Neurostimulation Devices Research Articles

Response to: Managing Intrathecal Drug Delivery Devices in a Global Pandemic

Response to: Managing Intrathecal Drug Delivery Devices in a Global Pandemic

Fractional-order model predictive control as a framework for electrical neurostimulation in epilepsy

Objective. Electrical neurostimulation is an increasingly adopted therapeutic methodology for neurological conditions such as epilepsy. Electrical neurostimulation devices are commonly characterized by their limited sensing, actuating, and computational capabilities. However, the sensing mechanisms are often used only for their detection potential (e.g. to detect seizures), which automatically and dynamically trigger the actuation capabilities, but ultimately deploy prespecified stimulation doses that resulted from a period of manual (and empirical) calibration. The potential information contained in the measurements acquired by the sensing mechanisms is, therefore, considerably underutilized, given that this type of stimulation strategy only entails an event-triggered relationship between the sensors and actuators of the device. Such stimulation strategies are suboptimal in general and lack theoretical guarantees regarding their performance. Approach. In order to leverage the aforementioned information, harvested during normal sensing-actuating operation, we must consider a real-time feedback (closed-loop) strategy. More precisely, the stimulation signal itself should automatically adapt based upon the state of the neurophysiological system at hand, estimated from data collected in real-time through sensors in the device. Main results. In this work, we propose a model-based approach for (real-time) closed-loop electrical neurostimulation, in which the evolution of the system is captured by a fractional-order system (FOS). More precisely, we propose a model predictive control (MPC) approach with an underlying FOS predictive model, due to the ability of fractional-order dynamics to more accurately capture the long-term dependence present in biological systems, compared to the standard linear time-invariant models. Furthermore, MPC offers, by design, an additional layer of robustness to compensate for system-model mismatch, which the more traditional strategies lack. To establish the potential of our framework, we focus on epileptic seizure mitigation by computational simulation of our proposed strategy upon seizure-like events. Lastly, we provide evidence of the effectiveness of our method on seizures simulated by commonly adopted models in the neuroscience and medical community present in the literature, as well as real seizure data as obtained from subjects with epilepsy. Significance Our study thus paves the way for the development and implementation of robust real-time closed-loop electrical neurostimulation which can then be used for the construction of more effective devices for epileptic seizure mitigation.

Complications of Intracranial Responsive Neurostimulation Devices for Epilepsy

Giles, Tyler X; Gendreau, Julian L BS; Bennet, Josiah; Stone, Courtney; Abraham, Mickey E Author Information

Peripheral Neuromodulation for the Management of Headache.

ContextNeuromodulation is an expanding field of study for headache treatment to reduce pain by targeting structures within the nervous system that are commonly involved in headache pathophysiology, such as the vagus nerve (VNS), occipital nerves, or sphenopalatine ganglion (SPG) for stimulation. Pharmaceutical medical therapies for abortive and prophylactic treatment, such as triptans, NSAIDs, beta-blockers, TCAs, and antiepileptics, are effective for some individuals, but the role that technology plays in investigating other therapeutic modalities is essential. Peripheral neuromodulation has gained popularity and FDA approval for use in treating certain headaches and migraine headache conditions, particularly in those who are refractory to treatment. Early trials found FDA approved neurostimulatory implant devices, including Cephaly and SpringTMS, improved patient-oriented outcomes with reductions in headaches per month (frequency) and severity.Evidence AcquisitionThis was a narrative review. The sources for this review are as follows: Searching on PubMed, Google Scholar, Medline, and ScienceDirect from 1990 - 2019 using keywords: Peripheral Neuromodulation, Headache, vagus nerve, occipital nerves, sphenopalatine ganglion.ResultsThe first noninvasive neurostimulator device approved for migraine treatment was the Cefaly device, an external trigeminal nerve stimulation device (e-TNS) that transcutaneously excites the supratrochlear and supraorbital branches of the ophthalmic nerve. The second noninvasive neurostimulation device receiving FDA approval was the single-pulse transcranial magnetic stimulator, SpringTMS, positioned at the occiput to treat migraine with aura. GammaCore is a handheld transcutaneous vagal nerve stimulator applied directly to the neck at home by the patient for treatment of cluster headache (CH) and migraine. Several other devices are in development for the treatment of headaches and target headache evolution at different levels and inputs. The Scion device is a caloric vestibular stimulator (CVS) which interfaces with the user through a set of small cones resting in the ear canal on either side and held in place by modified over-ear headphones. The pulsante SPG Microstimulator is a patient-controlled device implanted in the patient’s upper jaw via an hour-long oral procedure to target the sphenopalatine ganglion. The occipital nerve stimulator (ONS) is an invasive neuromodulation device for headache treatment that consists of an implanted pulse generator on the chest wall connected to a subcutaneous lead with 4 - 8 electrodes that is tunneled the occiput.ConclusionsThe aim of this review is to provide a comprehensive overview of the efficacy, preliminary outcomes, and limitations of neurostimulatory implants available for use in the US and those pending further development.

