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Phase Resetting and Phase Locking in Hybrid Circuits of One Model and One Biological Neuron

机译:一种模型和一种生物神经元混合电路中的相位复位和锁相

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摘要

To determine why elements of central pattern generators phase lock in a particular pattern under some conditions but not others, we tested a theoretical pattern prediction method. The method is based on the tabulated open loop pulsatile interactions of bursting neurons on a cycle-by-cycle basis and was tested in closed loop hybrid circuits composed of one bursting biological neuron and one bursting model neuron coupled using the dynamic clamp. A total of 164 hybrid networks were formed by varying the synaptic conductances. The prediction of 1:1 phase locking agreed qualitatively with the experimental observations, except in three hybrid circuits in which 1:1 locking was predicted but not observed. Correct predictions sometimes required consideration of the second order phase resetting, which measures the change in the timing of the second burst after the perturbation. The method was robust to offsets between the initiation of bursting in the presynaptic neuron and the activation of the synaptic coupling with the postsynaptic neuron. The quantitative accuracy of the predictions fell within the variability (10%) in the experimentally observed intrinsic period and phase resetting curve (PRC), despite changes in the burst duration of the neurons between open and closed loop conditions.
机译:为了确定为什么中央模式发生器的元素在某些条件下会锁定在特定模式下而不在其他情况下锁相,我们测试了一种理论模式预测方法。该方法基于逐周期的爆裂神经元的表式开环脉动相互作用,并在由动态生物钳耦合的一个爆裂生物神经元和一个爆裂模型神经元组成的闭环混合电路中进行了测试。通过改变突触电导形成总共164个混合网络。 1:1锁相的预测在质量上与实验结果一致,除了在三个混合电路中预测1:1锁相但未观察到。正确的预测有时需要考虑二阶相位重置,该二阶相位重置用于测量扰动后第二个脉冲串的时序变化。该方法对于抵消突触前神经元爆发的开始和突触后神经元与突触耦合的激活之间的抵消是鲁棒的。尽管在开环和闭环条件下神经元的爆发持续时间发生了变化,但预测的定量准确性仍在实验观察到的固有周期和相位重置曲线(PRC)的变化范围内(10%)。

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