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Spontaneous Activity of Hippocampal Cells in Various Physiological States

机译:不同生理状态下海马细胞的自发活动

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Time-series of interspike intervals from intracellular recordings in spontaneously firing hippocampal CA1 cells from rabbits are investigated. Slice preparations in three different experimental conditions are tested: immature from young rbbits up to seven postnatal days, mature from adult rabbits, and bicuculline-treated. also from adult rabbits. Bicuculline is a convulsion inducer through inhibition blockade. Preparations from immature rabbits show the dynamical behavior of a Poissonian process, while those from mature animals are periodically firing with additional Gaussian noise. Bicuculline-treated slices from mature animals show again the same dynamics as from immature, namely Poissonian noise. In addition to the Poissonian Processes in some immature and bicuculline preparations large proportions of bursts occur. We correct these bursts away and find better agreement with the null hypothesis of Poissonian processes. In some cases the frequent bursts even lead to signs of short time predictability, which is assumed to characterize deterministic chaos. However, we can also remove this predictability by burst correction. To test for stochasticity we use the Kolomogorov-Smirnov test which is especially well suited for small data sets like in the present experiments. Explicit graphical analysis of the distribution function provides useful qualitative comparison. The predictability tests for nonlinearity are applied to original data and its Gauss-scaled surrogates to test for any linearly correlated process. Conclusions for the dynamical interplay between excitatory and inhibitory networks are drawn.
机译:研究了自发激发兔海马CA1细胞中细胞内记录的峰间间隔的时间序列。测试了在三种不同实验条件下的切片制备物:年轻的rbbits直至出生后7天未成熟,成年兔子的成熟,以及bicuculline处理的。也来自成年兔子。 Bicuculline是通过抑制封锁引起的惊厥诱导剂。未成熟兔子的制备物表现出泊松过程的动力学行为,而成熟动物的制备物则周期性地发射高斯噪声。来自成年动物的双小分子处理的切片再次显示出与未成熟的相同的动力学,即泊松噪声。除泊松过程外,在某些未成熟和双小分子制剂中还会发生大比例的爆裂。我们纠正了这些突发现象,并与泊松过程的零假设找到了更好的一致性。在某些情况下,频繁的突发事件甚至会导致短期可预测性的迹象,这被认为是确定性混乱的特征。但是,我们也可以通过突发校正消除这种可预测性。为了测试随机性,我们使用Kolomogorov-Smirnov检验,该检验特别适合于像本实验这样的小型数据集。分布函数的显式图形分析提供了有用的定性比较。非线性的可预测性测试将应用于原始数据及其高斯比例的替代项,以测试任何线性相关的过程。得出了兴奋性和抑制性网络之间动态相互作用的结论。

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