Using phase resetting to predict 1:1 and 2:2 locking in two neuron networks in which firing order is not always preserved
Using phase resetting to predict 1:1 and 2:2 locking in two neuron networks in which firing order is not always preserved
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DOI：
10.1007/s10827-007-0040-z
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发表时间：
2008-02-01
影响因子：
1.2
通讯作者：
Canavier, Carmen C.
中科院分区：
文献类型：
--
作者：
Maran, Selva K.;Canavier, Carmen C.
我们的目标是了解几乎同步模式是如何在异质神经元网络中产生的。在异构网络中，几乎同步模式取代了精确同步模式，包括1:1和2:2锁相模式。在没有弱耦合假设的情况下，基于开环相位重置曲线（PRC），导出了互耦两神经元电路中2:2锁相模式的存在性和稳定性判据。每个组成神经元的PRC是利用突触前动作电位产生的突触电导变化作为扰动产生的。对于保留发射顺序的模式和交替发射顺序的模式，需要分别推导。由相互抑制耦合的两个模型神经元组成的网络被检查以测试预测。假设突触时间常数相对于周期较短，并考虑了二阶重置的影响，定性和定量地准确预测了两种几乎同步模式的参数体系。相比之下，基于弱耦合的PRC方法无法预测2:2模态，也无法达到强耦合方法预测1:1模态的精度。强耦合预测方法提供了对在两个神经元网络中促进近同步的操作的见解，并且可能对更大的网络也具有预测价值，这也可以显示放电顺序的变化。我们还确定了一种新的路由，通过这种路由，同步在轻度异构网络中丢失。
Our goal is to understand how nearly synchronous modes arise in heterogenous networks of neurons. In heterogenous networks, instead of exact synchrony, nearly synchronous modes arise, which include both 1:1 and 2:2 phase-locked modes. Existence and stability criteria for 2:2 phase-locked modes in reciprocally coupled two neuron circuits were derived based on the open loop phase resetting curve (PRC) without the assumption of weak coupling. The PRC for each component neuron was generated using the change in synaptic conductance produced by a presynaptic action potential as the perturbation. Separate derivations were required for modes in which the firing order is preserved and for those in which it alternates. Networks composed of two model neurons coupled by reciprocal inhibition were examined to test the predictions. The parameter regimes in which both types of nearly synchronous modes are exhibited were accurately predicted both qualitatively and quantitatively provided that the synaptic time constant is short with respect to the period and that the effect of second order resetting is considered. In contrast, PRC methods based on weak coupling could not predict 2:2 modes and did not predict the 1:1 modes with the level of accuracy achieved by the strong coupling methods. The strong coupling prediction methods provide insight into what manipulations promote near-synchrony in a two neuron network and may also have predictive value for larger networks, which can also manifest changes in firing order. We also identify a novel route by which synchrony is lost in mildly heterogenous networks.