Objectives: Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irrespective of the brain-related disorder. Thus, there is still a large margin for improvement. The goal of this manuscript is to 1) develop a general theoretical framework of brain functioning that is amenable to surgical neuromodulation, and 2) describe the engineering requirements of the next generation of implantable brain stimulators that follow from this theoretic model. Materials and Methods: A neuroscience and engineering literature review was performed to develop a universal theoretical model of brain functioning and dysfunctioning amenable to surgical neuromodulation. Results: Even though a single target can modulate an entire network, research in network science reveals that many brain disorders are the consequence of maladaptive interactions among multiple networks rather than a single network. Consequently, targeting the main connector hubs of those multiple interacting networks involved in a brain disorder is theoretically more beneficial. We, thus, envision next-generation network implants that will rely on distributed, multisite neuromodulation targeting correlated and anticorrelated interacting brain networks, juxtaposing alternative implant configurations, and finally providing solid recommendations for the realization of such implants. In doing so, this study pinpoints the potential shortcomings of other similar efforts in the field, which somehow fall short of the requirements. Conclusion: The concept of network stimulation holds great promise as a universal approach for treating neurologic and psychiatric disorders.

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State-of-the-art intracortical neural recording and stimulation systems rely on subdural implants tethered to a cranial implant which itself has a wireless power and data link to the outside world [1] (Fig. 6.2.1). However, this tethered configuration poses challenges such as scarring and potential damage to the surrounding tissue due to strain and micromotions, making this approach unsuitable for chronical implants [2]. Consequently, there is growing interest in wireless connections between cranial and subdural implants. This paper focuses on wireless powering between implants, traversing the dura and cerebrospinal fluid (CSF) tissue layers over distances of 0.5 to 1cm (transdural powering). With modern burr-hole craniotomy, the hole drilled in the skull is 6mm in diameter, limiting the available size for the TX. Moreover, the power dissipation of the TX must be low to keep tissue heating below 1°C [3]. RF and optical modalities suffer from higher attenuation in tissue compared to ultrasound (0.6dB/cm/MHz) [4]. Furthermore, for transdural powering, power losses from reflections at medium interfaces (e.g., skull) are avoided, making ultrasound (US) a prime candidate for efficient in-body wireless power transfer. US is also preferable to inductive powering since US beam steering up to large angles (>45°) is needed to maximize power delivery and compensate for brain micromotions of up to ±4mm [5] and misalignment during surgery. However, prior art US driving systems either use single-phase transducer driving [6, 7], incapable of beam steering, or use class D drivers with low power transfer efficiency (PTE) [8, 9]. A phased array with increased driving efficiency was presented in [10], but it cannot perform beam steering without grating lobes that can be eliminated with miniature transducers with a pitch close to λ/2. To facilitate direct integration between CMOS and the transducer array, the CMOS driving units should also be pitch matched [8, 9].

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In this paper, we present the surface modification of multilayer graphene electrodes with platinum (Pt) nanoparticles (NPs) using spark ablation. This method yields an individually selective local printing of NPs on an electrode surface at room temperature in a dry process. NP printing is performed as a post-process step to enhance the electrochemical characteristics of graphene electrodes. The NP-printed electrode shows significant improvements in impedance, charge storage capacity (CSC), and charge injection capacity (CIC), versus the equivalent electrodes without NPs. Specifically, electrodes with 40% NP surface density demonstrate 4.5 times lower impedance, 15 times higher CSC, and 4 times better CIC. Electrochemical stability, assessed via continuous cyclic voltammetry (CV) and voltage transient (VT) tests, indicated minimal deviations from the initial performance, while mechanical stability, assessed via ultrasonic vibration, is also improved after the NP printing. Importantly, NP surface densities up to 40% maintain the electrode optical transparency required for compatibility with optical imaging and optogenetics. These results demonstrate selective NP deposition and local modification of electrochemical properties in graphene electrodes for the first time, enabling the cohabitation of graphene electrodes with different electrochemical and optical characteristics on the same substrate for neural interfacing.@en