Treatment of Multi-Focal Epilepsy With Resective Surgery Plus Responsive Neurostimulation (RNS): One Institution's Experience

Objective: Patients with medically refractory focal epilepsy can be difficult to treat surgically, especially if invasive monitoring reveals multiple ictal onset zones. Possible therapeutic options may include resection, neurostimulation, laser ablation, or a combination of these surgical modalities. To date, no study has examined outcomes associated with resection plus responsive neurostimulation (RNS, Neuropace, Inc., Mountain View, CA) implantation and we describe our initial experience in patients with multifocal epilepsy undergoing this combination therapy.Methods: A total of 43 responsive neurostimulation (RNS) devices were implanted at UCI from 2015 to 2019. We retrospectively reviewed charts of patients from the same time period who underwent both resection and RNS implantation. Patients were required to have independent or multifocal onset, undergo resection and RNS implantation, and have a minimum of six-months for follow-up to be included in the study. Demographics, location of ictal onset, location of surgery, complications, and seizure outcome were collected.Results: Ten patients met inclusion criteria for the study, and seven underwent both procedures in the same setting. The average age was 36. All patients had multifocal ictal onset on video electroencephalogram or invasive EEG with four patients undergoing subdural grid placement and four patients undergoing bilateral sEEG prior to the definitive surgery. Five patients underwent resection plus ipsilateral RNS placement and the remainder underwent resection with contralateral RNS placement. Two minor complications were encountered in this group. At six months follow up, there was an average of 81% ± 9 reduction in seizures, while four patients experienced complete seizure freedom at 1 year.Conclusion: Patients with multifocal epilepsy can be treated with partial resection plus RNS. The complication rates are low with potential for worthwhile seizure reduction.

The RNS System: brain-responsive neurostimulation for the treatment of epilepsy

ABSTRACT Introduction: Epilepsy affects more than 1% of the US population, and over 30% of adults with epilepsy do not respond to antiseizure medications without life-impacting medication-related side effects. Resection of the seizure focus is not an option for many patients because it would cause unacceptable neurological or cognitive harm. For these patients, neuromodulation has emerged as a nondestructive, effective, and safe alternative. The NeuroPace® RNS® System, the only brain-responsive neurostimulation device, records neural activity from leads placed at one or two seizure foci. When the neurostimulator detects epileptiform activity, as defined for each patient by his or her physician, brief pulses of electrical stimulation are delivered to normalize the activity. Areas covered: This review describes the RNS System, the results of multi-year clinical trials, and the research discoveries enabled by the chronic ambulatory brain data collected by the RNS System. Expert commentary: Brain-responsive neurostimulation could potentially be used to treat any episodic neurological disorder that’s accompanied by a neurophysiological biomarker of severity. Combining advanced machine learning approaches with the chronic ambulatory brain data collected by the RNS System could eventually enable automatic fine-tuning of detection and stimulation for each patient, creating a general-purpose neurotechnological platform for precision medicine.

