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

对于任何概念，我们都知道它的特征和联系——例如，兔子是毛茸茸的，有长耳朵，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的理论框架（“分级约束”假设），该框架表明，灵活的语义认知出现在大规模网络的频谱中，这些网络支持更多的自动到受控的概念检索模式，这些网络沿着皮质表面以系统的方式组织。我们将研究这些网络的连接和激活如何根据特定语义处理任务的特征或要求而变化，以及这些网络组织的个体差异对语义处理的影响。

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.