MULTIREGIONAL ELECTRICAL ENCODING OF SOCIAL AGGRESSION

社会攻击的多区域电编码

基本信息

批准号：
10583574
负责人：
David E Carlson
金额：
$ 51.34万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-15 至 2026-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10583574
关键词：
Action Potentials Address Aggressive behavior Agonist Animals Architecture Artificial Intelligence Atlases Behavior Behavior Control Behavioral Paradigm Biological Blood Brain Brain region Catalogs Cells Chemicals Clinic Communication Complex Cues Data Development Dopamine Electrodes Emotional Emotions Etiology Experimental Models Eye Functional Magnetic Resonance Imaging Goals Guanfacine Habenula Hour Human Hypothalamic structure Imaging Techniques Implant Individual Lateral Learning Link Machine Learning Mammals Measures Mediating Methodology Methods Modeling Molecular Monitor Motor Mus Muscle Music Neurosciences Output Oxytocin Peptides Physiological Play Prefrontal Cortex Process Research Resolution Rodent Role Sensorimotor functions Serotonin Signal Transduction Site Sleep Social Network Stream System Techniques Technology Testing Therapeutic Time Viral Vision Work brain cell cellular targeting connectome designer receptors exclusively activated by designer drugs emotional behavior experimental study free behavior human subject imaging study in vivo information processing instrument machine learning method millisecond multidisciplinary network models neural neuroregulation receptor sensorimotor system social spatial integration spatiotemporal tool

项目摘要

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.

社会侵略的多区域电气编码神经科学的关键发展包括用于测序单个脑细胞的技术，朝着完成小鼠中完整的中尺度脑细胞地图集的进展，新的监测工具和操纵脑细胞的活性，精制成像技术，以发展结构和功能人类中的连接组地图集，以及对跨物种行为表征行为的新客观措施。然而，尚未解决的关键差距是开发一种模型，该模型将允许这一点新兴的蜂窝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。该差距之所以存在，是因为1）测量，监视和解码的技术在哺乳动物模型物种的自由行为过程中，整个大脑深度的中尺度活动具有然而，可以与细胞活性结合实施，可以监测和操纵，2）理论将细胞活动与中尺度网络活动联系起来的框架，并在跨受试者上概括逐个小鼠的基础尚未开发。我们的多学科团队已经建立了一套工具，用于研究大脑动态如何编码复杂的大脑国家。这些包括高级技术，用于在体内测量和监测大脑动力学，同时在整个大脑深度的许多地区，以高时空分辨率自由行为的老鼠，机器学习分析方法，将单个电路活动衡量复合网络，可用于诱导与情绪相关的大脑状态的行为操作，病毒探测细胞变化与大脑神经表达之间关系的方法动态和闭环刺激工具，可以潜在地测试大脑网络的因果关系调解情绪。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分类大脑如何产生侵略性。至关重要的是，我们认为这个模型框架将是广泛的也适用于其他情绪大脑状态。