Energy efficient neural stimulation: coupling circuit design and membrane biophysics

Highly efficient modeling and optimization of neural fiber responses to electrical stimulation

Peripheral neuromodulation has emerged as a powerful modality for controlling physiological functions and treating a variety of medical conditions including chronic pain and organ dysfunction. The underlying complexity of the nonlinear responses to electrical stimulation make it challenging to design precise and effective neuromodulation protocols. Computational models have thus become indispensable in advancing our understanding and control of neural responses to electrical stimulation. However, existing approaches suffer from computational bottlenecks, rendering them unsuitable for real-time applications, large-scale parameter sweeps, or sophisticated optimization. In this work, we introduce an approach for massively parallel estimation and optimization of neural fiber responses to electrical stimulation using machine learning techniques. By leveraging advances in high-performance computing and parallel programming, we present a surrogate fiber model that generates spatiotemporal responses to a wide variety of cuff-based electrical peripheral nerve stimulation protocols. We used our surrogate fiber model to design stimulation parameters for selective stimulation of pig and human vagus nerves. Our approach yields a several-orders-of-magnitude improvement in computational efficiency while retaining generality and high predictive accuracy, demonstrating its robustness and potential to enhance the design and optimization of peripheral neuromodulation therapies.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

A review of neurophysiological effects and efficiency of waveform parameters in deep brain stimulation

Neurostimulation has diverse clinical applications and potential as a treatment for medically refractory movement disorders, epilepsy, and other neurological disorders. However, the parameters used to program electrodes-polarity, pulse width, amplitude, and frequency-and how they are adjusted have remained largely untouched since the 1970 s. This review summarizes the state-of-the-art in Deep Brain Stimulation (DBS) and highlights the need for further research to uncover the physiological mechanisms of neurostimulation. We focus on studies that reveal the potential for clinicians to use waveform parameters to selectively stimulate neural tissue for therapeutic benefit, while avoiding activating tissue associated with adverse effects. DBS uses cathodic monophasic rectangular pulses with passive recharging in clinical practice to treat neurological conditions such as Parkinson's Disease. However, research has shown that stimulation efficiency can be improved, and side effects reduced, through modulating parameters and adding novel waveform properties. These developments can prolong implantable pulse generator lifespan, reducing costs and surgery-associated risks. Waveform parameters can stimulate neurons based on axon orientation and intrinsic structural properties, providing clinicians with more precise targeting of neural pathways. These findings could expand the spectrum of diseases treatable with neuromodulation and improve patient outcomes.

Fractal Microelectrodes for More Energy-Efficient Cervical Vagus Nerve Stimulation

Vagus nerve stimulation (VNS) has the potential to treat various peripheral dysfunctions, but the traditional cuff electrodes for VNS are susceptible to off-target effects. Microelectrodes may enable highly selective VNS that can mitigate off-target effects, but they suffer from the increased impedance. Recent studies on microelectrodes with non-Euclidean geometries have reported higher energy efficiency in neural stimulation applications. These previous studies use electrodes with mm/cm-scale dimensions, mostly targeted for myelinated fibers. This study evaluates fractal microelectrodes for VNS in a rodent model (N = 3). A thin-film device with fractal and circle microelectrodes is fabricated to compare their neural stimulation performance on the same radial coordinate of the nerve. The results show that fractal microelectrodes can activate C-fibers with up to 52% less energy (p = 0.012) compared to circle microelectrodes. To the best of the knowledge, this work is the first to demonstrate a geometric advantage of fractal microelectrodes for VNS in vivo.

Energy efficiency of pulse shaping in electrical stimulation: the interdependence of biophysical effects and circuit design losses

Power efficiency in electrical stimulator circuits is crucial for developing large-scale multichannel applications like bidirectional brain-computer interfaces and neuroprosthetic devices. Many state-of-the-art papers have suggested that some non-rectangular pulse shapes are more energy-efficient for exciting neural excitation than the conventional rectangular shape. However, additional losses in the stimulator circuit, which arise from employing such pulses, were not considered. In this work, we analyze the total energy efficiency of a stimulation system featuring non-rectangular stimuli, taking into account the losses in the stimulator circuit. To this end, activation current thresholds for different pulse shapes and durations in cortical neurons are modeled, and the energy required to generate the pulses from a constant voltage supply is calculated. The proposed calculation reveals an energy increase of 14-51% for non-rectangular pulses compared to the conventional rectangular stimuli, instead of the decrease claimed in previous literature. This result indicates that a rectangular stimulation pulse is more power-efficient than the tested alternative shapes in large-scale multichannel electrical stimulation systems.

