Cortical neural responses can be modulated by various factors, such as stimulus inputs and the behavior state of the animal. Understanding the circuit mechanisms underlying modulations of network dynamics is important to understand the flexibility of circuit computations. Identifying the dynamical state of a network is an important first step to predict network responses to external stimulus and top-down modulatory inputs. Models in stable or unstable dynamical regimes require different analytic tools to estimate the network responses to inputs and the structure of neural variability. In this article, I review recent cortical models of state-dependent responses and their predictions about the underlying modulatory mechanisms.

中文翻译：

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皮质网络模型中动态状态的调节。


皮质神经反应可以通过多种因素调节，例如刺激输入和动物的行为状态。了解网络动态调制背后的电路机制对于理解电路计算的灵活性非常重要。识别网络的动态状态是预测网络对外部刺激和自上而下的调制输入的响应的重要的第一步。稳定或不稳定动态状态下的模型需要不同的分析工具来估计网络对输入的响应和神经变异性的结构。在本文中，我回顾了最新的状态依赖性反应的皮层模型及其对潜在调节机制的预测。