4.4 Article

The neural correlates of statistical learning in a word segmentation task: An fMRI study

期刊

BRAIN AND LANGUAGE
卷 127, 期 1, 页码 46-54

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bandl.2012.11.007

关键词

fMRI; Statistical learning; Word segmentation; Artificial language; Sequence learning; Broca's area; LIFG

资金

  1. NSF
  2. NIH [HD037082, DC00167]
  3. ONR

向作者/读者索取更多资源

Functional magnetic resonance imaging (fMRI) was used to assess neural activation as participants learned to segment continuous streams of speech containing syllable sequences varying in their transitional probabilities. Speech streams were presented in four runs, each followed by a behavioral test to measure the extent of learning over time. Behavioral performance indicated that participants could discriminate statistically coherent sequences (words) from less coherent sequences (partwords). Individual rates of learning, defined as the difference in ratings for words and partwords, were used as predictors of neural activation to ask which brain areas showed activity associated with these measures. Results showed significant activity in the pars opercularis and pars triangularis regions of the left inferior frontal gyrus (LIFG). The relationship between these findings and prior work on the neural basis of statistical learning is discussed, and parallels to the frontal/subcortical network involved in other forms of implicit sequence learning are considered. (C) 2012 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据