five

Data for "Situation Model Manipulations Differently Engage Semantic and Default Mode Networks During Narrative Comprehension"

收藏
DataCite Commons2026-01-29 更新2026-05-07 收录
下载链接:
https://datashare.ed.ac.uk/handle/10283/9153
下载链接
链接失效反馈
官方服务:
资源简介:
Narrative comprehension involves creating a mental representation of the events of the story: a "situation model". Maintaining a situation model is thought to be supported by the Default Mode Network (DMN), but recent work suggests that the semantic system, and specifically the ventrolateral anterior temporal lobe (ATL), may play a role in reflecting on and restructuring the situation model via internally-driven or endogenous semantic processing. The present study used fMRI to investigate how ATL and DMN brain regions respond under varying exogenous, or input-driven, and endogenous processing demands when reading social and non-social stories. We studied neural responses to three types of situation model manipulation: 1) add - incorporating new information into the situation model, 2) use - using the information in the situation model to support comprehension of narrative language input, and 3) reconfigure - restructuring the situation model. Relative to add, use and reconfigure manipulations tended to elicit greater activation in regions of the DMN, including the dorsomedial prefrontal cortex, posterior cingulate cortex and precuneus, as well as the bilateral superior, middle and inferior ATL. Relative to non-social stories, add and use manipulations in social stories engaged the left anterior middle and superior temporal gyri and inferior parietal lobule (IPL), whereas reconfigure manipulations engaged the right superior, middle and inferior frontal gyri and IPL. The present results inform a developing framework for coordination between the ATL and DMN during narrative comprehension.
提供机构:
University of Edinburgh. School of Philosophy, Psychology and Language Sciences
创建时间:
2026-01-29
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作