MULTIREGIONAL ELECTRICAL ENCODING OF SOCIAL AGGRESSION

社会攻击性的多区域电子编码 神经科学的关键发展包括对单个脑细胞进行测序的技术， 在完成小鼠全中尺度脑细胞图谱方面的进展，监测和分析的新工具 操纵脑细胞的活动，改进成像技术，开发结构和功能 人类的连接组图谱，以及描述跨物种行为的新的客观测量。 然而，一个尚未解决的关键差距是开发一种能够实现这一点的模式 新兴的细胞信息目录将链接到编码情感的广泛功能网络 哺乳动物的行为。这一差距的存在部分是因为1)测量、监控和解码 哺乳动物模式物种在自由行为期间整个大脑深处的中尺度活动 尚未与细胞活动一起实施，可以被监测和操纵，以及2)理论上 将蜂窝活动与中尺度网络活动联系起来的框架，以及在 逐个鼠标的基础还有待开发。 我们的多学科团队已经建立了一套工具来研究大脑动力学如何编码复杂的大脑 各州。这些技术包括同时测量和监测体内脑动态的先进技术 以高时空分辨率对位于整个大脑深处的许多区域进行数月的扫描 行为自由的老鼠，机器学习分析方法，将单个电路活动测量构建为 复合网络，可用于诱导与情绪相关的大脑状态的行为操作，病毒式 探讨细胞变化与全脑神经表达关系的方法 动力学和闭环刺激工具，可以潜在地测试大脑网络状态的因果关系 调停情绪。通过将这套工具集成到单个框架中，我们打算创建一个模型，该模型将 记录大脑是如何产生攻击性的。至关重要的是，我们相信这一模式框架将广泛地 这也适用于其他情绪状态的大脑。

MULTIREGIONAL ELECTRICAL ENCODING OF SOCIAL AGGRESSION Critical developments in neuroscience have included technologies for sequencing individual brain cells, progress towards completing a full mesoscale brain cell atlas in mice, new tools for monitoring and manipulating the activity of brain cells, refined imaging techniques for developing structural and functional connectome atlases in humans, and new objective measures for characterizing behavior across species. Nevertheless, a critical gap that has yet to be addressed is the development of a model that would allow this emerging catalog of cellular information to be linked to the broad functional networks that encode emotional behavior in mammals. This gap exists in part because 1) technologies that measure, monitor, and decode mesoscale activity throughout the depth of the brain during free behavior in mammalian model species have yet to be implemented in conjunction with cellular activity can be monitored and manipulated, and 2) theoretical frameworks that link cellular activity to mesoscale network activity and that generalize across subjects on a mouse-by-mouse basis have yet to be developed. Our multi-disciplinary team has built a suite of tools for studying how brain dynamics encode complex brain states. These include advanced techniques to measure and monitor brain dynamics in vivo concurrently for months across many regions located throughout the depth of the brain at high spatiotemporal resolution in freely-behaving mice, machine-learning analytic approaches that build individual circuit activity measures into composite networks, behavioral manipulations that can be used to induce brain states related to emotions, viral methods that probe the relationship between cellular changes and the expression of brain-wide neural dynamics, and closed-loop stimulation tools that can potentially test the causality of brain network-states in mediating emotion. By integrating this suite of tools in a single framework, we intend to create a model that will catalogue how the brain generates aggression. Critically, we believe that this model framework will be broadly applicable to other emotional brain states as well.