MULTIREGIONAL ELECTRICAL ENCODING OF SOCIAL AGGRESSION

社会攻击的多区域电编码 神经科学的重要发展包括对单个脑细胞进行测序的技术， 在小鼠中完成完整的中尺度脑细胞图谱方面取得的进展， 操纵脑细胞的活动，改进成像技术， 人类的连接体图谱，以及描述跨物种行为的新的客观措施。 然而，一个尚待解决的关键差距是开发一种模式， 新出现的细胞信息目录将与编码情感的广泛功能网络联系起来， 哺乳动物的行为。这种差距的存在部分是因为1）测量，监控和解码的技术 在哺乳动物模型物种的自由行为期间，整个大脑深度的中尺度活动具有 可以监测和操纵尚待实施的与细胞活动结合的方法，以及2）理论上的 将细胞活动与中尺度网络活动联系起来的框架， 还没有开发出一个接一个鼠标的基础。 我们的多学科团队已经建立了一套工具，用于研究大脑动力学如何编码复杂的大脑 states.这些包括先进的技术，以测量和监测脑动力学在体内同时进行， 以高时空分辨率在位于整个大脑深度的许多区域上进行了几个月的观察， 自由行为的老鼠，机器学习分析方法，建立个人电路活动措施， 复合网络，行为操纵，可用于诱导与情绪有关的大脑状态，病毒 方法探讨细胞变化与全脑神经元表达之间的关系， 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， 调节情绪通过将这套工具集成到一个框架中，我们打算创建一个模型， 记录大脑如何产生攻击性。关键是，我们认为，这一模型框架将广泛 也适用于其他情绪大脑状态。

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.