University of Belgrade, Institute for Multidisciplinary Research, Department for Life Sciences, Kneza Višeslava 1, 11000 Belgrade, Serbia.
Comput Methods Programs Biomed. 2011 Nov;104(2):212-8. doi: 10.1016/j.cmpb.2011.07.006. Epub 2011 Aug 5.
We applied a combination of fractal analysis and Independent Component Analysis (ICA) method to detect the sources of fractal complexity in snail Br neuron activity induced by static magnetic field of 2.7 mT. The fractal complexity of Br neuron activity was analyzed before (Control), during (MF), and after (AMF) exposure to the static magnetic field in six experimental animals. We estimated the fractal dimension (FD) of electrophysiological signals using Higuchi's algorithm, and empirical FD distributions. By using the Principal Component Analysis (PCA) and FastICA algorithm we determined the number of components, and defined the statistically independent components (ICs) in the fractal complexity of signal waveforms. We have isolated two independent components of the empirical FD distributions for each of three groups of data by using FastICA algorithm. ICs represent the sources of fractal waveforms complexity of Br neuron activity in particular experimental conditions. Our main results have shown that there could be two opposite intrinsic mechanisms in single snail Br neuron response to static magnetic field stimulation. We named identified ICs that correspond to those mechanisms - the component of plasticity and the component of elasticity. We have shown that combination of fractal analysis with ICA method could be very useful for the decomposition and identification of the sources of fractal complexity of bursting neuronal activity waveforms.
我们应用分形分析和独立成分分析（ICA）方法的组合来检测 2.7 mT 静磁场诱导蜗牛 Br 神经元活动的分形复杂性的来源。在六个实验动物中，我们分析了 Br 神经元活动在暴露于静磁场之前（对照）、期间（MF）和之后（AMF）的分形复杂性。我们使用 Higuchi 算法和经验 FD 分布来估计电生理信号的分形维数（FD）。通过使用主成分分析（PCA）和 FastICA 算法，我们确定了组件的数量，并定义了信号波形分形复杂性中的统计独立组件（IC）。我们使用 FastICA 算法为每组数据的三个独立组分别分离出经验 FD 分布的两个独立分量。IC 代表特定实验条件下 Br 神经元活动的分形波形复杂性的来源。我们的主要结果表明，单个蜗牛 Br 神经元对静磁场刺激的反应可能存在两种相反的内在机制。我们将识别出的对应于这些机制的 IC 命名为可塑性组件和弹性组件。我们已经表明，分形分析与 ICA 方法的结合对于分解和识别突发神经元活动波形的分形复杂性的来源非常有用。
