González-Ramírez Laura R
Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, Mexico City, Mexico.
Front Comput Neurosci. 2022 Mar 24;16:788924. doi: 10.3389/fncom.2022.788924. eCollection 2022.
In this work, we establish a fractional-order neural field mathematical model with Caputo's fractional derivative temporal order α considering 0 < α < 2, to analyze the effect of fractional-order on cortical wave features observed preceding seizure termination. The importance of this incorporation relies on the theoretical framework established by fractional-order derivatives in which memory and hereditary properties of a system are considered. Employing Mittag-Leffler functions, we first obtain approximate fractional-order solutions that provide information about the initial wave dynamics in a fractional-order frame. We then consider the Adomian decomposition method to approximate pulse solutions in a wider range of orders and longer times. The former approach establishes a direct way to investigate the relationships between fractional-order and wave features, such as wave speed and wave width. In contrast, the latter approach displays wave propagation dynamics in different fractional orders for longer times. Using the previous two approaches, we establish approximate wave solutions with characteristics consistent with cortical waves preceding seizure termination. In our analysis, we find consistent differences in the initial effect of the fractional-order on the features of wave speed and wave width, depending on whether α <1 or α>1. Both cases can model the shape of cortical wave propagation for different fractional-orders at the cost of modifying the wave speed. Our results also show that the effect of fractional-order on wave width depends on the synaptic threshold and the synaptic connectivity extent. Fractional-order derivatives have been interpreted as the memory trace of the system. This property and the results of our analysis suggest that fractional-order derivatives and neuronal collective memory modify cortical wave features.
在这项工作中,我们建立了一个具有卡普托分数阶导数时间阶数α(0 < α < 2)的分数阶神经场数学模型,以分析分数阶对癫痫发作终止前观察到的皮层波特征的影响。这种纳入的重要性依赖于分数阶导数所建立的理论框架,其中考虑了系统的记忆和遗传特性。利用米塔格 - 莱夫勒函数,我们首先获得近似的分数阶解,这些解提供了分数阶框架中初始波动力学的信息。然后我们考虑用阿多米安分解法在更广泛的阶数范围和更长时间内近似脉冲解。前一种方法建立了一种直接的方式来研究分数阶与波特征之间的关系,如波速和波宽。相比之下,后一种方法展示了不同分数阶下更长时间的波传播动力学。利用前两种方法,我们建立了与癫痫发作终止前皮层波特征一致的近似波解。在我们的分析中,我们发现根据α < 1还是α > 1,分数阶对波速和波宽特征的初始影响存在一致的差异。两种情况都可以通过修改波速来模拟不同分数阶下皮层波传播的形状。我们的结果还表明,分数阶对波宽的影响取决于突触阈值和突触连接程度。分数阶导数已被解释为系统记忆痕迹。这一特性以及我们的分析结果表明,分数阶导数和神经元集体记忆会改变皮层波特征。