Zhang Benjamin J, Chamanzar Maysamreza, Alam Mohammad-Reza
Department of Mechanical Engineering, University of California, Berkeley, CA 94720, USA.
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA.
J R Soc Interface. 2017 Feb;14(127). doi: 10.1098/rsif.2016.0872.
Here we show that brain seizures can be effectively suppressed through random modulation of the brain medium. We use an established mesoscale cortical model in the form of a system of coupled stochastic partial differential equations. We show that by temporal and spatial randomization of parameters governing the firing rates of the excitatory and inhibitory neuron populations, seizure waves can be significantly suppressed. We find that the attenuation is the most effective when applied to the mean threshold potential. The proposed technique can serve as a non-invasive paradigm to mitigate epileptic seizures without knowing the location of the epileptic foci.
在此我们表明，通过对脑介质进行随机调制可有效抑制脑部癫痫发作。我们使用一个以耦合随机偏微分方程系统形式建立的中尺度皮质模型。我们表明，通过对控制兴奋性和抑制性神经元群体放电率的参数进行时间和空间上的随机化处理，癫痫波可得到显著抑制。我们发现，当应用于平均阈电位时，这种衰减最为有效。所提出的技术可作为一种非侵入性范式，在不知道癫痫病灶位置的情况下减轻癫痫发作。
