Wireless fast-scan cyclic voltammetry to monitor adenosine in patients with essential tremor during deep brain stimulation

Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning

With advances in our understanding regarding the neurochemical underpinnings of neurological and psychiatric diseases, there is an increased demand for advanced computational methods for neurochemical analysis. Despite having a variety of techniques for measuring tonic extracellular concentrations of neurotransmitters, including voltammetry, enzyme-based sensors, amperometry, and in vivo microdialysis, there is currently no means to resolve concentrations of structurally similar neurotransmitters from mixtures in the in vivo environment with high spatiotemporal resolution and limited tissue damage. Since a variety of research and clinical investigations involve brain regions containing electrochemically similar monoamines, such as dopamine and norepinephrine, developing a model to resolve the respective contributions of these neurotransmitters is of vital importance. Here we have developed a deep learning network, DiscrimNet, a convolutional autoencoder capable of accurately predicting individual tonic concentrations of dopamine, norepinephrine, and serotonin from both in vitro mixtures and the in vivo environment in anesthetized rats, measured using voltammetry. The architecture of DiscrimNet is described, and its ability to accurately predict in vitro and unseen in vivo concentrations is shown to vastly outperform a variety of shallow learning algorithms previously used for neurotransmitter discrimination. DiscrimNet is shown to generalize well to data captured from electrodes unseen during model training, eliminating the need to retrain the model for each new electrode. DiscrimNet is also shown to accurately predict the expected changes in dopamine and serotonin after cocaine and oxycodone administration in anesthetized rats in vivo. DiscrimNet therefore offers an exciting new method for real-time resolution of in vivo voltammetric signals into component neurotransmitters.

The Neurostimulationist will see you now: prescribing direct electrical stimulation therapies for the human brain in epilepsy and beyond

As the pace of research in implantable neurotechnology increases, it is important to take a step back and see if the promise lives up to our intentions. While direct electrical stimulation applied intracranially has been used for the treatment of various neurological disorders, such as Parkinson's, epilepsy, clinical depression, and Obsessive-compulsive disorder, the effectiveness can be highly variable. One perspective is that the inability to consistently treat these neurological disorders in a standardized way is due to multiple, interlaced factors, including stimulation parameters, location, and differences in underlying network connectivity, leading to a trial-and-error stimulation approach in the clinic. An alternate view, based on a growing knowledge from neural data, is that variability in this input (stimulation) and output (brain response) relationship may be more predictable and amenable to standardization, personalization, and, ultimately, therapeutic implementation. In this review, we assert that the future of human brain neurostimulation, via direct electrical stimulation, rests on deploying standardized, constrained models for easier clinical implementation and informed by intracranial data sets, such that diverse, individualized therapeutic parameters can efficiently produce similar, robust, positive outcomes for many patients closer to a prescriptive model. We address the pathway needed to arrive at this future by addressing three questions, namely: (1) why aren't we already at this prescriptive future?; (2) how do we get there?; (3) how far are we from this Neurostimulationist prescriptive future? We first posit that there are limited and predictable ways, constrained by underlying networks, for direct electrical stimulation to induce changes in the brain based on past literature. We then address how identifying underlying individual structural and functional brain connectivity which shape these standard responses enable targeted and personalized neuromodulation, bolstered through large-scale efforts, including machine learning techniques, to map and reverse engineer these input-output relationships to produce a good outcome and better identify underlying mechanisms. This understanding will not only be a major advance in enabling intelligent and informed design of neuromodulatory therapeutic tools for a wide variety of neurological diseases, but a shift in how we can predictably, and therapeutically, prescribe stimulation treatments the human brain.

