Respiratory neuronal assemblies.

Abstract

This review describes results from in vivo experiments on brain stem network mechanisms that control breathing. Multi-array recording technology and computational methods were used to test predictions derived from simulations of respiratory network models. This highly efficient approach has the advantage that many simultaneously recorded neurons are subject to shared stimulus, history, and state-dependent conditions. Our results have provided evidence for concurrent or parallel network interactions in the generation and modulation of the respiratory motor pattern. Recent data suggest that baroreceptors, chemoreceptors, nociceptors, and airway cough receptors shape the respiratory motor pattern, at least in part, through a system of shared coordinated 'multifunctional' neurons distributed in the brain stem. The 'gravity method' for the analysis and representation of multi-neuron data has demonstrated respiratory phase-dependent impulse synchrony among neurons with no respiratory modulation of their individual firing rates. The detection of this emergent property motivated the development of pattern detection methods that subsequently identified repeated transient configurations of these 'correlational assemblies'. These results support the view that information can be 'coded' in the nervous system by spike timing relationships, in addition to firing rate changes that traditionally have been measured by neurophysiologists.