Reconstructing the functional network of a neuron cluster is a fundamental step to reveal the complex interactions among neural systems of the brain. Current approaches to reconstruct a network of neurons or neural systems focus on establishing a static network by assuming the neural network structure does not change over time. To the best of our knowledge, this is the first attempt to build a time-varying directed network of neurons by using an ordinary differential equation model, which allows us to describe the underlying dynamical mechanism of network connections. The proposed method is demonstrated by estimating a network of wide dynamic range neurons located in the dorsal horn of the rats’ spinal cord in response to pain stimuli applied to the Zusanli acupoint on the right leg. The finite sample performance of the proposed method is also investigated with a simulation study.

中文翻译：

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估计时变定向神经网络

重建神经元簇的功能网络是揭示大脑神经系统之间复杂相互作用的基本步骤。当前重建神经元或神经系统网络的方法着重于通过假设神经网络结构不随时间变化而建立静态网络。据我们所知，这是首次尝试通过使用常微分方程模型建立神经元的时变定向网络，这使我们能够描述网络连接的基本动力学机制。通过估计响应于右腿足三里穴位的疼痛刺激，位于大鼠脊髓背角的宽动态范围神经元网络证明了所提出的方法。