dc.contributor.author | Luthra, Sahil | |
dc.contributor.author | Li, Monica Y. C. | |
dc.contributor.author | You, Heejo | |
dc.contributor.author | Brodbeck, Christian | |
dc.contributor.author | Magnuson, James S. | |
dc.date.accessioned | 2022-01-26T12:41:34Z | |
dc.date.available | 2022-01-26T12:41:34Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Luthra, S., Li, M.Y.C., You, H. et al. Does signal reduction imply predictive coding in models of spoken word recognition?. Psychon Bull Rev 28, 1381–1389 (2021). https://doi.org/10.3758/s13423-021-01924-x | es_ES |
dc.identifier.issn | 1069-9384 | |
dc.identifier.uri | http://hdl.handle.net/10810/55169 | |
dc.description | Published online: 14 April 2021 | es_ES |
dc.description.abstract | Pervasive behavioral and neural evidence for predictive processing has led to claims that language processing depends upon
predictive coding. Formally, predictive coding is a computational mechanism where only deviations from top-down expectations
are passed between levels of representation. In many cognitive neuroscience studies, a reduction of signal for expected inputs is
taken as being diagnostic of predictive coding. In the present work, we show that despite not explicitly implementing prediction,
the TRACE model of speech perception exhibits this putative hallmark of predictive coding, with reductions in total lexical
activation, total lexical feedback, and total phoneme activation when the input conforms to expectations. These findings may
indicate that interactive activation is functionally equivalent or approximant to predictive coding or that caution is warranted in
interpreting neural signal reduction as diagnostic of predictive coding. | es_ES |
dc.description.sponsorship | This researchwas supported by NSF 1754284, NSF IGERT
1144399, and NSF NRT 1747486 (PI: J.S.M.). This research was also
supported in part by the Basque Government through the BERC 2018-
2021program, and by the Agencia Estatal de Investigación through
BCBL Severo Ochoa excellenceaccreditation SEV-2015-0490. S.L.
was supported by an NSF Graduate Research Fellowship. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Psychonomic Bulletin & Review | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/SEV-2015-0490 | es_ES |
dc.relation | info:eu-repo/grantAgreement/BasqueGovernment/BERC2018-2021 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | prediction | es_ES |
dc.subject | spoken word recognition | es_ES |
dc.subject | computational models | es_ES |
dc.subject | cognitive neuroscience | es_ES |
dc.title | Does signal reduction imply predictive coding in models of spoken word recognition? | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | # The Author(s) 2021 | es_ES |
dc.relation.publisherversion | https://www.springer.com/journal/13423 | es_ES |
dc.identifier.doi | 10.3758/s13423-021-01924-x | |