Igarashi Yasunobu, Sakumura Yuichi, Ishii Shin
Graduate School of Information Science, Nara Institute of Science and Technology 8916-5, Takayama, Ikoma, Nara, Japan.
Neural Netw. 2006 Oct;19(8):1137-52. doi: 10.1016/j.neunet.2006.05.041. Epub 2006 Sep 1.
Recent experimental researches have suggested that sustained neural activity in the prefrontal cortex is a process of memory retention in decision making. Previous theoretical studies indicate that a balance between recurrent excitation and feedback inhibition is important for sustaining the activity. To investigate a plausible balancing mechanism, we simulated a biophysically realistic network model. Our model shows that short-term depression (STD) enables the network to sustain its activity despite the presence of long-term inhibition by GABA(B) receptors and that the sustained firing rates have a bell-shaped dependence on the degree of STD. By analyzing the neural network dynamics, we show that the bell-shaped dependence on STD is formed by destabilizing the balance with either excessive or insufficient STD. We also show that the optimal degree of STD has a linear relationship with the neural network size. These results suggest that STD provides a balancing mechanism and controls levels of sustained activities of various size networks.
近期的实验研究表明，前额叶皮层中持续的神经活动是决策过程中记忆保持的一个过程。先前的理论研究表明，循环兴奋和反馈抑制之间的平衡对于维持这种活动很重要。为了研究一种合理的平衡机制，我们模拟了一个具有生物物理真实性的网络模型。我们的模型表明，尽管存在GABA(B)受体的长期抑制作用，但短期抑制（STD）能使网络维持其活动，并且持续放电率对STD程度呈钟形依赖关系。通过分析神经网络动力学，我们表明对STD的钟形依赖关系是由STD过多或不足破坏平衡而形成的。我们还表明，STD的最佳程度与神经网络大小呈线性关系。这些结果表明，STD提供了一种平衡机制，并控制各种大小网络的持续活动水平。
