Time scales of spike-train correlation for neural oscillators with common drive
Time scales of spike-train correlation for neural oscillators with common drive
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DOI：
10.1103/physreve.81.011916
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发表时间：
2010-01-01
影响因子：
2.4
通讯作者：
Thilo, Evan L.
中科院分区：
文献类型：
--
作者：
Barreiro, Andrea K.;Shea-Brown, Eric;Thilo, Evan L.
我们研究了在一类接受噪声超阈值刺激的神经模型中，相位重置曲线对相关输入信号转换为相关输出尖峰的影响。我们使用线性响应理论根据相关退出时间问题的矩来近似尖峰相关系数，并比较 I 型模型与 II 型模型以及可以评估尖峰相关性的不同时间尺度的结果。我们发现，在长时间尺度上，I 型振荡器比 II 型振荡器更有效地传递相关性。在短时间尺度上，这种趋势会逆转，时间尺度上的相对效率切换取决于输入电流的平均值和标准偏差。这种切换随着时间尺度发生，可以被下游电路利用。
We examine the effect of the phase-resetting curve on the transfer of correlated input signals into correlated output spikes in a class of neural models receiving noisy superthreshold stimulation. We use linear-response theory to approximate the spike correlation coefficient in terms of moments of the associated exit time problem and contrast the results for type I vs type II models and across the different time scales over which spike correlations can be assessed. We find that, on long time scales, type I oscillators transfer correlations much more efficiently than type II oscillators. On short time scales this trend reverses, with the relative efficiency switching at a time scale that depends on the mean and standard deviation of input currents. This switch occurs over time scales that could be exploited by downstream circuits.