ECG Artifact by a Spinal Cord Neurostimulator: A Case Report

Background: Neurostimulator devices produce electrical oscillations that may prevent accurate diagnosis of an ECG.
 The Case: We present the case of a 68-year-old man who came to the emergency department with chest pain and a spinal cord neuromodulator device in situ to treat his polymyalgia rheumatic. A 12-lead ECG was obtained to determine the cause of the chest pain, and atrial fibrillation was wrongly diagnosed.
 Conclusion: This case reiterates the value of recognizing this uncommonly encountered ECG artifact to avoid unnecessary mistakes in interpretation of heart rhythms.

Neurolight: A Deep Learning Neural Interface for Cortical Visual Prostheses.

Visual neuroprosthesis, that provide electrical stimulation along several sites of the human visual system, constitute a potential tool for vision restoration for the blind. Scientific and technological progress in the fields of neural engineering and artificial vision comes with new theories and tools that, along with the dawn of modern artificial intelligence, constitute a promising framework for the further development of neurotechnology. In the framework of the development of a Cortical Visual Neuroprosthesis for the blind (CORTIVIS), we are now facing the challenge of developing not only computationally powerful tools and flexible approaches that will allow us to provide some degree of functional vision to individuals who are profoundly blind. In this work, we propose a general neuroprosthesis framework composed of several task-oriented and visual encoding modules. We address the development and implementation of computational models of the firing rates of retinal ganglion cells and design a tool - Neurolight - that allows these models to be interfaced with intracortical microelectrodes in order to create electrical stimulation patterns that can evoke useful perceptions. In addition, the developed framework allows the deployment of a diverse array of state-of-the-art deep-learning techniques for task-oriented and general image pre-processing, such as semantic segmentation and object detection in our system's pipeline. To the best of our knowledge, this constitutes the first deep-learning-based system designed to directly interface with the visual brain through an intracortical microelectrode array. We implement the complete pipeline, from obtaining a video stream to developing and deploying task-oriented deep-learning models and predictive models of retinal ganglion cells' encoding of visual inputs under the control of a neurostimulation device able to send electrical train pulses to a microelectrode array implanted at the visual cortex.

Nine-year prospective efficacy and safety of brain-responsive neurostimulation for focal epilepsy.

ObjectiveTo prospectively evaluate safety and efficacy of brain-responsive neurostimulation in adults with medically intractable focal onset seizures (FOS) over 9 years.MethodsAdults treated with brain-responsive neurostimulation in 2-year feasibility or randomized controlled trials were enrolled in a long-term prospective open label trial (LTT) to assess safety, efficacy, and quality of life (QOL) over an additional 7 years. Safety was assessed as adverse events (AEs), efficacy as median percent change in seizure frequency and responder rate, and QOL with the Quality of Life in Epilepsy (QOLIE-89) inventory.ResultsOf 256 patients treated in the initial trials, 230 participated in the LTT. At 9 years, the median percent reduction in seizure frequency was 75% (p < 0.0001, Wilcoxon signed rank), responder rate was 73%, and 35% had a ≥90% reduction in seizure frequency. We found that 18.4% (47 of 256) experienced ≥1 year of seizure freedom, with 62% (29 of 47) seizure-free at the last follow-up and an average seizure-free period of 3.2 years (range 1.04–9.6 years). Overall QOL and epilepsy-targeted and cognitive domains of QOLIE-89 remained significantly improved (p < 0.05). There were no serious AEs related to stimulation, and the sudden unexplained death in epilepsy (SUDEP) rate was significantly lower than predefined comparators (p < 0.05, 1-tailed χ2).ConclusionsAdjunctive brain-responsive neurostimulation provides significant and sustained reductions in the frequency of FOS with improved QOL. Stimulation was well tolerated; implantation-related AEs were typical of other neurostimulation devices; and SUDEP rates were low.ClinicalTrials.gov identifierNCT00572195.Classification of evidenceThis study provides Class IV evidence that brain-responsive neurostimulation significantly reduces focal seizures with acceptable safety over 9 years.

Plasmon-Coupled Photocapacitor Neuromodulators.

