Investigation of neuronal substrates for language processing, using word priming

Chunlin Li, Jinglong Wu, Hirosi Kusahara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We investigated changes in the behavioral performance and brain activities associated with word priming in a Word Stem Completion (WSC) task in Japanese. In the behavioral results, we found obvious facilitatory effects in subject's performance. The percentage of correct answers in word non priming (P/N) condition was 94%, while the percentage of correct answers in word priming P/Y-condition was 100%. Averaged reaction time in word P/N- condition was 1501ms, while that of word P/N-condition was 978ms and 3106ms in non word P/Y-condition respectively. In the fMRI experiment, the same tasks were performed by the block-design experimental paradigm without any overt response in MRI scanner. As the fMRI results, we found the activations in the bilateral middle and inferior frontal gyrus with right hemispheric prevalence, the superior and inferior parietal gyrus, and the supplementary motor area. The prefrontal-parietal network observed in our study is consistent with the activated areas in word stem task in English. These results suggested that the facilitatory effects observed in WSC-test include implicit memory access and the induced attention after successful retrieval.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Pages152-157
Number of pages6
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, China
Duration: Aug 9 2009Aug 12 2009

Publication series

Name2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009

Other

Other2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
CountryChina
CityChangchun
Period8/9/098/12/09

Keywords

  • Human memory system
  • Word priming
  • fMRI

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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