MODSEM. Graded network activation and connectivity during semantic processing depending on modality

调制解调器。

• 批准号: EP/Y014367/1
• 负责人: Beth Jefferies
• 金额: $ 23.84万
• 依托单位: University of York
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY014367%2F1
• 关键词: MODSEM.; Graded; network; activation; connectivity

For any concept, we have knowledge about its characteristics and associations - for example, a rabbit is furry, has long ears and eats carrots. However, specific features of concepts are relevant in different situations, so how do we flexibly retrieve this information in an adaptive way tailored to our current circumstances? This project will test and extend a novel theoretical framework (the "graded constraints" hypothesis) which suggests that flexible semantic cognition emerges from a spectrum of large-scale networks that support more automatic to controlled patterns of conceptual retrieval, with these networks organised in a systematic fashion along the cortical surface. We will investigate how connectivity and activation along these networks varies depending on the characteristics or demands of the specific semantic processing task, and what consequences do individual differences in organisation of these networks have on semantic processing.

对于任何概念，我们都了解其特征和关联 - 例如，兔子毛茸茸的，耳朵很长，吃胡萝卜。然而，概念的特定特征在不同的情况下是相关的，那么我们如何以适合我们当前情况的自适应方式灵活地检索这些信息呢？该项目将测试和扩展一个新颖的理论框架（“分级约束”假设），该框架表明灵活的语义认知来自一系列大规模网络，这些网络支持更自动的受控概念检索模式，这些网络沿着皮质表面以系统的方式组织起来。我们将研究这些网络的连接性和激活如何根据特定语义处理任务的特征或需求而变化，以及这些网络组织的个体差异对语义处理产生什么影响。