Efficient transduction of optical energy to bioelectrical stimuli is an important goal for effective communication with biological systems. For that, plasmonics has a significant potential via boosting the light–matter interactions. However, plasmonics has been primarily used for heat-induced cell stimulation due to membrane capacitance change (i.e., optocapacitance). Instead, here, we demonstrate that plasmonic coupling to photocapacitor biointerfaces improves safe and efficacious neuromodulating displacement charges for an average of 185% in the entire visible spectrum while maintaining the faradic currents below 1%. Hot-electron injection dominantly leads the enhancement of displacement current in the blue spectral window, and the nanoantenna effect is mainly responsible for the improvement in the red spectral region. The plasmonic photocapacitor facilitates wireless modulation of single cells at three orders of magnitude below the maximum retinal intensity levels, corresponding to one of the most sensitive optoelectronic neural interfaces. This study introduces a new way of using plasmonics for safe and effective photostimulation of neurons and paves the way toward ultrasensitive plasmon-assisted neurostimulation devices.

Automated human mind reading using EEG signals for seizure detection

Epilepsy is one of the most occurring neurological disease globally emerged back in 4000 BC. It is affecting around 50 million people of all ages these days. The trait of this disease is recurrent seizures. In the past few decades, the treatments available for seizure control have improved a lot with the advancements in the field of medical science and technology. Electroencephalogram (EEG) is a widely used technique for monitoring the brain activity and widely popular for seizure region detection. It is performed before surgery and also to predict seizure at the time operation which is useful in neuro stimulation device. But in most of cases visual examination is done by neurologist in order to detect and classify patterns of the disease but this requires a lot of pre-domain knowledge and experience. This all in turns put a pressure on neurosurgeons and leads to time wastage and also reduce their accuracy and efficiency. There is a need of some automated systems in arena of information technology like use of neural networks in deep learning which can assist neurologists. In the present paper, a model is proposed to give an accuracy of 98.33% which can be used for development of automated systems. The developed system will significantly help neurologists in their performance.

SPARC: Development of Human and Rodent Neuro‐Functionalized Computational Anatomical Models with Detailed Mapping of Peripheral Nervous System

There is a growing trend within the neuroscience community and the medical and health industries towards bioelectronics medicine: applying electrical signals to the nervous system to control and modulate functions of the body. These so‐called “electroceuticals” include numerous types of neurostimulation devices. To this end, we have developed reference animal and human anatomical models with unprecedented details in the peripheral nervous system, and connectivity to organs and muscles, which were functionalized with compartmental neuronal dynamics models to investigate device interactions with neuronal electrophysiology. The whole body rat model is being segmented from co‐registered high‐resolution (80 × 80 × 80 μm) magnetic resonance imaging (MRI) and computed tomography (CT) images of a female rat. The Visible Korean Human (1) male and female cryosection data was used as the basis for the new human phantoms, due to the unique resolution (0.1 × 0.1 × 0.2 mm) and quality of these images. To model important peripheral nerves trajectories, the nerves were segmented and anatomically correct trajectories were extracted automatically using a set of anatomical rules specifying, which dorsal or ventral roots are connected to a given nerve. Functionalization is achieved by assigning electrophysiological models of myelinated and unmyelinated axons to axon trajectories within nerve models based on histological investigations documented in the literature (2).The new human female and male human models called Yoon‐sun and Jeduk respectively, have been released as part of the Virtual Population (3) V4.0 model library. The neuro‐functionalized rat will be completed soon. These models will become integration centers for NIH SPARC neuroanatomy and electrophysiology models (4) and are expected to significantly influence the field of computational neuro‐electrophysiology research enabling studies of multi‐scale models with realistic anatomies and electrophysiology. Simulations will enhance our understanding of mechanisms of neurostimulation, e.g., by MRI gradient fields, provide experimental test‐beds for new therapeutic approaches and devices, and enable study of safety aspects, thus providing a tool to facilitate regulatory submissions and standardization activities.Support or Funding InformationThis work has been done with funding from NIH SPARC (1OT3OD025348‐01S1). The work on human anatomical models also received funding from Innosuisse (25290.1 PFLS‐LS) and KIAT.Computational rat model is shown with muscle tissue and limbs clipped to show interior tissue structures.Figure 1Side‐by‐side visualization of different tissue structures in the female computational human anatomical model ‘Yoon‐sun’. The model contains approximately 1100 separate tissues, with detailed bones, organs, muscles, blood vessels and peripheral nervous system (right).Figure 2

Advances in the Treatment of Drug-Resistant Pediatric Epilepsy.

