Within the field of computational neuroscience there are great expectations of finding new ways to rebalance the complex dynamic system of the human brain through controlled pharmacological or electromagnetic perturbation. Yet many obstacles remain between the ability to accurately predict how and where best to perturb to force a transition from one brain state to another. The foremost challenge is a commonly agreed definition of a given brain state. Recent progress in computational neuroscience has made it possible to robustly define brain states and force transitions between them. Here, we review the state of the art and propose a framework for determining the functional hierarchical organization describing any given brain state. We describe the latest advances in creating sophisticated whole-brain computational models with interacting neuronal and neurotransmitter systems that can be studied fully in silico to predict and design novel pharmacological and electromagnetic interventions to rebalance them in disease.

在计算神经科学领域内，人们非常希望找到通过控制药理或电磁扰动来重新平衡人脑复杂动态系统的新方法。在准确地预测如何以及在何处最佳地干扰以从一种大脑状态过渡到另一种大脑状态的能力之间，仍然存在许多障碍。最主要的挑战是对给定大脑状态的公认共识。计算神经科学方面的最新进展使得有可能稳健地定义大脑状态并在它们之间强制转换。在这里，我们回顾了现有技术，并提出了一个框架，用于确定描述任何给定大脑状态的功能层次组织。in silico预测和设计新颖的药理和电磁干预措施，以平衡疾病。