The neural basis of obligatory decomposition of suffixed words

Gwyneth Lewis, Olla Solomyak, Alec Marantz

Research output: Contribution to journalArticlepeer-review


Recent neurolinguistic studies present somewhat conflicting evidence concerning the role of the inferior temporal cortex (IT) in visual word recognition within the first 200 ms after presentation. On the one hand, fMRI studies of the Visual Word Form Area (VWFA) suggest that the IT might recover representations of the orthographic form of words. On the other hand, influential MEG studies of responses from the occipito-temporal regions around 150 ms post-stimulus onset indicate recognition of letters as opposed to symbols but not a sensitivity to statistical properties of letter strings associated with word form representations. Recent MEG experiments support the position that the IT does represent the visual word forms of morphemes and performs morphological decomposition modulated by the statistical relations between morphemes by 170 ms post presentation (at the M170 response). Responses to heteronyms show that the M170 does not make contact with the mental lexicon where word forms are connected to meanings. We report here an MEG study of pseudo-affixed words like brother, which masked priming studies have shown are decomposed in recognition. If the M170 response from IT does index obligatory morphological decomposition based on visual word forms but not lexical entries, we should find that the statistical relation between pseudo-stem and pseudo-suffix modulates the M170 for pseudo-affixed words, as for truly affixed words. The results of this experiment confirm this prediction. In addition, surface form frequency for these words also modulates the M170, providing some support for dual route recognition for words for which decomposition is a garden path.

Original languageEnglish (US)
Pages (from-to)118-27
Number of pages10
JournalBrain and Language
Issue number3
StatePublished - Sep 2011


  • Brain Mapping
  • Cerebral Cortex
  • Female
  • Humans
  • Magnetoencephalography
  • Male
  • Pattern Recognition, Visual
  • Reading
  • Signal Processing, Computer-Assisted
  • Young Adult


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