Network mechanisms for respiratory rhythm generation

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DESCRIPTION (provided by applicant): New evidence indicates that two mechanistically distinct, spatially separate networks can independently generate respiratory rhythm. We propose that the two networks in concert meet the conflicting demands of adaptive-ness and robustness required for the maintenance of blood-gas homeostasis. This new finding puts emphasis on the role of network interactions in rhythm generation. Because preparations currently available allow easy access to neurons but are too reduced (transverse slice preparation), or retain the networks of interest but do not allow easy access to them (en bloc preparation), we have developed a tilted saggital slice preparation that retains the networks present en bloc but affords good access to the networks of interest. We used optical recordings using a membrane permeable Ca++ indicator to determine the best parameters for cutting the slice, and use optical recording techniques routinely to monitor local network activity along the column of respiration modulated neurons in ventrolateral medulla that are exposed at the surface of the saggital slice. We will use optical signals to identify 2 classes of endogenously bursting respiratory neurons for detailed investigation using intracellular recording techniques. These endogenous bursters differ in that one population changes its bursting frequency as a function of membrane potential (voltage-dependent endogenous burster; VDEB), while the other does not (voltage-independent endogenous burster; VIEB). Due to this difference, VDEB cycle period can be altered by transient de- or hyperpolarizing impulses; while VIEBs will be less sensitive to such inputs. This provides a mechanism for our hypothesis; we propose that VDEBs mediate cycle-to-cycle adaptiveness to respiratory rhythm-generating networks, while VIEBs maintain network stability by rapidly restoring baseline rhythm. We propose to test this hypothesis at the network level, by selectively modulating VIEB and VDEB networks, and at the single neuron level, by characterizing perturbation responses in synaptically isolated VIEBs and VDEBs.