High-throughput Physiological Micro-connectivity Mapping in Vivo

项目总结 绘制大脑回路的突触连接图对于从机制上了解 行为、学习和认知的神经基础。虽然解剖学方法可以揭示 神经回路的结构，只有功能方法才能揭示每个突触的强度和动力学 在网络中。这些参数对于构建任何类型的定量和解释性模型至关重要 神经电路计算、编码和存储信息。这项提案将三个团队聚集在一起， 全息光遗传学和电生理学的互补专业知识(Adesnik)，高分辨率 体积成像(JI)和统计建模与实时实验设计(Paninski)，开发了两个 新技术将能够揭示大脑中单个神经元的大部分生理连接体。 第一种方法将体内高分辨率多光子光刺激与单细胞内光刺激相结合 完整大脑的电生理学，以及允许高通量映射的统计算法 靶向神经元的突触前连接体。第二种方法使用相同的光刺激系统， 但利用单个突触活动的光学记者来实现对 随着时间的推移，大脑皮层网络中的突触连接性。这两项新技术将使 神经科学家将获得关于大脑皮质网络生理微连接的定量数据 大脑皮层的一大部分。第一种方法提供了无与伦比的突触强度测量和 每个已识别的突触连接的动力学。第二种方法允许重复评估 同一动物体内相同神经元在许多天内的微连接，最终打开了 有机会描绘出大脑回路在发育、学习或 脑部疾病的进展。

PROJECT SUMMARY Mapping the synaptic connectivity of brain circuits is essential for obtaining a mechanistic understanding of the neural basis of behavior, learning, and cognition. While anatomical approaches can reveal the physical architecture of neural circuits, only a functional approach can reveal the strength and dynamics of each synapse in a network. These parameters are crucial for building any type of quantitative and explanatory model for how neural circuits compute, encode, and store information. This proposal brings together three teams with complementary expertise in holographic optogenetics and electrophysiology (Adesnik), high resolution volumetric imaging (Ji) and statistical modeling and real-time experimental design (Paninski), to develop two new technologies that will be able reveal much of the physiological connectome of single neurons in the brain. The first approach combines high resolution multiphoton photo-stimulation in vivo with single cell intracellular electrophysiology in the intact brain, and statistical algorithms that permit high-throughput mapping of the targeted neuron's presynaptic connectome. The second approach employs the same photo-stimulation system, but leverages optical reporters of activity in individual synapses to achieve the all-optical measurement of synaptic connectivity in a cortical network chronically over time. These two new technologies will allow neuroscientists to obtain the quantitative data on the physiological micro-connectivity of cortical networks across large fractions of the cortex. The first approach provides unparalleled measurements of synaptic strength and dynamics of each identified synaptic connections. The second approach permits the repeated assessment of the micro-connectivity of the same neurons in the same animal over many days, finally opening up the opportunity to map the reorganization of brain circuitry over the course of development, learning, or the progression of brain disease.