Model-Based Design and Experimental Validation of Control Modules for Neuromodulation Devices

International audienceGoal - The goal of this paper is to propose a model-based control design framework, adapted to the development of control modules for medical devices. A particular example is presented in which instantaneous heart rate is regulated in real-time, by modulating, in an adaptive manner, the current delivered to the vagus nerve by a neuromodulator. Methods - The proposed framework couples a control module, based on a classical PI controller, a mathematical model of the medical device, and a physiological model representing the cardiovascular responses to vagus nerve stimulation (VNS). In order to analyze and evaluate the behavior of the device, different control parameters are tested on a "virtual population," generated with the model, according to the Latin Hypercube sampling method. In particular, sensitivity analyses are applied for the identification of a domain of interest in the space of the control parameters. The obtained control parameter domain has been validated in an experimental evaluation on six sheep. Results - A range of control parameters leading to accurate results was successfully estimated by the proposed model-based design method. Experimental evaluation of the control parameters inside such a domain led to the best compromise between accuracy and time response of the VNS control. Conclusion - The feasibility and usefulness of the proposed model-based design method were shown, leading to a functional, real-time closed-loop control of the VNS for the regulation of heart rate

Miniaturized wireless electronic device for application on rodents thermal neuromodulation

Dissertação de mestrado em Biomedical Engineering, Medical Electronics BranchA epilepsia é uma doença neurológica que afeta muitas pessoas em todo o mundo, e cerca de 30% dos pacientes epiléticos são resistentes aos medicamentos. Normalmente, estes são obrigados a ficar em casa, uma vez que a opção é uma cirurgia de ressecção focal, o que nem sempre é possível ou aceite. Portanto, e como em muitas patologias onde é possível o desenvolvimento de dispositivos médicos capazes de melhorar a qualidade de vida dos pacientes, a tecnologia pode-se associar à medicina e fornecer uma solução alternativa para tais pacientes. Dos vários estudos já realizados neste campo, a neuromodulação térmica é uma técnica promissora, uma vez que reduz ou possivelmente interrompe as crises epiléticas. Assim, a fim de potencializar uma solução futura para estes pacientes, é necessário primeiro realizar vários testes experimentais com modelos animais. Com o intuito de melhor compreender o funcionamento dos testes in vivo, foram realizados testes em GAERS no Grenoble Institute of Neuroscience com um dispositivo previamente desenvolvido, a fim de recolher dados sobre o efeito de arrefecimento nos neurónios. Isso permitiu alargar o conhecimento sobre o arrefecimento focal, mas também permitiu encontrar limitações no dispositivo utilizado, dado que era necessário que este estivesse conectado por fios para ser possível aplicar frio e gravar o EEG. Assim, o objetivo desta dissertação foi melhorar a comunicação sem fios de um dispositivo eletrónico capaz de controlar um Peltier e registar a atividade elétrica cerebral de um roedor. O sistema possui dois módulos, um que maioritariamente transmite dados e outro que os recebe. Nesse sentido, o transmissor possui toda a eletrónica associada à comunicação sem fios, à aquisição de sinais eletrofisiológicos e ao controlo do Peltier. Já o recetor possui a eletrónica para a comunicação sem fios e um conector USB para se conectar ao computador. Com o intuito de aumentar o débito binário da transação de dados, os dois módulos foram programados com o protocolo proprietário da Nordic Semiconductor, denominado Enhanced ShockBurst que opera na banda 2.4 GHz. Após a implementação do software, obteve-se um débito binário de 368640 bps, o que é 17 vezes superior ao protocolo usado anteriormente. Assim, é possível adquirir biossinais com frequências mais elevadas, ou então, com frequências mais baixas, mas com mais resolução e, ainda a visualização de mais do que um canal. De forma a validar todo o sistema, realizaram-se vários testes. Um dos testes foi colocar nos elétrodos uma onda sinusoidal e observar no computador se a onda recebida era igual à onda de entrada. O outro foi determinar a taxa de erros associada à comunicação e o tempo de vida da bateria.Epilepsy is a neurological disorder that affects numerous people worldwide, and around 30% of epileptic patients are drug resistant. Usually, they are restrained at home, since the option is a focal resection surgery, which is not always possible or accepted. Therefore, and as in many pathologies, where it allows the development of medical devices capable of improving patients’ quality of life, technology may be used here to help medicine providing an alternative solution for such patients. Of the many studies already conducted in this field, thermal neuromodulation is a promising technique as it reduces or possibly interrupts epileptic seizures. Thus, in order to leverage a future solution for these patients, it’s first necessary to run several experimental tests with animal models. To better understand how in vivo tests work, tests were initially performed on GAERS at the Grenoble Institute of Neuroscience with a previously developed device in order to collect data on the cooling effect on neurons. This allowed to extend the knowledge about focal cooling, but also allowed to find limitations in the device used, as it was required to be wired in order to be able to apply cold and record the EEG. Therefore, the aim of this dissertation was to improve the wireless communication of an electronic device capable of controlling a Peltier module and recording the electrical brain activity of a rodent. The system has two modules, one that mostly transmits data and another that receives them. In this sense, the transmitter has all the electronics associated with wireless communication, electrophysiological signal acquisition, and Peltier control. The receiver, on the other hand, has the electronics for wireless communication and a USB connector to connect to the computer. In order to increase the binary throughput of the data transaction, the two modules were programmed with the 2.4 GHz proprietary protocol from Nordic Semiconductor, called Enhanced ShockBurst. After implementation of the software, a binary throughput of 368640 bps was obtained, which is 17 times higher than the previously used protocol. Thus, it is possible to acquire biosignals at higher frequencies, or at lower frequencies but with more resolution, and to visualize more than one channel. In order to validate the whole system, several tests were performed. One of the tests was to place a sine wave on the electrodes and observe in the computer if the signal received was equal to the input wave. The other, on the other hand, was to determine the error rate associated with communication and battery life

