Stimulus Waveform Research Articles

Galvanic Vestibular Stimulation: Data Analysis and Applications in Neurorehabilitation

A rapidly aging population worldwide has spurred interest in developing new strategies to cope with neural declines and neurodegenerative disorders. Noninvasive brain stimulation (NIBS) is increasingly being used to explore functional mechanisms of the brain and induce the therapeutic modulation of behavior, cognition, and emotion. Galvanic vestibular stimulation (GVS), a safe and well-tolerated NIBS technique, is capable of modulating activity in various cortical and subcortical areas involved in vestibular and multisensory processing. A key facet of GVS is that the resultant effects may, in part, be a function of the individual being treated and the stimulus waveform that is delivered. Yet, most GVS studies have utilized the same generic stimulus, chosen from a reduced repertoire of candidates, across all subjects. The future use and, ultimately, clinical adoption of this technology will rely on contributions from the signal processing community to customize stimuli that are optimized for their effect and to exert maximum influence on brain imaging biomarkers. We provide a signal processing-focused overview of the current GVS state of the art in neurorehabilitation, including general stimulation design, concurrent analysis with neuroimaging data, and suggestions for future directions.

Synergistic population coding of natural communication stimuli by hindbrain electrosensory neurons

Understanding how neural populations encode natural stimuli with complex spatiotemporal structure to give rise to perception remains a central problem in neuroscience. Here we investigated population coding of natural communication stimuli by hindbrain neurons within the electrosensory system of weakly electric fish Apteronotus leptorhynchus. Overall, we found that simultaneously recorded neural activities were correlated: signal but not noise correlations were variable depending on the stimulus waveform as well as the distance between neurons. Combining the neural activities using an equal-weight sum gave rise to discrimination performance between different stimulus waveforms that was limited by redundancy introduced by noise correlations. However, using an evolutionary algorithm to assign different weights to individual neurons before combining their activities (i.e., a weighted sum) gave rise to increased discrimination performance by revealing synergistic interactions between neural activities. Our results thus demonstrate that correlations between the neural activities of hindbrain electrosensory neurons can enhance information about the structure of natural communication stimuli that allow for reliable discrimination between different waveforms by downstream brain areas.

A simple electrical approach to diagnosing a suspected lead break in patients with implanted vagus nerve stimulators – Technical note

PurposeVagus nerve stimulation (VNS) is an effective adjunctive treatment for patients with drug-resistant epilepsy (DRE) or difficult-to-treat depression (DTD). The implanted system consists of a titanium-cased generator and a lead with platinum electrodes, placed around the cervical vagus nerve. In rare cases a lead may break, causing the patient to receive insufficient therapy or no therapy at all, with potentially dangerous consequences. In order to confirm a suspected lead breakage, physicians have the option to perform x-rays. However, x-rays often do not show a clear, unmistakable lead break. In this technical note an additional method to verify lead integrity electrophysiological is described in detail to provide the highest degree of certainty on the integrity of the lead when a broken lead is suspected before proceeding to revision surgery. MethodsWhen patients introduce themselves with symptoms indicating a suspected lead breakage, a systematic lead break management is required. This includes, beside the clinical anamneses, performing VNS Therapy® System Diagnostics (SD). If an unacceptable HIGH lead impedance is observed, performing x-rays (anteroposterior and lateral views) may help to confirm a lead breakage. Additionally, EMG recording equipment can be used to analyse the VNS stimulus waveform from the neck for verification of an electrical discontinuity. ResultsA differentiated VNS waveform with narrowed pulses or no waveform at all can confirm lead discontinuity. ConclusionThis Technical Note describes an easy but underused electrophysiological procedure to be included in the standardized protocol for identifying VNS lead breakage.

Population Coding of Natural Electrosensory Stimuli by Midbrain Neurons.