Recording neuronal activity triggered by electrical impulses is a powerful tool in neuroscience research and neural engineering. It is often applied in acute electrophysiological experimental settings to record compound nerve action potentials. However, the elicited neural response is often distorted by electrical stimulus artifacts, complicating subsequent analysis. In this work, we present a model to better understand the effect of the selected amplifier configuration and the location of the ground electrode in a practical electrophysiological nerve setup. Simulation results show that the stimulus artifact can be reduced by more than an order of magnitude if the placement of the ground electrode, its impedance, and the amplifier configuration are optimized. We experimentally demonstrate the effects in three different settings, in-vivo and in-vitro.@en

This paper presents a novel multi-channel stimulation backend with a multi-bit delta-sigma control loop, which enables precise adjustment of the stimulation current through modulation of the supply voltage. This minimizes the overhead voltage of series circuitry to the stimulation load and avoids the associated energy loss. Additionally, to address the bandwidth limitations commonly encountered in battery-less implants, we propose incorporating amplitude and duration scaling of the arbitrary stimulation waveform. The waveform is programmable with 64 7-bit samples and 4 scaling factors per channel, resulting in a minimum of 68% data reduction per channel compared to using the waveform without scaling. The proposed circuits are designed and simulated in 180nm BCD technology occupying a total silicon area of 9mm2. The fully integrated backend has a minimum compliance voltage of 8.5V and features a switched-capacitor multi-output DC-DC converter (MODDC) with pulse-skipping capability, a CMOS-only high-voltage (HV) multiplexer, and a unique HV H-bridge. Programming a sine-wave stimulus with a 4mA amplitude and a duration of 256μs achieved a signal-to-noise ratio of 40dB within a 10kHz bandwidth. For the same waveform, power efficiencies of 94% and 68% were observed without and with MODDC, respectively. Additionally, when programming constant-current stimuli ranging from 0.26mA to 4mA, high efficiencies of 78-97% and 23-79.4% were achieved without and with MODDC, respectively.@en

The key challenges in designing a multi-channel biosignal acquisition system for an ambulatory or invasive medical application with a high channel count are reducing the power consumption, area consumption and the outgoing wire count. This article proposes a spread-spectrum modulated biosignal acquisition system using a shared amplifier and an analog-to-digital converter (ADC). We propose a design method to optimize a recording system for a given application based on the required SNR performance, number of inputs, and area. The proposed method is tested and validated on real pre-recorded atrial electrograms and achieves an average percentage root-mean-square difference (PRD) performance of 2.65% and 3.02% for sinus rhythm (SR) and atrial fibrillation (AF), respectively by using pseudo-random binary-sequence (PRBS) codes with a code-length of 511, for 16 inputs. We implement a 4-input spread-spectrum analog front-end in a 0.18 μ m CMOS process to demonstrate the proposed approach. The analog front-end consists of a shared amplifier, a 2nd order Σ Δ ADC sampled at 7.8 MHz, used for digitization, and an on-chip 7-bit PRBS generator. It achieves a number-of-inputs to outgoing-wire ratio of 4:1 while consuming 23 μ A/input including biasing from a 1.8 V power supply and 0.067 mm ² in area.

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Developing neuroprosthetic bioelectronic devices requires wirelessly-powered implantable stimulator systems with hundreds to thousands of output channels. Power efficiency optimization is crucial for scaling up the number of output channels. Current-mode electrical stimulation is favored for safety but is power-inefficient in conventional designs, particularly in multichannel stimulators. An adaptive voltage supply can improve power efficiency, but implementing channel-specific voltage supplies in large-scale systems is challenging. Conventional power management suffers from losses and low efficiency due to multiple conversion stages. This work proposes a multichannel current-mode stimulator with a parallel, adaptive ac/dc power management strategy using single-stage phase-controlled converters to prevent cascaded losses. This allows for generating channel-specific supply voltages within a small area for high power efficiency and high-density electrical stimulation. The proposed circuit was designed and simulated using TSMC 180 nm technology and demonstrates an improvement in the power efficiency of up to 45% with respect to a conventional power-management strategy using a fixed supply voltage.@en

