Enhancing rodent behavioral phenotyping using guided ultrasonic waves

使用引导超声波增强啮齿动物行为表型

基本信息

批准号：
10532791
负责人：
MICHAEL R DREW
金额：
$ 19.81万
依托单位：
UNIVERSITY OF TEXAS AT AUSTIN
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-12-01 至 2024-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10532791
关键词：
Animal Behavior Animal Experiments Animals Anxiety Behavior Behavior Control Behavior assessment Behavior monitoring Behavioral Behavioral Assay Biomedical Research Breathing Classification Computer Vision Systems Data Detection Devices Elasticity Environment Equipment Freezing Frequencies Fright Gait Genetic Goals Heart Rate Immobilization Implant Intervention Involuntary Movements Locomotion Machine Learning Measures Mental Health Methods Modality Monitor Mus Muscle Muscle Contraction Muscle Tonus Musculoskeletal Neurosciences Outcome Pharmaceutical Preparations Phase Physiologic Monitoring Physiological Physiological Processes Physiology Process Protocols documentation Reporting Research Research Personnel Respiration Rest Rodent Seizures Signal Transduction Startle Reaction Stream Surface Techniques Telemetry Testing Time Ultrasonic wave Ultrasonics Variant anxiety-like behavior anxious behavior measurement behavioral phenotyping experimental study genetic manipulation heart rate monitor improved mental state neural pharmacologic public health relevance respiratory response sensor supervised learning transmission process unsupervised learning vibration waveguide wireless

项目摘要

Rodents are a cornerstone of neuroscience and physiology research, but the methods for monitoring behavior and physiology in these animals suffer from several key limitations. Monitoring physiological processes such as heart rate, breathing, and muscle activity requires invasive sensors that impede natural behavior of the animals. Similarly, behavioral assays can require highly constraining apparatus. This proposal is based on the hypothesis that we can greatly improve the sensitivity, accuracy, and reliability of rodent behavior quantification by taking advantage of a stream of information that, to date, has been completely ignored. When an animal is behaving in an environment, muscle contractions associated with breathing, heart rate, and voluntary and involuntary movements apply subtle forces to the surfaces the animal contacts. These forces generate elastic waves that propagate through the material (i.e., waveguide) at ultrasonic frequencies. The overarching hypothesis of this proposal is that these elastic waves − Guided Ultrasonic Waves (GUWs) − provide valuable information about mouse physiology, behavior, and underlying mental states. Under this proposal we will test the hypothesis that GUWs can be used to non-invasively track low-amplitude responses, such as breathing, heart rate, and startle, which currently can only be monitored using invasive or highly constraining apparatus. In addition, we predict that GUWs can be used to improve the sensitivity and accuracy with which other rodent behaviors can be identified and tracked. We will conduct experiments in which GUWs are recorded as mice explore an arena outfitted with piezoelectric sensors. We will simultaneously record information about physiology and behavior using traditional video tracking and implanted telemetry devices. By comparing these streams of information, we will identify GUW features that report mouse heart rate, startle, and a variety of other behaviors. In addition, we will use supervised and unsupervised machine learning approaches to develop GUW metrics that precisely and accurately classify behaviors that cannot be detected using current methods. Completion of these aims will yield hardware and associated analytics that will enhance the precision and objectivity of rodent behavior monitoring and allow researchers to simultaneously monitor behavior and physiology without the need for restrictive or invasive apparatus. Our goal is that the piezoelectric-based apparatus and associated analyses developed here will allow labs without specialized equipment or expertise to perform precise monitoring of mouse behavior and physiology without the need for invasive test equipment.

啮齿动物是神经科学和生理学研究的基石，但监测方法这些动物的行为和生理学受到几个关键限制。心率、呼吸和肌肉活动等过程需要侵入式传感器，这些传感器会阻碍自然反应同样，行为测定可能需要高度限制的设备。基于这样的假设：我们可以大大提高啮齿类动物的灵敏度、准确性和可靠性通过利用迄今为止已完全被了解的信息流来进行行为量化当动物在环境中行为时，与呼吸、心脏相关的肌肉收缩被忽视。速率以及自愿和非自愿运动对动物接触的表面施加微妙的力。力产生弹性波，该弹性波以超声波频率通过材料（即波导）传播。该提案的总体假设是这些弹性波 - 引导超声波（GUW） - 在此提供有关小鼠生理学、行为和潜在心理状态的有价值的信息。建议我们将测试 GUW 可用于非侵入性跟踪低幅度响应的假设，例如呼吸、心率和惊吓，目前只能使用侵入性或高度监测来监测此外，我们预测 GUW 可用于提高灵敏度和准确性。我们将进行 GUW 的实验，以识别和追踪其他啮齿动物的行为。当小鼠探索配备压电传感器的竞技场时，我们将同时记录。使用传统视频跟踪和植入遥测设备获取有关生理和行为的信息。比较这些信息流，我们将识别报告小鼠心率、惊吓、此外，我们将使用监督和无监督的机器学习。开发 GUW 指标的方法，对无法检测到的行为进行精确分类使用当前方法完成这些目标将产生可增强的硬件和相关分析。啮齿动物行为监测的精确性和客观性，并允许研究人员同时监测行为和生理学，而不需要限制性或侵入性设备。这里开发的基于压电的设备和相关分析将使实验室无需专门的设备或专业知识来对小鼠行为和生理进行精确监测，而不需要侵入式测试设备。