Born to learn: The inspiration, progress, and future of evolved plastic artificial neural networks

Biological plastic neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifetime learning. The interplay of these elements leads to the emergence of adaptive behavior and intelligence. Inspired by such intricate natural phenomena, Evolved Plastic Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed plastic neural networks with a large variety of dynamics, architectures, and plasticity rules: these artificial systems are composed of inputs, outputs, and plastic components that change in response to experiences in an environment. These systems may autonomously discover novel adaptive algorithms, and lead to hypotheses on the emergence of biological adaptation. EPANNs have seen considerable progress over the last two decades. Current scientific and technological advances in artificial neural networks are now setting the conditions for radically new approaches and results. In particular, the limitations of hand-designed networks could be overcome by more flexible and innovative solutions. This paper brings together a variety of inspiring ideas that define the field of EPANNs. The main methods and results are reviewed. Finally, new opportunities and developments are presented

Bidirectional Neural Interface Circuits with On-Chip Stimulation Artifact Reduction Schemes

Bidirectional neural interfaces are tools designed to “communicate” with the brain via recording and modulation of neuronal activity. The bidirectional interface systems have been adopted for many applications. Neuroscientists employ them to map neuronal circuits through precise stimulation and recording. Medical doctors deploy them as adaptable medical devices which control therapeutic stimulation parameters based on monitoring real-time neural activity. Brain-machine-interface (BMI) researchers use neural interfaces to bypass the nervous system and directly control neuroprosthetics or brain-computer-interface (BCI) spellers. In bidirectional interfaces, the implantable transducers as well as the corresponding electronic circuits and systems face several challenges. A high channel count, low power consumption, and reduced system size are desirable for potential chronic deployment and wider applicability. Moreover, a neural interface designed for robust closed-loop operation requires the mitigation of stimulation artifacts which corrupt the recorded signals. This dissertation introduces several techniques targeting low power consumption, small size, and reduction of stimulation artifacts. These techniques are implemented for extracellular electrophysiological recording and two stimulation modalities: direct current stimulation for closed-loop control of seizure detection/quench and optical stimulation for optogenetic studies. While the two modalities differ in their mechanisms, hardware implementation, and applications, they share many crucial system-level challenges. The first method aims at solving the critical issue of stimulation artifacts saturating the preamplifier in the recording front-end. To prevent saturation, a novel mixed-signal stimulation artifact cancellation circuit is devised to subtract the artifact before amplification and maintain the standard input range of a power-hungry preamplifier. Additional novel techniques have been also implemented to lower the noise and power consumption. A common average referencing (CAR) front-end circuit eliminates the cross-channel common mode noise by averaging and subtracting it in analog domain. A range-adapting SAR ADC saves additional power by eliminating unnecessary conversion cycles when the input signal is small. Measurements of an integrated circuit (IC) prototype demonstrate the attenuation of stimulation artifacts by up to 42 dB and cross-channel noise suppression by up to 39.8 dB. The power consumption per channel is maintained at 330 nW, while the area per channel is only 0.17 mm2. The second system implements a compact headstage for closed-loop optogenetic stimulation and electrophysiological recording. This design targets a miniaturized form factor, high channel count, and high-precision stimulation control suitable for rodent in-vivo optogenetic studies. Monolithically integrated optoelectrodes (which include 12 µLEDs for optical stimulation and 12 electrical recording sites) are combined with an off-the-shelf recording IC and a custom-designed high-precision LED driver. 