标题： 用于自发爆发海马切片中表观确定性混沌的神经网络模型 显示英文标题

标题： Neural Network Model for Apparent Deterministic Chaos in Spontaneously Bursting Hippocampal Slices

摘要： 一种表现出随机种群爆发的神经网络模型通过仿真进行研究。 首次返回图的爆发间隔呈现出类似实验中海马切片所发现的不稳定的周期轨道（UPO）轨迹。 各种控制方法和替代分析用于UPO检测也得到了与实验相似的结果。 我们的结果对实验数据作为确定性混沌证据的解释提出质疑，并建议在使用基于UPO的方法检测时间序列数据中的确定性时要谨慎。 显示英文摘要

摘要： A neural network model that exhibits stochastic population bursting is studied by simulation. First return maps of inter-burst intervals exhibit recurrent unstable periodic orbit (UPO)-like trajectories similar to those found in experiments on hippocampal slices. Applications of various control methods and surrogate analysis for UPO-detection also yield results similar to those of experiments. Our results question the interpretation of the experimental data as evidence for deterministic chaos and suggest caution in the use of UPO-based methods for detecting determinism in time-series data.