The Cognitive Atlas: Developing an Interdisciplinary Knowledge Base Through Socia

描述(申请人提供)：这项拟议的研究旨在开发一个框架，以整合跨多个学科的关于大脑、思维和行为的知识，我们将其称为认知图谱。该框架扩展了已建立的神经解剖图谱开发的现有知识和软件架构，目前正在加州大学洛杉矶分校计算生物学中心(CCB)进行主要开发。理解精神疾病的综合方法需要在症状、认知、行为和生物学之间进行转换，但这些领域中每一个领域日益专业化的程度阻碍了跨学科的交流、洞察和发现。拟议的项目旨在通过开发一个系统来表示关于认知任务、认知过程和大脑结构的知识，以弥合这些差距。我们建议利用协作知识建设的新技术以及文献挖掘的自动化方法，开发一个灵活的基于网络的系统，支持巩固关于认知表型的分布式知识，并允许建立多层次的跨学科联系。这一系统将为专家参与其领域知识的形式化提供基础。由此产生的知识库将提供一个图集，允许将认知表型映射到从基因到复杂症状的多个其他层面的生物医学知识。公共卫生相关性：拟议的研究旨在通过使对精神疾病的跨学科研究能够发现治疗和预防方法，从而改善公共健康，否则用目前的方法是不可能的。它将扩展国家生物计算中心的工作，开发一个将心理功能与大脑系统联系起来的知识库。这个涵盖症状、认知过程、神经系统和分子遗传学的知识库还将为科学家、从业者和患者提供不断发展和最新的教育资源。该项目开发的系统还将通过提供协作知识构建的新工具，在更广泛的范围内增强生物医学知识和发现。

DESCRIPTION (provided by applicant): The proposed research aims to develop a framework for integrating knowledge about brain, mind, and behavior across multiple disciplines, which we refer to as a }cognitive atlas." This framework extends the existing knowledge and software architecture for neuroanatomic atlas development that has been established and is now under major development in the UCLA Center for Computational Biology (CCB). A comprehensive approach to understanding mental illness requires translation between syndrome, cognition, behavior, and biology, but increasing specialization within each of these domains hinders interdisciplinary communication, insights and discoveries. The proposed project aims to bridge these gaps by developing a system for the representation of knowledge about cognitive tasks, cognitive processes, and brain structure. We propose to harness new technologies for collaborative knowledge-building along with automated methods of literature mining, to develop a flexible web-based system that will support the consolidation of distributed knowledge about cognitive phenotypes and allow creation of multi-level interdisciplinary links. This system will provide the foundation for involvement of experts in the formalization of their domain knowledge. The resulting knowledge base will provide an }atlas} that allows the mapping of cognitive phenotypes onto biomedical knowledge at manifold other levels, from genes to complex syndromes. PUBLIC HEALTH RELEVANCE: The proposed research aims to improve public health by enabling interdisciplinary research on mental disease to result in discovery of treatments and preventions that would not otherwise be possible with current approaches. It will extend the work of the National Centers for Biological Computing to develop a knowledge base that relates psychological functions to brain systems. This knowledge base spanning syndromes, cognitive processes, neural systems, and molecular genetics will additionally serve as an evolving and up-to-date educational resource for scientists, practitioners, and patients. The system developed in this project will also enhance biomedical knowledge and discovery more broadly by providing new tools for collaborative knowledge building.