning for sounds with degraded spectral content, having weak, but consistent, elevation-dependent cues, as demonstrated by low-gain stimulus-response relations. During training, we provided visual feedback for only six targets in the midsagittal plane, to which listeners gradually improved their response accuracy. Interestingly, listeners’ performance also improved without visual feedback, albeit less strongly. Post-training results showed generalised improved response behaviour, also to non-trained locations and acoustic spectra, presented throughout the two-dimensional frontal hemifield. We argue that the auditory system learns to reweigh contributions from low-informative spectral bands to update its prior elevation estimates, and explain our results with a neuro-computational model.