Department of Brain and Cognitive Sciences, University of Rochester, Meliora Hall, Box 270268, Rochester, NY 14627, USA.
Brain Lang. 2013 Oct;127(1):46-54. doi: 10.1016/j.bandl.2012.11.007. Epub 2013 Jan 11.
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.
功能性磁共振成像（fMRI）用于评估参与者在学习分割包含音节序列的连续语音流时的神经激活，这些音节序列在其过渡概率上有所不同。语音流在四个运行中呈现，每个运行后都进行行为测试，以衡量随时间推移的学习程度。行为表现表明，参与者可以从统计上不连贯的序列（部分词）中区分出连贯的序列（单词）。学习的个体速度（定义为单词和部分词的评分差异）被用作神经激活的预测指标，以询问哪些大脑区域显示与这些测量相关的活动。结果显示左额下回（LIFG）的后额回和三角部区域有显著的活动。这些发现与统计学习神经基础的先前研究的关系进行了讨论，并考虑了与其他形式的内隐序列学习涉及的额/皮质下网络的相似性。