Neural selectivity, efficiency, and dose equivalence in deep brain stimulation through pulse width tuning and segmented electrodes

BACKGROUND

Achieving deep brain stimulation (DBS) dose equivalence is challenging, especially with pulse width tuning and directional contacts. Further, the precise effects of pulse width tuning are unknown, and recent reports of the effects of pulse width tuning on neural selectivity are at odds with classic biophysical studies.

METHODS

We created multicompartment neuron models for two axon diameters and used finite element modeling to determine extracellular influence from standard and segmented electrodes. We analyzed axon activation profiles and calculated volumes of tissue activated.

RESULTS

We find that long pulse widths focus the stimulation effect on small, nearby fibers, suppressing distant white matter tract activation (responsible for some DBS side effects) and improving battery utilization when equivalent activation is maintained for small axons. Directional leads enable similar benefits to a greater degree. Reexamining previous reports of short pulse stimulation reducing side effects, we explore a possible alternate explanation: non-dose equivalent stimulation may have resulted in reduced spread of neural activation. Finally, using internal capsule avoidance as an example in the context of subthalamic stimulation, we present a patient-specific model to show how long pulse widths could help increase the biophysical therapeutic window.

DISCUSSION

We find agreement with classic studies and predict that long pulse widths may focus the stimulation effect on small, nearby fibers and improve power consumption. While future pre-clinical and clinical work is necessary regarding pulse width tuning, it is clear that future studies must ensure dose equivalence, noting that energy- and charge-equivalent amplitudes do not result in equivalent spread of neural activation when changing pulse width.

Real-Time In Vivo Control of Neural Membrane Potential by Electro-Ionic Modulation

Theoretically, by controlling neural membrane potential (V_m) in vivo, motion, sensation, and behavior can be controlled. Until now, there was no available technique that can increase or decrease ion concentration in vivo in real time to change neural membrane potential. We introduce a method that we coin electro-ionic modulation (EIM), wherein ionic concentration around a nerve can be controlled in real time and in vivo. We used an interface to regulate the Ca²⁺ ion concentration around the sciatic nerve of a frog and thus achieved stimulation and blocking with higher resolution and lower current compared with electrical stimulation. As EIM achieves higher controllability of V_m, it has potential to replace conventional methods used for the treatment of neurological disorders and may bring a new perspective to neuromodulation techniques.

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EIM regulates extracellular ion concentration in vivo in real time

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EIM stimulates or blocks the nerve via Ca²⁺ ion depletion or enhancement

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EIM achieves selective stimulation or blocking of large or small axons

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EIM is the most superior neuromodulation method for real-life applications

A Fully Integrated RF-Powered Energy-Replenishing Current-Controlled Stimulator

This paper presents a fully-integrated current-controlled stimulator that is powered directly from on-chip coil antenna and achieves adiabatic energy-replenishing operation without any bulky external components. Adiabatic supply voltages, which can reach a differential range of up to 7.2 V, are directly generated from an on-chip 190-MHz resonant LC tank via a self-cascading/folding rectifier network, bypassing the losses that would otherwise be introduced by the 0.8 V system supply-generating rectifier and regulator. The stimulator occupies 0.22 mm ² in a 180 nm silicon-on-insulator process and produces differential currents up to 145  μA. Using a charge replenishing scheme, the stimulator redirects the charges accumulated across the electrodes to the system power supplies for 63.1% of stimulation energy recycling. To benchmark the efficiency of stimulation, a figure of merit termed the stimulator efficiency factor (SEF) is introduced. The adiabatic power rails and energy replenishment scheme enabled our stimulator to achieve an SEF of 6.0.

