CRCNS:Predictability as a New Paradigm for Rodent Social Neurobiology

长久的社会依恋是通过与他人的积极互动过程建立起来的。 形成这种社会纽带涉及认知过程，如感知显著的感觉线索，学习他们的 积极的价值观，选择适当的亲社会行为行为。阐明这一现象的机制 复杂的自然行为是NIMH的战略目标。我们的建议将推动这一目标的实现 在社会过程、积极价值和认知的RDoC领域内贡献新知识 系统。我们的长期目标是使我们能够更深入地了解分子机制 影响神经回路，这些神经回路潜藏在每一时刻的过程中，这是建立持久的社会 债券。我们在这里的目标是使用刻板印象和可预测性的原则来阐明行为 以及草原田鼠(Microtus Ochrogaster)社会纽带的神经动力学，这是一种 揭示社会依恋的遗传和神经内分泌机制的系统。我们将衡量 社会行为和纹状体、皮质和杏仁核神经活动在长时间尺度和构建上的变化 导致联系的社会动态的预测模型。我们的中心假设是 刻板印象的社会行为和相应的神经活动是可以从潜在的内部状态预测的 对这种潜在状态的动态进行建模将有助于预测未来的社会 成对结合的草原田鼠之间的相互作用。我们将量化这种相互作用的可预测性 使用过去社会行为的与行为相关的社会背景(目标1)和行为特定的动态 社会脑神经网络中这些关键节点之间的功能连接(目标2)。我们的研究将 通过验证一个新的、定量的框架来研究社会的“暗物质”，从而产生积极的影响 神经科学，建立在一个人的动态过程中有可预见性的思想基础上 在刻板的社会互动的行为空间中的轨迹。通过建立可预测性作为 啮齿动物社会神经生物学的新范式，因此我们的研究将提出一个全面的框架 如何思考社会赤字以及如何鼓励亲社会行为。

A long-lasting social attachment is built over a course of positive interactions with another individual. Forming such social bonds involves cognitive processes like perceiving salient sensory cues, learning their positive value, and selecting appropriately prosocial behavioral actions. Elucidating the mechanisms of such a complex natural behavior is a Strategic Objective of the NIMH. Our proposal will advance this Objective by contributing new knowledge within the RDoC domains of Social Processes, Positive Valence and Cognitive Systems. Our long-term goal is to enable a more vertical understanding of how molecular mechanisms influence neural circuits underlying moment-by-moment processes that must occur to build enduring social bonds. Our objective here is to use the principles of stereotypy and predictability to elucidate the behavioral and neural dynamics that underlie social bonding in the prairie vole (Microtus ochrogaster), a premier system for uncovering genetic and neuroendocrine mechanisms of social attachments. We will measure social behaviors and striatal, cortical and amygdalar neural activity over long time scales and build predictive models of the social dynamics leading to a bond. Our central hypothesis is that trajectories of stereotyped social behaviors and corresponding neural activity are predictable from a latent internal state of "pair-bondedness"; and that modeling the dynamics of this latent state will help predict future social interactions between pair-bonded prairie voles. We will quantify the predictability of such interactions in ethologically-relevant social contexts using past social behavior (Aim 1) and behavior-specific dynamic functional connectivity between those key nodes in the social brain neural network (Aim 2). Our research will have a positive impact by validating a novel, quantitative framework for studying the "dark matter" of social neuroscience, grounded in the idea that there is predictability in the dynamic processes that underlie one's trajectory through a behavioral space of stereotypical social interactions. By establishing predictability as a new paradigm for rodent social neurobiology, our studies will thus advance a comprehensive framework for how to think about social deficits and how to encourage prosocial behavior.