Individual aortic baroreceptors are sensitive to different ranges of blood pressures

Responses of Nucleus Tractus Solitarius (NTS) early and late neurons to blood pressure changes in anesthetized F344 rats

Previously, many different types of NTS barosensitive neurons were identified. However, the time course of NTS barosensitive neuronal activity (NA) in response to arterial pressure (AP) changes, and the relationship of NA-AP changes, have not yet been fully quantified. In this study, we made extracellular recordings of single NTS neurons firing in response to AP elevation induced by occlusion of the descending aorta in anesthetized rats. Our findings were that: 1) Thirty-five neurons (from 46 neurons) increased firing, whereas others neurons either decreased firing upon AP elevation, or were biphasic: first decreased firing upon AP elevation and then increased firing during AP decrease. 2) Fourteen neurons with excitatory responses were activated and rapidly increased their firing during the early phase of AP increase (early neurons); whereas 21 neurons did not increase firing until the mean arterial pressure changes (ΔMAP) reached near/after the peak (late neurons). 3) The early neurons had a significantly higher firing rate than late neurons during AP elevation at a similar rate. 4) Early neuron NA-ΔMAP relationship could be well fitted and characterized by the sigmoid logistic function with the maximal gain of 29.3. 5) The increase of early NA correlated linearly with the initial heart rate (HR) reduction. 6) The late neurons did not contribute to the initial HR reduction. However, the late NA could be well correlated with HR reduction during the late phase. Altogether, our study demonstrated that the NTS excitatory neurons could be grouped into early and late neurons based on their firing patterns. The early neurons could be characterized by the sigmoid logistic function, and different neurons may differently contribute to HR regulation. Importantly, the grouping and quantitative methods used in this study may provide a useful tool for future assessment of functional changes of early and late neurons in disease models.

Identification of neural firing patterns, frequency and temporal coding mechanisms in individual aortic baroreceptors

In rabbit depressor nerve fibers, an on-off firing pattern, period-1 firing, and integer multiple firing with quiescent state were observed as the static pressure level was increased. A bursting pattern with bursts at the systolic phase of blood pressure, continuous firing, and bursting with burst at diastolic phase and quiescent state at systolic phase were observed as the mean level of the dynamic blood pressure was increased. For both static and dynamic pressures, the firing frequency of the first two firing patterns increased and of the last firing pattern decreased due to the quiescent state. If the quiescent state is disregarded, the spike frequency becomes an increasing trend. The instantaneous spike frequency of the systolic phase bursting, continuous firing, and diastolic phase bursting can reflect the temporal process of the systolic phase, whole procedure, and diastolic phase of the dynamic blood pressure signal, respectively. With increasing the static current corresponding to pressure level, the deterministic Hodgkin-Huxley (HH) model manifests a process from a resting state first to period-1 firing via a subcritical Hopf bifurcation and then to a resting state via a supercritical Hopf bifurcation, and the firing frequency increases. The on-off firing and integer multiple firing were here identified as noise-induced firing patterns near the subcritical and supercritical Hopf bifurcation points, respectively, using the stochastic HH model. The systolic phase bursting and diastolic phase bursting were identified as pressure-induced firings near the subcritical and supercritical Hopf bifurcation points, respectively, using an HH model with a dynamic signal. The firing, spike frequency, and instantaneous spike frequency observed in the experiment were simulated and explained using HH models. The results illustrate the dynamics of different firing patterns and the frequency and temporal coding mechanisms of aortic baroreceptor.