Toward Precise Modeling of Dopamine Release Kinetics: Comparison and Validation of Kinetic Models Using Voltammetry

Dopamine (DA) is a neurotransmitter present within the animal brain that is responsible for a wide range of physiologic functions, including motivation, reward, and movement control. Changes or dysfunction in the dynamics of DA release are thought to play a pivotal role in regulating various physiological and behavioral processes, as well as leading to neuropsychiatric diseases. Therefore, it is of fundamental interest to neuroscientists to understand and accurately model the kinetics that govern dopaminergic neurotransmission. In the past several decades, many mathematical models have been proposed to attempt to capture the biologic parameters that govern dopaminergic kinetics, with each model seeking to improve upon a previous model. In this review, each of these models are derived, and the ability of each model to properly fit two fast-scan cyclic voltammetry (FSCV) data sets will be demonstrated and discussed. The dopamine oxidation current in both FSCV data sets exhibits hang-up and overshoot behaviors, which have traditionally been difficult for mathematical models to capture. We show that more recent models are better able to model DA release that exhibits these behaviors but that no single model is clearly the best. Rather, models should be selected based on their mathematical properties to best fit the FSCV data one is trying to model. Developing such differential equation models to describe the kinetics of DA release from the synapse confers significant applications both for advancing scientific understanding of DA neurotransmission and for advancing clinical ability to treat neuropsychiatric diseases.

Insertional effect following electrode implantation: an underreported but important phenomenon

Deep brain stimulation has revolutionized the treatment of movement disorders and is gaining momentum in the treatment of several other neuropsychiatric disorders. In almost all applications of this therapy, the insertion of electrodes into the target has been shown to induce some degree of clinical improvement prior to stimulation onset. Disregarding this phenomenon, commonly referred to as 'insertional effect', can lead to biased results in clinical trials, as patients receiving sham stimulation may still experience some degree of symptom amelioration. Similar to the clinical scenario, an improvement in behavioural performance following electrode implantation has also been reported in preclinical models. From a neurohistopathologic perspective, the insertion of electrodes into the brain causes an initial trauma and inflammatory response, the activation of astrocytes, a focal release of gliotransmitters, the hyperexcitability of neurons in the vicinity of the implants, as well as neuroplastic and circuitry changes at a distance from the target. Taken together, it would appear that electrode insertion is not an inert process, but rather triggers a cascade of biological processes, and, as such, should be considered alongside the active delivery of stimulation as an active part of the deep brain stimulation therapy.

Platinum Nanoparticle Size and Density Impacts Purine Electrochemistry with Fast-Scan Cyclic Voltammetry

We demonstrate the density and shape of platinum nanoparticles (PtNP) on carbon-fiber microelectrodes with fast-scan cyclic voltammetry (FSCV) directly impacts detection of adenosine. Previously, we showed that metal nanoparticle-modified carbon significantly improves adenine-based purine detection; however, how the size and shape of the particles impact electrochemical detection was not investigated. Electrochemical investigations of how the surface topology and morphology impacts detection is necessary for designing ultrasensitive electrodes and for expanding fundamental knowledge of electrode-analyte interactions. To change the density and shape of the PtNP's on the surface, we varied the concentration of K₂PtCl₆ and electrodeposition time. We show that increasing the concentration of K₂PtCl₆ increases the density of PtNP's while increasing the electrodeposition time impacts both the density and size. These changes manipulate the adsorption behavior which impacts sensitivity. Based on these results, an optimal electrodeposition procedure was determined to be 1.0 mg/mL of K₂PtCl₆ deposited for 45 s and this results in an average increase in adenosine detection by 3.5 ±0.3-fold. Interestingly, increasing the size and density of PtNPs negatively impacts dopamine detection. Overall, this work provides fundamental insights into the differences between adenosine and dopamine interaction at electrode surfaces.

Therapeutic Devices for Motor Symptoms in Parkinson’s Disease: Current Progress and a Systematic Review of Recent Randomized Controlled Trials

Background

Pharmacotherapy is the first-line treatment option for Parkinson’s disease, and levodopa is considered the most effective drug for managing motor symptoms. However, side effects such as motor fluctuation and dyskinesia have been associated with levodopa treatment. For these conditions, alternative therapies, including invasive and non-invasive medical devices, may be helpful. This review sheds light on current progress in the development of devices to alleviate motor symptoms in Parkinson’s disease.

