Convergent neural signatures of speech prediction error are a biological marker for spoken word recognition

Ediz Sohoglu (), Loes Beckers and Matthew H. Davis ()
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Ediz Sohoglu: University of Sussex
Loes Beckers: University of Cambridge
Matthew H. Davis: University of Cambridge

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract We use MEG and fMRI to determine how predictions are combined with speech input in superior temporal cortex. We compare neural responses to words in which first syllables strongly or weakly predict second syllables (e.g., “bingo”, “snigger” versus “tango”, “meagre”). We further compare neural responses to the same second syllables when predictions mismatch with input during pseudoword perception (e.g., “snigo” and “meago”). Neural representations of second syllables are suppressed by strong predictions when predictions match sensory input but show the opposite effect when predictions mismatch. Computational simulations show that this interaction is consistent with prediction error but not alternative (sharpened signal) computations. Neural signatures of prediction error are observed 200 ms after second syllable onset and in early auditory regions (bilateral Heschl’s gyrus and STG). These findings demonstrate prediction error computations during the identification of familiar spoken words and perception of unfamiliar pseudowords.

Date: 2024
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DOI: 10.1038/s41467-024-53782-5

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