We compared a range of linear and nonlinear models based on how accurately they could describe resting-state functional magnetic resonance imaging and intracranial electroencephalography dynamics in humans. Linear autoregressive models were the most accurate in all cases. Using numerical simulations, we demonstrated that spatiotemporal averaging has a critical and robust role in this linearity.

中文翻译：

---

多模态证据表明大脑动力学在宏观尺度上呈线性

我们比较了一系列线性和非线性模型，基于它们描述人类静息态功能磁共振成像和颅内脑电图动力学的准确程度。在所有情况下，线性自回归模型都是最准确的。通过数值模拟，我们证明了时空平均在这种线性中具有关键而强大的作用。