Methods

We first conducted a narrative literature review to obtain an overview of current invasive and non-invasive medical devices and thereafter performed a systematic review of recent randomized controlled trials (RCTs) of these devices.

Results

Our review revealed different characteristics of each device and their effectiveness for motor symptoms. Although invasive medical devices are usually highly effective, surgical procedures can be burdensome for patients and have serious side effects. In contrast, non-pharmacological/non-surgical devices have fewer complications. RCTs of non-invasive devices, especially non-invasive brain stimulation and mechanical peripheral stimulation devices, have proven effectiveness on motor symptoms. Nearly no non-invasive devices have yet received Food and Drug Administration certification or a CE mark.

Conclusion

Invasive and non-invasive medical devices have unique characteristics, and several RCTs have been conducted for each device. Invasive devices are more effective, while non-invasive devices are less effective and have lower hurdles and risks. It is important to understand the characteristics of each device and capitalize on these.

Local accumbens in vivo imaging during deep brain stimulation reveals a strategy-dependent amelioration of hedonic feeding

Impulsive overeating is a common, disabling feature of eating disorders. Calcium imaging using fiber photometry has emerged as an in vivo methodology to measure neuronal population activity immune to electrical stimulation artifact from deep brain stimulation (DBS). Thus, when used simultaneously, calcium imaging can elucidate poorly understood DBS mechanisms. We show that nucleus accumbens D1 medial spiny calcium signaling increases in preparation of hedonic feeding of high-fat food. Further, responsive, over continuous, DBS strategies effectively disrupt this activity leading to decreased consumption. Implementation of this methodology to better understand mechanisms of these and other forms of neuromodulation for various indications may help advance the field to identify novel therapeutic targets with applications extending beyond obesity.

Impulsive overeating is a common, disabling feature of eating disorders. Both continuous deep brain stimulation (DBS) and responsive DBS, which limits current delivery to pathological brain states, have emerged as potential therapies. We used in vivo fiber photometry in wild-type, Drd1-cre, and A2a-cre mice to 1) assay subtype-specific medium spiny neuron (MSN) activity of the nucleus accumbens (NAc) during hedonic feeding of high-fat food, and 2) examine DBS strategy-specific effects on NAc activity. D1, but not D2, NAc GCaMP activity increased immediately prior to high-fat food approach. Responsive DBS triggered a GCaMP surge throughout the stimulation period and durably reduced high-fat intake. However, with continuous DBS, this surge decayed, and high-fat intake reemerged. Our results argue for a stimulation strategy-dependent modulation of D1 MSNs with a more sustained decrease in consumption with responsive DBS. This study illustrates the important role in vivo imaging can play in understanding effects of such novel therapies.

Feasibility of Applying Fourier Transform Electrochemical Impedance Spectroscopy in Fast Cyclic Square Wave Voltammetry for the In Vivo Measurement of Neurotransmitters