Inductively coupled, mm-sized, single channel optical neuro-stimulator with intensity enhancer

We introduce a single channel neuro-stimulator consisting of a reflector-coupled microscale light emitting diode (µLED) with an integrated mm-sized wireless receiver (Rx) coil for free-floating, battery-free, untethered optogenetics neuromodulation. The system utilizes a two-coil inductive link to deliver instantaneous power at a low operating frequency (<100 MHz) for continuous optical stimulation with minimized invasiveness and tissue exposure to electromagnetic radiation. Coupling a microscale reflector to the µLED provides significant light intensity enhancement compared to a bare µLED. Our activated stimulators have an operational temperature increase of <1 °C, well below the safety limit of biomedical implants. In vivo experiment and histological analysis verify the efficacy of wireless optical stimulation in the primary visual cortex of rats, using c-Fos biomarker as a reporter of light-evoked neuronal activity.

Non-rectangular waveforms are more charge-efficient than rectangular one in eliciting network-mediated responses of ON type retinal ganglion cells

OBJECTIVE

For individuals blinded by outer retinal degenerative diseases, retinal prostheses would be a promising option to restore sight. Unfortunately, however, the best performance of existing devices is still far removed from normal vision. One possible reason for the shortcoming is thought to be suboptimal stimulation conditions such as the waveform shape of electric stimulus. In this study, we explored the effects of varying waveforms on network-mediated responses arising in retinal ganglion cells (RGCs).

APPROACH

We used a cell-attached patch clamp technique to record RGC spiking activities in the isolated mouse retina. ON alpha RGCs were targeted by soma size and their light responses to stationary spot flashes. Spiking in targeted RGCs was measured in response to an epiretinally-delivered cathodal current pulse in four waveforms: rectangular, center triangular, increasing and decreasing ramp shapes. Each waveform was tested at three durations (20, 10, and 5 ms) with adjusted amplitude for a range of total charges (50-400 nC).

MAIN RESULTS

ON alpha RGCs always generated two bursts of spikes in responses to all stimuli conditions we tested. However, at a given charge, effects of differing waveforms were distinct in the two bursts. For the first burst, the increasing ramp was most effective among the four waveforms (p  <  0.05 for all pairwise comparisons with other waveforms). For example, in responses arising from 20 ms-long stimuli, the increasing ramp evoked ~44% more spikes on average than the rectangular shape which is the typical choice of neural stimulation. Also, the rectangular stimulus evoked the weakest response in the delayed burst arising from pulses of every duration. For instance, 20 ms-long stimuli in the three non-rectangular waveforms showed ~23% or more increment in spike counts compared to response arising from the rectangular one; but there was no statistical difference in response magnitudes across the non-rectangular waveforms.

SIGNIFICANCE

Although the rectangular waveform has been primarily used in retinal prostheses our results indicate that rectangular stimulus is not optimal for network-mediated responses of ON alpha RGCs. Instead, non-rectangular waveforms evoke stronger responses at a given charge, indicating higher charge-efficiency. Therefore, non-rectangular waveforms are expected to enhance clinical efficacy of retinal prostheses.

A mm-Sized Wireless Implantable Device for Electrical Stimulation of Peripheral Nerves

A wireless electrical stimulation implant for peripheral nerves, achieving >10× improvement over state of the art in the depth/volume figure of merit, is presented. The fully integrated implant measures just 2 mm × 3 mm × 6.5 mm (39 mm³, 78 mg), and operates at a large depth of 10.5 cm in a tissue phantom. The implant is powered using ultrasound and includes a miniaturized piezoelectric receiver (piezo), an IC designed in 180 nm HV BCD process, an off-chip energy storage capacitor, and platinum stimulation electrodes. The package also includes an optional blue light-emitting diode for potential applications in optogenetic stimulation in the future. A system-level design strategy for complete operation of the implant during the charging transient of the storage capacitor, as well as a unique downlink command/data transfer protocol, is presented. The implant enables externally programmable current-controlled stimulation of peripheral nerves, with a wide range of stimulation parameters, both for electrical (22 to 5000 μA amplitude, ∼14 to 470 μs pulse-width, 0 to 60 Hz repetition rate) and optical (up to 23 mW/mm² optical intensity) stimulation. Additionally, the implant achieves 15 V compliance voltage for chronic applications. Full integration of the implant components, end-to-end in vitro system characterizations, and results for the electrical stimulation of a sciatic nerve, demonstrate the feasibility and efficacy of the proposed stimulator for peripheral nerves.

