NeuroMathComp Laboratory, INRIA, CNRS, and ENS, Paris, France.
Neural Comput. 2011 Dec;23(12):3232-86. doi: 10.1162/NECO_a_00206. Epub 2011 Sep 15.
In this letter, we propose a general framework for studying neural mass models defined by ordinary differential equations. By studying the bifurcations of the solutions to these equations and their sensitivity to noise, we establish an important relation, similar to a dictionary, between their behaviors and normal and pathological, especially epileptic, cortical patterns of activity. We then apply this framework to the analysis of two models that feature most phenomena of interest, the Jansen and Rit model, and the slightly more complex model recently proposed by Wendling and Chauvel. This model-based approach allows us to test various neurophysiological hypotheses on the origin of pathological cortical behaviors and investigate the effect of medication. We also study the effects of the stochastic nature of the inputs, which gives us clues about the origins of such important phenomena as interictal spikes, interictal bursts, and fast onset activity that are of particular relevance in epilepsy.
在这封信中，我们提出了一个研究由常微分方程定义的神经质量模型的一般框架。通过研究这些方程的解的分岔及其对噪声的敏感性，我们建立了一个重要的关系，类似于字典，将它们的行为与正常和病理性的，特别是癫痫性的皮质活动模式联系起来。然后，我们将这个框架应用于对两个具有最有趣现象的模型的分析，即 Jansen 和 Rit 模型，以及 Wendling 和 Chauvel 最近提出的稍复杂一些的模型。这种基于模型的方法使我们能够对病理性皮质行为的起源进行各种神经生理学假设的测试，并研究药物治疗的效果。我们还研究了输入的随机性的影响，这为我们提供了有关棘波、爆发性活动和快速起始活动等重要现象起源的线索，这些现象在癫痫中具有特别重要的意义。
