Fractal and multifractal characterization of in vitro respiratory recordings of the pre-Bötzinger complex

Abstract

The pre-Bötzinger complex is a neural network located in the ventrolateral brainstem that generates the respiratory rhythm. Under normoxic conditions, this area shows two inspiratory burst patterns, sigh and non-sigh. Several studies have shown that in vitro application of peptides, such as bombesin, stimulates the respiratory rate and increases the appearance of sighs. However, it is difficult to distinguish between sighs and non-sighs waveforms, which makes it difficult to study their properties under experimental conditions. The fractal and multifractal analysis have proven to be valuable tools for studying physiological time series, thus in this study, we applied this methodology to characterize sighs and non-sighs. Our results regarding fractality, shown that the sighs and non-sighs have similar Hurst exponents and that the application of bombesin only decreased the Hurst exponent of non-sighs. On the other hand, our results on multifractality parameters scaling exponent ($\tau \left(q\right)$) and generalized Hurst exponent ($H\left(q\right)$) shown that both sighs and non-sighs were multifractal and this remained even after the application of bombesin. Further analysis showed that sighs and non-sighs had different $H\left(q\right)$ values, which changed after the bombesin application. To quantitatively analyzed the multifractal spectrum, we calculated the area of the spectrum ($I_{\alpha }$), which was similar between sighs and non-sighs and the application of bombesin did not change this. Altogether, these results show that the analysis of fractal and multifractal parameters allows to characterize and find statistical differences of sighs and non-sighs within and between different experimental conditions.

Statement of Significance

The characterization of the respiratory recordings is very difficult and time consuming when is done manually by a researcher. An automated software that can aid this can be very useful. Furthermore, this gives some parameters that can help to statistically differentiate between sighs and non sighs. One interesting finding was that multifractality show differences in the same condition between sighs and non sighs. Also, we found that the neuropeptide bombesin increases the number of sighs without changing the intrinsic structure of the respiration system. This is important to avoid the collapse of the lungs that can be incorporated in mechanical ventilators. We hope that you will find our paper suitable for publication in Brain Multiphysics and will look forward to receiving your response.