Department of Psychology, Harvard University, Cambridge, MA 02138, USA.
Neuroimage. 2011 Mar 15;55(2):705-12. doi: 10.1016/j.neuroimage.2010.12.040. Epub 2010 Dec 21.
Conventional analyses of functional magnetic resonance imaging (fMRI) data compare the brain's response to stimulus categories (e.g., pictures of faces, stories about beliefs) across participants. In order to infer that effects observed with the specific items (a particular set of pictures or stories) are generalizable to the entire population (all faces, or all stories about beliefs), it is necessary to perform an "item analysis." Item analyses may also reveal relationships between secondary (non-hypothesized) features of the items and functional activity. Here, we perform an item analysis on a set of stories commonly used for localizing brain regions putatively involved in Theory of Mind (ToM): right and left temporo-parietal junction (RTPJ/LTPJ), precuneus (PC), superior temporal sulcus (STS) and medial prefrontal cortex (MPFC). We address the following questions: Do brain regions that comprise the ToM network respond reliably across items (i.e. different stories about beliefs)? Do these brain regions demonstrate reliable preferences for items within the category? Can we predict any region's response to individual items, by using other features of the stimuli? We find that the ToM network responds reliably to stories about beliefs, generalizing across items as well as subjects. In addition, several regions in the ToM network have reliable preferences for individual items. Linguistic features of the stimuli did not predict these item preferences.
传统的功能磁共振成像 (fMRI) 数据分析比较了不同参与者对刺激类别（例如，人脸图片、信仰故事）的大脑反应。为了推断出使用特定项目（一组特定的图片或故事）观察到的效果可以推广到整个群体（所有面孔或所有关于信仰的故事），有必要进行“项目分析”。项目分析还可能揭示项目的次要（非假设）特征与功能活动之间的关系。在这里，我们对一组常用于定位被认为涉及心理理论 (ToM) 的大脑区域的故事进行了项目分析：右和左颞顶联合区 (RTPJ/LTPJ)、楔前叶 (PC)、颞上沟 (STS) 和内侧前额叶皮层 (MPFC)。我们解决了以下问题：构成 ToM 网络的大脑区域是否在不同项目（即不同的信仰故事）之间可靠地反应？这些大脑区域是否对类别内的项目有可靠的偏好？我们能否通过使用刺激的其他特征来预测任何区域对单个项目的反应？我们发现 ToM 网络对信仰故事有可靠的反应，不仅在项目之间，而且在受试者之间都有很好的反应。此外，ToM 网络中的几个区域对单个项目有可靠的偏好。刺激的语言特征并不能预测这些项目偏好。
