Optical reconstruction of cortical connectivity

计算神经科学中最大的挑战之一是重建大型复杂神经网络的连通性。 破译电路连接的能力将对我们理解神经系统的动力学特性和功能组织产生根本性的影响。 了解普遍的连接模式也将有助于了解网络可能运行的发展制约因素和学习规则。最近的事态发展为解决这一基本问题的合作努力开辟了新的可能性。 首先，双光子成像和光刺激方法的进步使得可以观察大量神经元的同时活动，同时以任意时空模式刺激神经元。 第二，从钙成像数据中提取动作电位时序信息的新统计方法，以及对小规模神经元集合的响应特性进行建模的新统计方法，现在已经足够有效，可以在线实施并扩大规模，以了解大型网络的功能。研究人员将联合收割机结合这些新的实验和分析方法，利用丘脑皮层切片中自发和诱发活动的双光子钙成像，首次估计大型新皮层回路的连接图。 这里的一个关键的新步骤是用双光子谷氨酸释放直接验证估计的电路模型，这允许电路中的任何神经元被激活（具有单细胞分辨率），同时监测诱发的突触后反应。这个跨学科的项目有三个互补的具体目标：（1）开发从钙成像数据中实时推断尖峰时间的最佳方法。 (2)使用这些尖峰定时推断方法来估计来自大规模多神经元钙成像的皮层切片的网络连接。 (3)通过光激活假定的突触前神经元，同时记录突触后细胞的细胞内，证实谷氨酸释放和膜片钳导出的连接图。 所提出的方法也应该被证明适用于研究神经系统的其他中枢和外周区域;数据分析软件将在网上公开提供，以加强计算神经科学研究和教育的基础设施。

One of the greatest challenges in computational neuroscience is to reconstruct the connectivity of large, complex neuronal networks. The ability to decipher circuit connectivity would have a fundamental impact on our understanding of the dynamical properties and the functional organization of the nervous system. Knowledge of prevalent connectivity patterns will also shed light on the developmental constraints and learning rules under which the network might be operating. Recent developments open new possibilities for collaborative efforts to tackle this basic problem. First, advances in two-photon imaging and photostimulation methods make it possible to observe the simultaneous activity of large ensembles of neurons, while stimulating neurons in arbitrary spatiotemporal patterns. Second, new statistical methods for extracting action potential timing information from calcium imaging data, and for modeling the response properties of small collections of neurons, are now efficient enough that they may be implemented on-line and scaled up to understand the function of large networks. The investigators will combine these new experimental and analytical methods to estimate, for the first time, the connectivity diagram of large neocortical circuits, using two-photon calcium imaging of spontaneous and evoked activity in thalamocortical slices. A key novel step here is to directly verify the estimated circuit model with two-photon glutamate uncaging, which allows any neuron in the circuit to be activated (with single-cell resolution) while the evoked postsynaptic responses are monitored. This interdisciplinary project has three complementary specific aims: (1) Develop statistically-optimal methods for real-time inference of spike timing from calcium imaging data. (2) Use these spike timing inference methods to estimate the network connectivity from large-scale multineuronal calcium-imaging of cortical slices. (3) Confirm the derived connectivity maps with glutamate uncaging and patch clamping, by photoactivating putative presynaptic neurons while recording intracellularly from postsynaptic cells. The proposed methods should also prove applicable to study other central and peripheral regions of the nervous system; data analysis software will be made publicly available online, to enhance the infrastructure for research and education in computational neuroscience.