Subword Representations Successfully Decode Brain Responses to Morphologically Complex Written Words

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openAccess

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Volume Title

A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2024-09-11

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Mcode

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Language

en

Pages

20

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Neurobiology of language, Volume 5, issue 4, pp. 844-863

Abstract

This study extends the idea of decoding word-evoked brain activations using a corpus-semantic vector space to multimorphemic words in the agglutinative Finnish language. The corpus-semantic models are trained on word segments, and decoding is carried out with word vectors that are composed of these segments. We tested several alternative vector-space models using different segmentations: no segmentation (whole word), linguistic morphemes, statistical morphemes, random segmentation, and character-level 1-, 2- and 3-grams, and paired them with recorded MEG responses to multimorphemic words in a visual word recognition task. For all variants, the decoding accuracy exceeded the standard word-label permutation-based significance thresholds at 350–500 ms after stimulus onset. However, the critical segment-label permutation test revealed that only those segmentations that were morphologically aware reached significance in the brain decoding task. The results suggest that both whole-word forms and morphemes are represented in the brain and show that neural decoding using corpus-semantic word representations derived from compositional subword segments is applicable also for multimorphemic word forms. This is especially relevant for languages with complex morphology, because a large proportion of word forms are rare and it can be difficult to find statistically reliable surface representations for them in any large corpus.

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Keywords

MEG, decoding, multimorphemic words, statistical morphemes, word2vec

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Citation

Hakala, T, Lindh-Knuutila, T, Hulten, A, Lehtonen, M & Salmelin, R 2024, ' Subword Representations Successfully Decode Brain Responses to Morphologically Complex Written Words ', Neurobiology of language, vol. 5, no. 4, pp. 844-863 . https://doi.org/10.1162/nol_a_00149