Epilepsy is a common disorder in children and adults that causes significant morbidity and affects many aspects of a patient's lives. Two-thirds of patients with epilepsy are controlled with established antiseizure medications, leaving a significant number of patients searching for other options. The purpose of this review is to provide an overview of recent advancements in the management of treatment-resistant epilepsy in pediatric patients. Recent publications have shown the efficacy of new pharmaceutical options such as fenfluramine and cannabidiol, some of which have been tested specifically in patients with childhood-onset epilepsy syndromes such as Dravet's syndrome and Lennox-Gastaut's syndrome. Furthermore, recent approval by the U.S. Food and Drug Administration of stiripentol has made available a previously difficult-to-obtain option for patients with Dravet's syndrome. Finally, implanted responsive neurostimulation devices for direct cortical stimulation and deep brain stimulation have shown efficacy in adult patients and may represent a thrilling new horizon for pediatric patients.

Sleep disruption is not observed with brain-responsive neurostimulation for epilepsy.

ObjectiveNeurostimulation devices that deliver electrical impulses to the nervous system are widely used to treat seizures in patients with medically refractory epilepsy, but the effects of these therapies on sleep are incompletely understood. Vagus nerve stimulation can contribute to obstructive sleep apnea, and thalamic deep brain stimulation can cause sleep disruption. A device for brain‐responsive neurostimulation (RNS® System, NeuroPace, Inc) is well tolerated in clinical trials, but potential effects on sleep are unknown.MethodsSix adults with medically refractory focal epilepsy treated for at least six months with the RNS System underwent a single night of polysomnography (PSG). RNS System lead locations included mesial temporal and neocortical targets. Sleep stages and arousals were scored according to standard guidelines. Stimulations delivered by the RNS System in response to detections of epileptiform activity were identified by artifacts on scalp electroencephalography.ResultsOne subject was excluded for technical reasons related to unreliable identification of stimulation artifact on EEG during PSG. In the remaining five subjects, PSG showed fragmented sleep with frequent arousals. Arousal histograms aligned to stimulations revealed a significant peak in arousals just before stimulation. In one of these subjects, the arousal peak began before stimulation and extended ~1 seconds after stimulation. A peak in arousals occurring only after stimulation was not observed.SignificanceIn this small cohort of patients, brain‐responsive neurostimulation does not appear to disrupt sleep. If confirmed in larger studies, this could represent a potential clinical advantage of brain‐responsive neurostimulation over other neurostimulation modalities.

Safety Analysis of Dorsal Root Ganglion Stimulation in the Treatment of Chronic Pain

BackgroundStimulation of the dorsal root ganglion (DRG) in the treatment of chronic, intractable pain has shown excellent clinical results in multiple published studies, including a large prospective, randomized, controlled trial. Both safety and efficacy have been demonstrated utilizing this therapeutic approach for many chronic complaints. Continued assessment of neuromodulation therapies, such as DRG stimulation, are not only an important aspect of vigilant care, but are also necessary for the evaluation for safety.Materials and MethodsSafety and complaint records for DRG and spinal cord stimulation (SCS) stimulation were obtained from the manufacturer, analyzed and compiled to further assess ongoing device safety. Complaint event data were stratified according to complain type as well as overall rates. Data from similar time periods were compared between epidural neurostimulation devices by the same manufacturer as well as rates reported in the literature.ResultsOverall, DRG stimulation device event rates were lower or comparable to similar epidurally placed neurostimulation devices. Rates of events varied from 0 to 1.0% for DRG stimulation (n >500+ implants) which was similar to the event rate for SCS by the same manufacturer (n >2000+ implants). In comparison, complaints and adverse events ranged from 0 to 14% for SCS in the literature.DiscussionsThe current results from a large consecutive cohort obtained from manufacturer records indicates that DRG stimulation demonstrates an excellent safety profile. Reported event rates are similar to previously reported adverse event and complaint rates in the literature for this therapy. Similarly, safety events rates were lower or similar to previously reported rates for SCS, further demonstrating the comparative safety of this neuromodulation technique for chronic pain treatment.

