Medical Research Council, Cognition and Brain Sciences Unit, Cambridge, United Kingdom.
Hum Brain Mapp. 2009 Dec;30(12):3837-50. doi: 10.1002/hbm.20811.
Here, we ask whether frontotemporal cortex is functionally dissociated into distributed lexical and category-specific semantic networks. To this end, fMRI activation patterns elicited during the processing of words from different semantic categories were categorized using k-means cluster algorithms. Results showed a distributed pattern of inferiorfrontal, superiortemporal, and fusiform activation shared by different word categories. This shared activation contrasted with patterns of category-specific semantic activation in widely distributed neural systems. Clustering revealed congruent functional specificity of focal area activations in frontal and temporal cortex; thus suggesting a correspondence between functional partitionings of frontocentral mirror neuron systems and those of inferiortemporal lexical and semantic circuits. Action words related to the face, arms, and legs specifically activated the motor system in a somatotopic manner, whereas form-related words activated prefrontal areas. Similar functional specificity was evident in temporal cortex, where a different semantic topography emerged for form- and action-related words. Results were replicated in a separate data set, therefore recommending fMRI cluster analysis as a reliable method for scrutinizing the brain basis of lexical, semantic, and conceptual systems in humans. As focal modules do not explain the distributed character of functionally specific clusters and their distinct topographies are at variance with general distributed processing accounts, the functionally-homogenous distributed clusters specific to semantic types are best explained by specifically-distributed cortical circuits which, similar to Hebbian cell assemblies, represent functional units with specific roles in cognitive processing, especially in lexical and semantic access and memory.
在这里,我们探讨额颞叶皮层在功能上是否分为分布的词汇和类别特定的语义网络。为此,我们使用 k-均值聚类算法对不同语义类别单词的处理过程中诱发的 fMRI 激活模式进行分类。结果显示,不同单词类别之间存在额下回、颞上回和梭状回激活的分布式模式。这种共享激活与广泛分布的神经系统中特定于类别的语义激活模式形成对比。聚类揭示了额颞叶皮层中焦点区域激活的功能特异性一致;因此,提示额皮质镜像神经元系统的功能分区与下颞叶词汇和语义回路的功能分区之间存在对应关系。与面部、手臂和腿部相关的动作词以躯体定位方式特异性地激活运动系统,而与形状相关的词则激活前额叶区域。颞叶中也存在类似的功能特异性,其中形式和动作相关的词出现了不同的语义拓扑。在另一个数据集的重复研究中,推荐 fMRI 聚类分析作为一种可靠的方法,用于研究人类词汇、语义和概念系统的大脑基础。由于焦点模块不能解释功能特异性聚类的分布式特征,并且它们的独特拓扑与一般分布式处理解释不一致,因此特定于语义类型的功能同质分布式聚类最好用特定分布的皮质回路来解释,类似于赫布细胞集合,代表认知处理中具有特定作用的功能单元,特别是在词汇和语义访问和记忆中。