The shape of things to come in speech production: A functional magnetic resonance imaging study of visual form interference during lexical access
Number of pages
SourceJournal of Cognitive Neuroscience, 31, 6, (2019), pp. 913-921
Article / Letter to editor
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SW OZ DCC NRP
PI Group Neurobiology of Language
Journal of Cognitive Neuroscience
Subject110 000 Neurocognition of Language; Neuropsychology and rehabilitation psychology; Neuro- en revalidatiepsychologie
Studies of context effects in speech production have shown that semantic feature overlap produces interference in naming of categorically related objects. In neuroimaging studies, this semantic interference effect is consistently associated with involvement of left superior and middle temporal gyri. However, at least part of this effect has recently been shown to be attributable to visual form similarity, as categorically related objects typically share visual features. This fMRI study examined interference produced by visual form overlap in the absence of a category relation in a picture–word interference paradigm. Both visually similar and visually dissimilar distractors led to increased BOLD responses in the left inferior frontal gyrus compared with the congruent condition. Naming pictures in context with a distractor word denoting an object visually similar in form slowed RTs compared with unrelated words and was associated with reduced activity in the left posterior middle temporal gyrus. This area is reliably observed in lexical level processing during language production tasks. No significant differential activity was observed in areas typically engaged by early perceptual or conceptual feature level processing or in areas proposed to be engaged by postlexical language processes, suggesting that visual form interference does not arise from uncertainty or confusion during perceptual or conceptual identification or after lexical processing. We conclude that visual form interference has a lexical locus, consistent with the predictions of competitive lexical selection models.
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