Neural Connectivity Resource Core

摘要 任何神经回路的功能和动力学的准确和预测模型都需要完整的图片 所有复合细胞类型之间的突触连接。尽管做了大量工作，但我们仍然缺乏这样一个 图V1中，或哺乳动物中枢神经系统中的任何其他神经回路。Neural的目标 Connectivity Resource Core是将体内多光子光遗传学电路映射与功能性钙结合联合收割机 成像和事后seqFISH RNA分析，以获得所有转录的功能性连接体， 可区分的V1细胞类型-这是V1的所有组成细胞类型之间的完整连接图， 特别是包括单一单突触连接的强度和短期可塑性的数据， 每种细胞类型之间。因此，它将为需要这些的理论建模项目提供关键支持。 数据来建立V1动力学的精确模型。此外，通过在体内工作，该资源核心将映射 突触连接到神经元上，也将在功能上表征它们对 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， 和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。 最准确和预测的视觉皮层动力学和计算的理论模型。

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.