Metrics of high cofluctuation and entropy to describe control of cardiac function in the stellate ganglion.

Stellate ganglia within the intrathoracic cardiac control system receive and integrate central, peripheral, and cardiopulmonary information to produce postganglionic cardiac sympathetic inputs. Pathological anatomical and structural remodeling occurs within the neurons of the stellate ganglion (SG) in the setting of heart failure (HF). A large proportion of SG neurons function as interneurons whose networking capabilities are largely unknown. Current therapies are limited to targeting sympathetic activity at the cardiac level or surgical interventions such as stellectomy, to treat HF. Future therapies that target the SG will require understanding of their networking capabilities to modify any pathological remodeling. We observe SG networking by examining cofluctuation and specificity of SG networked activity to cardiac cycle phases. We investigate network processing of cardiopulmonary transduction by SG neuronal populations in porcine with chronic pacing-induced HF and control subjects during extended in-vivo extracellular microelectrode recordings. We find that information processing and cardiac control in chronic HF by the SG, relative to controls, exhibits: (i) more frequent, short-lived, high magnitude cofluctuations, (ii) greater variation in neural specificity to cardiac cycles, and (iii) neural network activity and cardiac control linkage that depends on disease state and cofluctuation magnitude.

Studying Cardiac Neural Network Dynamics: Challenges and Opportunities for Scientific Computing.

Neural control of the heart involves continuous modulation of cardiac mechanical and electrical activity to meet the organism's demand for blood flow. The closed-loop control scheme consists of interconnected neural networks with central and peripheral components working cooperatively with each other. These components have evolved to cooperate control of various aspects of cardiac function, which produce measurable "functional" outputs such as heart rate and blood pressure. In this review, we will outline fundamental studies probing the cardiac neural control hierarchy. We will discuss how computational methods can guide improved experimental design and be used to probe how information is processed while closed-loop control is operational. These experimental designs generate large cardio-neural datasets that require sophisticated strategies for signal processing and time series analysis, while presenting the usual large-scale computational challenges surrounding data sharing and reproducibility. These challenges provide unique opportunities for the development and validation of novel techniques to enhance understanding of mechanisms of cardiac pathologies required for clinical implementation.

A novel metric linking stellate ganglion neuronal population dynamics to cardiopulmonary physiology.

Cardiopulmonary sympathetic control is exerted via stellate ganglia (SG); however, little is known about how neuronal firing patterns in the stellate ganglion relate to dynamic physiological function in the heart and lungs. We performed continuous extracellular recordings from SG neurons using multielectrode arrays in chloralose-anesthetized pigs (n = 6) for 8-9 h. Respiratory and left ventricular pressures (RP and LVP, respectively) and the electrocardiogram (ECG) were recorded concomitantly. Linkages between sampled spikes and LVP or RP were determined using a novel metric to evaluate specificity in neural activity for phases of the cardiac and pulmonary cycles during resting conditions and under various cardiopulmonary stressors. Firing frequency (mean 4.6 ± 1.2 Hz) varied spatially across the stellate ganglion, suggesting regional processing. The firing pattern of most neurons was synchronized with both cardiac (LVP) and pulmonary (RP) activity indicative of cardiopulmonary integration. Using the novel metric to determine cardiac phase specificity of neuronal activity, we found that spike density was highest during diastole and near-peak systole. This specificity was independent of the actual LVP or population firing frequency as revealed by perturbations to the LVP. The observed specificity was weaker for RP. Stellate ganglion neuronal populations exhibit cardiopulmonary integration and profound specificity toward the near-peak systolic phase of the cardiac cycle. This novel approach provides practically deployable tools to probe stellate ganglion function and its relationship to cardiopulmonary pathophysiology.NEW & NOTEWORTHY Activity of stellate ganglion neurons is often linking indirectly to cardiac function. Using novel approaches coupled with extended period of recordings in large animals, we link neuronal population dynamics to mechanical events occurring at near-peak systole. This metric can be deployed to probe stellate ganglion neuronal control of cardiopulmonary function in normal and disease states.