When and where do you know what you know? fMRI-guided MEG and TMS studies of semantic cognition

这个项目调查了语义认知的生物学基础，它指的是我们(I)为我们所见、所听、所读、所闻、所味赋予意义的能力，以及(Ii)以适合任务或上下文的方式使用这些知识的能力。这巩固了我们与人交流、识别手势、面部表情等能力，以及以适当的方式使用物体的能力。由于它与日常推理和行为相关，因此大量的研究工作被用于描绘支持语义认知的大脑区域。以前的工作已经表明，语义表征和控制过程并不局限于单一的大脑区域，而是依赖于一组分布的、相互连接的区域。尽管取得了这一进展，但目前对这些分布的大脑区域之间的相互作用如何产生意义提取知之甚少。这个重要的问题是我们项目的重点。该项目利用了神经科学方法论中的最新进展，召集了一群在多种方法方面具有专业知识的研究人员，并建立在我们对语义表征和控制以及利用这些成分的行为方法的理解方面的最新进展。我们利用了三种互补的神经科学技术，每种技术都有独特的优势。时间敏感的脑磁图(MEG)记录将被用来捕捉激活在整个网络中的传播，这使我们能够推断大脑区域之间的通信模式。然后，我们将在特定的时间点和地点(通过经颅磁刺激；TMS)中断神经处理，以验证脑磁图结果。为了提高这两种分析的空间精度，我们还将从功能神经成像(FMRI)中获取高分辨率图像。在我们的建议的第一部分，我们使用MEG的时间信息来定义意义需要多长时间才能出现(例如，在一个单词被呈现后)，以及需要什么样的知识。脑磁图最近的研究结果表明，语义加工涉及到从感觉语义区到非运动性语义区的快速前向激活。当我们接触概念时，我们也激活了特定于感觉的信息(例如，关于概念看起来像什么以及它是如何移动的信息)；然而，我们目前几乎不知道这种特定于感觉的信息何时与非常规知识相结合，以激活整个概念。我们还使用TMS在特定时间点扰乱特定大脑区域的功能，以确定网络中的站点何时对语义认知做出必要贡献。我们研究的第二个目的是探索支撑语义控制的神经网络--即允许我们专注于知识的相关方面而忽略其他信息的机制。我们以前的发现表明，语义网络中的激活具有高度的灵活性和任务特异性，语义控制的不同方面可能涉及大脑不同区域的不同子集(例如，自上而下的紧张性影响与刺激驱动的自下而上控制)。有了MEG，我们可以通过描述活动在站点之间流动的顺序以及不同语义控制操作的激活时间/持续时间如何不同，来获得对这些控制过程的新见解。此外，我们可以第一次评估语义控制需求对存储语义知识的大脑区域的影响：在要求控制的情况下，非节律概念可能被更晚或更长时间激活，感觉特定区域可能被特定任务策略性地招募。除了提出语义认知的生物学模型外，我们的项目还具有更广泛的意义。它将展示MEG/fMRI/TMS联合研究的力量，以促进我们对认知功能的生物学基础的了解。在未来，它可以增加我们对语义认知障碍患者的理解、诊断和治疗。

This project investigates the biological basis of semantic cognition, which refers to our ability to (i) assign meaning to everything we see, hear, read, smell and taste, and (ii) use this knowledge in a way that is appropriate to the task or context. This underpins our ability to communicate with people, recognise signs, gestures, faces etc, and use objects in an appropriate way.Because of its relevance for everyday reasoning and behaviour, substantial research effort has been directed towards delineating the brain areas that support semantic cognition. Previous work has shown that semantic representation and control processes are not localised to a single brain area but rely on a set of distributed, interconnected regions. Despite this progress, little is currently known about how meaning retrieval emerges from interactions between these distributed brain areas. This important question is the focus of our project.The project takes advantage of recent advances within neuroscience methodology, draws together a group of investigators with expertise in multiple methods, and builds on recent advances in our understanding of semantic representation and control, as well as behavioural methods that tap these components. We make use of three complementary neuroscience techniques, each with unique strengths. Time-sensitive magnetoencephalography (MEG) recordings will be used to capture the spread of activation across the network, which allow us to infer patterns of communication between brain areas. We will then disrupt neural processing at specific time points and locations (via transcranial magnetic stimulation; TMS) to validate the MEG results. To increase spatial accuracy in both analyses, we will also acquire high-resolution images from functional neuroimaging (fMRI). In the first part of our proposal, we use temporal information from MEG to define how long it takes for meaning to emerge (e.g., after a word has been presented) and what kind of knowledge is necessary. Recent MEG findings suggest that semantic processing involves a rapid forward sweep of activation from sensory to amodal semantic areas. When we access concepts, we also activate sensory-specific information (e.g., information about what the concept looks like and how it moves); however, we currently have little knowledge of when this sensory-specific information is integrated with amodal knowledge, in order to activate the full concept. We also use TMS to disrupt the function of specific brain areas at particular points in time, to establish when sites within the network make a necessary contribution to semantic cognition. The second aim of our study is to explore the neural network underpinning semantic control - i.e., the mechanisms that allow us to focus on relevant aspects of knowledge and ignore other information. Our previous findings suggest that activation in the semantic network is highly flexible and task-specific and that different aspects of semantic control may involve different subsets of brain areas (e.g., tonic top-down influences vs. stimulus-driven bottom-up control). With MEG, we can gain new insights into these control processes by describing the order in which activity flows between sites and how the timing/duration of activation differs across semantic control manipulations. Moreover, we can assess, for the first time, the impact of semantic control demands on brain areas that store semantic knowledge: amodal concepts may be activated later or for longer in control-demanding situations, and sensory-specific regions may be strategically recruited by specific tasks.In addition to advancing biological models of semantic cognition, our project has broader implications. It will demonstrate the power of combined MEG/fMRI/TMS studies for advancing our knowledge of the biological basis of cognitive functions. In the future, it could augment our understanding, diagnosis and treatment of patients with disorders of semantic cognition.