The mechanisms of information storage and retrieval in brain circuits are still the subject of debate. It is widely believed that information is stored at least in part through changes in synaptic connectivity in networks that encode this information and that these changes lead in turn to modifications of network dynamics, such that the stored information can be retrieved at a later time. Here, we review recent progress in deriving synaptic plasticity rules from experimental data and in understanding how plasticity rules affect the dynamics of recurrent networks. We show that the dynamics generated by such networks exhibit a large degree of diversity, depending on parameters, similar to experimental observations in vivo during delayed response tasks.

脑回路中信息存储和检索的机制仍然是争论的主题。人们普遍认为，信息至少部分是通过对这些信息进行编码的网络中突触连接的变化而存储的，并且这些变化反过来会导致网络动态的修改，以便可以在以后检索存储的信息。在这里，我们回顾了从实验数据推导突触可塑性规则以及了解可塑性规则如何影响循环网络的动态方面的最新进展。我们表明，此类网络产生的动态表现出很大程度的多样性，具体取决于参数，类似于延迟响应任务期间的体内实验观察。