| Efficient Coding and Statistically Optimal Weighting of Covariance among Acoustic Attributes in Novel Sounds. | |
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MedLine Citation:
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PMID: 22292057 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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To the extent that sensorineural systems are efficient, redundancy should be extracted to optimize transmission of information, but perceptual evidence for this has been limited. Stilp and colleagues recently reported efficient coding of robust correlation (r = .97) among complex acoustic attributes (attack/decay, spectral shape) in novel sounds. Discrimination of sounds orthogonal to the correlation was initially inferior but later comparable to that of sounds obeying the correlation. These effects were attenuated for less-correlated stimuli (r = .54) for reasons that are unclear. Here, statistical properties of correlation among acoustic attributes essential for perceptual organization are investigated. Overall, simple strength of the principal correlation is inadequate to predict listener performance. Initial superiority of discrimination for statistically consistent sound pairs was relatively insensitive to decreased physical acoustic/psychoacoustic range of evidence supporting the correlation, and to more frequent presentations of the same orthogonal test pairs. However, increased range supporting an orthogonal dimension has substantial effects upon perceptual organization. Connectionist simulations and Eigenvalues from closed-form calculations of principal components analysis (PCA) reveal that perceptual organization is near-optimally weighted to shared versus unshared covariance in experienced sound distributions. Implications of reduced perceptual dimensionality for speech perception and plausible neural substrates are discussed. |
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Authors:
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Christian E Stilp; Keith R Kluender |
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Publication Detail:
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Type: Journal Article Date: 2012-01-23 |
Journal Detail:
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Title: PloS one Volume: 7 ISSN: 1932-6203 ISO Abbreviation: PLoS ONE Publication Date: 2012 |
Date Detail:
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Created Date: 2012-01-31 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101285081 Medline TA: PLoS One Country: United States |
Other Details:
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Languages: eng Pagination: e30845 Citation Subset: IM |
Affiliation:
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Department of Psychology, University of Wisconsin - Madison, Madison, Wisconsin, United States of America. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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