Dodla Ramana, Wilson Charles J
Department of Biology, University of Texas at San Antonio, San Antonio, Texas 78249, USA.
Phys Rev Lett. 2009 Feb 13;102(6):068102. doi: 10.1103/PhysRevLett.102.068102. Epub 2009 Feb 10.
We study a network model of two conductance-based pacemaker neurons of differing natural frequency, coupled with either mutual excitation or inhibition, and receiving shared random inhibitory synaptic input. The networks may phase lock spike to spike for strong mutual coupling. But the shared input can desynchronize the locked spike pairs by selectively eliminating the lagging spike or modulating its timing with respect to the leading spike depending on their separation time window. Such loss of synchrony is also found in a large network of sparsely coupled heterogeneous spiking neurons receiving shared input.
我们研究了一个网络模型,该模型由两个具有不同固有频率的基于电导的起搏器神经元组成,它们通过相互兴奋或抑制进行耦合,并接收共享的随机抑制性突触输入。对于强相互耦合,网络可能会使尖峰与尖峰相位锁定。但是共享输入可以通过选择性地消除滞后尖峰或根据它们的分离时间窗口调节其相对于领先尖峰的时间,使锁定的尖峰对去同步。在一个接收共享输入的稀疏耦合异质脉冲神经元的大型网络中也发现了这种同步性的丧失。