Electrical stimulation is proven to be an effective way of neuromodulation in bioelectronic medicine (e.g. cochlear implants, deep brain stimulators, etc.), delivering localized treatment by the means of electrical pulses. To increase the stimulation efficiency and neural-type selectivity, there is an increasing interest to employ non-rectangular stimulation waveforms [1-4]. Even though delivering and storing digital data at the stimulator provides the highest flexibility for generating stimulation waveforms, state-of-the-art approaches suffer either from poor resolution or the requirement of high data bandwidth for wirelessly powered implants [2]. Using Analog waveform generators is an alternative approach at the cost of extra implementation complexity for each type of waveform [3]. To fulfill the same goals as employing arbitrary waveforms for stimulation, we propose to shape the typical rectangular waveform using a programmable first-order low-pass filter, mimicking the natural filtering characteristic of the neural membrane. Using bio-realistic modeling, we show that such a pre-filtered waveform requires less or equal energy for the activation of neurons when compared with other energy-efficient waveforms (e.g. Gaussian). Notably, this comes at the low cost of only one extra programmable parameter (i.e., the filter’s corner frequency), on top of the typical duration and amplitude parameters. The basic concept of this work is driven by the fact that the natural low-pass characteristic of the neuron’s membrane limits the energy transfer efficiency from the stimulator to the cell. Thus, it is proposed to pre-filter the high-frequency components of the stimulus [4]. The method is validated for a Hodgkin-Huxley (HH) axon-cable model using NEURON v8.0 software. The required activation energy is simulated for rectangular, Gaussian, half-sine, triangular, ramp-up, and ramp-down waveforms, all with pulse durations of 10-1000µs, and low-pass filtered with cut-off frequencies of 0.5-50kHz. Simulations show a 51.5% reduction in the required activation energy for the shortest rectangular pulse (i.e., 10-μs pulse width) after filtering at 5kHz. It is also shown that the minimum required activation energy can be decreased by 11.04%, 9.49%, 8.28%, 1.81%, 0.17%, and 0% when an appropriate pre-filter is applied to the rectangular, ramp-down, ramp-up, half-sine, triangular, and Gaussian waveforms, respectively. Finally, a perspective usage of this method to improve the selectivity of electrical stimulation is drawn. @en

This paper presents a new communication method between micro-scale freely floating brain implants based on galvanic coupling (GC), called "Brain-Coupled Communication" (BCC). Since the transmission efficiency based on GC is highly dependent on the system’s geometry and the electromagnetic properties of the tissue, finite element models in COMSOL Multiphysics® are employed for characterizing the proposed method. Concurrent scaling of channel length (i.e., the distance between two implants), the inter-electrode distance (on a single implant), and electrode dimensions with a constant ratio down to 2 % of their typical values show an increase in the optimum frequency of the communication by 50 times (from 200 kHz to 10 MHz). This, in turn, yields a substantial increase in the channel bandwidth. The proposed method also shows excellent robustness against misalignment. Up to 60 ° of angular misalignment and 1 mm of lateral displacement result in a voltage-gain attenuation of less than 5 dB and 2 dB, respectively. Furthermore, a negligible shading effect between implants is observed by exploring multi-implant scenarios. Moreover, based on the conducted compliance study, no safety hazards were observed for the intended conditions. In conclusion, the proposed method exhibits a multitude of desirable qualities that position it as an excellent choice for establishing a network of freely floating brain implants.@en

