Miao Yao, Suzuki Hiroharu, Sugano Hidenori, Ueda Tetsuya, Iimura Yasushi, Matsui Ryosuke, Tanaka Toshihisa
IEEE Trans Biomed Eng. 2024 Feb;71(2):531-541. doi: 10.1109/TBME.2023.3308616. Epub 2024 Jan 19.
Temporallobe epilepsy (TLE) has been conceptualized as a brain network disease, which generates brain connectivity dynamics within and beyond the temporal lobe structures in seizures. The hippocampus is a representative epileptogenic focus in TLE. Understanding the causal connectivity in terms of brain network during seizures is crucial in revealing the triggering mechanism of epileptic seizures originating from the hippocampus (HPC) spread to the lateral temporal cortex (LTC) by ictal electrocorticogram (ECoG), particularly in high-frequency oscillations (HFOs) bands. In this study, we proposed the unified-epoch dynamic causality analysis method to investigate the causal influence dynamics between two brain regions (HPC and LTC) at interictal and ictal phases in the frequency range of 1-500 Hz by introducing the phase transfer entropy (PTE) out/in-ratio and sliding window. We also proposed PTE-based machine learning algorithms to identify epileptogenic zone (EZ). Nine patients with a total of 26 seizures were included in this study. We hypothesized that: 1) HPC is the focus with the stronger causal connectivity than that in LTC in the ictal state at gamma and HFOs bands. 2) Causal connectivity in the ictal phase shows significant changes compared to that in the interictal phase. 3) The PTE out/in-ratio in the HFOs band can identify the EZ with the best prediction performance.
颞叶癫痫（TLE）已被概念化为一种脑网络疾病，它在癫痫发作时会在颞叶结构内外产生脑连接动力学。海马体是TLE中一个具有代表性的致痫灶。通过发作期皮质脑电图（ECoG），尤其是在高频振荡（HFOs）频段，了解癫痫发作期间脑网络的因果连接对于揭示源自海马体（HPC）并扩散至颞叶外侧皮质（LTC）的癫痫发作触发机制至关重要。在本研究中，我们提出了统一时段动态因果分析方法，通过引入相位转移熵（PTE）的出入比和滑动窗口，来研究1 - 500 Hz频率范围内发作间期和发作期两个脑区（HPC和LTC）之间的因果影响动态。我们还提出了基于PTE的机器学习算法来识别致痫区（EZ）。本研究纳入了9例患者，共26次癫痫发作。我们假设：1）在发作期的γ频段和HFOs频段，HPC是因果连接比LTC更强的焦点。2）与发作间期相比，发作期的因果连接显示出显著变化。3）HFOs频段的PTE出入比能够以最佳预测性能识别EZ。