We previously reported on the use of fast cyclic square wave voltammetry (FCSWV) as a new voltammetric technique. Fourier transform electrochemical impedance spectroscopy (FTEIS) has recently been utilized to provide information that enables a detailed analytical description of an electrified interface. In this study, we report on attempts to combine FTEIS with FCSWV (FTEIS-FCSWV) and demonstrate the feasibility of FTEIS-FCSWV in the in vivo detection of neurotransmitters, thus giving a new type of electrochemical impedance information such as biofouling on the electrode surface. From FTEIS-FCSWV, three new equivalent circuit element voltammograms, consisting of charge-transfer resistance (R_ct), solution-resistance (R_s), and double-layer capacitance (C_dl) voltammograms were constructed and investigated in the phasic changes in dopamine (DA) concentrations. As a result, all R_ct, R_s, and C_dl voltammograms showed different DA redox patterns and linear trends for the DA concentration (R² > 0.99). Furthermore, the R_ct voltammogram in FTEIS-FCSWV showed lower limit of detection (21.6 ± 15.8 nM) than FSCV (35.8 ± 17.4 nM). FTEIS-FCSWV also showed significantly lower prediction errors than FSCV in selectivity evaluations of unknown mixtures of catecholamines. Finally, C_dl from FTEIS-FCSWV showed a significant relationship with fouling effect on the electrode surface by showing decreased DA sensitivity in both flow injection analysis experiment (r = 0.986) and in vivo experiments. Overall, this study demonstrates the feasibility of FTEIS-FCSWV, which could offer a new type of neurochemical spectroscopic information concerning electrochemical monitoring of neurotransmitters in the brain, and the ability to estimate the degree of sensitivity loss caused by biofouling on the electrode surface.

The Pathophysiology and Treatment of Essential Tremor: The Role of Adenosine and Dopamine Receptors in Animal Models

Essential tremor (ET) is one of the most common neurological disorders that often affects people in the prime of their lives, leading to a significant reduction in their quality of life, gradually making them unable to independently perform the simplest activities. Here we show that current ET pharmacotherapy often does not sufficiently alleviate disease symptoms and is completely ineffective in more than 30% of patients. At present, deep brain stimulation of the motor thalamus is the most effective ET treatment. However, like any brain surgery, it can cause many undesirable side effects; thus, it is only performed in patients with an advanced disease who are not responsive to drugs. Therefore, it seems extremely important to look for new strategies for treating ET. The purpose of this review is to summarize the current knowledge on the pathomechanism of ET based on studies in animal models of the disease, as well as to present and discuss the results of research available to date on various substances affecting dopamine (mainly D3) or adenosine A1 receptors, which, due to their ability to modulate harmaline-induced tremor, may provide the basis for the development of new potential therapies for ET in the future.

Simultaneous fMRI and fast-scan cyclic voltammetry bridges evoked oxygen and neurotransmitter dynamics across spatiotemporal scales

The vascular contributions of neurotransmitters to the hemodynamic response are gaining more attention in neuroimaging studies, as many neurotransmitters are vasomodulatory. To date, well-established electrochemical techniques that detect neurotransmission in high magnetic field environments are limited. Here, we propose an experimental setting enabling simultaneous fast-scan cyclic voltammetry (FSCV) and blood oxygenation level-dependent functional magnetic imaging (BOLD fMRI) to measure both local tissue oxygen and dopamine responses, and global BOLD changes, respectively. By using MR-compatible materials and the proposed data acquisition schemes, FSCV detected physiological analyte concentrations with high temporal resolution and spatial specificity inside of a 9.4 T MRI bore. We found that tissue oxygen and BOLD correlate strongly, and brain regions that encode dopamine amplitude differences can be identified via modeling simultaneously acquired dopamine FSCV and BOLD fMRI time-courses. This technique provides complementary neurochemical and hemodynamic information and expands the scope of studying the influence of local neurotransmitter release over the entire brain.

