Brody CD
Lab 126, Instituto de Fisiologia Celular S/N, Ciudad Universitaria, Universidad Nacional Autonoma de Mexico, Apartado Postal 70-523 C.P. 04510, Lab 126, Mexico DF 04510 MEXICO.
Neural Comput. 1999 Oct 1;11(7):1537-51. doi: 10.1162/089976699300016133.
Peaks in spike train correlograms are usually taken as indicative of spike timing synchronization between neurons. Strictly speaking, however, a peak merely indicates that the two spike trains were not independent. Two biologically plausible ways of departing from independence that are capable of generating peaks very similar to spike timing peaks are described here: covariations over trials in response latency and covariations over trials in neuronal excitability. Since peaks due to these interactions can be similar to spike timing peaks, interpreting a correlogram may be a problem with ambiguous solutions. What peak shapes do latency or excitability interactions generate? When are they similar to spike timing peaks? When can they be ruled out from having caused an observed correlogram peak? These are the questions addressed here. The previous article in this issue proposes quantitative methods to tell cases apart when latency or excitability covariations cannot be ruled out.
脉冲序列互相关图中的峰值通常被视为神经元之间脉冲发放时间同步的指标。然而,严格来说,一个峰值仅仅表明这两个脉冲序列并非相互独立。这里描述了两种生物学上合理的偏离独立性的方式,它们能够产生与脉冲发放时间峰值非常相似的峰值:试验中反应潜伏期的协变以及试验中神经元兴奋性的协变。由于这些相互作用导致的峰值可能与脉冲发放时间峰值相似,所以解释互相关图可能会出现有多种模糊答案的问题。潜伏期或兴奋性相互作用会产生什么样的峰值形状?它们何时与脉冲发放时间峰值相似?何时可以排除它们导致观察到的互相关图峰值的可能性?这些就是本文要解决的问题。本期的上一篇文章提出了一些定量方法,以便在无法排除潜伏期或兴奋性协变的情况下区分不同情况。