McMillan Corey T, Clark Robin, Moore Peachie, Devita Christian, Grossman Murray
Department of Neurology, University of Pennsylvania Medical Center, Philadelphia, PA 19104-4283, USA.
Neuropsychologia. 2005;43(12):1729-37. doi: 10.1016/j.neuropsychologia.2005.02.012. Epub 2005 Apr 7.
Generalized quantifiers like "all cars" are semantically well understood, yet we know little about their neural representation. Our model of quantifier processing includes a numerosity device, operations that combine number elements and working memory. Semantic theory posits two types of quantifiers: first-order quantifiers identify a number state (e.g. "at least 3") and higher-order quantifiers additionally require maintaining a number state actively in working memory for comparison with another state (e.g. "less than half"). We used BOLD fMRI to test the hypothesis that all quantifiers recruit inferior parietal cortex associated with numerosity, while only higher-order quantifiers recruit prefrontal cortex associated with executive resources like working memory. Our findings showed that first-order and higher-order quantifiers both recruit right inferior parietal cortex, suggesting that a numerosity component contributes to quantifier comprehension. Moreover, only probes of higher-order quantifiers recruited right dorsolateral prefrontal cortex, suggesting involvement of executive resources like working memory. We also observed activation of thalamus and anterior cingulate that may be associated with selective attention. Our findings are consistent with a large-scale neural network centered in frontal and parietal cortex that supports comprehension of generalized quantifiers.
像“所有汽车”这样的广义量词在语义上很容易理解,但我们对它们的神经表征却知之甚少。我们的量词处理模型包括一个数量装置、组合数字元素的操作和工作记忆。语义理论提出了两种类型的量词:一阶量词确定一个数量状态(例如“至少3个”),而高阶量词还需要在工作记忆中积极维持一个数量状态以便与另一个状态进行比较(例如“少于一半”)。我们使用血氧水平依赖性功能磁共振成像(BOLD fMRI)来检验以下假设:所有量词都会激活与数量相关的顶下小叶,而只有高阶量词会激活与工作记忆等执行资源相关的前额叶皮层。我们的研究结果表明,一阶和高阶量词都会激活右侧顶下小叶,这表明数量成分有助于量词理解。此外,只有高阶量词的探测会激活右侧背外侧前额叶皮层,这表明工作记忆等执行资源参与其中。我们还观察到丘脑和前扣带回的激活,这可能与选择性注意有关。我们的研究结果与以额叶和顶叶皮层为中心的大规模神经网络一致,该网络支持对广义量词的理解。