Behavioral and neural mechanisms mediating social motivation in a rat model for ASD

项目摘要 自闭症谱系障碍(ASD)的特征是社交能力受损，通常被归因于 对情绪暗示的误读。尽管在了解ASD方面取得了进展，但治疗选择仍然有限。 这在一定程度上是由于ASD动物模型的局限性，未能捕捉到ASD的一个重要方面 条件--自闭症患者参与社会交往的动机受损。我们最近 开发了一个在上瘾药物和社会互动之间进行选择的操作员模型，表明操作员 社会奖励可防止药物自我管理和药物复发。我们的模型强调了 将社会因素融入成瘾神经科学，以更接近人类的情况。我们的模特 使我们能够直接评估社会奖励和参与社会的动机以及 使用机器学习方法实现复杂社会的自然意志社会互动 行为。一种新的可操作性社会模型和先进的计算神经行为学的结合 分析管道为研究社会奖励背后的神经生物学机制提供了一个独特的工具包 ASD啮齿动物模型中社会动机的潜在干扰。这项建议的主要目的是 研究调节社会动机的神经机制和Shank3突变的影响(大鼠模型 ASD)。在目标1中，我们将使用具有图形界面和直观工作流的开源Python包， 使用姿势估计，创建基于监督和非监督机器学习的预测分类器 社交行为。我们推测，Shank3基因缺陷的大鼠模型，而不是野生型大鼠会表现出异常 社会行为。在目标2中，我们将调查自闭症样导致的社会动机的潜在变化。 不同的行为方式：社会寻求、社会进步比率和社会自我管理 负面后果。通过将我们的社会自我管理模型与ASD的大鼠模型相结合，我们将 验证这样的假设，即Shank3基因缺陷的大鼠将表现出社会动机行为的中断，相对于 野生型老鼠。在目标3中，我们将使用单单位电生理记录到杏仁内侧核(Mea- 对社会行为至关重要的大脑区域)，以识别编码大鼠社会动机或潜在缺陷的单位 使用翻译相关社会选择程序的社会动机。此外，我们还将使用光生技术 扭转清醒行为大鼠潜在的Shank3依赖的社会动机缺陷的方法。这些 方法将为我们提供新的框架，使我们理解MEA在预测以下方面的作用 未来的社会相关事件，并使用这些预测来指导ASD大鼠模型中的行为。我们的 该提案将为调节社会动机的行为和神经机制提供新的见解 ASD大鼠模型的相互作用。

Project Summary Autism spectrum disorder (ASD) is characterized by impaired social communication, often attributed to misreading of emotional cues. Despite progress toward understanding ASD, treatment options remain limited. This is partly due to limitations of animal models of ASD that fail to capture an essential aspect of the ASD condition – people with ASD have impairments in the motivation to engage in social interactions. We recently developed an operant model of choice between addictive drugs and social interaction, showing that operant social reward prevents drug self-administration and drug relapse. Our model highlights the importance of incorporating social factors into addiction neuroscience to mimic the human condition more closely. Our model allows us to directly assess both social reward and motivation to engage socially and the ethology of consequent naturalistic volitional social interactions using machine learning approaches for complex social behavior. The combination of a novel operant social model and advanced computational neuroethological analytical pipelines provides a unique toolkit to study the neurobiological mechanisms underlying social reward and potential disruption of social motivation in rodent model for ASD. The overarching aim of this proposal is to study the neural mechanisms mediating social motivation and the impact of Shank3 mutation (a rat model for ASD). In Aim 1, we will use open-source Python packages with graphical interface and intuitive workflow that uses pose-estimation, to create supervised and unsupervised machine learning-based predictive classifiers of social behavior. We hypothesize that Shank3-deficient rat model, but not wild-type rats will show aberrant social behaviors. In Aim 2, we will investigate the potential autism-like-induced shifts in social motivation using different behavioral approaches: social seeking, social progressive ratio, and social self-administration despite negative consequences. By combining our social self-administration model with a rat model of ASD, we will test the hypothesis that Shank3-deficient rats will show a disruption in social motivation behaviors, relative to wild-type rats. In Aim 3, we will use single-unit electrophysiological recording into the Medial Amygdala (MeA – a brain region critical for social behaviors) to identify units encoding rats’ social motivation or potential deficit in social motivation using a translational relevant social choice procedure. Additionally, we will use optogenetic approaches to reverse potential Shank3-dependent social motivation deficit in awake-behaving rats. These approaches will provide new frameworks on our understanding of the role of MeA for predicting aspects of future social-related events and for using these predictions to guide behavior within a rat model for ASD. Our proposal will provide new insights into behavioral and neural mechanisms mediating the motivation for social interaction in rat model for ASD.