32 recording and 12 stimulation channels can be individually accessed and controlled on a small headstage with dimensions of 2.16 x 2.38 x 0.35 cm and mass of 1.9 g. A third system prototype improves the optogenetic headstage prototype by furthering system integration and improving power efficiency facilitating wireless operation. The custom application-specific integrated circuit (ASIC) combines recording and stimulation channels with a power management unit, allowing the system to be powered by an ultra-light Li-ion battery. Additionally, the µLED drivers include a high-resolution arbitrary waveform generation mode for shaping of µLED current pulses to preemptively reduce artifacts. A prototype IC occupies 7.66 mm2, consumes 3.04 mW under typical operating conditions, and the optical pulse shaping scheme can attenuate stimulation artifacts by up to 3x with a Gaussian-rise pulse rise time under 1 ms.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147674/1/mendrela_1.pd

Exploring Neuromodulatory Systems for Dynamic Learning

In a continual learning system, the network has to dynamically learn new tasks from few samples throughout its lifetime. It is observed that neuromodulation acts as a key factor in continual and dynamic learning in the central nervous system. In this work, the neuromodulatory plasticity is embedded with dynamic learning architectures. The network has an inbuilt modulatory unit that regulates learning depending on the context and the internal state of the system, thus rendering the networks with the ability to self modify their weights. In one of the proposed architectures, ModNet, a modulatory layer is introduced in a random projection framework. This layer modulates the weights of the output layer neurons in tandem with hebbian learning. Moreover, to explore modulatory mechanisms in conjunction with backpropagation in deeper networks, a modulatory trace learning rule is introduced. The proposed learning rule, uses a time dependent trace to automatically modify the synaptic connections as a function of ongoing states and activations. The trace itself is updated via simple plasticity rules thus reducing the demand on resources. A digital architecture is proposed for ModNet, with on-device learning and resource sharing, to facilitate the efficacy of dynamic learning on the edge. The proposed modulatory learning architecture and learning rules demonstrate the ability to learn from few samples, train quickly, and perform one shot image classification in a computationally efficient manner. The ModNet architecture achieves an accuracy of ∼91% for image classification on the MNIST dataset while training for just 2 epochs. The deeper network with modulatory trace achieves an average accuracy of 98.8%±1.16 on the omniglot dataset for five-way one-shot image classification task. In general, incorporating neuromodulation in deep neural networks shows promise for energy and resource efficient lifelong learning systems

Robotic control based on the human nervous system

This article presents a model of robotic control system inspired by the human neuroregulatory system. This model allows the application of functional and organizational principles of biological systems to robotic systems. It also proposes appropriate technologies to implement this proposal, in particular the services. To illustrate the proposal, we implemented a control system for mobile robots in dynamic open environments, demonstrating the viability of both the model and the technologies chosen for implementation

