Modulation of respiratory sinus arrhythmia in rats with central pattern generator hardware

Respiratory-cardiovascular interactions

Much of biology is rhythmical and comprises oscillators that can couple. These have optimized energy efficiency and have been preserved during evolution. The respiratory and cardiovascular systems contain numerous oscillators, and importantly, they couple. This coupling is dynamic but essential for an efficient transmission of neural information critical for the precise linking of breathing and oxygen delivery while permitting adaptive responses to changes in state. The respiratory pattern generator and the neural network responsible for sympathetic and cardiovagal (parasympathetic) tone generation interact at many levels ensuring that cardiac output and regional blood flow match oxygen delivery to the lungs and tissues efficiently. The most classic manifestations of these interactions are respiratory sinus arrhythmia and the respiratory modulation of sympathetic nerve activity. These interactions derive from shared somatic and cardiopulmonary afferent inputs, reciprocal interactions between brainstem networks and inputs from supra-pontine regions. Disrupted respiratory-cardiovascular coupling can result in disease, where it may further the pathophysiological sequelae and be a harbinger of poor outcomes. This has been well documented by diminished respiratory sinus arrhythmia and altered respiratory sympathetic coupling in animal models and/or patients with myocardial infarction, heart failure, diabetes mellitus, and neurological disorders as stroke, brain trauma, Parkinson disease, or epilepsy. Future research needs to assess the therapeutic potential for ameliorating respiratory-cardiovascular coupling in disease.

Reverse re-modelling chronic heart failure by reinstating heart rate variability

Heart rate variability (HRV) is a crucial indicator of cardiovascular health. Low HRV is correlated with disease severity and mortality in heart failure. Heart rate increases and decreases with each breath in normal physiology termed respiratory sinus arrhythmia (RSA). RSA is highly evolutionarily conserved, most prominent in the young and athletic and is lost in cardiovascular disease. Despite this, current pacemakers either pace the heart in a metronomic fashion or sense activity in the sinus node. If RSA has been lost in cardiovascular disease current pacemakers cannot restore it. We hypothesized that restoration of RSA in heart failure would improve cardiac function. Restoration of RSA in heart failure was assessed in an ovine model of heart failure with reduced ejection fraction. Conscious 24 h recordings were made from three groups, RSA paced (n = 6), monotonically paced (n = 6) and heart failure time control (n = 5). Real-time blood pressure, cardiac output, heart rate and diaphragmatic EMG were recorded in all animals. Respiratory modulated pacing was generated by a proprietary device (Ceryx Medical) to pace the heart with real-time respiratory modulation. RSA pacing substantially increased cardiac output by 1.4 L/min (20%) compared to contemporary (monotonic) pacing. This increase in cardiac output led to a significant decrease in apnoeas associated with heart failure, reversed cardiomyocyte hypertrophy, and restored the T-tubule structure that is essential for force generation. Re-instating RSA in heart failure improves cardiac function through mechanisms of reverse re-modelling; the improvement observed is far greater than that seen with current contemporary therapies. These findings support the concept of re-instating RSA as a regime for patients who require a pacemaker.

Optimal solid state neurons

Bioelectronic medicine is driving the need for neuromorphic microcircuits that integrate raw nervous stimuli and respond identically to biological neurons. However, designing such circuits remains a challenge. Here we estimate the parameters of highly nonlinear conductance models and derive the ab initio equations of intracellular currents and membrane voltages embodied in analog solid-state electronics. By configuring individual ion channels of solid-state neurons with parameters estimated from large-scale assimilation of electrophysiological recordings, we successfully transfer the complete dynamics of hippocampal and respiratory neurons in silico. The solid-state neurons are found to respond nearly identically to biological neurons under stimulation by a wide range of current injection protocols. The optimization of nonlinear models demonstrates a powerful method for programming analog electronic circuits. This approach offers a route for repairing diseased biocircuits and emulating their function with biomedical implants that can adapt to biofeedback.

