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

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• 作者：Elisabeth A. Karuza ; Elissa L. Newport ; Richard N. Aslin ; Sarah J. Starling ; Madalina E. Tivarus ; Daphne Bavelier
• 关键词：fMRI ; Statistical learning ; Word segmentation ; Artificial language ; Sequence learning ; Broca&rsquo ; s area ; LIFG
• 刊名：Brain and Language
• 出版年：2013
• 出版时间：October, 2013
• 年：2013
• 卷：127
• 期：1
• 页码：46-54
• 全文大小：878 K

文摘

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.