| dc.contributor.author | McPherson, Malinda J | |
| dc.contributor.author | McDermott, Josh H | |
| dc.date.accessioned | 2021-10-27T19:57:34Z | |
| dc.date.available | 2021-10-27T19:57:34Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/133997 | |
| dc.description.abstract | © 2020 National Academy of Sciences. All rights reserved. Perceptual systems have finite memory resources and must store incoming signals in compressed formats. To explore whether representations of a sound's pitch might derive from this need for compression, we compared discrimination of harmonic and inharmonic sounds across delays. In contrast to inharmonic spectra, harmonic spectra can be summarized, and thus compressed, using their fundamental frequency (f0). Participants heard two sounds and judged which was higher. Despite being comparable for sounds presented back-to-back, discrimination was better for harmonic than inharmonic stimuli when sounds were separated in time, implicating memory representations unique to harmonic sounds. Patterns of individual differences (correlations between thresholds in different conditions) indicated that listeners use different representations depending on the time delay between sounds, directly comparing the spectra of temporally adjacent sounds, but transitioning to comparing f0s across delays. The need to store sound in memory appears to determine reliance on f0-based pitch and may explain its importance in music, in which listeners must extract relationships between notes separated in time. | |
| dc.language.iso | en | |
| dc.publisher | Proceedings of the National Academy of Sciences | |
| dc.relation.isversionof | 10.1073/pnas.2008956117 | |
| dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | |
| dc.source | PNAS | |
| dc.title | Time-dependent discrimination advantages for harmonic sounds suggest efficient coding for memory | |
| dc.type | Article | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences | |
| dc.contributor.department | McGovern Institute for Brain Research at MIT | |
| dc.contributor.department | Center for Brains, Minds, and Machines | |
| dc.relation.journal | Proceedings of the National Academy of Sciences of the United States of America | |
| dc.eprint.version | Final published version | |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | |
| dc.date.updated | 2021-03-18T14:34:00Z | |
| dspace.orderedauthors | McPherson, MJ; McDermott, JH | |
| dspace.date.submission | 2021-03-18T14:34:02Z | |
| mit.journal.volume | 117 | |
| mit.journal.issue | 50 | |
| mit.license | PUBLISHER_POLICY | |
| mit.metadata.status | Authority Work and Publication Information Needed | |