Role of Semantic Paradigms for Optimization of Language Mapping in Clinical fMRI Studies

BACKGROUND AND PURPOSE: The optimal paradigm choice for language mapping in clinical fMRI studies is challenging due to the variability in activation among different paradigms, the contribution to activation of cognitive processes other than language, and the difficulties in monitoring patient performance. In this study, we compared language localization and lateralization between 2 commonly used clinical language paradigms and 3 newly designed dual-choice semantic paradigms to define a streamlined and adequate language-mapping protocol.

MATERIALS AND METHODS: Twelve healthy volunteers performed 5 language paradigms: Silent Word Generation, Sentence Completion, Visual Antonym Pair, Auditory Antonym Pair, and Noun-Verb Association. Group analysis was performed to assess statistically significant differences in fMRI percentage signal change and lateralization index among these paradigms in 5 ROIs: inferior frontal gyrus, superior frontal gyrus, middle frontal gyrus for expressive language activation, middle temporal gyrus, and superior temporal gyrus for receptive language activation.

RESULTS: In the expressive ROIs, Silent Word Generation was the most robust and best lateralizing paradigm (greater percentage signal change and lateralization index than semantic paradigms at P < .01 and P < .05 levels, respectively). In the receptive region of interest, Sentence Completion and Noun-Verb Association were the most robust activators (greater percentage signal change than other paradigms, P < .01). All except Auditory Antonym Pair were good lateralizing tasks (the lateralization index was significantly lower than other paradigms, P < .05).

CONCLUSIONS: The combination of Silent Word Generation and ≥1 visual semantic paradigm, such as Sentence Completion and Noun-Verb Association, is adequate to determine language localization and lateralization; Noun-Verb Association has the additional advantage of objective monitoring of patient performance.