System Identification Software for Cognitive Electrophysiology

描述(由申请人提供)：认知行为神经学家缺乏足够的计算工具来从包括脑电和脑磁图在内的人类电生理数据中识别确定的和随机的线性和非线性动力系统模型。这使得系统地研究许多具有科学和临床意义的现象变得困难或不可能。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)改变诱发反应成分、通过跟随刺激改变(例如，掩蔽)、多感觉诱发反应(例如，听觉-视觉促进)以及与感觉和运动相关的脑反应的反应时间依赖性(例如，心理不应期)。根据这一SBIR项目开发的商业软件工具将使认知行为神经生理学家能够在与事件相关的Volterra建模框架内表征这些可变事件相关瞬变的调制。这些新的建模工具将促进新的实验设计，利用关于大脑动力学的一个很大程度上未被开发的信息来源：事件间隔序列的变化。该软件将使用模拟和实验数据进行验证，包括一项初步研究，这将为确定精神分裂症研究的候选生物标记物奠定基础。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 Suite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从人类电生理数据中识别线性和非线性动态系统模型，这使得系统地研究许多具有科学和临床意义的现象变得困难或不可能，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。根据这一SBIR项目开发的商业软件工具将使认知行为神经生理学家能够表征这些可变事件相关瞬变的调制。该软件将使用模拟和实验数据进行验证，包括一项初步研究，这将为确定精神分裂症研究的候选生物标记物奠定基础。

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.