Evidence map›Paper›PMID 38689188›Full record

ArticlePsychonomic bulletin & review2024

Neural representation of phonological wordform in temporal cortex.

David O Sorensen, Enes Avcu, Skyla Lynch, Seppo P Ahlfors, David W Gow

Abstract read
In one paragraph

Article in Psychonomic bulletin & review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

David O SorensenDivision of Medical Sciences, Harvard Medical School, Cambridge, MA, USA.
Enes AvcuDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Skyla LynchDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Seppo P AhlforsAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
David W GowDivision of Medical Sciences, Harvard Medical School, Cambridge, MA, USA. dgow@mgh.harvard.edu.

Funding

Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Susie Yi Huang · 2020 to 2026
$10.9M
Identifying the neural structures and dynamics that regulate phonological structureR01DC015455 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHLFORS, SEPPO PENTTI, GOW, DAVID W · 2017 to 2021
$2.7M
TRIUX neo MEG system UpgradeS10OD030469 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI AHLFORS, SEPPO PENTTI · 2021 to 2021
$2.0M
NIBIB NIH HHS P41 EB030006NIDCD NIH HHS R01 DC015455NIDCD NIH HHS R01DC015455NIH HHS S10 OD030469
6 · The paper itself

Abstract

While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words activate a variety of representations (e.g., segmental, semantic, articulatory) in addition to form-based representations. We addressed these challenges through a novel integrated neural decoding and effective connectivity design using region of interest (ROI)-based, source-reconstructed magnetoencephalography/electroencephalography (MEG/EEG) data collected during a lexical decision task. To identify wordform representations, we trained classifiers on words and nonwords from different phonological neighborhoods and then tested the classifiers' ability to discriminate between untrained target words that overlapped phonologically with the trained items. Training with word neighbors supported significantly better decoding than training with nonword neighbors in the period immediately following target presentation. Decoding regions included mostly right hemisphere regions in the posterior temporal lobe implicated in phonetic and lexical representation. Additionally, neighbors that aligned with target word beginnings (critical for word recognition) supported decoding, but equivalent phonological overlap with word codas did not, suggesting lexical mediation. Effective connectivity analyses showed a rich pattern of interaction between ROIs that support decoding based on training with lexical neighbors, especially driven by right posterior middle temporal gyrus. Collectively, these results evidence functional representation of wordforms in temporal lobes isolated from phonemic or semantic representations.

Indexed as

ElectroencephalographyMagnetoencephalographySpeech PerceptionTemporal LobeAdultFemaleHumansMalePhoneticsPsycholinguisticsYoung AdultNeural decodingNeural representationPhonologyRecognitionSpoken word

Identifiers

PMID38689188
PMCPMC11680662

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.