Rodrigues Pedro L C, Baccala Luiz A
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:5493-5496. doi: 10.1109/EMBC.2016.7591970.
This paper illustrates the effectiveness of generalized partial directed coherence (gPDC) in characterizing time-varying neural connectivity by properly extrapolating its single trial asymptotic statistical results to a multi trial setting. Time-varying estimation is performed with a sliding-window procedure based on the proposal in [1], whereby a time-frequency map of the connectivity between channels is built. The technique is validated on a non-linear toy model generating simulated EEG and then applied to a publicly available real EEG dataset for benchmarking purposes.
本文通过将广义偏相干（gPDC）的单试次渐近统计结果合理外推至多试次设置，展示了其在表征时变神经连接方面的有效性。时变估计基于文献[1]中的提议，采用滑动窗口程序进行，由此构建通道间连接性的时频图。该技术在生成模拟脑电图的非线性玩具模型上得到验证，然后应用于一个公开可用的真实脑电图数据集以进行基准测试。