Carbon-based neural electrodes: promises and challenges

Neural electrodes are primary functional elements of neuroelectronic devices designed to record neural activity based on electrochemical signals. These electrodes may also be utilized for electrically stimulating the neural cells, such that their response can be simultaneously recorded. In addition to being medically safe, the electrode material should be electrically conductive and electrochemically stable under harsh biological environments. Mechanical flexibility and conformability, resistance to crack formation and compatibility with common microfabrication techniques are equally desirable properties. Traditionally, (noble) metals have been the preferred for neural electrode applications due to their proven biosafety and a relatively high electrical conductivity. Carbon is a recent addition to this list, which is far superior in terms of its electrochemical stability and corrosion resistance. Carbon has also enabled 3D electrode fabrication as opposed to the thin-film based 2D structures. One of carbon's peculiar aspects is its availability in a wide range of allotropes with specialized properties that render it highly versatile. These variations, however, also make it difficult to understand carbon itself as a unique material, and thus, each allotrope is often regarded independently. Some carbon types have already shown promising results in bioelectronic medicine, while many others remain potential candidates. In this topical review, we first provide a broad overview of the neuroelectronic devices and the basic requirements of an electrode material. We subsequently discuss the carbon family of materials and their properties that are useful in neural applications. Examples of devices fabricated using bulk and nano carbon materials are reviewed and critically compared. We then summarize the challenges, future prospects and next-generation carbon technology that can be helpful in the field of neural sciences. The article aims at providing a common platform to neuroscientists, electrochemists, biologists, microsystems engineers and carbon scientists to enable active and comprehensive efforts directed towards carbon-based neuroelectronic device fabrication.

Clinical applications of neurochemical and electrophysiological measurements for closed-loop neurostimulation

The development of closed-loop deep brain stimulation (DBS) systems represents a significant opportunity for innovation in the clinical application of neurostimulation therapies. Despite the highly dynamic nature of neurological diseases, open-loop DBS applications are incapable of modifying parameters in real time to react to fluctuations in disease states. Thus, current practice for the designation of stimulation parameters, such as duration, amplitude, and pulse frequency, is an algorithmic process. Ideal stimulation parameters are highly individualized and must reflect both the specific disease presentation and the unique pathophysiology presented by the individual. Stimulation parameters currently require a lengthy trial-and-error process to achieve the maximal therapeutic effect and can only be modified during clinical visits. The major impediment to the development of automated, adaptive closed-loop systems involves the selection of highly specific disease-related biomarkers to provide feedback for the stimulation platform. This review explores the disease relevance of neurochemical and electrophysiological biomarkers for the development of closed-loop neurostimulation technologies. Electrophysiological biomarkers, such as local field potentials, have been used to monitor disease states. Real-time measurement of neurochemical substances may be similarly useful for disease characterization. Thus, the introduction of measurable neurochemical analytes has significantly expanded biomarker options for feedback-sensitive neuromodulation systems. The potential use of biomarker monitoring to advance neurostimulation approaches for treatment of Parkinson's disease, essential tremor, epilepsy, Tourette syndrome, obsessive-compulsive disorder, chronic pain, and depression is examined. Further, challenges and advances in the development of closed-loop neurostimulation technology are reviewed, as well as opportunities for next-generation closed-loop platforms.

Review-Recent Advances in FSCV Detection of Neurochemicals via Waveform and Carbon Microelectrode Modification

Fast scan cyclic voltammetry (FSCV) is an analytical technique that was first developed over 30 years ago. Since then, it has been extensively used to detect dopamine using carbon fiber microelectrodes (CFMEs). More recently, electrode modifications and waveform refinement have enabled the detection of a wider variety of neurochemicals including nucleosides such as adenosine and guanosine, neurotransmitter metabolites of dopamine, and neuropeptides such as enkephalin. These alterations have facilitated the selectivity of certain biomolecules over others to enhance the measurement of the analyte of interest while excluding interferants. In this review, we detail these modifications and how specializing CFME sensors allows neuro-analytical researchers to develop tools to understand the neurochemistry of the brain in disease states and provide groundwork for translational work in clinical settings.

