Vagal stimulation what is

The prospects for resolving these questions in an experiment are clearly limited. Added to these difficulties is the fact that the neural control system of the heart is a multilevel network [14]. As such, it is not known how effects of VNS therapy influence the dynamics of cardiac control.

Similar questions arise in cranial nerve stimulation which is a growing therapeutical strategy for treating epilepsy and various psychiatric disorders [15] — [22]. In this paper we present a model in which the direct and the indirect pathways of VNS therapy on individual elements of the cardiac hierarchy can be isolated. This permits understanding the putative complexity of cardiac responsiveness to such therapy.

By selectively activating the different elements of the VSC and observing their individual impact on the cardiac control hierarchy, our aim is to establish a relationship between stimulation of the various components of the VSC and the ensuing effects within the neural control hierarchy of the heart.

In the classical view, neural control of the heart was explained mainly in terms of central neural command, specifically in terms of medullary and spinal cord autonomic efferent preganglionic neurons targeting efferent postganglionic neurons that innervate the heart [23]. In recent years it has become clear that there is a 3-level hierarchy of cardiac control, two of these residing outside the central nervous system, specifically 1 within the intrinsic cardiac nervous system and 2 within intrathoracic extracardiac ganglia.

The results we present in this paper are based on a model of this 3-level control system which has previously been shown to explain heart rate phenomena which could not be explained with the classical view of cardiac control by central command [14] , [24] , [25].

A key feature of this model is that each of the three levels of control is assumed to consist of a population of neurons which influence and are influenced by each other at their own level of control as well as at adjacent levels. Two indices, are used to identify the neuron at the level. The state of activity level of discharge of neuron at time interval is denoted by for sympathetic control, for indirect parasympathetic control, and for direct parasympathetic control as explained in more detail below.

All neural activity is scaled to range between 1. Broadly speaking, the neural network receives continuous neuronal updates of current demand for blood flow and current heart rate, and processes this state of the system at each time interval to produce an appropriate change in heart rate.

The main result of this process, which is a key feature of the model, is that demand for blood flow does not proceed directly to the heart or to central command but to the neural network as a whole.

The way this occurs is described briefly below, more details can be found in [14] , [24]. Heart rate is constrained to lie between a prescribed base value and a prescribed maximum value. The average activity of sympathetic efferent postganglionic neurons at the cardiac level is used as an external input to motor neurons at the cardiac level such that the efferent sympathetic neural input to the heart satisfies 1 where is a sympathetic gain, is a sympathetic time constant, is a sympathetic reference level and 2 where is the number of sympathetic neurons at the cardiac level.

Indirect parasympathetic efferent preganglionic neural activity passes through the neural network and appears as input to parasympathetic efferent postganglionic motor neurons at the cardiac level such that the efferent indirect parasympathetic neural input to the heart satisfies 3 where is an indirect parasympathetic gain, is indirect parasympathetic time constant, is the indirect parasympathetic reference level and 4 where is the number of indirect parasympathetic neurons at the cardiac level.

Within each time interval , heart rate is a continuous function of time governed by a first order linear system 7 where is a time constant and 8. For simplicity, this time dependence will not be shown explicitly in what follows but will be implicit within each time interval. In general, the level of activity of a neuron neural discharge is determined by the demand for blood flow but is also affected by current heart rate and by the level of activity of neighboring neurons.

Specifically, the action potential generated by a neuron within the network in time interval is represented by the state of activity of that neuron.

A change in the state of activity of the neuron due to these effects shall be denoted respectively by , , , and total change by. Thus the change in the state of activity of a sympathetic neuron is given by 9 10 and the corresponding change in the state of activity of an indirect parasympathetic neuron is similarly given by 11 It is a key feature of the model whereby every neuron within the network influences and is influenced by other neurons.

Networking is represented by in Eqs. The extent of networking between a particular neuron and its neighboring neurons , upper case being used to represent neighboring neurons is determined by the weighted sum of the difference prevailing in time interval between the state of activity of that neuron and the states of activity of the neighboring neurons. Thus, for a sympathetic neuron we have 17 and for a parasympathetic neuron 18 where is a weighting, a measure of the connectivity between neuron and its neighbor.

Vagal stimulation experiments described below were performed on intact dogs specifically to demonstrate threshold phenomena in observed heart rate changes as the level of VNS stimulation was gradually increased from zero. Response to VNS was examined in the conscious and anesthetized states.