Natural stimuli display spatiotemporal characteristics that typically vary over orders of magnitude, and their encoding by sensory neurons remains poorly understood. We investigated population coding of highly heterogeneous natural electrocommunication stimuli in Apteronotus leptorhynchus of either sex. Neuronal activities were positively correlated with one another in the absence of stimulation, and correlation magnitude decayed with increasing distance between recording sites. Under stimulation, we found that correlations between trial-averaged neuronal responses (i.e., signal correlations) were positive and higher in magnitude for neurons located close to another, but that correlations between the trial-to-trial variability (i.e., noise correlations) were independent of physical distance. Overall, signal and noise correlations were independent of stimulus waveform as well as of one another. To investigate how neuronal populations encoded natural electrocommunication stimuli, we considered a nonlinear decoder for which the activities were combined. Decoding performance was best for a timescale of 6 ms, indicating that midbrain neurons transmit information via precise spike timing. A simple summation of neuronal activities (equally weighted sum) revealed that noise correlations limited decoding performance by introducing redundancy. Using an evolution algorithm to optimize performance when considering instead unequally weighted sums of neuronal activities revealed much greater performance values, indicating that midbrain neuron populations transmit information that reliably enable discrimination between different stimulus waveforms. Interestingly, we found that different weight combinations gave rise to similar discriminability, suggesting robustness. Our results have important implications for understanding how natural stimuli are integrated by downstream brain areas to give rise to behavioral responses.SIGNIFICANCE STATEMENT We show that midbrain electrosensory neurons display correlations between their activities and that these can significantly impact performance of decoders. While noise correlations limited discrimination performance by introducing redundancy, considering unequally weighted sums of neuronal activities gave rise to much improved performance and mitigated the deleterious effects of noise correlations. Further analysis revealed that increased discriminability was achieved by making trial-averaged responses more separable, as well as by reducing trial-to-trial variability by eliminating noise correlations. We further found that multiple combinations of weights could give rise to similar discrimination performances, which suggests that such combinatorial codes could be achieved in the brain. We conclude that the activities of midbrain neuronal populations can be used to reliably discriminate between highly heterogeneous stimulus waveforms.

Falling off a limit cycle using phase-agnostic stimuli: Applications to clinical oscillopathies

For over a century, physiological studies have shown that precisely timed pulses can switch off a biological oscillator. This empiric finding has shaped our mechanistic understanding of how perturbations start, stop, and reset biological oscillators and has led to treatments that suppress pathological oscillations using electrical pulses given within specified therapeutic phase windows. Here, we present evidence, using numerical simulations of models of epileptic seizures and reentrant tachycardia, that the phase window can be opened to the entire cycle using novel complex stimulus waveforms. Our results reveal that the trajectories are displaced by such phase-agnostic stimuli off the oscillator's limit cycle and corralled into a region where oscillation is suppressed, irrespective of the phase at which the stimulus was applied. Our findings suggest the need for broadening theoretical understanding of how complex perturbing waveforms interact with biological oscillators to access their arrhythmic states. In clinical practice, oscillopathies may be treated more effectively with non-traditional stimulus waveforms that obviate the need for phase specificity.

A Multiscale Approach to Axon and Nerve Stimulation Modeling: A Review.

Electrical nerve fiber stimulation is a technique widely used in prosthetics and rehabilitation, and its study from a computational point of view can be a useful instrument to support experimental tests. In the last years, there was an increasing interest in computational modeling of neural cells and numerical simulations on nerve fibers stimulation because of its usefulness in forecasting the effect of electrical current stimuli delivered to tissues through implanted electrodes, in the design of optimal stimulus waveforms based on the specific application (i.e., inducing limb movements, sensory feedback or physiological function restoring), and in the evaluation of the current stimuli properties according to the characteristics of the nerves surrounding tissue. Therefore, a review study on the main modeling and computational frameworks adopted to investigate peripheral nerve stimulation is an important instrument to support and drive future research works. To this aim, this paper deals with mathematical models of neural cells with a detailed description of ion channels and numerical simulations using finite element methods to describe the dynamics of electrical stimulation by implanted electrodes in peripheral nerve fibers. In particular, we evaluate different nerve cell models considering different ion channels present in neurons and provide a guideline on multiscale numerical simulations of electrical nerve fibers stimulation.

Falling off a limit cycle using phase-agnostic stimuli: Definitions and conceptual framework.