Automatic and Reliable Quantification of Tonic Dopamine Concentrations In Vivo Using a Novel Probabilistic Inference Method

Dysregulation of the neurotransmitter dopamine (DA) is implicated in several neuropsychiatric conditions. Multiple-cyclic square-wave voltammetry (MCSWV) is a state-of-the-art technique for measuring tonic DA levels with high sensitivity (<5 nM), selectivity, and spatiotemporal resolution. Currently, however, analysis of MCSWV data requires manual, qualitative adjustments of analysis parameters, which can inadvertently introduce bias. Here, we demonstrate the development of a computational technique using a statistical model for standardized, unbiased analysis of experimental MCSWV data for unbiased quantification of tonic DA. The oxidation current in the MCSWV signal was predicted to follow a lognormal distribution. The DA-related oxidation signal was inferred to be present in the top 5% of this analytical distribution and was used to predict a tonic DA level. The performance of this technique was compared against the previously used peak-based method on paired in vivo and post-calibration in vitro datasets. Analytical inference of DA signals derived from the predicted statistical model enabled high-fidelity conversion of the in vivo current signal to a concentration value via in vitro post-calibration. As a result, this technique demonstrated reliable and improved estimation of tonic DA levels in vivo compared to the conventional manual post-processing technique using the peak current signals. These results show that probabilistic inference-based voltammetry signal processing techniques can standardize the determination of tonic DA concentrations, enabling progress toward the development of MCSWV as a robust research and clinical tool.

Recent Advances in In Vivo Neurochemical Monitoring

The brain is a complex network that accounts for only 5% of human mass but consumes 20% of our energy. Uncovering the mysteries of the brain's functions in motion, memory, learning, behavior, and mental health remains a hot but challenging topic. Neurochemicals in the brain, such as neurotransmitters, neuromodulators, gliotransmitters, hormones, and metabolism substrates and products, play vital roles in mediating and modulating normal brain function, and their abnormal release or imbalanced concentrations can cause various diseases, such as epilepsy, Alzheimer's disease, and Parkinson's disease. A wide range of techniques have been used to probe the concentrations of neurochemicals under normal, stimulated, diseased, and drug-induced conditions in order to understand the neurochemistry of drug mechanisms and develop diagnostic tools or therapies. Recent advancements in detection methods, device fabrication, and new materials have resulted in the development of neurochemical sensors with improved performance. However, direct in vivo measurements require a robust sensor that is highly sensitive and selective with minimal fouling and reduced inflammatory foreign body responses. Here, we review recent advances in neurochemical sensor development for in vivo studies, with a focus on electrochemical and optical probes. Other alternative methods are also compared. We discuss in detail the in vivo challenges for these methods and provide an outlook for future directions.

Evaluation of electrochemical methods for tonic dopamine detection in vivo

Dysfunction in dopaminergic neuronal systems underlie a number of neurologic and psychiatric disorders such as Parkinson's disease, drug addiction, and schizophrenia. Dopamine systems communicate via two mechanisms, a fast "phasic" release (sub-second to second) that is related to salient stimuli and a slower "tonic" release (minutes to hours) that regulates receptor tone. Alterations in tonic levels are thought to be more critically important in enabling normal motor, cognitive, and motivational functions, and dysregulation in tonic dopamine levels are associated with neuropsychiatric disorders. Therefore, development of neurochemical recording techniques that enable rapid, selective, and quantitative measurements of changes in tonic extracellular levels are essential in determining the role of dopamine in both normal and disease states. Here, we review state-of-the-art advanced analytical techniques for in vivo detection of tonic levels, with special focus on electrochemical techniques for detection in humans.

Laser Driven Miniature Diamond Implant for Wireless Retinal Prostheses

The design and benchtop operation of a wireless miniature epiretinal stimulator implant is reported. The implant is optically powered and controlled using safe illumination at near-infrared wavelengths. An application-specific integrated circuit (ASIC) hosting a digital control unit is used to control the implant's electrodes. The ASIC is powered using an advanced photovoltaic (PV) cell and programmed using a single photodiode. Diamond packaging technology is utilized to achieve high-density integration of the implant optoelectronic circuitry, as well as individual connections between a stimulator chip and 256 electrodes, within a 4.6 mm × 3.7 mm × 0.9 mm implant package. An ultrahigh efficiency PV cell with a monochromatic power conversion efficiency of 55% is used to power the implant. On-board photodetection circuity with a bandwidth of 3.7 MHz is used for forward data telemetry of stimulation parameters. In comparison to implants which utilize inductively coupled coils, laser power delivery enables a high degree of miniaturization and lower surgical complexity. The device presented combines the benefits of implant miniaturization and a flexible stimulation strategy provided by a dedicated stimulator chip. This development provides a route to fully wireless miniaturized minimally invasive implants with sophisticated functionalities.

