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 在几乎每一次社会交往中，我们都在不断地评估和判断他人的行为。 行为，如他们的话语，姿势或语气。虽然神经科学在研究 大脑编码自己的行为，在任何模型系统中，关于神经回路如何评估 另一个人的行为，以适当的社会反应。虽然这是一个活跃的研究领域， 人工智能算法解决了这个问题。这种缺乏了解是一个主要障碍 治疗大量患有社会评价障碍的人，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专门的行为和专门的神经系统。 电路来评估男性歌曲，作为一种新的社会评价机制模型。择偶是一个质数 社会评估的例子，动物评估潜在配偶的质量。伯德桑是 大多数可量化的信号是雄性用来追求雌性的，这使得雌性鸣禽成为社交的理想模式。 评价雄性斑胸草雀是神经科学中的一个极好的模型， 运动序列和它的大脑包含一个易于处理的歌曲系统，专门用于唱歌。虽然只有雄性会唱歌 女性也拥有一个“歌曲系统”，需要在几个物种的非歌唱女性感知歌曲。 因此，我们的总体假设是，斑胸草雀的歌声系统已经共同进化， 二型性状：雄性的歌曲产生和雌性的歌曲评价和偏好。雌性斑胸草雀 我更喜欢刻板的歌曲，而不是多变的歌曲，但评估刻板并不是微不足道的;大脑必须首先形成一个内部的 代表的追求者的歌曲，然后迅速比较功能，在显示出偏好之前， 最吸引人的歌曲。我建议研究雌性鸣禽来解决三个基本问题： 大脑是如何编码他人行为的内部表征的？大脑如何评估 别人的行为质量？大脑如何表现出对他人最可取行为的偏好？ 反映出神经科学对雄性的更大偏见，鸣禽研究也主要集中在 男性的歌曲产生，离开女性的大脑，以及择偶的神经机制，主要是 忽视对于新的创新者奖，我建议一个独特的融合神经生物学，行为学，和进化 利用最先进的行为（歌曲偏好分析，基于机器学习的社会行为跟踪）， 神经（光度学，光遗传学，多区域电生理学），和计算方法来建立 雌性鸣鸟作为我们如何评价他人行为的机械模型。这样的细胞和电路- 水平的理解将为解码交配，一夫一妻制和配对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， 社会互动，如失语症，失认症，自闭症。