Abstract

Recent studies have shown that gamma-band oscillations are directly related to pain intensity. Pain can be exacerbated or diminished via deactivation or activation of inhibitory interneurons in the dorsal horn. We consider a biologically plausible network model with different proportion of inhibitory neurons to emulate gamma elicited activity during pain processes. We perform an analysis using graph theory to gain further insight in the functional state of the circuitry underlying nociceptive process, considering all the possible gamma elicited configurations of pain when changing the number of inhibitory neurons. The probability distribution of the signal associated with each node or neuron is estimated through the Bandt and Pompe approach. We evaluate the Jensen–Shannon distance between all the possible pairs of nodes/neurons, characterizing the different network configurations by calculating the closeness centrality. Thus, by building the graph properties through the node strength distributions and using an information theoretical approach, we characterize the dynamics of the network configurations of pain. This allows us to identify the nonlinear dynamical structure underlying the nociceptive process. Importantly, our findings show that a network configuration with a \(20\%\) of inhibitory neurons boosts information transmission of the complex network circuitry associated with the pain processing.

Graphic abstract

中文翻译：

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痛苦的网络配置：信息传输的效率表征

摘要

最近的研究表明，伽马带振荡与疼痛强度直接相关。通过使背角中的抑制性中神经元失活或激活，可使疼痛加剧或减轻。我们考虑具有不同比例的抑制性神经元的生物学上合理的网络模型，以模拟伽玛诱发的疼痛过程中的活动。我们使用图论进行分析，以进一步了解伤害感受过程中潜在的电路功能状态，并在改变抑制神经元数量时考虑所有可能的伽马引发的疼痛构型。通过Bandt和Pompe方法估计与每个节点或神经元相关的信号的概率分布。我们评估所有可能的节点/神经元对之间的詹森-香农距离，通过计算紧密度中心点来表征不同的网络配置。因此，通过通过节点强度分布构建图形属性并使用信息理论方法，我们可以表征疼痛网络配置的动态。这使我们能够确定伤害感受过程背后的非线性动力学结构。重要的是，我们的发现表明，具有抑制神经元的（20％）促进了与疼痛处理相关的复杂网络电路的信息传输。

图形摘要