Combining theory and experiments to infer how recurrent and top-down connectivity in the corticothalamic circuit gives rise to V1 selectivity

为了理解计算是如何在神经回路中实现的，重要的是要澄清局部的，循环的连接与反馈回路的作用。在紧密的合作中，我们的项目结合了理论和实验方法，并根据早期视觉系统功能反应特性的测量来执行基于模型的突触连接性推断。在上一个资助期，我们使用活体电生理学方法测量初级视皮层（V1）中假定的兴奋性（E）和抑制性（I）神经元群体的对比敏感度和方向选择性和来自丘脑背外侧膝状体核（dLGN）的输入。我们观察到，所有dLGN和大多数V1神经元（86.2%）是对比度不变的，这也适用于相应的神经群体。基于电路的对比度不变性，我们使用方向和对比度响应结合超线性稳定建模框架来推断局部突触连接性和输入轮廓。我们发现，I人口形成了一个子网络，具有最强的经常性连接，从E子网络的预测是最弱的贡献者V1的反应，这是符合以前的连接组学研究。值得注意的是，我们推断的V1的前馈输入表明，抑制性V1神经元比E子网络更容易被dLGN投射所靶向。综上所述，我们的结果表明，总体对比度不变性是电路布线和V1响应的重要约束。在下一个资助期，我们将结合体内实验和超线性稳定电路模型，并将在3个方面取得进展：（1）进一步验证推断的V1连通性，并通过光遗传学操作研究小白蛋白阳性（PV+）抑制性中间神经元对V1建立方向选择性、对比敏感性和对比不变性的功能作用。(2)我们将扩展我们的理论网络模型，以包含生物神经回路的一些复杂性，包括皮质-丘脑反馈作为V1的额外经常性输入。我们将通过丘脑上L 6皮质丘脑（CT）轴突终末的光遗传学操作来限制该模型，同时测量V1回路的活性和对方向和对比度的选择性。(3)比较V1皮质内抑制，CT反馈和控制条件的光遗传学操作过程中的V1响应的时间过程，我们将研究这些关键电路元件如何有助于V1功能的方向和对比度的选择性的时间动态。我们将在我们的网络模型中测试调谐和/或增益的变化是否伴随着特定网络群体之间推断的连接性的变化。

To understand how computations are implemented in neural circuits it is important to clarify the role of local, recurrent connectivity versus feedback loops. In a tight collaboration, our project combines theoretical and experimental approaches and performs model-based inference of synaptic connectivity from measurements of functional response properties in the early visual system.In the previous funding period, we used in vivo electrophysiology to measure contrast sensitivity and orientation selectivity in putative excitatory (E) and inhibitory (I) populations of neurons in primary visual cortex (V1) and its inputs from the dorsolateral geniculate nucleus (dLGN) of the thalamus. We observed that all dLGN and the majority of V1 neurons (86.2 %) are contrast-invariant, and that this also holds true for the respective neural populations. Building on the contrast invariance property of the circuit, we used orientation and contrast responses in combination with a supralinear stabilized modeling framework to infer the local synaptic connectivity and input profiles. We found that the I population forms a sub-network with strongest recurrent connections, and that projections from E sub-network are the weakest contributors to V1 responses, which is in line with previous connectomics studies. Notably, our inferred feedforward inputs to V1 indicate that inhibitory V1 neurons are targeted stronger by dLGN projections than E sub-network.Taken together, our results indicate that the population-wide contrast invariance is an important constraint for circuit wiring and V1 responses.For the next funding period, we will build on our results combining in vivo experiments and the supralinear stabilized circuit model, and will advance in 3 aspects: (1) We will further test the inferred V1 connectivity and investigate via optogenetic manipulations the functional role of recurrent inhibition contributed by parvalbumin-positive (PV+) inhibitory interneurons to the establishment of orientation selectivity, contrast sensitivity and contrast invariance in V1. (2) We will expand our theoretical network model to embrace some of the complexity of biological neural circuits, by including cortico-thalamic feedback as an additional recurrent input to V1. We will constrain this model by optogenetic manipulations of L6 corticothalamic (CT) axon terminals over thalamus, while measuring the V1 circuit activity and selectivity for orientation and contrast. (3) Comparing the time course of V1 responses during optogenetic manipulations of V1 intracortical inhibition, CT feedback and control conditions, we will investigate how these key circuit elements contribute to the temporal dynamics of V1 feature selectivity for orientation and contrast. We will test in our network model whether changes in tuning and/or gain are accompanied by changes in inferred connectivity between specific network populations.