Nearly a half-century of biomedical research has revealed methods and mechanisms by which an oscillator with bistable limit cycle kinetics can be stopped using critical stimuli applied at a specific phase. Is it possible to construct a stimulus that stops oscillation regardless of the phase at which the stimulus is applied? Using a radial isochron clock model, we demonstrate the existence of such stimulus waveforms, which can take on highly complex shapes but with a surprisingly simple mechanism of rhythm suppression. The perturbation, initiated at any phase of the limit cycle, first corrals the oscillator to a narrow range of new phases, then drives the oscillator to its phase singularity. We further constructed a library of waveforms having different durations, each achieving phase-agnostic suppression of rhythm but with varying rates of phase corralling prior to amplitude suppression. The optimal stimulus energy to achieve phase-agnostic suppression of rhythm is dependent on the rate of phase corralling and the configuration of the phaseless set. We speculate that these results are generic and suggest the existence of stimulus waveforms that can stop the rhythm of more complex oscillators irrespective of the applied phase.

Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics.

While multicompartment models have long been used to study the biophysics of neurons, it is still challenging to infer the parameters of such models from data including uncertainty estimates. Here, we performed Bayesian inference for the parameters of detailed neuron models of a photoreceptor and an OFF- and an ON-cone bipolar cell from the mouse retina based on two-photon imaging data. We obtained multivariate posterior distributions specifying plausible parameter ranges consistent with the data and allowing to identify parameters poorly constrained by the data. To demonstrate the potential of such mechanistic data-driven neuron models, we created a simulation environment for external electrical stimulation of the retina and optimized stimulus waveforms to target OFF- and ON-cone bipolar cells, a current major problem of retinal neuroprosthetics.

Programmable Transcranial Magnetic Stimulation: A Modulation Approach for the Generation of Controllable Magnetic Stimuli.

A transcranial magnetic stimulation system with programmable stimulus pulses and patterns is presented. The stimulus pulses of the implemented system expand beyond conventional damped cosine or near-rectangular pulses and approach an arbitrary waveform. The desired stimulus waveform shape is defined as a reference signal. This signal controls the semiconductor switches of an H-bridge inverter to generate a high-power imitation of the reference. The design uses a new paradigm for TMS, applying pulse-width modulation with a non-resonant, high-frequency switching architecture to synthesize waveforms that leverages the low-pass filtering properties of neuronal cells. The modulation technique enables control of the waveform, frequency, pattern, and intensity of the stimulus. A system prototype was developed to demonstrate the technique. The experimental measurements demonstrate that the system is capable of generating stimuli up to 4 kHz with peak voltage and current values of ±1000 V and ±3600 A, respectively. The maximum transferred energy measured in the experimental validation was 100.4 Joules. To characterize repetitive TMS modalities, the efficiency of generating consecutive pulse triplets and quadruplets with interstimulus intervals of 1 ms was tested and verified. The implemented TMS device can generate consecutive rectangular pulses with a predetermined time interval, widths and polarities, enables the synthesis of a wide range of magnetic stimuli. New waveforms promise functional advantages over the waveforms generated by current-generation TMS systems for clinical neuroscience research.

Neuronal On- and Off-type heterogeneities improve population coding of envelope signals in the presence of stimulus-induced noise

Understanding the mechanisms by which neuronal population activity gives rise to perception and behavior remains a central question in systems neuroscience. Such understanding is complicated by the fact that natural stimuli often have complex structure. Here we investigated how heterogeneities within a sensory neuron population influence the coding of a noisy stimulus waveform (i.e., the noise) and its behaviorally relevant envelope signal (i.e., the signal). We found that On- and Off-type neurons displayed more heterogeneities in their responses to the noise than in their responses to the signal. These differences in heterogeneities had important consequences when quantifying response similarity between pairs of neurons. Indeed, the larger response heterogeneity displayed by On- and Off-type neurons made their pairwise responses to the noise on average more independent than when instead considering pairs of On-type or Off-type neurons. Such relative independence allowed for better averaging out of the noise response when pooling neural activities in a mixed-type (i.e., On- and Off-type) than for same-type (i.e., only On-type or only Off-type), thereby leading to greater information transmission about the signal. Our results thus reveal a function for the combined activities of On- and Off-type neurons towards improving information transmission of envelope stimuli at the population level. Our results will likely generalize because natural stimuli across modalities are characterized by a stimulus waveform whose envelope varies independently as well as because On- and Off-type neurons are observed across systems and species.

