Neural Connectivity Resource Core

摘要 任何神经电路的功能和动力学的准确和可预测的模型都需要一个完整的画面 其所有复合细胞类型之间的突触连接。尽管做了大量的工作，但我们仍然缺乏这样的 V1中的图表，或哺乳动物中枢神经系统中的任何其他神经回路。神经学的目标 连接性资源核心是将体内多光子光遗传电路图谱与功能钙相结合 成像和组织后序列FISH RNA分析以获得所有转录的功能连接体 可区分的V1信元类型--这是所有V1‘S成分信元类型之间的完整连通图， 具体包括关于么正单突触连接的强度和短期可塑性的数据 在每种细胞类型之间。因此，它将为理论建模项目提供关键支持，这些项目需要 数据来建立V1动力学的准确模型。此外，通过在体内工作，这种资源核心将映射 神经元上的突触连接也将根据它们对 视觉刺激。这将允许视觉反应、突触连接和动力学之间的直接关联， 以及细胞水平上的转录同一性。这一知识对于限制我们的发展至关重要 最准确和最具预测性的视觉皮质动力学和计算理论模型。

ABSTRACT An accurate and predictive model of the function and dynamics of any neural circuit requires a complete picture of the synaptic connections between all of its composite cell types. Despite extensive work, we still lack such a diagram in V1, or for any other neural circuit in the mammalian central nervous system. The goal of the Neural Connectivity Resource Core is to combine in vivo multiphoton optogenetic circuit mapping with functional calcium imaging and post-hoc seqFISH RNA profiling to obtain the functional connectome of all transcriptionally distinguishable V1 cell types – that is a complete connectivity diagram between all of V1’s component cell types, specifically including data on the strength and short-term plasticity of the unitary monosynaptic connections between each cell type. It will thus provide critical support to the theoretical modeling projects that require these data to build accurate models of V1 dynamics. Furthermore, by working in vivo, this resource core will map synaptic connectivity onto neurons that will also be functionally characterized with respect to their responses to visual stimuli. This will permit direct correlation between visual responses, synaptic connectivity and dynamics, and transcriptional identity at the cellular level. This knowledge is critical for constraining our development of the most accurate and predictive theoretical models of visual cortical dynamics and computation.