Does signal reduction imply predictive coding in models of spoken word recognition?

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...

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Bibliographic Details
Published in:Psychonomic bulletin & review Vol. 28; no. 4; pp. 1381 - 1389
Main Authors: Luthra, Sahil, Li, Monica Y. C., You, Heejo, Brodbeck, Christian, Magnuson, James S.
Format: Journal Article
Language:English
Published: New York Springer US 01.08.2021
Springer Nature B.V
Subjects:
Behavioral Science and Psychology
Brief Report
Cognitive Psychology
Humans
Language
Medical imaging
Neurosciences
Psychology
Speech Perception
computational models
prediction
spoken word recognition
cognitive neuroscience
ISSN:1069-9384, 1531-5320, 1531-5320
Online Access:Get full text
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Summary: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.
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ISSN:1069-9384
1531-5320
1531-5320
DOI:10.3758/s13423-021-01924-x