论文标题

简单的学习规则生成复杂的规范电路

Simple Learning Rules Generate Complex Canonical Circuits

论文作者

Olson, Joseph, Kreiman, Gabriel

论文摘要

皮质电路的特征是在未分化的网络开发过程中出现的精美复杂的连接模式。这些电路的发展由精确的分子线索的结合,这些提示决定神经元认同和位置以及有助于建立,完善和维持神经元连接性的活动依赖机制。在这里,我们询问简单的可塑性机制是否可以从具有全能连接的网络开始,以构成范围的层间连接组装皮质微电路。目标规范的微电路基于通常在啮齿动物,猫和猴子的多个皮质区域中发现的皮质层之间的连接模式。我们使用计算模型作为原则证明,以证明经典和反向尖峰依赖的可塑性规则会导致形成类似于规范微电路的网络。该模型会收敛到生物学合理的解决方案,但仅对于一小部分可塑性规则组合,增强和抑郁之间存在平衡,并增强了对第4层的投入。该模型对跨皮质层的学习计算及其在开发过程中的动态部署进行了特定的可测试预测。

Cortical circuits are characterized by exquisitely complex connectivity patterns that emerge during development from undifferentiated networks. The development of these circuits is governed by a combination of precise molecular cues that dictate neuronal identity and location along with activity dependent mechanisms that help establish, refine, and maintain neuronal connectivity. Here we ask whether simple plasticity mechanisms can lead to assembling a cortical microcircuit with canonical inter-laminar connectivity, starting from a network with all-to-all connectivity. The target canonical microcircuit is based on the pattern of connections between cortical layers typically found in multiple cortical areas in rodents, cats and monkeys. We use a computational model as a proof-of-principle to demonstrate that classical and reverse spike-timing dependent plasticity rules lead to a formation of networks that resemble canonical microcircuits. The model converges to biologically reasonable solutions provided that there is a balance between potentiation and depression and enhanced inputs to layer 4, only for a small combination of plasticity rules. The model makes specific testable predictions about the learning computations operant across cortical layers and their dynamic deployment during development.

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