Inhibition delay increases neural network capacity through Stirling transform

Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2)^{-N}-fold increase in capacity for an N-neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

Utility of a Novel Biofeedback Device for Within-Breath Modulation of Heart Rate in Rats: A Quantitative Comparison of Vagus Nerve vs. Right Atrial Pacing

In an emerging bioelectronics era, there is a clinical need for physiological devices incorporating biofeedback that permits natural and demand-dependent control in real time. Here, we describe a novel device termed a central pattern generator (CPG) that uses cutting edge analog circuitry producing temporally controlled, electrical stimulus outputs based on the real time integration of physiological feedback. Motivated by the fact that respiratory sinus arrhythmia (RSA), which is the cyclical changes in heart rate every breath, is an essential component of heart rate variability (HRV) (an indicator of cardiac health), we have explored the versatility and efficiency of the CPG for producing respiratory modulation of heart rate in anesthetized, spontaneously breathing rats. Diaphragmatic electromyographic activity was used as the input to the device and its output connected to either the right cervical vagus nerve or the right atrium for pacing heart rate. We found that the CPG could induce respiratory related heart rate modulation that closely mimicked RSA. Whether connected to the vagus nerve or right atrium, the versatility of the device was demonstrated by permitting: (i) heart rate modulation in any phase of the respiratory cycle, (ii) control of the magnitude of heart rate modulation, and (iii) instant adaptation to changes in respiratory frequency. Vagal nerve pacing was only possible following transection of the nerve limiting its effective use chronically. Pacing via the right atrium permitted better flexibility and control of heart rate above its intrinsic level. This investigation now lays the foundation for future studies using this biofeedback technology permitting closer analysis of both the function and dysfunction of RSA.

Experimental observation of multistability and dynamic attractors in silicon central pattern generators

We report on the multistability of chaotic networks of silicon neurons and demonstrate how spatiotemporal sequences of voltage oscillations are selected with timed current stimuli. A three neuron central pattern generator was built by interconnecting Hodgkin-Huxley neurons with mutually inhibitory links mimicking gap junctions. By systematically varying the timing of current stimuli applied to individual neurons, we generate the phase lag maps of neuronal oscillators and study their dependence on the network connectivity. We identify up to six attractors consisting of triphasic sequences of unevenly spaced pulses propagating clockwise and anticlockwise. While confirming theoretical predictions, our experiments reveal more complex oscillatory patterns shaped by the ratio of the pulse width to the oscillation period. Our work contributes to validating the command neuron hypothesis.

Silicon central pattern generators for cardiac diseases

Cardiac rhythm management devices provide therapies for both arrhythmias and resynchronisation but not heart failure, which affects millions of patients worldwide. This paper reviews recent advances in biophysics and mathematical engineering that provide a novel technological platform for addressing heart disease and enabling beat-to-beat adaptation of cardiac pacing in response to physiological feedback. The technology consists of silicon hardware central pattern generators (hCPGs) that may be trained to emulate accurately the dynamical response of biological central pattern generators (bCPGs). We discuss the limitations of present CPGs and appraise the advantages of analog over digital circuits for application in bioelectronic medicine. To test the system, we have focused on the cardio-respiratory oscillators in the medulla oblongata that modulate heart rate in phase with respiration to induce respiratory sinus arrhythmia (RSA). We describe here a novel, scalable hCPG comprising physiologically realistic (Hodgkin-Huxley type) neurones and synapses. Our hCPG comprises two neurones that antagonise each other to provide rhythmic motor drive to the vagus nerve to slow the heart. We show how recent advances in modelling allow the motor output to adapt to physiological feedback such as respiration. In rats, we report on the restoration of RSA using an hCPG that receives diaphragmatic electromyography input and use it to stimulate the vagus nerve at specific time points of the respiratory cycle to slow the heart rate. We have validated the adaptation of stimulation to alterations in respiratory rate. We demonstrate that the hCPG is tuneable in terms of the depth and timing of the RSA relative to respiratory phase. These pioneering studies will now permit an analysis of the physiological role of RSA as well as its any potential therapeutic use in cardiac disease.