Electrochemical Evaluations of Fractal Microelectrodes for Energy Efficient Neurostimulation

Advancements in microfabrication has enabled manufacturing of microscopic neurostimulation electrodes with smaller footprint than ever possible. The smaller electrodes can potentially reduce tissue damage and allow better spatial resolution for neural stimulation. Although electrodes of any shape can easily be fabricated, substantial effort have been focused on identification and characterization of new materials and surface morphology for efficient charge injection, while maintaining simple circular or rectangular Euclidean electrode geometries. In this work we provide a systematic electrochemical evaluation of charge injection capacities of serpentine and fractal-shaped platinum microelectrodes and compare their performance with traditional circular microelectrodes. Our findings indicate that the increase in electrode perimeter leads to an increase in maximum charge injection capacity. Furthermore, we found that the electrode geometry can have even more significant impact on electrode performance than having a larger perimeter for a given surface area. The fractal-shaped microelectrodes, despite having smaller perimeter than other designs, demonstrated superior charge injection capacity. Our results suggest that electrode design can significantly affect both Faradaic and non-Faradaic electrochemical processes, which may be optimized to enable a more energy efficient design for neurostimulation.

Stimulation Efficiency With Decaying Exponential Waveforms in a Wirelessly Powered Switched-Capacitor Discharge Stimulation System

The purpose of this study was to test the feasibility of using a switched-capacitor discharge stimulation (SCDS) system for electrical stimulation, and, subsequently, determine the overall energy saved compared to a conventional stimulator. We have constructed a computational model by pairing an image-based volume conductor model of the cat head with cable models of corticospinal tract (CST) axons and quantified the theoretical stimulation efficiency of rectangular and decaying exponential waveforms, produced by conventional and SCDS systems, respectively. Subsequently, the model predictions were tested in vivo by activating axons in the posterior internal capsule and recording evoked electromyography (EMG) in the contralateral upper arm muscles. Compared to rectangular waveforms, decaying exponential waveforms with time constants >500 μs were predicted to require 2%-4% less stimulus energy to activate directly models of CST axons and 0.4%-2% less stimulus energy to evoke EMG activity in vivo. Using the calculated wireless input energy of the stimulation system and the measured stimulus energies required to evoke EMG activity, we predict that an SCDS implantable pulse generator (IPG) will require 40% less input energy than a conventional IPG to activate target neural elements. A wireless SCDS IPG that is more energy efficient than a conventional IPG will reduce the size of an implant, require that less wireless energy be transmitted through the skin, and extend the lifetime of the battery in the external power transmitter.

Innovations in deep brain stimulation methodology

Deep brain stimulation is a powerful clinical method for movement disorders that no longer respond satisfactorily to pharmacological management, but its progress has been hampered by stagnation in technological procedure solutions and device development. Recently, the combined research efforts of bioengineers, neuroscientists, and clinicians have helped to better understand the mechanisms of deep brain stimulation, and solutions for the translational roadblock are emerging. Here, we define the needs for methodological advances in deep brain stimulation from a neurophysiological perspective and describe technological solutions that are currently evaluated for near-term clinical application. © 2016 International Parkinson and Movement Disorder Society.

Optogenetic versus Electrical Stimulation of Human Cardiomyocytes: Modeling Insights

