4.6 Article

Predictive Uncertainty Underlies Auditory Boundary Perception

期刊

PSYCHOLOGICAL SCIENCE
卷 32, 期 9, 页码 1416-1425

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/0956797621997349

关键词

entropy; prediction; perception; grouping; music; open data; open materials

资金

  1. Horizon 2020 Marie Sklodowska-Curie Actions [754513]
  2. Social Sciences and Humanities Research Council of Canada [435-2016-1442]
  3. Canadian Institute for Advanced Research
  4. Natural Sciences and Engineering Research Council of Canada [RGPIN-2019-05416]
  5. Canadian Institutes of Health Research [MOP-153130]
  6. Danmarks Grundforskningsfond [DNRF 117]
  7. Aarhus Universitets Forskningsfond

向作者/读者索取更多资源

The study found that events generating high entropy in auditory sequence perception can prospectively contribute to event segmentation, making the perception sound more complete, independently of the properties of the subsequent events.
Anticipating the future is essential for efficient perception and action planning. Yet the role of anticipation in event segmentation is understudied because empirical research has focused on retrospective cues such as surprise. We address this concern in the context of perception of musical-phrase boundaries. A computational model of cognitive sequence processing was used to control the information-dynamic properties of tone sequences. In an implicit, self-paced listening task (N = 38), undergraduates dwelled longer on tones generating high entropy (i.e., high uncertainty) than on those generating low entropy (i.e., low uncertainty). Similarly, sequences that ended on tones generating high entropy were rated as sounding more complete (N = 31 undergraduates). These entropy effects were independent of both the surprise (i.e., information content) and phrase position of target tones in the original musical stimuli. Our results indicate that events generating high entropy prospectively contribute to segmentation processes in auditory sequence perception, independently of the properties of the subsequent event.

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