Wireless tools for neuromodulation

Epilepsy is a spectrum of diseases characterized by recurrent seizures. It is estimated that 50 million individuals worldwide are affected and 30% of cases are medically refractory or drug resistant. Vagus nerve stimulation (VNS) and deep brain stimulation (DBS) are the only FDA approved device based therapies. Neither therapy offers complete seizure freedom in a majority of users. Novel methodologies are needed to better understand mechanisms and chronic nature of epilepsy. Most tools for neuromodulation in rodents are tethered. The few wireless devices use batteries or are inductively powered. The tether restricts movement, limits behavioral tests, and increases the risk of infection. Batteries are large and heavy with a limited lifetime. Inductive powering suffers from rapid efficiency drops due to alignment mismatches and increased distances. Miniature wireless tools that offer behavioral freedom, data acquisition, and stimulation are needed. This dissertation presents a platform of electrical, optical and radiofrequency (RF) technologies for device based neuromodulation. The platform can be configured with features including: two channels differential recording, one channel electrical stimulation, and one channel optical stimulation. Typical device operation consumes less than 4 mW. The analog front end has a bandwidth of 0.7 Hz - 1 kHz and a gain of 60 dB, and the constant current driver provides biphasic electrical stimulation. For use with optogenetics, the deep brain optical stimulation module provides 27 mW/mm2 of blue light (473 nm) with 21.01 mA. Pairing of stimulating and recording technologies allows closed-loop operation. A wireless powering cage is designed using the resonantly coupled filter energy transfer (RCFET) methodology. RF energy is coupled through magnetic resonance. The cage has a PTE ranging from 1.8-6.28% for a volume of 11 x 11 x 11 in3. This is sufficient to chronically house subjects. The technologies are validated through various in vivo preparations. The tools are designed to study epilepsy, SUDEP, and urinary incontinence but can be configured for other studies. The broad application of these technologies can enable the scientific community to better study chronic diseases and closed-loop therapies

Translingual neurostimulation combined with physical therapy to improve walking and balance in multiple sclerosis (NeuroMSTraLS): Study protocol for a randomized controlled trial

INTRODUCTION: Physical rehabilitation restores lost function and promotes brain plasticity in people with Multiple Sclerosis (MS). Research groups worldwide are testing the therapeutic effects of combining non-invasive neuromodulation with physical therapy (PT) to further improve functional outcomes in neurological disorders but with mixed results. Whether such devices enhance function is not clear. We present the rationale and study design for a randomized controlled trial evaluating if there is additional benefit to the synergistic pairing of translingual neurostimulation (TLNS) with PT to improve walking and balance in MS. METHODS AND ANALYSIS: A parallel group [PT + TLNS or PT + Sham], quadruple-blinded, randomized controlled trial. Participants (N = 52) with gait and balance deficits due to relapsing-remitting or progressive MS, who are between 18 and 70 years of age, will be recruited through patient registries in Newfoundland & Labrador and Saskatchewan, Canada. All participants will receive 14 weeks of PT while wearing either a TLNS or sham device. Dynamic Gait Index is the primary outcome. Secondary outcomes include fast walking speed, subjective ratings of fatigue, MS impact, and quality of life. Outcomes are assessed at baseline (Pre), after 14 weeks of therapy (Post), and 26 weeks (Follow Up). We employ multiple methods to ensure treatment fidelity including activity and device use monitoring. Primary and secondary outcomes will be analyzed using linear mixed-effect models. We will control for baseline score and site to test the effects of Time (Post vs. Follow-Up), Group and the Group x Time interaction as fixed effects. A random intercept of participant will account for the repeated measures in the Time variable. Participants must complete the Post testing to be included in the analysis. ETHICS AND DISSEMINATION: The Human Research Ethics Boards in Newfoundland & Labrador (HREB#2021.085) & Saskatchewan (HREB Bio 2578) approved the protocol. Dissemination avenues include peer-reviewed journals, conferences and patient-oriented communications