Dynamic neural network reorganization associated with second language vocabulary acquisition: A multimodal imaging study

Chihiro Hosoda, Kanji Tanaka, Tadashi Nariai, Manabu Honda, Takashi Hanakawa*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

109 Citations (Scopus)

Abstract

It remains unsettled whether human language relies exclusively on innately privileged brain structure in the left hemisphere or is more flexibly shaped through experiences, which induce neuroplastic changes in potentially relevant neural circuits. Here we show that learning of second language (L2) vocabulary and its cessation can induce bidirectional changes in the mirror-reverse of the traditional language areas. A cross-sectional study identified that gray matter volume in the inferior frontal gyrus pars opercularis (IFGop) and connectivity of the IFGop with the caudate nucleus and the superior temporal gyrus/supramarginal (STG/SMG), predominantly in the right hemisphere, were positively correlated withL2 vocabulary competence.We then implemented acohort study involving 16 weeks of L2 training in university students. Brain structure before training did not predict the later gain in L2 ability. However, training intervention did increase IFGop volume and reorganization of white matter including the IFGop-caudate and IFGop-STG/SMG pathways in the right hemisphere. These "positive" plastic changes were correlated with the gain in L2 abilityin the trained group but were not observed in the control group. We propose that the right hemispheric network can be reorganized into language-related areas through use-dependent plasticity in young adults, reflecting a repertoire of flexible reorganization of the neural substrates responding to linguistic experiences.

Original languageEnglish
Pages (from-to)13663-13672
Number of pages10
JournalJournal of Neuroscience
Volume33
Issue number34
DOIs
Publication statusPublished - 2013 Aug 27
Externally publishedYes

ASJC Scopus subject areas

  • Neuroscience(all)

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