System Identification Software for Cognitive Electrophysiology

认知电生理学系统识别软件

• 批准号: 7760204
• 负责人: Mark E Pflieger
• 金额: $ 37.06万
• 依托单位: SOURCE SIGNAL IMAGING, INC.
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7760204
• 关键词: Address; Algorithms; Auditory; Behavioral; Behavioral Paradigm; Biological Markers; Biological Models; Brain; Characteristics; Clinical; Code; Cognitive; Complex; Computer Analysis; Computer software; Data; Dependence; Development; Development Plans; Diagnostic tests; Electroencephalography; Electromagnetics; Electrophysiology (science); Event; Event-Related Potentials; Experimental Designs; Frequencies; Functional Magnetic Resonance Imaging; Human; Imagery; Masks; Measures; Memory; Modeling; Modification; Motor; Movement; Neurosciences; Phase; Pilot Projects; Process; Protocols documentation; Psychological Refractory Period; Reaction Time; Recovery of Function; Research; Research Personnel; Schizophrenia; Sensory; Signal Transduction; Simulate; Small Business Innovation Research Grant; Software Engineering; Software Tools; Source; Stimulus; System; Time; Variant; Visual; abstracting; base; clinically significant; cognitive neuroscience; computerized tools; data modeling; design; encephalography; graphical user interface; improved; innovation; magnetic field; multisensory; neurophysiology; neuropsychiatry; novel; prototype; public health relevance; response; sensory gating; theories; tool

DESCRIPTION (provided by applicant): Cognitive-behavioral neuroscientists lack adequate computational tools for identifying linear and nonlinear dynamical system models, both deterministic and stochastic from human electrophysiological data, including electro- and magneto-encephalography. This makes it difficult or impossible to investigate systematically many scientifically and clinically significant phenomena. These phenomena include modification of evoked response components by preceding stimuli (e.g., response suppression or facilitation, recovery functions, sensory gating, echoic memory lifetimes, priming), modification by following stimuli (e.g., masking), multisensory evoked responses (e.g., auditory-visual facilitation), and reaction time dependence of sensory-related and motor-related brain responses (e.g., psychological refractory period). Commercial software tools to be developed under this SBIR project will enable cognitive-behavioral neurophysiologists to characterize these modulations of variable event-related transients within the framework of event-related Volterra modeling. These novel modeling tools will facilitate new experimental designs that harness a largely unexploited source of information about brain dynamics: variation of inter-event interval sequences. The software will be validated using simulated and experimental data, including a pilot study that will lay the basis for identifying candidate biomarkers for schizophrenia research. These tools will be integrated into our existing EMSE Suite software product using an FDA-compliant quality management process for use initially by basic and clinical neuroscience researchers. PUBLIC HEALTH RELEVANCE: Cognitive-behavioral neuroscientists lack adequate computational tools for identifying linear and nonlinear dynamical system models, from human electrophysiological data, making it difficult or impossible to investigate systematically many scientifically and clinically significant phenomena, including response suppression or facilitation, recovery functions, sensory gating, echoic memory lifetimes, and priming. Commercial software tools to be developed under this SBIR project will enable cognitive-behavioral neurophysiologists to characterize these modulations of variable event-related transients. The software will be validated using simulated and experimental data, including a pilot study that will lay the basis for identifying candidate biomarkers for schizophrenia research.

描述（由申请人提供）：认知行为神经科学家缺乏足够的计算工具来识别线性和非线性动态系统模型，包括来自人类电生理数据的确定性和随机性，包括脑电图和脑磁图。这使得很难或不可能系统地调查许多科学和临床上重要的现象。这些现象包括通过先前刺激（例如，反应抑制或促进、恢复功能、感觉门控、回声记忆寿命、启动），通过跟随刺激的修改（例如，掩蔽），多感觉诱发反应（例如，视觉-视觉促进），以及感觉相关和运动相关脑反应的反应时间依赖性（例如，心理不应期）。在该SBIR项目下开发的商业软件工具将使认知行为神经生理学家能够在事件相关的沃尔泰拉建模框架内表征可变事件相关瞬变的这些调制。这些新的建模工具将促进新的实验设计，利用一个基本上未开发的信息来源的大脑动力学：事件间间隔序列的变化。该软件将使用模拟和实验数据进行验证，包括一项试点研究，该研究将为确定精神分裂症研究的候选生物标志物奠定基础。这些工具将使用符合FDA的质量管理流程集成到我们现有的EMSE套件软件产品中，最初供基础和临床神经科学研究人员使用。 公共卫生相关性：认知行为神经科学家缺乏足够的计算工具来识别线性和非线性动力系统模型，从人类电生理数据，使得它很难或不可能系统地调查许多科学和临床上重要的现象，包括反应抑制或促进，恢复功能，感觉门控，回声记忆寿命，和启动。商业软件工具将在这个SBIR项目下开发，使认知行为神经生理学家来表征这些变量的事件相关的瞬变调制。该软件将使用模拟和实验数据进行验证，包括一项试点研究，该研究将为识别精神分裂症研究的候选生物标志物奠定基础。