We have found in previous studies that both in the conscious see Experimental Results section and anesthetized [12] , [28] states the system maintains bidirectional sensitivity. The main results we present are based on the response to VNS from an animal that was anesthetized. We also show the average response to VNS from 7 animals that were in the conscious state. Following a two week recovery period, animals were trained to the Pavlov stand.

Heart rate responses were quantified by the percent change from the baseline in response to VNS as shown in the results. The left femoral vein was catheterized to allow fluid replacement as well as the administration of anesthetic and pharmacological agents.

Left ventricular chamber pressure was measured via a 5-Fr Mikro-Tip pressure transducer catheter Millar Instruments, Houston, TX inserted into that chamber via the left femoral artery. The right femoral artery was catheterized to monitor aortic pressure using another Mikro-Tip transducer. All hemodynamic data were digitized Cambridge Electronic Design power acquisition system with Spike 2 software for subsequent off-line analysis.

Following a ventral midline incision, both cervical vagosympathetic nerve trunks were isolated. For the right cervical vagosympathetic trunk, a bipolar helical cuff stimulation electrode Cyberonics, Inc was placed around that nerve, with the distal electrode positioned distal to the head.

Throughout all surgical procedures, depth of anesthesia was assessed by monitoring corneal reflexes, jaw tone and alterations in cardiovascular indices. The right cervical vagus was stimulated electrically with current intensities ranging from 0. We employed a stimulus isolation unit Grass model PSIU6 photoelectric isolation unit which was connected to the Grass stimulator to active the vagosympathetic complex with constant current for anesthetized studies.

This is illustrated in Figures 1 — 4 in which the intensity of stimulation was at baseline 0. At the lowest intensity, heart rate response to stimulation is inconsistent and barely noticeable. At the intermediate intensity of 0. While these results were based on an anesthetized animal, the average response to VNS from 7 animals that were in the conscious state is shown in Figure 5.

Note the variations in heart rate that occur in the normal state. No discernible heart rate changes are observed. Pronounced tachycardia is observed. Pronounced bradycardia is observed. The model simulations described in what follows were designed to examine the interplay between the direct and the indirect pathways to the heart as the VSC is stimulated at different intensities. While in the experiment these pathways cannot be separated, in the model they can be activated with different intensities and independently from each other or can actually be turned on or off entirely.

The two effects are applied simultaneously and continuously while stimulation is ON, and to both sympathetic and parasympathetic local circuit neurons. Stimulation of the direct component is implemented by an increase in the intensity of the efferent direct parasympathetic input to the heart a r in Eq.

It is important to point out that while the progression of this stimulation intensity in the model from zero to higher levels will mimic the corresponding progression of stimulation in the experiment, it is not possible to actually relate the levels of these two stimulation intensities in any direct way. Instead, in what follows we present the effect on heart rate only as the stimulation intensity is progressively increased from zero.

The pattern of heart rate with zero stimulation is shown in Figure 6. The oscillatory pattern and the variability in that pattern is similar to that observed in the experiment Figure 1 and is typical at low blood demand and in the presence of low level noise within the system [14].

Brief intervals of resonance whereby the oscillations are subdued can be observed in both cases. Brief intervals of resonance, whereby the oscillations are subdued, can be observed in both cases. Subthreshold: As the level of stimulation is increased from zero in the model the effect on heart rate is barely visible, as observed in Figure 7.

Here the direct component of the VSC is turned off and the indirect component is minimally stimulated as described above. It is important to point out that while the direct component of the VSC is not being activated at this level of stimulation, the indirect component of the VSC and therefore the local circuit elements of the neural network are being activated.

This has important implications which will be discussed later. Here, as in the experiment Figure 2 , there are no discernible changes in heart rate. Red bars indicate time intervals when VNS is on. Sympathetic Threshold: As the level of stimulation is increased above the subthreshold level, but with the direct component of the VSC remaining OFF, a significant tachycardia occurs as shown in Figure 8. Within the construct of the model, this is clearly because we have chosen to make the indirect component of the VSC dominant over the direct element.

Pronounced tachycardia is observed, similar to that seen in the experiment under moderate intensity stimulation Figure 3. Parasympathetic Threshold: Finally, as the level of activation of the direct component of the VSC is gradually increased from zero, with the level of stimulation of the indirect component being maintained under the sympathetic threshold conditions, the parasympathetic elements of the direct component of the VSC become dominant. The central nervous system is made up of the brain and spinal cord.

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