Non Invasive Treatment to Relieve the Pain due to Headaches &amp; Sinus using Vibration on Acupressure Points

Headache is a common term that causes pain in the region of head, neck, and scalp. It is a neurological disorder. The nerves are tending to be in under stress condition. The main causes of the headache are due to stress, depression, tension, anxiety and due to some climatic changes, etc. Headache is classified into different types. Migraine, cluster headache, sinus, normal headache are some of the types of headache. Most headaches can be treated with some medication and neuro stimulator devices. This paper involves the usage of vibration by non-invasive method on the acupressure point of the human body which can relief the pain. The acupressure point is a pressure point, when used in a correct method will lead to decrease the level of pain. The vibration is provided by the motor vibrator and the frequency of the vibration is controlled by the arduino (Atmega 328). Frequency changes can be monitored by the pc. This vibration based treatment will effectively reduce the pain and also the device is cost effective and more comfortable to the patient.

Robot-assisted versus manual navigated stereoelectroencephalography in adult medically-refractory epilepsy patients

ObjectiveStereoelectroencephalography (SEEG) has experienced a recent growth in adoption for epileptogenic zone (EZ) localization. Advances in robotics have the potential to improve the efficiency and safety of this intracranial seizure monitoring method. We present our institutional experience employing robot-assisted SEEG and compare its operative efficiency, seizure reduction outcomes, and direct hospital costs with SEEG performed without robotic assistance using navigated stereotaxy. MethodsWe retrospectively identified 50 consecutive adult SEEG cases at our institution in this IRB-approved study, of which 25 were navigated with image guidance (hereafter referred to as “navigated”) (02/2014-10/2016) and 25 were robot-assisted (09/2016-12/2017). A thorough review of medical/surgical history and operative records with imaging and trajectory plans was done for each patient. Direct inpatient costs related to each technique were compared. ResultsMost common seizure etiologies for patients undergoing navigated and robot-assisted SEEG included non-lesional and benign temporal lesions. Despite having a higher mean number of leads-per-patient (10.2 ± 3.5 versus 7.2 ± 2.6, P = 0.002), robot-assisted cases had a significantly shorter mean operative time than navigated cases (125.5±48.5 versus 173.4±84.3 min, P = 0.02). Comparison of robot-assisted cases over the study interval revealed no significant difference in mean operative time (136.4±51.4 min for the first ten cases versus 109.9±75.8 min for the last ten cases, P = 0.25) and estimated operative time-per-lead (13.4±6.0 min for the first ten cases versus 12.9±7.7 min for the last ten cases, P = 0.86). The mean depth, radial, target, and entry point errors for robot-assisted cases were 2.12±1.89, 1.66±1.58, 3.05±2.02 mm, and 1.39 ± 0.75 mm, respectively. The two techniques resulted in equivalent EZ localization rate (navigated 88 %, robot-assisted 96 %, P = 0.30). Common types of epilepsy surgery performed consisted of implantation of responsive neurostimulation (RNS) device (56 %), resection (19.1 %), and laser ablation (23.8 %) for navigated SEEG. For robot-assisted SEEG, either RNS implantation (68.2 %) or laser ablation (22.7 %) were performed or offered. A majority of navigated and robot-assisted patients who underwent epilepsy surgery achieved either Engel Class I (navigated 36.8 %, robot-assisted 31.6 %) or II (navigated 36.8 %, robot-assisted 15.8 %) outcome with no significant difference between the groups (P = 0.14). Direct hospital cost for robot-assisted SEEG was 10 % higher than non-robotic cases. ConclusionThis single-institutional study suggests that robotic assistance can enhance efficiency of SEEG without compromising safety or precision when compared to image guidance only. Adoption of this technique with uniform safety and efficacy over a short period of time is feasible with favorable epilepsy outcomes.