During the last few decades, electrical neural stimulators have successfully been employed as a means of treatment for a wide range of neurological disorders. By targeting the peripheral and central nervous systems, electrical neurostimulators activate/inhibit neural activity by manipulating the stimulus- induced electric field arising at the targeted area through diverse electrode configurations. Aiming at reducing the overall size of implanted stimulator systems, these are being designed to be wirelessly powered and batteryless. Technologies for wireless power transfer to implants are mainly based on inductive coupling and, more recently, ultrasonic waves. To increase the power efficiency and thereby minimize the power consumption of the implant, we have previously proposed a stimulation technique that alters the electric field at the tissue by delivering charge in small packets in a very rapid manner (e.g. 1 Mpps). This charge is consequently accumulated by the tissue’s integrating nature.1 This approach removes the need to ensure continuous accurate control of the stimulus current amplitude, resulting in power savings. To the same end, in an ultrasonically powered system, unnecessary power-conversion blocks can be eliminated, as the incoming ultrasonic wave is harvested, converted into an electrical signal, rectified, and then directly used for stimulation.2 Inspired by the above, this work focuses on providing a discrete-component multi-channel neural stimulator, powered wirelessly through ultrasound (US), to activate and inhibit neural activity. The use of mostly commercially available discrete components will ensure reproducibility by other research labs and help provide a platform technology that can be used as an experimental tool in a variety of applications.3 The US pressure wave obtained at the receiving US transducer will be converted into electrical energy and used both for powering the system as well as to shape the charge packets of the eventual stimulus pulse. In this manner, the need for DC-DC up-conversion, typically needed for neuromodulation, will be eliminated.4 A charge-balancing technique, matching the fast pulse repetition rates (PRR) required for inhibition of neural activity (typically ≥ 5 kHz), will ensure the safety of the implant, while the injected charge will be constantly monitored and adapted for safe and efficacious activation/inhibition.@en

In an attempt to reduce the side effects caused by the chemically-based drugs used to treat neurological disorders, the field of bioelectronics has been focusing on the development of smart and reliable solutions that could, ideally, interact with the tissue at a resolution of individual cells.1 Conventionally, electrically-based systems have been used.2 However, increasing the resolution at which they interact with the body leads to the development of invasive electrode arrays, which can cause long-term side effects.3 Another approach, based on acoustic waves, has recently emerged. Ultrasound (US) neuromodulation has been proven to be effective in modulating the response of peripheral nerves, in an in-vivo setup4 and has the potential to achieve higher spatial selectivity.5 In this work, we aim to fabricate an implantable cuff for US neuromodulation, which would employ an array of US transducers to deliver focused US to specific nerve areas in a non-invasive manner. To this end, the potential of different US transducer arrays for peripheral nerve applications is evaluated, assessing the acoustic performances as well as ease of assembly and integration. More specifically, two of the most important parameters that affect neural excitation are the frequency and output pressure generated by the US transducers.4 Conventional bulk PZT transducers can generate a wide range of output pressures but these are not small enough for this application. PZT-based arrays, integrated on CMOS have recently emerged, and will be part of this evaluation6. However, these have not yet been integrated on flexible substrates. On the other hand, micromachined US transducers (MUTs) have been gaining a lot of interest, particularly capacitive MUTs (CMUTs) which can operate at high frequencies, thus reducing the focal point significantly.5 CMUTs can be fabricated on flexible substrates, using biocompatible materials, rendering them a very attractive candidate for the envisioned cuff. However, CMUTs usually feature lower Q factors compared to PZTs, hence the output pressure still has to be evaluated for neuromodulation. In addition, this work will also discuss important characteristics of the materials used for encapsulation, as these should ensure the required flexibility of the cuff without negatively affecting the acoustic performance of the transducers.@en

Over the past decades, neuromodulation has been proven to be an effective treatment for several neurological disorders. Moreover, it continues to be a rapidly evolving field with a wide-ranging potential for biomedical applications. However, efficient and patient-specific targeted neuromodulation remains one of the biggest challenges for implantable devices. Current studies explore the possibility of using multimodal neuromodulation techniques by combining electrical, thermal, optical, ultrasonic, and/or pharmacological methods to increase the specificity of therapies.1 Moreover, it is hypothesized that the safety profiles and spatiotemporal resolution could potentially increase by combining electrical and ultrasonic methods into a hybrid neuromodulation technique.2 Low-intensity focused ultrasound has the potential to alter the neural response in a wide range of neuronal targets, with an improved spatial resolution.3,4 However, the most effective, reliable, and safe acoustic parameters are currently unknown, especially for the peripheral nervous system, due to the little understanding of the mechanisms that govern this method.5 In this study, we propose an investigational platform that will allow us to explore a variety of ultrasound parameters for a multimodal neuromodulation approach. The platform integrates a custom- adapted system for stimulation and neural recording, commercially available components for the ultrasound stimulation system, and an experimental control unit with a PC interface. The proposed setup facilitates the evaluation of the tested parameters during experiments on explanted nerve models. Here we will describe potential implementations of such a system and discuss challenges that can be faced during experiments on explanted nerves. This work can be useful to increase our understanding of ultrasound neuromodulation on peripheral nerves and its benefits when integrated into a hybrid platform dedicated to multimodal neuromodulation.@en

