Gutkin Boris S, Ermentrout G Bard, Reyes Alex D
Receptors and Cognition, Department of Neuroscience, Institut Pasteur, 75015 Paris, France.
J Neurophysiol. 2005 Aug;94(2):1623-35. doi: 10.1152/jn.00359.2004. Epub 2005 Apr 13.
Neuronal firing is determined largely by incoming barrages of excitatory postsynaptic potentials (EPSPs), each of which produce a transient increase in firing probability. To measure the effects of weak transient inputs on firing probability of cortical neurons, we compute phase-response curves (PRCs). PRCs, whose shape can be related to the dynamics of spike generation, document the changes in timing of spikes caused by an EPSP in a repetitively firing neuron as a function of when it arrives in the interspike interval (ISI). The PRC can be exactly related to the poststimulus time histogram (PSTH) so that knowledge of one uniquely determines the other. Typically, PRCs have zero values at the start and end of the ISI, where EPSPs have minimal effects and a peak in the middle. Where the peak occurs depends in part on the firing properties of neurons. The PRC can have regions of positivity and negativity corresponding respectively to speeding up and slowing down the time of the next spike. A simple canonical model for spike generation is introduced that shows how both the background firing rate and the degree of postspike afterhyperpolarization contribute to the shape of the PRC and thus to the PSTH. PRCs in strongly adapting neurons are highly skewed to the right (indicating a higher change in probability when the EPSPs appear late in the ISI) and can have negative regions (indicating a decrease in firing probability) early in the ISI. The PRC becomes more skewed to the right as the firing rate decreases. Thus at low firing rates, the spikes are triggered preferentially by inputs that occur only during a small time interval late in the ISI. This implies that the neuron is more of a coincidence detector at low firing frequencies and more of an integrator at high frequencies. The steady-state theory is shown to also hold for slowly varying inputs.
神经元放电很大程度上由兴奋性突触后电位（EPSP）的传入脉冲决定，每个EPSP都会使放电概率产生短暂增加。为了测量微弱瞬态输入对皮层神经元放电概率的影响，我们计算了相位响应曲线（PRC）。PRC的形状与动作电位产生的动力学有关，它记录了重复放电神经元中EPSP引起的动作电位时间变化，该变化是EPSP到达峰间间隔（ISI）时间的函数。PRC与刺激后时间直方图（PSTH）密切相关，因此知道其中一个就能唯一确定另一个。通常，PRC在ISI的开始和结束时为零值，此时EPSP的影响最小，而在中间有一个峰值。峰值出现的位置部分取决于神经元的放电特性。PRC可以有正性和负性区域，分别对应于下一个动作电位时间的加快和减慢。我们引入了一个简单的动作电位产生的规范模型，该模型展示了背景放电率和动作电位后超极化程度如何共同影响PRC的形状，进而影响PSTH。强适应性神经元的PRC高度右偏（表明EPSP在ISI后期出现时概率变化更大），并且在ISI早期可能有负性区域（表明放电概率降低）。随着放电率降低，PRC向右偏斜得更厉害。因此，在低放电率时，动作电位优先由仅在ISI后期的一小段时间间隔内出现的输入触发。这意味着神经元在低放电频率下更像是一个巧合探测器，而在高频率下更像是一个积分器。稳态理论也被证明适用于缓慢变化的输入。
