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.

项目概要 几乎在每一次社交互动中，我们都在不断地评估和判断他人的行为 行为，例如他们的言语、姿势或语气。虽然神经科学在如何 大脑对自己的行为进行编码，但在任何模型系统中，人们对神经回路如何评估知之甚少 另一个人为了适当的社会反应而采取的行动。尽管这是一个活跃的研究领域，但它也没有 人工智能算法解决了这个问题。这种缺乏理解是一个主要障碍 治疗大量患有社会评价障碍的人，例如听觉处理障碍， 失语症、失认症、自闭症谱系障碍和几种神经退行性疾病。 在这里，我提出了雌性鸣禽，它已经进化出了一种特殊的行为和专用的神经网络 评估男性歌曲的电路，作为社会评估的一种新颖的机制模型。择偶是首要任务 社会评估的例子，其中动物评估潜在配偶的质量。鸟鸣声是其中之一 雄性用来求爱雌性的最可量化的信号，使雌性鸣禽成为社交的理想模型 评估。雄性斑胸草雀是神经科学领域的优秀模型，因为它们的歌曲是高度刻板的 运动序列及其大脑包含一个专门用于唱歌的易处理的歌曲系统。虽然只有男性唱歌， 雌性还拥有“歌曲系统”，这是几种非唱歌雌性感知歌曲所必需的。 因此，我们的总体假设是，斑胸草雀的鸣叫系统是为了互补性而共同进化的。 二态性特征：雄性的歌曲产生和雌性的歌曲评估和偏好。雌性斑马雀 比起变化多端的歌曲，更喜欢刻板印象，但评估刻板印象并非易事；大脑首先必须形成内部 代表求婚者的歌曲，然后快速比较不同版本的特征，然后再显示偏好 寻找最有吸引力的歌曲。我建议研究雌性鸣禽来解决三个基本问题： 大脑如何编码他人行为的内部表征？大脑如何评价 他人的行为质量？大脑如何表现出对他人最理想行为的偏好？ 鸣禽研究也主要集中于神经科学领域对男性的更大偏见 男性的歌曲产生，离开女性的大脑，以及择偶的神经机制，很大程度上 被忽视了。对于新创新者奖，我提出了神经生物学、行为学和进化论的独特融合 具有最先进的行为（歌曲偏好分析、基于机器学习的社交行为跟踪）， 神经（光度测定、光遗传学、多区域电生理学）和计算方法来建立 雌性鸣禽作为我们如何评估他人行为的机械模型。这样的蜂窝和电路- 水平理解将为解码交配、一夫一妻制和配对关系的神经回路铺平道路， 为新兴的人工智能算法提供信息，并提供对以缺陷为特征的疾病的见解 社交互动，例如失语症、失认症和自闭症。