A Medical Body Area Network (MBAN) is an ensemble of collaborating, potentially heterogeneous, medical devices located inside, on the surface of or around the human body with the objective of tackling one or multiple medical conditions of the MBAN host. These devices-which are a special category of Wireless Body Area Networks (WBANs)–collect, process and transfer medical data outside of the network, while in some cases they also administer medical treatment autonomously. Since communication is so pivotal to their operation, the newfangled IEEE 802.15.6 standard is aimed at the communication aspects of WBANs. It places a set of physical and communication constraints while it also includes association/disassociation protocols and security services that WBAN applications need to comply with. However, the security specifications put forward by the standard can be easily shown to be insufficient when considering realistic MBAN use cases and need further enhancements. The present work addresses these shortcomings by, first, providing a structured analysis of the IEEE 802.15.6 security features and, afterwards, proposing comprehensive and tangible recommendations on improving the standard’s security.@en

The first two objectives were to establish which stimulation parameters of kilohertz frequency alternating current (KHFAC) neuromodulation influence the effectiveness of pudendal nerve block and its safety. The third aim was to determine whether KHFAC neuromodulation of the pudendal nerve can relax the pelvic musculature, including the anal sphincter. Simulation experiments were conducted to establish which parameters can be adjusted to improve the effectiveness and safety of the nerve block. The outcome measures were block threshold (measure of effectiveness) and block threshold charge per phase (measure of safety). In vivo, the pudendal nerves in 11 male and 2 female anesthetized Sprague Dawley rats were stimulated in the range of 10 Hz to 40 kHz, and the effect on anal pressure was measured. The simulations showed that block threshold and block threshold charge per phase depend on waveform, interphase delay, electrode-to-axon distance, interpolar distance, and electrode array orientation. In vivo, the average anal pressure during unilateral KHFAC stimulation was significantly lower than the average peak anal pressure during low-frequency stimulation (p < 0.001). Stimulation with 20 kHz and 40 kHz (square wave, 10 V amplitude, 50% duty cycle, no interphase delay) induced the largest anal pressure decrease during both unilateral and bilateral stimulation. However, no statistically significant differences were detected between the different frequencies. This study showed that waveform, interphase delay and the alignment of the electrode along the nerve affect the effectiveness and safety of KHFAC stimulation. Additionally, we showed that KHFAC neuromodulation of the pudendal nerves with an electrode array effectively reduces anal pressure in rats.@en

In multi-electrode arrays (MEAs), for electrical recording and electrical stimulation, high voltage (HV) switches are employed to build an analog multiplexer to conduct either a HV stimulation signal from the pulse generator circuit to an electrode or a low-voltage noise-sensitive signal from the electrode to a recording stage. In this brief, a new circuit structure is proposed for HV switches that significantly improves their switching speed, reduces their power dissipation, and also employs a minimum number of bulky HV devices. In order to reduce the transition time of the proposed switch without consuming a large amount of power, during the transition time that the switch is turning on/off, a large current flows through the driver circuit of the switch to turn the switch on/off rapidly; however, after the transition times, this current is significantly reduced to save power. Based on the proposed HV switch, a multiplexer structure has been implemented in 25-V, 0.18- μm CMOS IC technology and the measurement results prove its efficacy. Supplied with 25 V and operating with 300 nA current consumption, this switch swings over 20 V with a relatively constant on-resistance of 100Ω and features a 80 ns transition time.