Stimulus waveform design for decreasing charge and increasing stimulation selectivity in retinal prostheses.

Retinal degenerative diseases, such as retinitis pigmentosa, begin with damage to the photoreceptor layer of the retina. In the absence of presynaptic input from photoreceptors, networks of electrically coupled AII amacrine and cone bipolar cells have been observed to exhibit oscillatory behaviour and result in spontaneous firing of ganglion cells. This ganglion cell activity could interfere with external stimuli provided by retinal prosthetic devices and potentially degrade their performance. In this work, the authors computationally investigate stimulus waveform designs, which can improve the performance of retinal prostheses by suppressing undesired spontaneous firing of ganglion cells and generating precise temporal spiking patterns. They utilise a multi-scale computational model for electrical stimulation of degenerated retina based on the admittance method and NEURON simulation environments. They present a class of asymmetric biphasic pulses that can generate precise ganglion cell firing patterns with up to 55% lower current requirements compared to traditional symmetric biphasic pulses. This lower current results in activation of only proximal ganglion cells, provides more focused stimulation and lowers the risk of tissue damage.

Harmonic-balance circuit analysis for electro-neural interfaces

Objective. Avoidance of the adverse electrochemical reactions at the electrode-electrolyte interface defines the voltage safety window and limits the charge injection capacity (CIC) of an electrode material. For an electrode that is not ideally capacitive, the CIC depends on the waveform of the stimulus. We study the modeling of the charge injection dynamics to optimize the waveforms for efficient neural stimulation within the electrochemical safety limits. Approach. The charge injection dynamics at the electrode-electrolyte interface is typically characterized by the electrochemical impedance spectrum, and is often approximated by discrete-element circuit models. We compare the modeling of the complete circuit, including a non-linear driver such as a photodiode, based on the harmonic-balance (HB) analysis with the analysis based on various - (discrete-element) approximations. To validate the modeling results, we performed experiments with iridium-oxide electrodes driven by a current source with diodes in parallel, which mimics a photovoltaic circuit. Main results. Application of HB analysis based on a full impedance spectrum eliminates the complication of finding the discrete-element circuit model in traditional approaches. HB-based results agree with the experimental data better than the discrete-element circuit. HB technique can be applied not only to demonstrate the circuit response to periodic stimulation, but also to describe the initial transient behavior when a burst waveform is applied. Significance. HB-based circuit analysis accurately describes the dynamics of electrode-electrolyte interfaces and driving circuits for all pulsing schemes. This allows optimizing the stimulus waveform to maximize the CIC, based on the impedance spectrum alone.

Waveform discrimination in a pair of pulse‐generating electric fishes

Studies of pulse-type gymnotiform electric fishes have suggested that the electric organ discharge waveforms (EODw) allow individuals to discriminate between conspecific and allospecific signals, but few have approached this experimentally. Here we implement a phase-locked playback technique for a syntopic species pair, Brachyhypopomus gauderio and Gymnotus omarorum. Both species respond to changes in stimulus waveform with a transitory reduction in the interpulse interval of their self-generated discharge, providing strong evidence of discrimination. We also document sustained rate changes in response to different EODws, which may suggest recognition of natural waveforms. This article is protected by copyright. All rights reserved.

Neural Synchrony Gives Rise to Amplitude- and Duration-Invariant Encoding Consistent With Perception of Natural Communication Stimuli.

