Control of colonic motility using electrical stimulation to modulate enteric neural activity

Electrical stimulation of the enteric nervous system (ENS) is an attractive approach to modify gastrointestinal transit. Colonic motor complexes (CMCs) occur with a periodic rhythm, but the ability to elicit a premature CMC depends, at least in part, upon the intrinsic refractory properties of the ENS, which are presently unknown. The objectives of this study were to record myoelectric complexes (MCs, the electrical correlates of CMCs) in the smooth muscle and (i) determine the refractory periods of MCs, (ii) inform and evaluate closed-loop stimulation to repetitively evoke MCs, and (iii) identify stimulation methods to suppress MC propagation. We dissected the colon from male and female C57BL/6 mice, preserving the integrity of intrinsic circuitry while removing the extrinsic nerves, and measured properties of spontaneous and evoked MCs in vitro. Hexamethonium abolished spontaneous and evoked MCs, confirming the necessary involvement of the ENS for electrically-evoked MCs. Electrical stimulation reduced the mean interval between evoked and spontaneous CMCs (24.6 ± 3.5 vs 70.6 ± 15.7 s, p = 0.0002, n = 7). The absolute refractory period was 4.3 s (95% CI = 2.8 - 5.7 s, R2 = 0.7315, n = 8). Electrical stimulation applied during fluid distention-evoked MCs led to an arrest of MC propagation, and following stimulation, MC propagation resumed at an increased velocity (n = 9). The timing parameters of electrical stimulation increased the rate of evoked MCs and the duration of entrainment of MCs, and the refractory period provides insight into timing considerations for designing neuromodulation strategies to treat colonic dysmotility.

Real-Time Closed-Loop Suppression of Repolarization Alternans Reduces Arrhythmia Susceptibility In Vivo

Background: Repolarization alternans (RA) has been implicated in the pathogenesis of ventricular arrhythmias and sudden cardiac death. Methods: We have developed a real-time, closed-loop system to record and analyze RA from multiple intracardiac leads, and deliver dynamically R-wave triggered pacing stimuli during the absolute refractory period. We have evaluated the ability of this system to control RA and reduce arrhythmia susceptibility, in vivo. Results: R-wave triggered pacing can induce RA, the magnitude of which can be modulated by varying the amplitude, pulse width, and size of the pacing vector. Using a swine model (n=9), we demonstrate that to induce a 1 µV change in the alternans voltage on the body surface, coronary sinus and left ventricle leads, requires a delivered charge of 0.04±0.02, 0.05±0.025, and 0.06±0.033 µC, respectively, while to induce a one unit change of the K score , requires a delivered charge of 0.93±0.73, 0.32±0.29, and 0.33±0.37 µC, respectively. For all body surface and intracardiac leads, both Δ(alternans voltage) and ΔK score between baseline and R-wave triggered paced beats increases consistently with an increase in the pacing pulse amplitude, pulse width, and vector spacing. Additionally, we show that the proposed method can be used to suppress spontaneously occurring alternans (n=7), in the presence of myocardial ischemia. Suppression of RA by pacing during the absolute refractory period results in a significant reduction in arrhythmia susceptibility, evidenced by a lower S rank score during programmed ventricular stimulation compared with baseline before ischemia. Conclusions: We have developed and evaluated a novel closed-loop method to dynamically modulate RA in a swine model. Our data suggest that suppression of RA directly reduces arrhythmia susceptibility and reinforces the concept that RA plays a critical role in the pathophysiology of arrhythmogenesis.

Damped oscillations of the probability of random events followed by absolute refractory period

Many events are followed by an absolute refractory state, when for some time after the event a repetition of a similar event is impossible. If uniform events, each of which is followed by the same period of absolute refractoriness, occur randomly, as in the Bernoulli scheme, then the event probability as a function of time can exhibit damped transient oscillations caused by a specific initial condition. Here we give an exact analytical description of the oscillations, with a focus on application within neuroscience. The resulting formulas stand out for their relative simplicity, enabling analytical calculation of the damping coefficients for the second and third peaks of the event probability.

Inferring causal connectivity from pairwise recordings and optogenetics

To study how the brain works, it is crucial to identify causal interactions between neurons, which is thought to require perturbations. However, when using optogenetics we typically perturb multiple neurons, producing a confound - any of the stimulated neurons can have affected the postsynaptic neuron. Here we show how this produces large biases, and how they can be reduced using the instrumental variable (IV) technique from econometrics. The interaction between stimulation and the absolute refractory period produces a weak, approximately random signal which can be exploited to estimate causal connectivity. When simulating integrate-and-fire neurons, we find that estimates from IV are better than naïve techniques (R2= 0.77 vsR2= 0.01). The difference is important as the estimates disagree when applied to experimental data from stimulated neurons with recorded spiking activity. Presented is a robust analysis framework for mapping out network connectivity based on causal neuron interactions.

Multistability in Spiking Neuron Models of Delayed Recurrent Inhibitory Loops

We consider the effect of the effective timing of a delayed feedback on the excitatory neuron in a recurrent inhibitory loop, when biological realities of firing and absolute refractory period are incorporated into a phenomenological spiking linear or quadratic integrate-and-fire neuron model. We show that such models are capable of generating a large number of asymptotically stable periodic solutions with predictable patterns of oscillations. We observe that the number of fixed points of the so-called phase resetting map coincides with the number of distinct periods of all stable periodic solutions rather than the number of stable patterns. We demonstrate how configurational information corresponding to these distinct periods can be explored to calculate and predict the number of stable patterns.