Electrical stimulation induces synaptic changes in the peripheral auditory system.

Since a rapidly increasing number of neurostimulation devices are used clinically to modulate specific neural functions, the impact of electrical stimulation on targeted neural structure and function has become a key issue. In particular, the specific effect of electrical stimulation via a cochlear implant (CI) on inner hair cell (IHC) synapses remains unclear. Importantly, CI candidacy has recently expanded to include patients with partial hearing loss. Unfortunately, some CI recipients experience progressive hearing loss after activation of electrical stimulation. The mechanism(s) accounting for loss of residual hearing following electrical stimulation is unknown. Here normal-hearing guinea pigs were implanted with customized CIs. Intracochlear electrical stimulation with an intensity equal to or above electrically evoked compound action potential (ECAP) threshold decreased the excitability of auditory nerve. Furthermore, the number of synapses between IHCs and the afferent spiral ganglion neurons (SGNs) also decreased after electrical stimulation with higher intensities. However, no significant change was observed in the packing density and perikaryal area of SGNs as well as the quantity of hair cells. These results carry important implications for use of CIs in patients with residual hearing and for an increasing number of patients treated with other neurostimulation devices. Notably, the results were based on acute electrical stimulation. Considering the complex interaction between CIs and targeted tissues, it is urgent to conduct further research to clarify whether the similar changes could be induced by chronic electrical stimulation.

Dimensions of Ethical Direct-to-Consumer Neurotechnologies

The direct-to-consumer (DTC) neurotechnology market, which includes some brain-computer interfaces, neurostimulation devices, virtual reality systems, wearables, and smartphone apps is rapidly growing. Given this technology’s intimate relationship with the brain, a number of ethical dimensions must be addressed so that the technology can achieve the goal of contributing to human flourishing. This paper identifies safety, transparency, privacy, epistemic appropriateness, existential authenticity, just distribution, and oversight as such dimensions. After an initial exploration of the relevant ethical foundations for DTC neurotechnologies, this paper lays out each dimension and uses examples to justify its inclusion.

Computational Simulation Expands Understanding of Electrotransfer-Based Gene Augmentation for Enhancement of Neural Interfaces

The neural interface is a critical factor in governing efficient and safe charge transfer between a stimulating electrode and biological tissue. The interface plays a crucial role in the efficacy of electric stimulation in chronic implants and both electromechanical properties and biological properties shape this. In the case of cochlear implants, it has long been recognized that neurotrophins can stimulate growth of the target auditory nerve fibers into a favorable apposition with the electrode array, and recently such arrays have been re-purposed to enable electrotransfer (electroporation)-based neurotrophin gene augmentation to improve the “bionic ear.” For both this acute bionic array-directed electroporation and for chronic conventional cochlear implant arrays, the electric fields generated in target tissue during pulse delivery are central to efficacy, but are challenging to map. We present a computational model for predicting electric fields generated by array-driven DNA electrotransfer in the cochlea. The anatomically realistic model geometry was reconstructed from magnetic resonance images of the guinea pig cochlea and an eight-channel electrode array embedded within this geometry. The model incorporates a description of both Faradaic and non-Faradaic mechanisms occurring at the electrode-electrolyte interface with frequency dependency optimized to match experimental impedance spectrometry measurements. Our simulations predict that a tandem electrode configuration with four ganged cathodes and four ganged anodes produces three to fourfold larger area in target tissue where the electric field is within the range for successful gene transfer compared to an alternate paired anode-cathode electrode configuration. These findings matched in vivo transfection efficacy of a green fluorescent protein (GFP) reporter following array-driven electrotransfer of the reporter-encoding plasmid DNA. This confirms utility of the developed model as a tool to optimize the safety and efficacy of electrotransfer protocols for delivery of neurotrophin growth factors, with the ultimate aim of using gene augmentation approaches to improve the characteristics of the electrode-neural interfaces in chronically implanted neurostimulation devices.