System for automatic classification of rodent vocalizations

啮齿动物发声自动分类系统

• 批准号: 8715027
• 负责人: Garet Lahvis
• 金额: $ 32.43万
• 依托单位: BIOSPEECH, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8715027
• 关键词: Academia; Acoustics; Alleles; Animal Model; Animal Vocalization; Animals; Behavior; Behavior assessment; Behavioral; Biology; Categories; Classification; Classification Scheme; Collaborations; Computational algorithm; Computer Analysis; Computer software; Data; Dementia; Disease; Evaluation; Expressed Emotion; Face; Frequencies; Genetic; Growth; Health; Human; Impairment; Individual; Industry; Investments; Knock-out; Label; Laboratories; Measures; Mental Depression; Mental disorders; Methods; Modeling; Motivation; Mouse Strains; Mus; Neurologic; Noise; Outcome; Output; Pattern; Pharmacological Treatment; Phase; Phenotype; Preclinical Drug Evaluation; Production; Rat Strains; Reporting; Research Personnel; Rodent; Rodent Model; Schizophrenia; Shapes; Social Behavior; Social Conditions; Social Interaction; Social isolation; Solutions; Speech; Speech Disorders; Substance abuse problem; Surveys; System; Testing; Time; Training; Transgenic Model; Ultrasonics; Visual; Work; base; behavior change; computerized tools; developmental disease; digital; disability; drug discovery; drug of abuse; genetic manipulation; genetic strain; graphical user interface; improved; interest; mathematical methods; mental state; neuropsychiatry; research study; small molecule; social; social communication; software development; software systems; therapy development; time interval; tool; vocalization

DESCRIPTION (provided by applicant): Depression, dementia, schizophrenia, substance abuse, developmental disorders and speech- related disabilities can feature impairments in the ability to express emotions. Development of treatments for these impairments presents a formidable challenge. In this regard, several researchers who study rodent models of mental illness have more recently focused upon the frequency modulations associated with rodent ultrasonic vocalizations (USVs). Measures of USVs are an attractive behavioral phenotype because they model the prosodic deficits in existing mental disorders. A critical impasse for researchers is that USV extraction from background noise is difficult and time-consuming and the approaches used to classify these calls into categories remain arbitrary. Thus, most researchers report simple tallies of the numbers of USVs produced by their rodent models. We propose a software system that allows the user to efficiently and effectively interrogate rodent vocalization data for prosodic content. Our collaboration brings together an expert in mouse social behavior (Lahvis) with an expert in computational assessment of human prosody (van Santen). We propose to take advantage of two well-defined genetic strains of mouse sociability, the C57Bl/6 and BALB/c strains, which have been tested extensively for USVs under highly controlled social conditions. With audio recordings of these two strains of mice under conditions of social interaction, social solicitation, and social isolation, we will develop software that automatically segments, tracks, and classifies mouse USVs from acoustic recordings. This software will vastly improve researcher efficiency in academic and industry--based analysis of rodent vocalizations. It will improve routine USV assessments, from counts of call rates toward analyses of frequency modulations within each call. Further, our software will allow users to classify calls according to mathematical approaches, rather than the arbitrary currently used. This analytical capacity is not currently available despite broad demand for software with this function. The proposed software will provide researchers with a powerful new tool for determining how genetic and pharmacological manipulations moderate vocal patterns. It will have widespread value for application in academia and industry.

描述（由申请人提供）：抑郁症、痴呆症、精神分裂症、药物滥用、发育障碍和言语相关障碍可能会导致表达情绪能力受损。开发针对这些损伤的治疗方法是一项艰巨的挑战。在这方面，一些研究啮齿动物精神疾病模型的研究人员最近将注意力集中在与啮齿动物超声波发声（USV）相关的频率调制上。 USV 的测量是一种有吸引力的行为表型，因为它们模拟了现有精神障碍的韵律缺陷。研究人员面临的一个关键僵局是，从背景噪声中提取 USV 既困难又耗时，而且用于将这些呼叫分类的方法仍然是任意的。因此，大多数研究人员报告了他们的啮齿动物模型产生的无人水面艇数量的简单统计。我们提出了一种软件系统，允许用户高效且有效地询问啮齿动物发声数据以获取韵律内容。我们的合作汇集了小鼠社交行为专家 (Lahvis) 和人类韵律计算评估专家 (van Santen)。我们建议利用两种明确的小鼠社交性遗传品系，即 C57Bl/6 和 BALB/c 品系，这两种品系已在高度控制的社会条件下对 USV 进行了广泛的测试。通过这两种小鼠在社交互动、社交招揽和社交隔离条件下的录音，我们将开发软件，自动从录音中分割、跟踪和分类小鼠 USV。该软件将极大地提高研究人员在啮齿动物发声的学术和行业分析方面的效率。它将改进常规 USV 评估，从呼叫率计数到每次呼叫内的频率调制分析。此外，我们的软件将允许用户根据数学方法而不是当前使用的任意方法对呼叫进行分类。尽管对具有此功能的软件有广泛的需求，但目前尚不具备这种分析能力。拟议的软件将为研究人员提供一个强大的新工具，用于确定遗传和药理学操作如何调节声音模式。它将在学术界和工业界具有广泛的应用价值。