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Brain areas activated by action words: ERP and efMRI evidence (Poster)
NeuroImage 19(2) Suppl1, S57
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Objective: Processing action words referring to leg, arm and face movements (e.g. to kick, to pick, to lick) may activate different areas in the fronto-central cortex. Here, we use event-related potentials and event-related fMRI to compare time course and loci of cortical activation elicited by action words from different semantic categories. Methods and Material: Words referring to leg-, arm-, and face-actions were selected on the basis of a rating study and were matched for important psycholinguistic variables. Right-handed native speakers of English had to read single words presented at an SOA of 2.5s. The EEG was recorded from 12 subjects at 64 scalp electrodes. We applied a linear beam-former technique to obtain optimal estimates of the sources underlying the word-evoked potentials. These were then submitted to group statistical analysis. Event-related fMRI was recorded in a separate set of 6 subjects. Volumes consisting of 21 slices with matrix size 128*128 were acquired with a TR=3s. The General Linear Model based on a canonical HRF was used for analysis. Results: The ERP data suggest differential activation in fronto-central areas of the cortex at ~220ms after stimulus onset. These areas include primary motor, pre-motor and pre-frontal sites. Leg words activated central areas more strongly than face- or arm-related words, which corresponds to a central peak of metabolic activation in the inter-hemispheric cleft. Face-words produced more activity at left inferior-frontal sites probably anterior to Broca’s area, in both EEG and fMRI. Surprisingly, arm-words activated inferior-frontal areas in the right hemisphere, again both in EEG and fMRI. Conclusion: In this data set, source localization performed on EEG data and efMRI provided consistent clues about the cortical loci of action word processing. Consistent with earlier findings, fronto-central areas were differentially activated by face-, arm- and leg-words. Results support current neurobiological models of language emphasizing the role of distributed neuronal ensembles and mirror neurons in language processing.