Amorn Wongsarnpigoon

Energy-efficient waveform shapes for neural stimulation revealed with a genetic algorithm.

The energy efficiency of stimulation is an important consideration for battery-powered implantable stimulators. We used a genetic algorithm (GA) to determine the energy-optimal waveform shape for neural stimulation. The GA was coupled to a computational model of extracellular stimulation of a mammalian myelinated axon. As the GA progressed, waveforms became increasingly energy efficient and converged upon an energy-optimal shape. The results of the GA were consistent across several trials, and resulting waveforms resembled truncated Gaussian curves. When constrained to monophasic cathodic waveforms, the GA produced waveforms that were symmetric about the peak, which occurred approximately during the middle of the pulse. However, when the cathodic waveforms were coupled to rectangular charge-balancing anodic pulses, the location and sharpness of the peak varied with the duration and timing (i.e., before or after the cathodic phase) of the anodic phase. In a model of a population of mammalian axons and in vivo experiments on a cat sciatic nerve, the GA-optimized waveforms were more energy efficient and charge efficient than several conventional waveform shapes used in neural stimulation. If used in implantable neural stimulators, GA-optimized waveforms could prolong battery life, thereby reducing the frequency of recharge intervals, the volume of implanted pulse generators, and the costs and risks of battery-replacement surgeries.

Computational modeling of epidural cortical stimulation

Epidural cortical stimulation (ECS) is a developing therapy to treat neurological disorders. However, it is not clear how the cortical anatomy or the polarity and position of the electrode affects current flow and neural activation in the cortex. We developed a 3D computational model simulating ECS over the precentral gyrus. With the electrode placed directly above the gyrus, about half of the stimulus current flowed through the crown of the gyrus while current density was low along the banks deep in the sulci. Beneath the electrode, neurons oriented perpendicular to the cortical surface were depolarized by anodic stimulation, and neurons oriented parallel to the boundary were depolarized by cathodic stimulation. Activation was localized to the crown of the gyrus, and neurons on the banks deep in the sulci were not polarized. During regulated voltage stimulation, the magnitude of the activating function was inversely proportional to the thickness of the CSF and dura. During regulated current stimulation, the activating function was not sensitive to the thickness of the dura but was slightly more sensitive than during regulated voltage stimulation to the thickness of the CSF. Varying the width of the gyrus and the position of the electrode altered the distribution of the activating function due to changes in the orientation of the neurons beneath the electrode. Bipolar stimulation, although often used in clinical practice, reduced spatial selectivity as well as selectivity for neuron orientation.

Efficiency Analysis of Waveform Shape for Electrical Excitation of Nerve Fibers

Stimulation efficiency is an important consideration in the stimulation parameters of implantable neural stimulators. The objective of this study was to analyze the effects of waveform shape and duration on the charge, power, and energy efficiency of neural stimulation. Using a population model of mammalian axons and in vivo experiments on cat sciatic nerve, we analyzed the stimulation efficiency of four waveform shapes: square, rising exponential, decaying exponential, and rising ramp. No waveform was simultaneously energy-, charge-, and power-optimal, and differences in efficiency among waveform shapes varied with pulse width (PW). For short PWs (≤0.1 ms), square waveforms were no less energy-efficient than exponential waveforms, and the most charge-efficient shape was the ramp. For long PW s (≥ 0.5 ms), the square was the least energy-efficient and charge-efficient shape, but across most PW s, the square was the most power-efficient shape. Rising exponentials provided no practical gains in efficiency over the other shapes, and our results refute previous claims that the rising exponential is the energy-optimal shape. An improved understanding of how stimulation parameters affect stimulation efficiency will help improve the design and programming of implantable stimulators to minimize tissue damage and extend battery life.

