Biocomplexity Of Respiratory Neural Network During Early Maturation

Previous studies in various animal models have shown that respiratory premotor and motor neurons undergo rapid changes in biochemical and bioelectric properties during the first month of postnatal life. Early in postnatal life, there is an increase in the complexity of the morphology of the dendritic tree of respiratory neurons as it changes from a bipolar to a multipolar morphology. During normal breathing (eupnea), the phrenic nerve has a slow, ramping output which reflects the orderly recruitment of phrenic motoneurons throughout inspiration when viewed in the time domain. Hypercapnia stimulates the respiratory system increasing both the respiratory frequency and amplitude. During severe hypoxia, the output of the phrenic nerve initially falls to zero and then returns with a completely different firing pattern, gasping. During gasping the phrenic nerve fires with an abrupt onset and rises rapidly to maximal neural activity with a decrementing decline. During recovery from hypoxia a variety of respiratory patterns between eupnea and gasping are seen in the time domain. Both the time and frequency analysis methods, however, give little information about the system generating the output. In contrast, the nonlinear dynamic neural analysis method we propose has been found to be a useful method for quantifying the complexity (irregularity) of both physical systems and physiological signals. The respiratory motor output depends on the integrated properties of the neural network. The phrenic neurogram that is generated by this network has features that reflect the dynamics of the respiratory pattern generator that we will use to develop our model. Our previous use of nonlinear dynamical analysis of phrenic neurograms in piglets showed that the complexity measures for the 3-6 days old group were higher than those of the 10-31 days old age group. Also, during hypoxic gasping the complexity measures of the phrenic neurogram were significantly reduced when the piglet was shi- - fted from eupnea to gasping regardless of age group. In addition, the complexity measure of the phrenic neurogram in piglets during severe hypoxia and early recovery following severe hypoxia were significantly reduced, but gradually became higher during reoxygenation (after 5 minutes of reoxygenation). These observations suggest that hypoxia reduces the complexity of the phrenic neurogram and reverses the configuration of respiratory neural network. The effect of hypercapnia on the complexity of respiratory output is not yet fully understood