Morphological representations are extrapolated from morpho-syntactic rules

Laura Gwilliams, Alec Marantz

Research output: Contribution to journalArticle

Abstract

The field of psycho- and neuro-linguistics has long-debated the decompositional model of visual word processing: Are written words processed via the visual forms of stem and affix morphemes, or as complex wholes? Although many have now settled upon a decompositional view, it is unclear what heuristic the brain uses to generate these visual morpheme-forms in the first place. Here we conduct a magneto-encephalography study to test two hypotheses for how this may be done: i) the brain encodes representations of the morphemes that follow the morpho-syntactic rules governing constituents: A stem morpheme will be represented if the word obeys the grammatical behaviour associated with its suffix; ii) the brain only encodes stem morphemes that occur with multiple suffixes or as words in isolation. Our results indicate that words with morpho-syntactic wellformedness as stem-suffix combinations are decomposed by the system, thus supporting the former hypothesis. This suggests that knowledge of morpho-syntactic rules can be used to form morphological representations of written words, in absence of independent experience with all of their constituent morphemes. Possible mechanisms supporting this computation are discussed.

Original languageEnglish (US)
Pages (from-to)77-87
Number of pages11
JournalNeuropsychologia
Volume114
DOIs
StatePublished - Jun 1 2018

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Brain
Word Processing
Linguistics
benzoylprop-ethyl
Heuristics

Keywords

  • Magnetoencephalography
  • Morphology
  • Neural representations
  • Visual word recognition

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Behavioral Neuroscience

Cite this

Morphological representations are extrapolated from morpho-syntactic rules. / Gwilliams, Laura; Marantz, Alec.

In: Neuropsychologia, Vol. 114, 01.06.2018, p. 77-87.

Research output: Contribution to journalArticle

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