Neural ElectroMagnetic Ontologies: ERP Knowledge Representation & Integration

神经电磁本体：ERP 知识表示

• 批准号: 8269994
• 负责人: Dejing Dou
• 金额: $ 48.71万
• 依托单位: UNIVERSITY OF OREGON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-05-01 至 2014-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8269994
• 关键词: Address; Area; Auditory; Automatic Data Processing; Brain; Brain imaging; Brodmann' s area; Calibration; Classification; Clinical; Clinical Research; Code; Cognitive; Collaborations; Communities; Comprehension; Computer software; Data; Data Analyses; Data Provenance; Data Set; Data Storage and Retrieval; Databases; Development; Electromagnetics; Environment; Equipment; Evaluation; Event-Related Potentials; Generations; Goals; Head; Health; Human; Internet; Knowledge; Label; Laboratories; Laboratory Research; Language; Lead; Location; Logic; Maps; Measures; Meta-Analysis; Metadata; Methods; Modeling; Nature; Neuropsychology; Neurosciences; Neurosciences Research; Online Systems; Ontology; Pattern; Procedures; Process; Reading; Research; Research Methodology; Research Personnel; Resolution; Resource Sharing; Rest; Scalp structure; Scanning; Semantics; Series; Simulate; Site; Solutions; Source; Stream; Surface; System; Techniques; Technology; Testing; To specify; Translations; Visual; Work; base; data acquisition; data integration; data management; data mining; data sharing; density; design; encephalography; evaluation/testing; information organization; interdisciplinary approach; interest; member; neurodevelopment; neuroinformatics; relating to nervous system; relational database; research study; sensor; spatiotemporal; success; task analysis; tool; tool development; web-accessible

Description (provided by applicant): Research in the design and implementation of "Neural ElectroMagnetic Ontologies" (NEMO) will address a critical need for tools to support representation, storage, and sharing of brain electromagnetic data. Electro- encephalography (EEG) and event-related potentials (ERP) are venerable techniques for cognitive and clinical research on human brain function. To realize their full potential, however, it will be necessary to address some long-standing challenges in comparing results across experiments and research laboratories. NEMO will address this need by providing ERP ontologies that can be used for meta-analysis of patterns across experiment contexts and research labs. Given the widespread use of EEG and ERP methods, and their clinical as well as research applications, development of such a system is both timely and significant. System design and implementation will rest on six specific aims. The first goal is to develop rigorous procedures for classification and labeling of electrophysiological patterns (event-related potentials, or ERPs) (Aim 1). The methods and tools that are developed initially for classification and labeling of surface (sensor- level) data will then be extended to support classification of data in source (anatomical) space (Aim 2). Next, we will represent the concepts that define ERP patterns as formal logics, or "ontologies," and will use those concepts to describe the ERP patterns. Relational databases will be modeled based on the ontologies to support high-level questions about the nature of ERP patterns and the relationships between patterns that are associated with different lab, experiment, and analysis contexts (Aim 3). The application domain for our project is reading and language. We have established a consortium of experts in this area who will contribute EEG and ERP data from experimental studies and will collaborate with us on the design and testing, and evaluation of the tools developed for this project. The practical scientific aim will be to conduct meta-analyses of ERP patterns in reading and language. In addition to re-analyses of existing cross-lab data, new experiment paradigms (adapted from the fBIRN project) will be carried out across research sites to calibrate data acquisition and preprocessing methods, and to test the robustness of patterns across different experiment contexts (Aim 4). Initially, we will develop a different ontology for each representational space (e.g., sensor and source space) and each analysis method. Then, we will capture the semantic mappings between different sets of patterns (different ontologies) using data mining (Aim 5). To support this work, we will develop an integrated tool environment for storage and management of EEG and ERP data and meta-data, measure generation and labeling, ontology development, and meta-analysis. This environment will be web-accessible so that partners will have shared access to the project data, analysis tools, ontologies, and meta-analysis results (Aim 6). At the end of this project, the ontologies, annotated database, tools, and technologies will be made available to the larger research community. PUBLIC HEALTH RELEVANCE The practical goal for the NEMO project is to build an ontology database to support data sharing and meta- analysis of EEG and ERP results. The ability to describe brain electrophysiological patterns from different research laboratories and different experiment contexts within a common framework will have immediate benefits for the neuroscience community, as well as long-term benefits for neuroscience research and for scientific areas with similar requirements for robust data representation and integration, and data and resources sharing.

