Department of Psychology, University of York, United Kingdom.
J Cogn Neurosci. 2012 Jan;24(1):133-47. doi: 10.1162/jocn_a_00123. Epub 2011 Aug 23.
To understand the meanings of words and objects, we need to have knowledge about these items themselves plus executive mechanisms that compute and manipulate semantic information in a task-appropriate way. The neural basis for semantic control remains controversial. Neuroimaging studies have focused on the role of the left inferior frontal gyrus (LIFG), whereas neuropsychological research suggests that damage to a widely distributed network elicits impairments of semantic control. There is also debate about the relationship between semantic and executive control more widely. We used TMS in healthy human volunteers to create "virtual lesions" in structures typically damaged in patients with semantic control deficits: LIFG, left posterior middle temporal gyrus (pMTG), and intraparietal sulcus (IPS). The influence of TMS on tasks varying in semantic and nonsemantic control demands was examined for each region within this hypothesized network to gain insights into (i) their functional specialization (i.e., involvement in semantic representation, controlled retrieval, or selection) and (ii) their domain dependence (i.e., semantic or cognitive control). The results revealed that LIFG and pMTG jointly support both the controlled retrieval and selection of semantic knowledge. IPS specifically participates in semantic selection and responds to manipulations of nonsemantic control demands. These observations are consistent with a large-scale semantic control network, as predicted by lesion data, that draws on semantic-specific (LIFG and pMTG) and domain-independent executive components (IPS).
为了理解单词和物体的含义,我们需要具备关于这些物品本身的知识,还需要具备以任务适当的方式计算和操作语义信息的执行机制。语义控制的神经基础仍然存在争议。神经影像学研究集中于左侧下额叶(LIFG)的作用,而神经心理学研究表明,广泛分布的网络损伤会导致语义控制受损。关于语义和执行控制之间的关系也存在争议。我们使用 TMS 在健康的人类志愿者中创建了“虚拟损伤”,这些损伤通常发生在语义控制缺陷患者的结构中:左侧下额叶(LIFG)、左侧后颞中回(pMTG)和顶内沟(IPS)。在该假设网络中的每个区域内检查了 TMS 对语义和非语义控制需求变化的任务的影响,以深入了解(i)它们的功能专业化(即参与语义表示、受控检索或选择)和(ii)它们的领域依赖性(即语义或认知控制)。结果表明,LIFG 和 pMTG 共同支持语义知识的受控检索和选择。IPS 专门参与语义选择,并响应非语义控制需求的操作。这些观察结果与基于损伤数据预测的大型语义控制网络一致,该网络依赖于语义特异性(LIFG 和 pMTG)和领域独立的执行组件(IPS)。