The flexible and interactive neural, computational and neurobiological mechanisms underpinning semantic cognition and its disorders.

支持语义认知及其疾病的灵活且交互式的神经、计算和神经生物学机制。

• 批准号: MR/R023883/1
• 负责人: Matthew Lambon Ralph
• 金额: $ 191.62万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FR023883%2F1
• 关键词: flexible; interactive; neural; computational; neurobiological

Semantic memory refers to the rich database of knowledge we have about the meanings of words, objects, people and all the stimuli present in our environment. We activate this information when we comprehend a word or recognise an object. We use the same knowledge for speech or non-verbal activities such as object use. The aim of communication, itself, is for meaning to be conveyed between people. It is evident, therefore, that semantic knowledge is crucial for many everyday activities both at work and at home. When this type of knowledge disintegrates or becomes inaccessible after brain damage, patients become significantly disabled in many aspects of their lives. Imagine, for example, being able to comprehend only a small proportion of the words in everyday conversation, a letter or newspaper; being stuck with significant word-finding problems; or being unable to understand everyday symbols or road signs. Sadly, these kinds of problems are a common feature of many types of brain disease. Semantic impairment is a characteristic of certain types of dementia, brain infections and after stroke or neurosurgery. In our last research programme, we developed the necessary methods and clinical links to undertake unique, detailed comparisons of different patient groups (semantic dementia, semantic aphasia, herpes simplex virus encephalitis, Alzheimer's disease, resection for temporal lobe epilepsy, and Wernicke's aphasia) and linked these patient studies directly with parallel explorations of the healthy semantic system. In particular, we discovered that there are two subsystems - one for coding the database of semantic information and a separate brain network for manipulating and shaping this information depending on the task requirements or context.The core aims of our continuing research programme, therefore, are (a) to investigate the nature and function of different key areas within each semantic brain network; (b) examine the flexible interaction between the networks when the system comes under pressure and the associated compensatory processes that are triggered by brain damage; and (c) we will begin to explore both the brain structures and brain chemicals that are involved in semantic function. These steps will be used to improve: detection of semantic deficits; differential diagnosis; clinical management; and evidence-based interventions. Our ultimate aim is to build up a complete picture and model of the network of brain regions that support semantic processing. We have pioneered a new type of mathematical model which mirrors brain regions and their connections, and after training, generates human semantic behaviours. When these models are damaged they can mimic the types of impairment found in different patient groups. We will use the new findings from the studies of patients and healthy participants to generate a model of semantic processing that includes the networks for both semantic knowledge and semantic manipulation. We will use this model to reproduce each patient group's pattern of performance. We will then be able to use this model not only to understand the nature of semantic problems across all these different patient groups but also to use the model to gain new insights about minimising these problems and for generating new interventions that could be used by speech therapists with these patient groups.

语义记忆指的是我们拥有的关于单词、物体、人和环境中所有刺激的含义的丰富知识数据库。当我们理解一个单词或识别一个物体时，我们就会激活这个信息。我们将同样的知识用于言语或非言语活动，如宾语的使用。交流的目的本身就是为了在人与人之间传达意义。因此，很明显，语义知识对于工作和家庭中的许多日常活动都是至关重要的。当这种类型的知识在脑损伤后分解或变得无法获取时，患者在生活的许多方面都会严重残疾。例如，想象一下，你只能理解日常对话、信件或报纸中的一小部分单词；遇到重大的单词查找问题；或者无法理解日常符号或路标。可悲的是，这些类型的问题是许多类型大脑疾病的共同特征。语义障碍是某些类型的痴呆症、脑感染以及中风或神经外科手术后的特征。在我们上一个研究计划中，我们开发了必要的方法和临床联系，对不同的患者组(语义性痴呆、语义性失语、单纯疱疹病毒性脑炎、阿尔茨海默病、颞叶癫痫切除术和韦尼克失语症)进行独特、详细的比较，并将这些患者研究与健康语义系统的平行探索直接联系起来。特别是，我们发现有两个子系统-一个用于对语义信息数据库进行编码，以及一个独立的大脑网络用于根据任务要求或上下文操纵和塑造这些信息。因此，我们持续研究计划的核心目标是(A)调查每个语义大脑网络中不同关键区域的性质和功能；(B)检查系统在压力下的网络之间的灵活相互作用以及由脑损伤触发的相关补偿过程；以及(C)我们将开始探索参与语义功能的大脑结构和脑化学物质。这些步骤将用于改进：检测语义缺陷；鉴别诊断；临床管理；以及循证干预。我们的最终目标是建立一个支持语义处理的大脑区域网络的完整图景和模型。我们首创了一种新型的数学模型，它反映了大脑区域及其联系，并在训练后产生人类的语义行为。当这些模型受损时，它们可以模拟在不同患者组中发现的受损类型。我们将使用来自患者和健康参与者的研究的新发现来生成一个语义处理模型，该模型包括语义知识和语义操作的网络。我们将使用这个模型来再现每个患者组的表现模式。然后，我们将不仅能够使用该模型来了解所有这些不同患者组的语义问题的性质，而且还可以使用该模型来获得关于将这些问题降至最低的新见解，并生成可供语言治疗师对这些患者组使用的新干预措施。

项目成果

Semantic-specific and domain-general mechanisms for integration and update of contextual information.

• DOI: 10.1002/hbm.26454
• 发表时间: 2023-12-01
• 期刊: HUMAN BRAIN MAPPING
• 影响因子: 4.8
• 作者: Branzi, Francesca M.;Ralph, Matthew A. Lambon
• 通讯作者: Ralph, Matthew A. Lambon

Revealing the neural networks that extract conceptual gestalts from continuously evolving or changing semantic contexts

揭示从不断发展或变化的语义上下文中提取概念格式塔的神经网络

• DOI: 10.1101/666370
• 发表时间: 2019
• 作者: Branzi F

The Left Angular Gyrus Is Causally Involved in Context-dependent Integration and Associative Encoding during Narrative Reading.

左角回在叙事阅读过程中因果性地参与上下文相关的整合和联想编码。

• DOI: 10.17863/cam.65384
• 发表时间: 2021
• 作者: Branzi F

Revealing the neural networks that extract conceptual gestalts from continuously evolving or changing semantic contexts.

• DOI: 10.1016/j.neuroimage.2020.116802
• 发表时间: 2020-10-15
• 期刊: NeuroImage
• 影响因子: 5.7
• 作者: Branzi FM;Humphreys GF;Hoffman P;Lambon Ralph MA
• 通讯作者: Lambon Ralph MA