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This work proposes a guideline for designing more energy-efficient electrical stimulators by analyzing the frequency spectrum of the stimuli. It is shown that the natural low-pass characteristic of the neuron’s membrane limits the energy transfer efficiency from the stimulator to the cell. Thus, to improve the transfer efficiency, it is proposed to pre-filter the high-frequency components of the stimulus. The method is validated for a Hodgkin-Huxley (HH) axon cable model using NEURON v8.0 software. To this end, the required activation energy is simulated for rectangular pulses with durations between 10 µs and 5 ms, which are low-pass filtered with cut-off frequencies of 0.5-50 kHz. Simulations show a 51.5% reduction in the required activation energy for the shortest pulse width (i.e., 10 µs) after filtering at 5 kHz. It is also shown that the minimum required activation energy can be decreased by 11.04% when an appropriate pre-filter is applied. Finally, we draw a perspective for future use of this method to improve the selectivity of electrical stimulation.@en

Multimodal platforms combining electrical neural recording and stimulation, optogenetics, optical imaging, and magnetic resonance (MRI) imaging are emerging as a promising platform to enhance the depth of characterization in neuroscientific research. Electrically conductive, optically transparent, and MRI-compatible electrodes can optimally combine all modalities. Graphene as a suitable electrode candidate material can be grown via chemical vapor deposition (CVD) processes and sandwiched between transparent biocompatible polymers. However, due to the high graphene growth temperature (≥ 900 °C) and the presence of polymers, fabrication is commonly based on a manual transfer process of pre-grown graphene sheets, which causes reliability issues. In this paper, we present CVD-based multilayer graphene electrodes fabricated using a wafer-scale transfer-free process for use in optically transparent and MRI-compatible neural interfaces. Our fabricated electrodes feature very low impedances which are comparable to those of noble metal electrodes of the same size and geometry. They also exhibit the highest charge storage capacity (CSC) reported to date among all previously fabricated CVD graphene electrodes. Our graphene electrodes did not reveal any photo-induced artifact during 10-Hz light pulse illumination. Additionally, we show here, for the first time, that CVD graphene electrodes do not cause any image artifact in a 3T MRI scanner. These results demonstrate that multilayer graphene electrodes are excellent candidates for the next generation of neural interfaces and can substitute the standard conventional metal electrodes. Our fabricated graphene electrodes enable multimodal neural recording, electrical and optogenetic stimulation, while allowing for optical imaging, as well as, artifact-free MRI studies. [Figure not available: see fulltext.].

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In neuromodulation applications, conventional current mode stimulation is often preferred over its voltage mode equivalent due to its good control of the injected charge. However, it comes at the cost of less energy-efficient output stages. To increase energy efficiency, recent studies have explored non-rectangular stimuli. The current work highlights the importance of an adaptive supply for an output stage with programmable non-rectangular stimuli and accordingly proposes a system-level architecture for multi-channel stimulators. In the proposed architecture, a multi-output DC/DC Converter (DDC) allows each channel to choose among the available supply levels (i.e., DDC outputs) independently and based on its instant voltage/current requirement. A system-level analysis is carried out in Matlab to calculate the possible energy savings of this solution, compared to the conventional approach with a fixed supply. The energy savings have been simulated for a variety of supply levels and waveform amplitudes, suggesting energy savings of up to 83% when employing 6 DDC outputs and the lowest current amplitude explored (250A), and as high as 26% for a full-scale amplitude (4 mA).

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Deep brain stimulation is currently the only technique used in the clinical setting to modulate the neural activity of deep brain nuclei. Recently, low-intensity transcranial focused ultrasound (LIFU) has been shown to reversibly modulate brain activity through a transcranial pathway. Transcranial LIFU requires a low-frequency ultrasound of around 0.5 MHz due to skull attenuation, thus providing poor axial and lateral resolution. This paper proposes a new conceptual device that would use a stent to place a high-frequency ultrasound array within the brain vasculature to achieve high axial and lateral spatial resolution. The first part of this work identified the most commonly treated deep brain nuclei and examined the human brain vasculature for stent placement. Next, a finite element analysis was carried out using a piezoelectric array that follows the blood vessels curvature, and its ability to focus ultrasound waves in clinically relevant brain nuclei was evaluated. The analytical solution provided promising results for deep brain stimulation via a stent with ultrasound transducers for high spatial resolution neuromodulation.@en

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.@en