When confronted with a highly variable environment, it remains poorly understood how neural populations encode and classify natural stimuli to give rise to appropriate and consistent behavioral responses. Here we investigated population coding of natural communication signals with different attributes (i.e., amplitude and duration) in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. Our results show that, while single peripheral neurons encode the detailed timecourse of different stimulus waveforms, measures of population synchrony are effectively unchanged because of coordinated increases and decreases in activity. A phenomenological mathematical model reproduced this invariance and shows that this can be explained by considering homogeneous populations whose responses are solely determined by single neuron firing properties. Moreover, recordings from downstream central neurons reveal that synchronous afferent activity is actually decoded and thus most likely transmitted to higher brain areas. Finally, we demonstrate that the associated behavioral responses at the organism level are invariant. Our results provide a mechanism by which amplitude- and duration-invariant coding of behaviorally relevant sensory input emerges across successive brain areas thereby presumably giving rise to invariant behavioral responses. Such mechanisms are likely to be found in other systems that share anatomical and functional features with the electrosensory system (e.g., auditory, visual, vestibular).

Consonance perception beyond the traditional existence region of pitch.

Some theories posit that the perception of consonance is based on neural periodicity detection, which is dependent on accurate phase locking of auditory nerve fibers to features of the stimulus waveform. In the current study, 15 listeners were asked to rate the pleasantness of complex tone dyads (2 note chords) forming various harmonic intervals and bandpass filtered in a high-frequency region (all components >5.8 kHz), where phase locking to the rapid stimulus fine structure is thought to be severely degraded or absent. The two notes were presented to opposite ears. Consonant intervals (minor third and perfect fifth) received higher ratings than dissonant intervals (minor second and tritone). The results could not be explained in terms of phase locking to the slower waveform envelope because the preference for consonant intervals was higher when the stimuli were harmonic, compared to a condition in which they were made inharmonic by shifting their component frequencies by a constant offset, so as to preserve their envelope periodicity. Overall the results indicate that, if phase locking is indeed absent at frequencies greater than ∼5 kHz, neural periodicity detection is not necessary for the perception of consonance.

Optimizing Stimulation Strategies for Retinal Electrical Stimulation: a Modelling Study.

In this research, a continuum multi-compartmental model of retinal electrical stimulation was utilized to find the best strategy for activating retinal ganglion cells (RGCs). Two types of return electrodes configuration placed suprachoroidally were used: monopolar and hexapolar. The current was delivered either simultaneously or sequentially with two kinds of waveforms: biphasic symmetric charge-balanced cathodic and anodic first pulses. Our results revealed there is no significant difference in current threshold between single monopolar and hexapolar stimulation regardless of the applied current stimulus waveform. Moreover, sequential stimulation for both monopolar or hexapolar was more effective in reducing current threshold than simultaneous stimulation when biphasic cathodic first pulses were used. Concurrent monopolar stimulation was significant in reducing the current threshold compared to single monopolar whereas concurrent hexapolar did not alter the current threshold. Overall, concurrent monopolar stimulation was efficacious in reducing current threshold regardless of the stimulus waveforms and sequential stimulation was more useful only with biphasic cathodic first pulses.

Computational comparison of conventional and novel electroconvulsive therapy electrode placements for the treatment of depression

BackgroundElectroconvulsive therapy (ECT) is a highly effective treatment for severe psychiatric disorders. Despite its high efficacy, the use of ECT would be greater if the risk of cognitive side effects were reduced. Over the last 20 years, developments in ECT technique, including improvements in the dosing methodology and modification of the stimulus waveform, have allowed for improved treatment methods with reduced adverse cognitive effects. There is increasing evidence that the electrode placement is important for orienting the electrical stimulus and therefore modifying treatment outcomes, with potential for further improvement of the placements currently used in ECT. ObjectiveWe used computational modelling to perform an in-depth examination into regional differences in brain excitation by the ECT stimulus for several lesser known and novel electrode placements, in order to investigate the potential for an electrode placement that may optimise clinical outcomes. MethodsHigh resolution finite element human head models were generated from MRI scans of three subjects. The models were used to compare regional differences in average electric field (EF) magnitude among a total of thirteen bipolar ECT electrode placements, i.e. three conventional placements as well as ten lesser known and novel placements. Results and conclusionIn this exploratory study on a systemic comparison of thirteen ECT electrode placements, the EF magnitude at regions of interest (ROIs) was highly dependent upon the position of both electrodes, especially the ROIs close to the cortical surface. Compared to conventional right-unilateral (RUL) ECT using a temporo-parietal placement, fronto-parietal and supraorbito-parietal RUL also robustly stimulated brain regions considered important for efficacy, while sparing regions related to cognitive functions, and may be a preferrable approach to the currently used placement for RUL ECT. The simulations also found that regional average EF magnitude varied between individual subjects, due to factors such as head size, and results also depended on the size of the defined ROI.

