Wilson Charles J
Department of Biology, University of Texas at San Antonio, San Antonio, Texas
J Neurophysiol. 2017 Aug 1;118(2):855-873. doi: 10.1152/jn.00143.2017. Epub 2017 May 10.
Spike-timing effects of small-amplitude sinusoidal currents were measured in mouse striatal spiny neurons firing repetitively. Spike-timing reliability varied with the stimulus frequency. For frequencies near the cell's firing rate, the cells altered firing rate to match the stimulus and became phase locked to it. The stimulus phase of firing during lock depended on the stimulus frequency relative to the cell's unperturbed firing rate. Interspike intervals during sinusoidal stimulation were predicted using an iterative map constructed from the cells' phase-resetting curve. Variability of interspike intervals was reduced by stimulation at all frequencies higher than about half the cell's unperturbed rate, and interspike intervals were accurately predicted by the map. Long sequences of spike times were predicted by iterating on the map. The accuracy of that prediction varied with frequency. Spike time predictability was highest near and during phase lock. The map predicted the phase of firing on the input and its dependence on stimulus frequency. Prediction errors, when they occurred, were of two kinds: unpredicted variation in interspike interval from intrinsic cell noise and accumulation of prediction errors from previous interspike intervals. Each type of prediction error arose from a different mechanism, and their impact was also predicted from the phase model. When two oscillatory input currents were presented simultaneously, striatal neurons responded selectively to only one of them, the one closest in frequency to the cell's unperturbed firing rate. Their spike times encoded the frequency and phase of that single oscillatory input. During repetitive firing, the timing of action potentials is determined by the interaction between the input and voltage-sensitive currents throughout the interspike interval. This interaction is encapsulated in the neuron's phase-resetting curve. The phase-resetting curve predicted spike timing to small sinusoidal currents over a wide range of stimulus frequencies. Firing patterns were most sensitive to oscillatory components near the cell's own firing rate, even in the presence of noise and other inputs.
在重复放电的小鼠纹状体棘状神经元中测量了小幅度正弦电流的峰电位时间效应。峰电位时间可靠性随刺激频率而变化。对于接近细胞放电率的频率,细胞会改变放电率以匹配刺激并与之锁相。锁相期间放电的刺激相位取决于相对于细胞未受干扰放电率的刺激频率。使用由细胞相位重置曲线构建的迭代映射预测正弦刺激期间的峰电位间隔。在高于约一半细胞未受干扰放电率的所有频率下,刺激可降低峰电位间隔的变异性,并且该映射可准确预测峰电位间隔。通过在映射上迭代预测长序列的峰电位时间。该预测的准确性随频率而变化。在锁相附近和期间,峰电位时间可预测性最高。该映射预测了输入上放电的相位及其对刺激频率的依赖性。当出现预测误差时,有两种类型:由于细胞内在噪声导致的峰电位间隔的不可预测变化以及来自先前峰电位间隔的预测误差积累。每种类型的预测误差都源于不同的机制,并且它们的影响也可从相位模型中预测。当同时呈现两个振荡输入电流时,纹状体神经元仅对其中一个有选择性反应,即频率最接近细胞未受干扰放电率的那个。它们的峰电位时间编码了该单个振荡输入的频率和相位。在重复放电期间,动作电位的时间由整个峰电位间隔期间输入电流与电压敏感电流之间的相互作用决定。这种相互作用包含在神经元的相位重置曲线中。相位重置曲线在很宽的刺激频率范围内预测了对小幅度正弦电流的峰电位时间。即使存在噪声和其他输入,放电模式对接近细胞自身放电率的振荡成分最为敏感。