König P
Max-Planck-Institut für Hirnforschung, Frankfurt, Germany.
J Neurosci Methods. 1994 Sep;54(1):31-7. doi: 10.1016/0165-0270(94)90157-0.
Interactions between neurones can be analysed by simultaneously recording from several cells and computing correlation functions between the respective activities. Recent studies have revealed that neuronal responses are often synchronous and exhibit an oscillatory temporal structure. These two properties are commonly assessed together from correlation functions. In order to evaluate these variables independently a method was devised for the quantification of a generalized Gabor function that was fitted to the correlograms. The performance of the method was tested on a large data set from cat area 17 and its stability was examined with respect to its dependence on the number of free parameters. The results demonstrate that the proposed fitting algorithm is robust in that it is rather independent of starting conditions and converges to optimal fits even with different settings of free variables. The fitted correlation function allow for an automatic and independent classification of synchrony on the one hand and oscillatory firing patterns on the other.
神经元之间的相互作用可以通过同时记录多个细胞并计算各自活动之间的相关函数来进行分析。最近的研究表明，神经元反应通常是同步的，并且呈现出振荡的时间结构。这两个特性通常一起从相关函数中进行评估。为了独立评估这些变量，设计了一种方法来量化拟合到相关图的广义伽博函数。该方法的性能在来自猫17区的一个大数据集上进行了测试，并就其对自由参数数量的依赖性检查了其稳定性。结果表明，所提出的拟合算法具有鲁棒性，因为它相当独立于起始条件，即使在自由变量的不同设置下也能收敛到最优拟合。拟合的相关函数一方面允许对同步性进行自动和独立的分类，另一方面允许对振荡放电模式进行分类。
