[论文解读] Mechanisms underlying the response of mouse cortical networks to optogenetic manipulation

Alexandre Mahrach, Guang Chen+3 more|arXiv (Cornell University)|Jul 1, 2019

Neural dynamics and brain function参考文献 93被引用 35

一句话总结

本论文分析小鼠皮层网络在光遗传学刺激PV抑制性中间神经元时的响应，在特定层中呈现矛盾的PV响应，并提出能够解释观测结果的网络架构。它使用解析计算与数值模拟来约束电路模型。

ABSTRACT

GABAergic interneurons can be subdivided into three subclasses: parvalbumin positive (PV), somatostatin positive (SOM) and serotonin positive neurons. With principal cells (PCs) they form complex networks. We examine PCs and PV responses in mouse anterior lateral motor cortex (ALM) and barrel cortex (S1) upon PV photostimulation in vivo. In layer 5, the PV response is paradoxical: photoexcitation reduces their activity. This is not the case in ALM layer 2/3. We combine analytical calculations and numerical simulations to investigate how these results constrain the architecture. Two-population models cannot account for the results. Networks with three inhibitory populations and V1-like architecture account for the data in ALM layer 2/3. Our data in layer 5 can be accounted for if SOM neurons receive inputs only from PCs and PV neurons. In both four-population models, the paradoxical effect implies not too strong recurrent excitation. It is not evidence for stabilization by inhibition.

研究动机与目标

• Investigate how PV interneuron stimulation affects principal cells and PV cells in mouse cortex (ALM and S1).
• Test whether two-population models can explain observed responses to PV photostimulation.
• Identify network architectures that account for paradoxical PV responses in specific cortical layers.
• Constrain inhibitory circuit organization by combining analytic and numerical modeling with in vivo data.

提出的方法

• Use in vivo PV photostimulation experiments in mouse ALM and S1 to observe PC and PV responses.
• Develop and analyze network models with varying numbers of inhibitory populations (two-, three-, and four-population architectures).
• Apply analytical calculations to derive conditions for paradoxical responses and stability.
• Run numerical simulations to test model predictions against experimental data.
• Infer architectural constraints such as connectivity and input sources (e.g., SOM inputs to SOM being PC- and PV-driven) from model-data comparisons.

实验结果

研究问题

• RQ1 Can two-population models explain the observed PV response to photostimulation in mouse cortex?
• RQ2 Which network architectures (two-, three-, or four-population) can reproduce the experimental observations in ALM and S1?
• RQ3 What do paradoxical PV responses imply about recurrent excitation and inhibitory stabilization within these networks?
• RQ4 What specific inhibitory pathways and inputs are necessary to reproduce layer-specific responses (e.g., ALM layer 2/3 vs. layer 5)?

主要发现

• Paradoxical PV responses occur in mouse S1 layer 5 but not in ALM layer 2/3 upon PV photostimulation.
• Two-population models cannot account for the observed responses, necessitating more complex architectures.
• Three-inhibitory-population models with a V1-like architecture can account for ALM layer 2/3 data.
• In layer 5, a model where SOM neurons receive inputs only from PCs and PVs can explain the observations.
• In both four-population models, the paradoxical effect does not necessarily indicate stabilization by inhibition, but implies that recurrent excitation is not too strong.