Department of Mathematics, College of Natural Sciences and Mathematics, University of Houston Houston, TX, USA.
Front Comput Neurosci. 2010 Apr 19;4:9. doi: 10.3389/fncom.2010.00009. eCollection 2010.
Correlations between spike trains can strongly modulate neuronal activity and affect the ability of neurons to encode information. Neurons integrate inputs from thousands of afferents. Similarly, a number of experimental techniques are designed to record pooled cell activity. We review and generalize a number of previous results that show how correlations between cells in a population can be amplified and distorted in signals that reflect their collective activity. The structure of the underlying neuronal response can significantly impact correlations between such pooled signals. Therefore care needs to be taken when interpreting pooled recordings, or modeling networks of cells that receive inputs from large presynaptic populations. We also show that the frequently observed runaway synchrony in feedforward chains is primarily due to the pooling of correlated inputs.
尖峰脉冲序列之间的相关性可以强烈调节神经元的活动，并影响神经元编码信息的能力。神经元整合来自数千个传入的输入。同样，许多实验技术被设计用来记录群体细胞的活动。我们回顾和总结了许多以前的结果，这些结果表明，在反映它们集体活动的信号中，群体中细胞之间的相关性如何被放大和扭曲。基础神经元反应的结构会显著影响此类汇总信号之间的相关性。因此，在解释汇总记录或对接收来自大突触前群体输入的细胞网络进行建模时，需要谨慎。我们还表明，在前馈链中经常观察到的失控同步主要是由于相关输入的汇总。