描述（由申请人提供）：“神经电磁本体”（NEMO）的设计和实施研究将解决对支持脑电磁数据表示、存储和共享的工具的迫切需求。脑电图（EEG）和事件相关电位（ERP）是用于人脑功能认知和临床研究的古老技术。然而，为了充分发挥其潜力，有必要解决比较实验和研究实验室结果方面长期存在的一些挑战。 NEMO 将通过提供可用于跨实验环境和研究实验室的模式元分析的 ERP 本体来满足这一需求。鉴于 EEG 和 ERP 方法的广泛使用及其临床和研究应用，开发这样的系统既及时又有意义。系统设计和实施将基于六个具体目标。第一个目标是制定严格的电生理模式（事件相关电位或 ERP）分类和标记程序（目标 1）。最初为表面（传感器级）数据分类和标记而开发的方法和工具将被扩展以支持源（解剖）空间中的数据分类（目标 2）。接下来，我们将把定义 ERP 模式的概念表示为形式逻辑或“本体”，并使用这些概念来描述 ERP 模式。关系数据库将基于本体进行建模，以支持有关 ERP 模式的性质以及与不同实验室、实验和分析环境相关的模式之间的关系的高级问题（目标 3）。我们项目的应用领域是阅读和语言。我们已经建立了该领域的专家联盟，他们将提供实验研究中的脑电图和 ERP 数据，并将与我们合作设计、测试以及评估为此项目开发的工具。实际的科学目标是对阅读和语言的 ERP 模式进行荟萃分析。除了重新分析现有的跨实验室数据外，还将在各个研究地点实施新的实验范式（改编自 fBIRN 项目），以校准数据采集和预处理方法，并测试不同实验背景下模式的稳健性（目标 4）。最初，我们将为每个表示空间（例如传感器和源空间）和每种分析方法开发不同的本体。然后，我们将使用数据挖掘捕获不同模式集（不同本体）之间的语义映射（目标 5）。为了支持这项工作，我们将开发一个集成工具环境，用于存储和管理 EEG 和 ERP 数据及元数据、测量生成和标签、本体开发和元分析。该环境将可通过网络访问，以便合作伙伴可以共享项目数据、分析工具、本体和元分析结果（目标 6）。在该项目结束时，本体、带注释的数据库、工具和技术将提供给更大的研究社区。公共卫生相关性 NEMO 项目的实际目标是建立一个本体数据库，以支持 EEG 和 ERP 结果的数据共享和元分析。在一个共同框架内描述来自不同研究实验室和不同实验背景的大脑电生理模式的能力将为神经科学界带来直接好处，也为神经科学研究和对稳健数据表示和集成以及数据和资源共享有类似要求的科学领域带来长期好处。

项目成果

Using ontology databases for scalable query answering, inconsistency detection, and data integration.

• DOI: 10.1007/s10844-010-0133-4
• 发表时间: 2011-10
• 期刊: JOURNAL OF INTELLIGENT INFORMATION SYSTEMS
• 影响因子: 3.4
• 作者: LePendu, Paea;Dou, Dejing
• 通讯作者: Dou, Dejing

Ontology Database: A New Method for Semantic Modeling and an Application to Brainwave Data

• DOI: 10.1007/978-3-540-69497-7_21
• 发表时间: 2008-07
• 作者: P. LePendu;D. Dou;G. Frishkoff;Jiawei Rong

Sharing and Integration of Cognitive Neuroscience Data: Metric and Pattern Matching across Heterogeneous ERP Datasets.

认知神经科学数据的共享和集成：跨异构 ERP 数据集的指标和模式匹配。

• DOI: 10.1016/j.neucom.2012.01.028
• 发表时间: 2012
• 期刊: Neurocomputing
• 影响因子: 6
• 作者: Liu,Haishan;Frishkoff,Gwen;Frank,Robert;Dou,Dejing
• 通讯作者: Dou,Dejing

Minimal Information for Neural Electromagnetic Ontologies (MINEMO): A standards-compliant method for analysis and integration of event-related potentials (ERP) data.

• DOI: 10.4056/sigs.2025347
• 发表时间: 2011-11-30
• 期刊: Standards in genomic sciences
• 作者: Frishkoff G;Sydes J;Mueller K;Frank R;Curran T;Connolly J;Kilborn K;Molfese D;Perfetti C;Malony A
• 通讯作者: Malony A

Breaking the Deadlock: Simultaneously Discovering Attribute Matching and Cluster Matching with Multi-Objective Metaheuristics.

• DOI: 10.1007/s13740-012-0010-0
• 发表时间: 2012-08-01
• 期刊: JOURNAL ON DATA SEMANTICS
• 作者: Liu, Haishan;Dou, Dejing;Wang, Hao
• 通讯作者: Wang, Hao