Aoki Takaaki, Aoyagi Toshio
Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan.
Neural Comput. 2007 Oct;19(10):2720-38. doi: 10.1162/neco.2007.19.10.2720.
Although context-dependent spike synchronization among populations of neurons has been experimentally observed, its functional role remains controversial. In this modeling study, we demonstrate that in a network of spiking neurons organized according to spike-timing-dependent plasticity, an increase in the degree of synchrony of a uniform input can cause transitions between memorized activity patterns in the order presented during learning. Furthermore, context-dependent transitions from a single pattern to multiple patterns can be induced under appropriate learning conditions. These findings suggest one possible functional role of neuronal synchrony in controlling the flow of information by altering the dynamics of the network.
尽管在实验中已观察到神经元群体间上下文依赖的尖峰同步现象,但其功能作用仍存在争议。在这项建模研究中,我们证明,在一个根据尖峰时间依赖可塑性组织的脉冲神经元网络中,均匀输入同步程度的增加可导致在学习过程中按呈现顺序在记忆活动模式之间进行转换。此外,在适当的学习条件下,可诱导从单一模式到多种模式的上下文依赖转换。这些发现表明,神经元同步在通过改变网络动态来控制信息流方面可能具有一种功能作用。