Concept Representation in the Human Brain

人脑中的概念表征

• 批准号: 9764323
• 负责人: JEFFREY R BINDER
• 金额: $ 60.61万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9764323
• 关键词: Accidents; Address; Affective; Anatomy; Architecture; Behavior; Behavioral; Biological; Brain; Brain Injuries; Brain Mapping; Brain region; Categories; Cognition; Cognitive; Complex; Concept Formation; Correlation Studies; Data; Data Analyses; Dimensions; Emotional; Emotions; Environment; Episodic memory; Etiology; Event; Foundations; Functional Magnetic Resonance Imaging; Future; Human; Impairment; Inferior; Knowledge; Language; Lesion; Life; Link; Maps; Modality; Modeling; Modernization; Motion; Motor; Multivariate Analysis; Neurobiology; Neurologic; Neuropsychology; Ontology; Parietal; Parietal Lobe; Patients; Pattern; Process; Reporting; Retrieval; Role; Semantics; Sensory; Series; Social Interaction; Stream; Stroke; Support System; Symptoms; System; Techniques; Temporal Lobe; Testing; Time; Work; base; brain machine interface; brain surgery; design; experience; focal brain damage; high dimensionality; imaging study; information organization; lexical; multimodality; multisensory; neuromechanism; novel; rehabilitation strategy; relating to nervous system; repaired; risk minimization; social cognition; stroke patient

Concepts are the building blocks of human cognition, providing the basic content for language, episodic memory, social interaction, planning, and many other essential capabilities. Modern evidence suggests that human conceptual knowledge is represented in a widely distributed and hierarchically organized system involving much of the brain. Despite the central importance of this cognitive domain, there are large gaps in our understanding of very fundamental issues concerning how concepts are represented and organized at a systems level. This project addresses several of these gaps using a novel, high-dimensional, biologically based model of word meaning that captures the extent to which a concept is derived from various types of sensory, action, emotional, spatial, temporal, and cognitive experiences. We use this model in a series of information-based analyses of fMRI data and multivariate analyses of lesion-deficit correlations in patients with stroke. Our main hypothesis is that much of conceptual knowledge is represented in abstract form within content-specific experiential networks and multi-level convergences between these networks. Aim 1 is to clarify the detailed architecture of these hierarchical convergences, including intermediate crossmodal networks that we hypothesize arise in the brain due to proximity of neural processing streams and systematic covariation between experiential dimensions. Aim 2 is to test the hypothesis that event concepts (e.g., PARTY, ACCIDENT, SNEEZE) are primarily represented in inferior parietal convergence networks due to strong contributions from motion, action, spatial, and temporal experiences in the formation of these concepts, whereas object concepts have stronger representation in temporal lobe convergence networks that capture static multisensory experiences. Aim 3 is to clarify how concept categories are differentially represented and how this organization gives rise to category-related impairments in patients with focal brain damage. We hypothesize that neural representations of both concrete and abstract categories emerge from differently weighted mixtures of experiential information at high levels in the representational hierarchy. The high-dimensional, experiential representation of word meaning on which these hypotheses are based, combined with advanced fMRI techniques for mapping information content, makes it possible to address these basic knowledge gaps systematically for the first time. Combining state-of-the-art lesion-deficit correlation analyses with these healthy brain fMRI studies provides a powerful means of establishing causal links between fMRI activity patterns and successful concept retrieval. Understanding this large, complex, and particularly human brain system has far- reaching implications for understanding a range of neurological conditions that impair knowledge representation and retrieval, is likely to be transformative in the realm of functional mapping for brain surgery, and will be a prerequisite for developing rational and effective rehabilitation strategies for such patients, including future therapies involving modulatory stimulation, brain-machine interfaces, and biological repair.

概念是人类认知的基石，提供了语言的基本内容 记忆、社交、计划和许多其他基本能力。现代证据表明 人类的概念性知识表现在一个广泛分布、层次分明的系统中 涉及到大脑的大部分区域。尽管这一认知领域至关重要，但在我们的 理解非常基本的问题，涉及如何在 系统级别。该项目使用一种新颖的、高维的、生物学的 基于词义的模型，捕捉概念从各种类型派生出来的程度 感觉、动作、情感、空间、时间和认知体验。我们将此模型用于一系列 脑血管疾病患者功能磁共振成像数据的信息化分析及病变-缺失相关性的多因素分析 卒中。我们的主要假设是，许多概念性知识都是以抽象的形式在 内容特定的体验式网络以及这些网络之间的多层次融合。目标1是澄清 这些层次化融合的详细体系结构，包括中间跨模式网络 我们的假设产生于大脑，是由于神经处理流的接近和系统的协变 在经验维度之间。目标2是测试事件概念(例如，当事人，事故， 打喷嚏)主要表现在顶下汇合网络，这是由于 运动、动作、空间和时间经验在这些概念的形成中，而对象概念 在捕捉静态多感觉的颞叶会聚网络中具有更强的代表性 经历。目标3是阐明概念类别的不同表示方式，以及本组织如何 导致局灶性脑损伤患者出现与类别相关的损害。我们假设神经 具体类别和抽象类别的表示都来自不同权重的 在表征层次中的高级别的经验信息。高维度、体验式的 这些假设所基于的词义表示，与高级功能磁共振相结合 用于映射信息内容的技术使解决这些基本知识差距成为可能 这是第一次有系统地。将最先进的病变-缺陷相关性分析与这些健康的 脑功能磁共振研究提供了一种强有力的手段，可以建立功能磁共振活动模式和脑功能磁共振成像之间的因果联系 概念检索成功。了解这个庞大、复杂、尤其是人类的大脑系统- 对理解损害知识的一系列神经疾病的影响 表示和检索在脑外科的功能映射领域中很可能是变革性的， 并将是为这类患者制定合理有效的康复策略的先决条件， 包括未来涉及调制刺激、脑机接口和生物修复的治疗。