Consistency and signal strength of respiratory neuronal activity.
Consistency and signal strength of respiratory neuronal activity.
复制标题
呼吸神经元活动的一致性和信号强度。
DOI：
10.1152/jn.1983.50.5.1098
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发表时间：
1983
影响因子：
2.5
通讯作者：
Dick,T
中科院分区：
文献类型：
--
作者：
Orem,J;Dick,T
本研究关注的是分类学。我们证明了呼吸神经元活动的定义特征。这个特征是呼吸细胞活动中呼吸成分的程度或大小。呼吸活动的基本特征是它与呼吸周期的某个部分同步发生。因此，神经元活动可以排列在一个矩阵中，其中列是呼吸周期的分数，行是呼吸，正如Netick和Orem（10）所示，可以用方差分析来分析这个矩阵，以确定活动是否包含呼吸成分。然而，方差分析表明没有关于统计上显著的呼吸分量的大小。我们假设，不同呼吸细胞活性中呼吸成分的大小在细胞间不同，但在任何给定细胞中是一个稳定的特征。用于量化呼吸活动程度的指数是eta 2，呼吸神经元活动的总方差的比例，包括呼吸周期各部分之间发生的方差。该指数理论上取决于a）呼吸周期中的活动水平范围和活动水平在该范围内的分散（表示呼吸信号强度的参数）和B）呼吸中细胞活动的变化（表示呼吸活动一致性的参数）。理论上，eta 2值可以在0.0至1.0之间变化，分别表明呼吸效应不能解释或解释细胞活性在呼吸过程中的所有变化。用eta 2分析慢性猫非快动眼睡眠（NREM）期间记录的32个延髓呼吸神经元活动中呼吸成分的大小。这些不同的呼吸细胞的活动模式与eta 2值范围从0.1到0.9。然而，给定细胞的活性产生的eta 2值在样品之间是一致的。因此，细胞活性的eta 2值是该细胞的定义性、稳定性特征。细胞活性的eta 2值与其放电模式的一致性有很强的相关性（rx，y = 0.975）。（400字处截断摘要）
The concerns of this study are taxonomic. We demonstrate a defining characteristic of respiratory neuronal activity. This characteristic is the degree or size of the respiratory component in the activity of a respiratory cell. The essential feature of respiratory activity is that it occurs in phase with some portion of the respiratory cycle. Therefore, neuronal activity can be arranged within a matrix in which the columns are fractions of the respiratory cycle and the rows are breaths and, as Netick and Orem (10) have shown, this matrix can be analyzed with an analysis of variance to determine whether the activity contains a respiratory component. However, the analysis of variance indicates nothing about the size of a statistically significant respiratory component. We hypothesized that the size of the respiratory component in the activity of different respiratory cells differed among cells but was a stable characteristic of any given cell. The index used to quantify the degree of respiratory activity was eta 2, the proportion of the total variance of the activity of a respiratory neuron consisting of the variance occurring across fractions of the respiratory cycle. This index theoretically depends on a) the range of activity levels across a respiratory cycle and the dispersion of activity levels over this range (parameters signifying the strength of the respiratory signal) and b) the variability in the activity of the cell across breaths (a parameter signifying the consistency of the respiratory activity). Theoretically, eta 2 values can vary from 0.0 to 1.0 indicating, respectively, that none or all of the variability in the activity of a cell across breaths is accounted for by a respiratory effect. eta 2 was used to analyze the size of the respiratory component in the activity of 32 medullary respiratory neurons recorded during nonrapid eye movement (NREM) sleep in chronic cats. These different respiratory cells had activity patterns with eta 2 values ranging from 0.1 to 0.9. However, the activity of a given cell produced eta 2 values that were consistent from sample to sample. Therefore, the eta 2 value of the activity of a cell was a defining, stable characteristic of that cell. The eta 2 values of the activity of the cells were strongly correlated with the consistency of their discharge pattern from breath to breath (r x,y = 0.975).(ABSTRACT TRUNCATED AT 400 WORDS)