A multiple modulation synthesis method with high spatial resolution for noninvasive neurostimulation.

Noninvasive neurostimulation plays a pivotal role in the direct control of neural circuits and the modulation of neuronal function. However, it is difficult to balance both spatial resolution and penetration depth when stimulating deep neurons. Here, we designed a multiple (time-division, frequency and polarity) modulation synthesis (MMS) method for noninvasively stimulating deep neurons with low-frequency envelopes. Compared to conventional transcranial electrical stimulation, we demonstrated that it can stimulate deep neurons at the desired firing rate (beat frequency) with higher spatial resolution via a computational model combining finite element analysis and Hodgkin-Huxley action potential model. Additionally, we measured the distribution of stimulus waveforms in saline solution to validate its effect. Taken together, the results of this study indicate that MMS stimulation with higher spatial resolution is steerable and might be a potential alternative to traditional implanted electrodes.

Reduced Heat Generation During Magnetic Stimulation of Rat Sciatic Nerve Using Current Waveform Truncation.

Current truncating circuit designs used in some controllable pulse width transcranial magnetic stimulation systems can be adapted for use with the peripheral nervous system. Such a scaled-down stimulator produces neuromuscular activation using less stimulus energy than described in previous reports of sciatic nerve stimulation. To evaluate the energy reductions possible with current truncation, we performed six in vivo experiments in rats where the magnetic stimulating coil abutted the sciatic nerve. We used electromyographic data to quantify neuromuscular response, with a criterion level of 20%-of-maximum to indicate a useful level of neuromuscular activation. The energy required to evoke this criterion response from muscles innervated by the sciatic nerve was reduced by approximately 34% from 10.7J with a stimulus waveform lasting 300 [Formula: see text] to 7.1J with a waveform lasting 50 [Formula: see text]. In water, the 300 [Formula: see text] pulse heated the coil by 0.30°C whereas the 50 [Formula: see text] pulse heated the coil by 0.15°C. Truncated-waveform magnetic stimulation systems can be used in basic research and clinical applications not requiring rapidly pulsed stimuli. An example of such a clinical application is left vagus nerve stimulation, a treatment that is reported to reduce epileptic partial-onset seizures.

Comparison of the efficiency of chopped and non-rectangular electrical stimulus waveforms in activating small vagus nerve fibers

BackgroundIn the context of morbid obesity, vagus nerve stimulation could be used to control gastric function targeting the small afferent B-fibers and C-fibers. Compared to large A-fibers, activation thresholds of these small efferent fibers are 10 to 100 times greater, inducing technical constraints and possible nerve damages. Although rectangular waveform is commonly used in nerve stimulation, recent modeling and experimental studies suggest that non-rectangular waveforms could reduced the charge injected by the stimulator. New methodThe objective of the present study is to evaluate the charge injection of complex waveforms such as the ramp, quarter sine and chopped pulses in the context of vagus nerve stimulation. We performed in-vivo study on the porcine abdominal vagus nerves and evaluated charge injection at activation thresholds. A modeling study was performed to further extent the results obtained in-vivo. Comparison with existing methodCompared to the rectangular pulse, the ramp and quarter sine waveforms activated gastric fibers with the lowest charge injection: −23.2% and −30.1% respectively. The efficacy of chopped pulses is questioned through the consideration of the strength-duration curve. ConclusionContinuous ramp and quarter sine waveforms effectively activate small diameter fibers. These pulse shapes may be considered for long-term vagus nerve stimulation. The results predicted by computational models were qualitatively consistent with experiments. This suggested the relevance of using modeling in the context of complex waveforms prior to future in-vivo tests.