Non-Additive Coupling Enables Propagation of Synchronous Spiking Activity in Purely Random Networks

Despite the current debate about the computational role of experimentally observed precise spike patterns it is still theoretically unclear under which conditions and how they may emerge in neural circuits. Here, we study spiking neural networks with non-additive dendritic interactions that were recently uncovered in single-neuron experiments. We show that supra-additive dendritic interactions enable the persistent propagation of synchronous activity already in purely random networks without superimposed structures and explain the mechanism underlying it. This study adds a novel perspective on the dynamics of networks with nonlinear interactions in general and presents a new viable mechanism for the occurrence of patterns of precisely timed spikes in recurrent networks.

尽管当前学界对于实验观测到的精确锋电位模式的计算作用尚存争议，但在何种条件下、以及这类模式如何在神经环路中涌现，目前在理论层面仍未有明确结论。本文针对近期在单神经元实验中被揭示的具有非加性树突交互的脉冲神经网络（spiking neural networks）展开研究。我们证明，超加性树突交互可使得无附加结构的纯随机网络中实现同步活动的持续传播，并阐明了其背后的核心机制。本研究为一般性非线性交互网络的动力学特性提供了全新视角，同时为循环神经网络（recurrent networks）中精确时序锋电位模式的出现提供了一种全新的可行机制。