Optogenetics provides an alternative to electrical stimulation to manipulate membrane voltage, and trigger or modify action potentials (APs) in excitable cells. We compare biophysically and energetically the cellular responses to direct electrical current injection versus optical stimulation mediated by genetically expressed light-sensitive ion channels, e.g., Channelrhodopsin-2 (ChR2). Using a computational model of ChR2(H134R mutant), we show that both stimulation modalities produce similar-in-morphology APs in human cardiomyocytes, and that electrical and optical excitability vary with cell type in a similar fashion. However, whereas the strength-duration curves for electrical excitation in ventricular and atrial cardiomyocytes closely follow the theoretical exponential relationship for an equivalent RC circuit, the respective optical strength-duration curves significantly deviate, exhibiting higher nonlinearity. We trace the origin of this deviation to the waveform of the excitatory current-a nonrectangular self-terminating inward current produced in optical stimulation due to ChR2 kinetics and voltage-dependent rectification. Using a unifying charge measure to compare energy needed for electrical and optical stimulation, we reveal that direct electrical current injection (rectangular pulse) is more efficient at short pulses, whereas voltage-mediated negative feedback leads to self-termination of ChR2 current and renders optical stimulation more efficient for long low-intensity pulses. This applies to cardiomyocytes but not to neuronal cells (with much shorter APs). Furthermore, we demonstrate the cell-specific use of ChR2 current as a unique modulator of intrinsic activity, allowing for optical control of AP duration in atrial and, to a lesser degree, in ventricular myocytes. For self-oscillatory cells, such as Purkinje, constant light at extremely low irradiance can be used for fine control of oscillatory frequency, whereas constant electrical stimulation is not feasible due to electrochemical limitations. Our analysis offers insights for designing future new energy-efficient stimulation strategies in heart or brain.

Model-based analysis and design of waveforms for efficient neural stimulation

The design space for electrical stimulation of the nervous system is extremely large, and because the response to stimulation is highly nonlinear, the selection of stimulation parameters to achieve a desired response is a challenging problem. Computational models of the response of neurons to extracellular stimulation allow analysis of the effects of stimulation parameters on neural excitation and provide an approach to select or design optimal parameters of stimulation. Here, I review the use of computational models to understand the effects of stimulation waveform on the energy efficiency of neural excitation and to design novel stimulation waveforms to increase the efficiency of neural stimulation.

Engineering the next generation of clinical deep brain stimulation technology

Deep brain stimulation (DBS) has evolved into a powerful clinical therapy for a range of neurological disorders, but even with impressive clinical growth, DBS technology has been relatively stagnant over its history. However, enhanced collaborations between neural engineers, neuroscientists, physicists, neurologists, and neurosurgeons are beginning to address some of the limitations of current DBS technology. These interactions have helped to develop novel ideas for the next generation of clinical DBS systems. This review attempts collate some of that progress with two goals in mind. First, provide a general description of current clinical DBS practices, geared toward educating biomedical engineers and computer scientists on a field that needs their expertise and attention. Second, describe some of the technological developments that are currently underway in surgical targeting, stimulation parameter selection, stimulation protocols, and stimulation hardware that are being directly evaluated for near term clinical application.

Deep brain stimulation (DBS) at the interface of neurology and psychiatry

Deep brain stimulation (DBS) is an emerging interventional therapy for well-screened patients with specific treatment-resistant neuropsychiatric diseases. Some neuropsychiatric conditions, such as Parkinson disease, have available and reasonable guideline and efficacy data, while other conditions, such as major depressive disorder and Tourette syndrome, have more limited, but promising results. This review summarizes both the efficacy and the neuroanatomical targets for DBS in four common neuropsychiatric conditions: Parkinson disease, Tourette syndrome, major depressive disorder, and obsessive-compulsive disorder. Based on emerging new research, we summarize novel approaches to optimization of stimulation for each neuropsychiatric disease and we review the potential positive and negative effects that may be observed following DBS. Finally, we summarize the likely future innovations in the field of electrical neural-network modulation.

Optimal stimulus profiles for neuroprosthetic devices: monophasic versus biphasic stimulation

Designing stimulation signals for neuroprosthetic devices can be cast as an optimal control problem. Rectangular Lilly-type stimulation waveforms have been used extensively in these devices. In this paper, we rigorously formulate the charge optimization problem from a control perspective and distinguish between monophasic and biphasic stimuli. We show that for a monophasic stimulus, the important factor in stimulating a neuron is the total delivered charge per unit cell membrane. This factor is a consequence of the subthreshold linear behavior of the neural membrane. On the other hand, biphasic pulses, which are ubiquitous in the neuron stimulation context, can stimulate a neuron in its non-linear range, thereby challenging the finding that total charge delivery is the only critical factor. As a result, there may be even more optimal stimulus profiles than Lilly-type rectangular waveforms for biphasic stimulation. Furthermore, solving the charge minimization problem also will reduce the risk of electrode corrosion, which is an important factor in improving the performance of neuroprosthetic devices.