title: Is predictability salient? A study of attentional capture by auditory patterns.
abstract: In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention.This article is part of the themed issue 'Auditory and visual scene analysis'.
authors.affiliation: Ear Institute, University College London, London WC1X 8EE, UK.
authors.forename: Rosy
authors.initials: R
authors.lastname: Southwell
authors.affiliation: Ear Institute, University College London, London WC1X 8EE, UK.
authors.forename: Anna
authors.initials: A
authors.lastname: Baumann
authors.affiliation: Ear Institute, University College London, London WC1X 8EE, UK.
authors.forename: Cécile
authors.initials: C
authors.lastname: Gal
authors.affiliation: École Normale Supérieure, Paris 75005, France.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Barascud
authors.affiliation: Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK.
authors.forename: Karl
authors.initials: K
authors.lastname: Friston
authors.affiliation: Ear Institute, University College London, London WC1X 8EE, UK m.chait@ucl.ac.uk.
authors.forename: Maria
authors.identifier: 0000-0002-7808-3593
authors.initials: M
authors.lastname: Chait
mesh_terms: D000161:Acoustic Stimulation; D000328:Adult; D001288:Attention; D001307:Auditory Perception; D004569:Electroencephalography; D005260:Female; D006801:Humans; D008297:Male; D055815:Young Adult
keywords: attention; auditory scene analysis; electroencephalography; predictive coding; regularity; statistical learning