Deep brain stimulation: a review of the open neural engineering challenges

OBJECTIVE

Deep brain stimulation (DBS) is an established and valid therapy for a variety of pathological conditions ranging from motor to cognitive disorders. Still, much of the DBS-related mechanism of action is far from being understood, and there are several side effects of DBS whose origin is unclear. In the last years DBS limitations have been tackled by a variety of approaches, including adaptive deep brain stimulation (aDBS), a technique that relies on using chronically implanted electrodes on 'sensing mode' to detect the neural markers of specific motor symptoms and to deliver on-demand or modulate the stimulation parameters accordingly. Here we will review the state of the art of the several approaches to improve DBS and summarize the main challenges toward the development of an effective aDBS therapy.

APPROACH

We discuss models of basal ganglia disorders pathogenesis, hardware and software improvements for conventional DBS, and candidate neural and non-neural features and related control strategies for aDBS.

MAIN RESULTS

We identify then the main operative challenges toward optimal DBS such as (i) accurate target localization, (ii) increased spatial resolution of stimulation, (iii) development of in silico tests for DBS, (iv) identification of specific motor symptoms biomarkers, in particular (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) clarify how stimulation affects the cortico-basal-ganglia-thalamic network to (vii) design optimal stimulation patterns.

SIGNIFICANCE

This roadmap will lead neural engineers novel to the field toward the most relevant open issues of DBS, while the in-depth readers might find a careful comparison of advantages and drawbacks of the most recent attempts to improve DBS-related neuromodulatory strategies.

Moving Fast-Scan Cyclic Voltammetry toward FDA Compliance with Capacitive Decoupling Patient Protection

Carbon-fiber microelectrodes allow for high spatial and temporal measurements of electroactive neurotransmitter measurements in vivo using fast-scan cyclic voltammetry (FSCV). However, common instrumentation for such measurements systems lack patient safety precautions. To add safety precautions as well as to overcome chemical and electrical noise, a two-electrode FSCV headstage was modified to introduce an active bandpass filter on the electrode side of the measurement amplifier. This modification reduced the measured noise and ac-coupled the voltammetric measurement and moved it from a classical direct current response measurement. ac-coupling not only reduces the measured noise, but also moves FSCV toward compliance with IEC-60601-1, enabling future human trials. Here, we develop a novel ac-coupled voltammetric measurement method of electroactive neurotransmitters. Our method allows for the modeling of a system to then calculate a waveform to compensate for added impedance and capacitance for the system. We describe how first by measuring the frequency response of the system and modeling the analogue response as a digital filter we can then calculate a predicted waveform. The predicted waveform, when applied to the bandpass filter, is modulated to create a desired voltage sweep at the electrode interface. Further, we describe how this modified FSCV waveform is stable, allowing for the measurement of electroactive neurotransmitters. We later describe a 32.7% sensitivity enhancement for dopamine with this new measurement as well as maintaining a calibration curve for dopamine, 3,4-dihydroxyphenylacetic acid, ascorbic acid, and serotonin in vitro. We then validate dopamine in vivo with stimulated release. Our developed measurement method overcame the added capacitance that would traditionally make a voltammetric measurement impossible, and it has wider applications in electrode sensor development, allowing for measurement with capacitive systems, which previously would not have been possible.

An Update on the Neurochemistry of Essential Tremor

Background:

The pathophysiology and neurochemical mechanisms of essential tremor (ET) are not fully understood, because only a few post-mortem studies have been reported, and there is a lack of good experimental model for this disease.

