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人类颞上回中言语加工和产生的区域异质性。

Regional heterogeneity in the processing and the production of speech in the human planum temporale.

机构信息

Center for Mind & Brain Sciences (CIMeC), The University of Trento, Italy.

出版信息

Cortex. 2013 Jan;49(1):143-57. doi: 10.1016/j.cortex.2011.09.004. Epub 2011 Sep 29.

DOI:10.1016/j.cortex.2011.09.004
PMID:22019203
Abstract

INTRODUCTION

The role of the left planum temporale (PT) in auditory language processing has been a central theme in cognitive neuroscience since the first descriptions of its leftward neuroanatomical asymmetry. While it is clear that PT contributes to auditory language processing there is still some uncertainty about its role in spoken language production.

METHODS

Here we examine activation patterns of the PT for speech production, speech perception and single word reading to address potential hemispheric and regional functional specialization in the human PT. To this aim, we manually segmented the left and right PT in three non-overlapping regions (medial, lateral and caudal PT) and examined, in two complementary experiments, the contribution of exogenous and endogenous auditory input on PT activation under different speech processing and production conditions.

RESULTS

Our results demonstrate that different speech tasks are associated with different regional functional activation patterns of the medial, lateral and caudal PT. These patterns are similar across hemispheres, suggesting bilateral processing of the auditory signal for speech at the level of PT.

CONCLUSIONS

Results of the present studies stress the importance of considering the anatomical complexity of the PT in interpreting fMRI data.

摘要

简介

自左颞平面(PT)的左侧神经解剖学不对称首次被描述以来,其在听觉语言处理中的作用一直是认知神经科学的一个核心主题。虽然很明显 PT 有助于听觉语言处理,但对于其在口语产生中的作用仍存在一些不确定性。

方法

在这里,我们检查了 PT 在言语产生、言语感知和单个单词阅读中的激活模式,以解决人类 PT 中潜在的半球和区域功能专业化问题。为此,我们在三个不重叠的区域(内侧、外侧和尾部 PT)中手动分割左、右 PT,并在两个互补的实验中,检查在外源性和内源性听觉输入下,不同言语处理和产生条件下 PT 激活的情况。

结果

我们的结果表明,不同的言语任务与内侧、外侧和尾部 PT 的不同区域功能激活模式相关。这些模式在半球间相似,表明听觉信号在 PT 水平上对言语进行双侧处理。

结论

本研究的结果强调了在解释 fMRI 数据时考虑 PT 的解剖复杂性的重要性。

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