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      Dynamics of hemispheric activity during metaphor comprehension: electrophysiological measures.

      Neuroimage
      Brain Mapping, Cerebral Cortex, physiology, Comprehension, Dominance, Cerebral, Electroencephalography, Evoked Potentials, Humans, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Judgment, Metaphor, Problem Solving, Reading, Semantics

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          Abstract

          Brain imaging studies have lead to conflicting findings regarding the involvement of the right hemisphere (RH) in metaphor comprehension. Some report more relative RH activation when processing figurative expressions but others have shown just the opposite. The inconsistencies might be a result of the low temporal resolution related to current brain imaging techniques which is insufficient to uncover patterns of hemispheric interaction that change over time. Event-related potentials and a source estimation technique (LORETA) were used to investigate such temporal interactions when processing two-word expressions denoting literal, conventional metaphoric, and novel metaphoric meaning, as well as unrelated word pairs. Participants performed a semantic judgment task in which they decided whether each word pair conveyed a meaningful expression. Our findings indicate that during comprehension of novel metaphors there are some stages of considerable RH involvement, mainly of the temporal and superior frontal areas. Although the processing mechanisms used for all types of expressions were similar and require both hemispheres, the relative contribution of each hemisphere at specific processing stages depended on stimulus type. Those stages correspond roughly to the N400 and LPC components which reflect semantic and contextual integration, respectively. The present study demonstrates that RH mechanisms are necessary, but not sufficient, for understanding metaphoric expressions. Both hemispheres work in concert in a complex dynamical pattern during literal and figurative language comprehension. Electrophysiological recordings together with source localization algorithms such as LORETA are a viable tool for measuring this type of activity patterns.

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