Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA.
Proc Natl Acad Sci U S A. 2012 Dec 18;109(51):21116-21. doi: 10.1073/pnas.1210047110. Epub 2012 Dec 4.
Why seizures spontaneously terminate remains an unanswered fundamental question of epileptology. Here we present evidence that seizures self-terminate via a discontinuous critical transition or bifurcation. We show that human brain electrical activity at various spatial scales exhibits common dynamical signatures of an impending critical transition--slowing, increased correlation, and flickering--in the approach to seizure termination. In contrast, prolonged seizures (status epilepticus) repeatedly approach, but do not cross, the critical transition. To support these results, we implement a computational model that demonstrates that alternative stable attractors, representing the ictal and postictal states, emulate the observed dynamics. These results suggest that self-terminating seizures end through a common dynamical mechanism. This description constrains the specific biophysical mechanisms underlying seizure termination, suggests a dynamical understanding of status epilepticus, and demonstrates an accessible system for studying critical transitions in nature.
为什么癫痫发作会自行终止仍然是癫痫学中一个未解决的基本问题。在这里,我们提出的证据表明,癫痫发作通过不连续的临界转变或分岔自行终止。我们表明,在癫痫发作终止过程中,人类大脑的电活动在各种空间尺度上都表现出即将发生临界转变的共同动力学特征——减缓、相关性增加和闪烁。相比之下,持续时间较长的癫痫发作(癫痫持续状态)则反复接近临界转变,但未越过。为了支持这些结果,我们实施了一个计算模型,该模型表明,代表发作期和发作后期的替代稳定吸引子模拟了观察到的动力学。这些结果表明,自行终止的癫痫发作是通过共同的动力学机制结束的。这种描述限制了导致癫痫发作终止的特定生物物理机制,为癫痫持续状态提供了一个动力学理解,并展示了一个易于研究自然界中临界转变的系统。