Evidence for early morphological decomposition: Combining masked priming with magnetoencephalography

Minna Lehtonen, Philip J. Monahan, David Poeppel

Research output: Contribution to journalArticle

Abstract

Are words stored as morphologically structured representations? If so, when during word recognition are morphological pieces accessed? Recent masked priming studies support models that assume early decomposition of (potentially) morphologically complex words. The electrophysiological evidence, however, is inconsistent. We combined masked morphological priming with magneto-encephalography (MEG), a technique particularly adept at indexing processes involved in lexical access. The latency of an MEG component peaking, on average, 220 msec post-onset of the target in left occipito-temporal brain regions was found to be sensitive to the morphological prime-target relationship under masked priming conditions in a visual lexical decision task. Shorter latencies for related than unrelated conditions were observed both for semantically transparent (cleaner-CLEAN) and opaque (corner-CORN) prime-target pairs, but not for prime-target pairs with only an orthographic relationship (brothel-BROTH). These effects are likely to reflect a prelexical level of processing where form-based representations of stems and affixes are represented and are in contrast to models positing no morphological structure in lexical representations. Moreover, we present data regarding the transitional probability from stem to affix in a post hoc comparison, which suggests that this factor may modulate early morphological decomposition, particularly for opaque words. The timing of a robust MEG component sensitive to the morphological relatedness of prime-target pairs can be used to further understand the neural substrates and the time course of lexical processing.

Original languageEnglish (US)
Pages (from-to)3366-3379
Number of pages14
JournalJournal of Cognitive Neuroscience
Volume23
Issue number11
DOIs
StatePublished - Nov 2011

ASJC Scopus subject areas

  • Cognitive Neuroscience

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