Computer-based model of epidural motor cortex stimulation: Effects of electrode position and geometry on activation of cortical neurons

OBJECTIVE The aim of this study was to determine the effects of electrode placement, geometry, and polarity during epidural cortical stimulation (ECS) on thresholds for direct activation of cortical neurons. METHODS We used a computational model of epidural electrical stimulation of the motor cortex coupled to compartmental models of cortical neurons. RESULTS Thresholds varied with stimulation polarity and neuron position, and neurons deep within the sulci had much larger thresholds than those on the crowns or lips of the gyri. Axons were more excitable than cell bodies or dendrites. Delivering stimulation with the lead placed above or perpendicular to the sulci resulted in substantial stimulation of the gyri adjacent to the target gyrus. Electrode diameter and inter-electrode spacing influenced thresholds and affected the spread of activation in the cortex. CONCLUSIONS Electrode placement, geometry, and polarity during ECS influence excitation properties of cortical neurons substantially. SIGNIFICANCE Epidural leads have varying geometries, and in clinical studies of ECS the placement of the lead has been inconsistent. These results provide an improved understanding of the effects of electrode placement, geometry, and polarity on the outcome of ECS and can facilitate the rational implantation and programming of ECS systems.

Fabrication and evaluation of conductive elastomer electrodes for neural stimulation.

This study explored the feasibility of applying nanocomposites derived from conducting organic polymers and silicone elastomers to fabricate electrodes for neural stimulation. A novel combination of nanoparticulate polypyrrole polymerized within a processable elastomeric silicone host polymer was evaluated in vitro and in vivo. The electrical properties of the elastomeric conductors were strongly dependent on their composition, and mixtures were identified that provided high and stable conductivity. Methods were developed for incorporating conductive polymer–siloxane co-polymer nanocomposite and silicone insulating polymers into thin-layered structures for simple single-poled electrode fabrication. In vitro testing revealed that the materials were stable under continuous pulsing for at least 10 days. Single contact prototype nerve cuff electrodes were fabricated and device functionality was demonstrated in vivo following acute implantation. The results of this study demonstrate the feasibility of conductive elastomers for peripheral nerve stimulating electrodes. Matching the mechanical properties of cuff electrode to those of the underlying neural tissue is expected to improve the long-term tissue response to the presence of the electrode.

Effects of stimulation parameters and electrode location on thresholds for epidural stimulation of cat motor cortex

Epidural electrical stimulation (ECS) of the motor cortex is a developing therapy for neurological disorders. Both placement and programming of ECS systems may affect the therapeutic outcome, but the treatment parameters that will maximize therapeutic outcomes and minimize side effects are not known. We delivered ECS to the motor cortex of anesthetized cats and investigated the effects of electrode placement and stimulation parameters on thresholds for evoking motor responses in the contralateral forelimb. Thresholds were inversely related to stimulation frequency and the number of pulses per stimulus train. Thresholds were lower over the forelimb representation in motor cortex (primary site) than surrounding sites (secondary sites), and thresholds at sites <4 mm away from the primary site were significantly lower than at sites >4 mm away. Electrode location and montage influenced the effects of polarity on thresholds: monopolar anodic and cathodic thresholds were not significantly different over the primary site, cathodic thresholds were significantly lower than anodic thresholds over secondary sites and bipolar thresholds were significantly lower with the anode over the primary site than with the cathode over the primary site. A majority of bipolar thresholds were either between or equal to the respective monopolar thresholds, but several bipolar thresholds were greater than or less than the monopolar thresholds of both the anode and cathode. During bipolar stimulation, thresholds were influenced by both electric field superposition and indirect, synaptically mediated interactions. These results demonstrate the influence of stimulation parameters and electrode location during cortical stimulation, and these effects should be considered during the programming of systems for therapeutic cortical stimulation.

Genetic Algorithm Reveals Energy-Efficient Waveforms for Neural Stimulation

Energy consumption is an important consideration for battery-powered implantable stimulators. We used a genetic algorithm (GA) that mimics biological evolution to determine the energy-optimal waveform shape for neural stimulation. The GA was coupled to NEURON using a model of extracellular stimulation of a mammalian myelinated axon. Stimulation waveforms represented the organisms of a population, and each waveforms shape was encoded into genes. The fitness of each waveform was based on its energy efficiency and ability to elicit an action potential. After each generation of the GA, waveforms mated to produce offspring waveforms, and a new population was formed consisting of the offspring and the fittest waveforms of the previous generation. Over the course of the GA, waveforms became increasingly energy-efficient and converged upon a highly energy-efficient shape. The resulting waveforms resembled truncated normal curves or sinusoids and were 3–74% more energy-efficient than several waveform shapes commonly used in neural stimulation. If implemented in implantable neural stimulators, the GA optimized waveforms could prolong battery life, thereby reducing the costs and risks of battery-replacement surgery.