Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan.
Institute of Physics, Academia Sinica, Taipei, Taiwan.
Sci Rep. 2018 May 23;8(1):8027. doi: 10.1038/s41598-018-26286-8.
Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. We employed two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. We found that inhibitory interneurons enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, we have described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. In this work, we evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems.
果蝇嗅觉系统中的局部中间神经元（LNs）表现出神经元多样性和可变性，但目前尚不清楚这些特征如何影响复杂 LN 网络中的信息编码能力和可靠性。我们采用两种策略来构建一个多样化的兴奋性-抑制性神经网络，从环形网络结构开始，然后将不同类型的抑制性中间神经元和电路变异性引入模拟网络。节点集合内的活动连续性（振荡模式）被用作读出，以描述网络活动的时间动态。我们发现，抑制性中间神经元通过在网络布线复杂度非常高时保护网络免受极短的激活期，从而提高了编码能力。此外，不同类型的中间神经元对编码能力和可靠性有不同的影响。电路变异性可以在不影响编码能力的情况下提高编码可靠性。因此，我们描述了中间神经元的电路变异性如何与兴奋性-抑制性多样性相互作用，以增强神经网络的编码能力和可区分性。在这项工作中，我们评估了不同类型和程度的连接多样性对环形模型的影响，该模型可能模拟果蝇嗅觉系统或其他生物系统中的中间神经元网络。
