The Female Songbird as a Novel Mechanistic Model for the Neural Basis of Social Evaluation

雌性鸣禽作为社会评价神经基础的新机制模型

• 批准号: 10472986
• 负责人: Vikram Gadagkar
• 金额: $ 148.05万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10472986
• 关键词: Address; Agnosia; Animals; Aphasia; Area; Auditory Perceptual Disorders; Award; Behavior; Behavioral; Biological Assay; Biological Models; Brain; Computational Technique; Computing Methodologies; Disease; Electrophysiology (science); Ethology; Evaluation; Evolution; Female; Individual; Judgment; Machine Learning; Modeling; Motor; Neurobiology; Neurodegenerative Disorders; Neurosciences; Pair Bond; Partner in relationship; Persons; Photometry; Posture; Production; Research; Signal Transduction; Social Behavior; Social Interaction; Songbirds; Stereotyping; System; Voice; artificial intelligence algorithm; autism spectrum disorder; base; bird song; court; innovation; insight; male; neglect; neural circuit; neural model; neuromechanism; novel; optogenetics; preference; relating to nervous system; response; sexual dimorphism; social; social deficits; stereotypy; trait; zebra finch

Project Summary In nearly every social interaction, we are constantly evaluating and making judgments about other people’s behaviors, such as their words, posture, or tone of voice. While neuroscience is making rapid progress on how the brain encodes one’s own behavior, little is known, in any model system, about how neural circuits evaluate another individual’s actions for proper social responses. Though an active area of research, neither has this problem been resolved by artificial intelligence algorithms. This lack of understanding presents a major obstacle to treating the large number of people with disorders of social evaluation, such as auditory processing disorders, aphasias, agnosias, autism spectrum disorder, and several neurodegenerative diseases. Here I propose the female songbird, which has evolved a specialized behavior and dedicated neural circuits to evaluate male song, as a novel mechanistic model for social evaluation. Mate choice is a prime example of social assessment, in which animals evaluate the quality of potential mates. Birdsong is one of the most quantifiable signals males use to court females, making the female songbird an ideal model for social evaluation. The male zebra finch is an excellent model in neuroscience because song is a highly stereotyped motor sequence and its brain contains a tractable song system dedicated to singing. While only males sing, females also possess a ‘song system’, required for perceiving song in several species of non-singing females. Thus, our overarching hypothesis is that the zebra finch song system has co-evolved for complementary sexually dimorphic traits: song production in males and song evaluation and preference in females. Female zebra finches prefer stereotyped over variable songs but evaluating stereotypy is not trivial; the brain must first form an internal representation of the suitor’s song, then rapidly compare features across renditions, before showing a preference for the most attractive songs. I propose studying the female songbird to address three fundamental questions: How does the brain encode an internal representation of others’ behavior? How does the brain evaluate the quality of others’ behavior? How does the brain show a preference for the most desirable behavior in others? Reflecting a larger bias toward males in neuroscience, songbird research has also primarily focused on song production in males, leaving the female brain, and the neural mechanisms of mate choice, largely neglected. For the New Innovator Award, I propose a unique melding of neurobiology, ethology, and evolution with state of the art behavioral (song preference assays, machine-learning based social behavior tracking), neural (photometry, optogenetics, multi-region electrophysiology), and computational methods to establish the female songbird as a mechanistic model for how we evaluate the actions of others. Such a cellular and circuit- level understanding will pave the way to decoding the neural circuits for mating, monogamy, and the pair bond, inform emerging artificial intelligence algorithms, and provide insights into disorders characterized by deficits in social interactions, such as aphasias, agnosias, and autism.

项目摘要 在几乎每种社交互动中，我们都在不断评估和制作其他人的法官 行为，例如他们的言语，姿势或语气。而神经科学正在快速发展如何 大脑编码自己的行为，在任何模型系统中，关于神经电路的评估方式鲜为人知 另一个人对适当社会反应的行为。虽然是一个积极的研究领域，但也没有 人工智能算法解决了问题。缺乏理解带来了一个主要障碍 治疗大量社会评估障碍的人，例如听觉处理障碍， 失语症，不知不际，自闭症谱系障碍和几种神经退行性疾病。 在这里，我提出了女鸣鸟，该鸣鸟已经发展出一种专业的行为和专用的神经元 评估男性歌曲的圈子，是一种用于社会评估的新机械模型。伴侣选择是素数 社会评估的例子，其中动物评估潜在伴侣的质量。鸟鸣是 大多数可量化的信号雄性用于法院女性，使女性鸣禽成为社会的理想模型 评估。男性斑马罚款是神经科学的出色模型，因为歌曲是一种高度定型的观念 运动序列及其大脑包含一个专门用于唱歌的可寓言歌曲系统。而只有男性唱歌， 女性还拥有一个“歌曲系统”，这是在几种非抚养女性中感知歌曲所必需的。 这就是我们的总体假设是，斑马精美的歌曲系统已共同发展以进行性爱 二态性状：男性的歌曲制作以及女性的歌曲评估和偏好。女斑马罚款 优于刻板印象，而不是可变歌曲，但是评估刻板印象并不是很微不足道的。大脑必须首先形成内部 表示求婚者歌曲的代表，然后迅速比较跨演绎的功能，然后才显示偏好 最吸引人的歌曲。我建议研究女鸣鸟以解决三个基本问题： 大脑如何编码他人行为的内部表示？大脑如何评估 他人行为的质量？大脑如何表现出对他人最理想的行为的偏爱？ 鸣鸟研究反映了对神经科学中男性的偏见，主要集中于 男性的歌曲制作，留下女性大脑和伴侣选择的神经机制，在很大程度上 被忽视。对于新的创新奖，我提出了一个独特的神经生物学，伦理学和进化论 具有艺术状态的行为（歌曲偏好分析，基于机器学习的社会行为跟踪）， 神经（光度法，光遗传学，多区域电生理学）和计算方法以建立 女歌鸟是我们如何评估他人行为的机械模型。这样的细胞和电路 水平的理解将为交配，一夫一妻制和双方结合的神经回路铺平道路 告知新兴人工智能算法，并提供有关以定义为特征的疾病的见解 社交互动，例如失语症，不可思议和自闭症。