Attentional and Contextual Priors in Sound Perception
Behavioral and neural studies of selective attention have consistently demonstrated that explicit attentional cues to particular perceptual features profoundly alter perception and performance. The statistics of the sensory environment can also provide cues about what perceptual features to expect,...
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Published in | PloS one Vol. 11; no. 2; p. e0149635 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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Public Library of Science
16.02.2016
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Abstract | Behavioral and neural studies of selective attention have consistently demonstrated that explicit attentional cues to particular perceptual features profoundly alter perception and performance. The statistics of the sensory environment can also provide cues about what perceptual features to expect, but the extent to which these more implicit contextual cues impact perception and performance, as well as their relationship to explicit attentional cues, is not well understood. In this study, the explicit cues, or attentional prior probabilities, and the implicit cues, or contextual prior probabilities, associated with different acoustic frequencies in a detection task were simultaneously manipulated. Both attentional and contextual priors had similarly large but independent impacts on sound detectability, with evidence that listeners tracked and used contextual priors for a variety of sound classes (pure tones, harmonic complexes, and vowels). Further analyses showed that listeners updated their contextual priors rapidly and optimally, given the changing acoustic frequency statistics inherent in the paradigm. A Bayesian Observer model accounted for both attentional and contextual adaptations found with listeners. These results bolster the interpretation of perception as Bayesian inference, and suggest that some effects attributed to selective attention may be a special case of contextual prior integration along a feature axis. |
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AbstractList | Behavioral and neural studies of selective attention have consistently demonstrated that explicit attentional cues to particular perceptual features profoundly alter perception and performance. The statistics of the sensory environment can also provide cues about what perceptual features to expect, but the extent to which these more implicit contextual cues impact perception and performance, as well as their relationship to explicit attentional cues, is not well understood. In this study, the explicit cues, or attentional prior probabilities, and the implicit cues, or contextual prior probabilities, associated with different acoustic frequencies in a detection task were simultaneously manipulated. Both attentional and contextual priors had similarly large but independent impacts on sound detectability, with evidence that listeners tracked and used contextual priors for a variety of sound classes (pure tones, harmonic complexes, and vowels). Further analyses showed that listeners updated their contextual priors rapidly and optimally, given the changing acoustic frequency statistics inherent in the paradigm. A Bayesian Observer model accounted for both attentional and contextual adaptations found with listeners. These results bolster the interpretation of perception as Bayesian inference, and suggest that some effects attributed to selective attention may be a special case of contextual prior integration along a feature axis. |
Audience | Academic |
Author | Wolmetz, Michael Elhilali, Mounya |
AuthorAffiliation | 2 Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N Charles Street, Barton Hall, Rm 105, Baltimore, MD 21218, United States of America 1 Applied Neuroscience Section, Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD 20723, United States of America UNLV, UNITED STATES |
AuthorAffiliation_xml | – name: 2 Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N Charles Street, Barton Hall, Rm 105, Baltimore, MD 21218, United States of America – name: 1 Applied Neuroscience Section, Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD 20723, United States of America – name: UNLV, UNITED STATES |
Author_xml | – sequence: 1 givenname: Michael surname: Wolmetz fullname: Wolmetz, Michael organization: Applied Neuroscience Section, Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Rd, Laurel, MD 20723, United States of America – sequence: 2 givenname: Mounya surname: Elhilali fullname: Elhilali, Mounya organization: Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 N Charles Street, Barton Hall, Rm 105, Baltimore, MD 21218, United States of America |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26882228$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1098_rspb_2019_2001 crossref_primary_10_1121_1_4968783 crossref_primary_10_1186_s13636_023_00286_7 |
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Copyright | COPYRIGHT 2016 Public Library of Science 2016 Wolmetz, Elhilali. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2016 Wolmetz, Elhilali 2016 Wolmetz, Elhilali |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceived and designed the experiments: MW ME. Performed the experiments: MW ME. Analyzed the data: MW ME. Contributed reagents/materials/analysis tools: MW ME. Wrote the paper: MW ME. Competing Interests: The authors have declared that no competing interests exist. |
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SubjectTerms | Acoustic frequencies Adaptation Adolescent Adult Analysis Attention - physiology Auditory Perception Bayes Theorem Bayesian analysis Behavior Biology and Life Sciences Cues Environmental statistics Female Humans Male Models, Biological Noise Perception Physical Sciences Pitch Perception Probability Social Sciences Sound Statistical inference Statistics Time Factors Trends Visual task performance Vowels Young Adult |
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Title | Attentional and Contextual Priors in Sound Perception |
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