Identifying bilingual semantic neural representations across languages

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• 作者：Augusto Buchweitz^a ; ^d ; ^{abuchweitz@gmail.com} ; Svetlana V. Shinkareva^b ; Robert A. Mason^a ; Tom M. Mitchell^c ; Marcel Adam Just^a
• 关键词：fMRI ; Bilingualism ; Pattern-based classification
• 刊名：Brain and Language
• 出版年：2012
• 期刊代码：121_0093934x
• 类别：cp
• 出版时间：March, 2012
• 卷：120
• 期：3
• 页码：282-289
• 文件大小：601 K

摘要

The goal of the study was to identify the neural representation of a noun鈥檚 meaning in one language based on the neural representation of that same noun in another language. Machine learning methods were used to train classifiers to identify which individual noun bilingual participants were thinking about in one language based solely on their brain activation in the other language. The study shows reliable (p < .05) pattern-based classification accuracies for the classification of brain activity for nouns across languages. It also shows that the stable voxels used to classify the brain activation were located in areas associated with encoding information about semantic dimensions of the words in the study. The identification of the semantic trace of individual nouns from the pattern of cortical activity demonstrates the existence of a multi-voxel pattern of activation across the cortex for a single noun common to both languages in bilinguals.