Objective:

The main aim of this review is to update data regarding the neurochemical features of ET. Alterations of certain catecholamine systems, the dopaminergic, serotonergic, GABAergic, noradrenergic, and adrenergic systems have been described, and are the object of this revision.

Methods:

For this purpose, we performed a literature review on alterations of the neurotransmitter or neuromodulator systems (catecholamines, gammaaminobutyric acid or GABA, excitatory amino acids, adenosine, T-type calcium channels) in ET patients (both post-mortem or in vivo) or in experimental models resembling ET.

Results and Conclusion:

The most consistent data regarding neurochemistry of ET are related with the GABAergic and glutamatergic systems, with a lesser contribution of adenosine and dopaminergic and adrenergic systems, while there is not enough evidence of a definite role of other neurotransmitter systems in ET. The improvement of harmaline-induced tremor in rodent models achieved with T-type calcium channel antagonists, cannabinoid 1 receptor, sphingosine-1-phosphate receptor agonists, and gap-junction blockers, suggests a potential role of these structures in the pathogenesis of ET.

Advances in neurochemical measurements: A review of biomarkers and devices for the development of closed-loop deep brain stimulation systems

Neurochemical recording techniques have expanded our understanding of the pathophysiology of neurological disorders, as well as the mechanisms of action of treatment modalities like deep brain stimulation (DBS). DBS is used to treat diseases such as Parkinson's disease, Tourette syndrome, and obsessive-compulsive disorder, among others. Although DBS is effective at alleviating symptoms related to these diseases and improving the quality of life of these patients, the mechanism of action of DBS is currently not fully understood. A leading hypothesis is that DBS modulates the electrical field potential by modifying neuronal firing frequencies to non-pathological rates thus providing therapeutic relief. To address this gap in knowledge, recent advances in electrochemical sensing techniques have given insight into the importance of neurotransmitters, such as dopamine, serotonin, glutamate, and adenosine, in disease pathophysiology. These studies have also highlighted their potential use in tandem with electrophysiology to serve as biomarkers in disease diagnosis and progression monitoring, as well as characterize response to treatment. Here, we provide an overview of disease-relevant neurotransmitters and their roles and implications as biomarkers, as well as innovations to the biosensors used to record these biomarkers. Furthermore, we discuss currently available neurochemical and electrophysiological recording devices, and discuss their viability to be implemented into the development of a closed-loop DBS system.

Fornix Stimulation Induces Metabolic Activity and Dopaminergic Response in the Nucleus Accumbens

The Papez circuit, including the fornix white matter bundle, is a well-known neural network that is involved in multiple limbic functions such as memory and emotional expression. We previously reported a large-animal study of deep brain stimulation (DBS) in the fornix that found stimulation-induced hemodynamic responses in both the medial limbic and corticolimbic circuits on functional resonance imaging (fMRI) and evoked dopamine responses in the nucleus accumbens (NAc), as measured by fast-scan cyclic voltammetry (FSCV). The effects of DBS on the fornix are challenging to analyze, given its structural complexity and connection to multiple neuronal networks. In this study, we extend our earlier work to a rodent model wherein we characterize regional brain activity changes resulting from fornix stimulation using fludeoxyglucose (¹⁸F-FDG) micro positron emission tomography (PET) and monitor neurochemical changes using FSCV with pharmacological confirmation. Both global functional changes and local changes were measured in a rodent model of fornix DBS. Functional brain activity was measured by micro-PET, and the neurochemical changes in local areas were monitored by FSCV. Micro-PET images revealed increased glucose metabolism within the medial limbic and corticolimbic circuits. Neurotransmitter efflux induced by fornix DBS was monitored at NAc by FSCV and identified by specific neurotransmitter reuptake inhibitors. We found a significant increase in the metabolic activity in several key regions of the medial limbic circuits and dopamine efflux in the NAc following fornix stimulation. These results suggest that electrical stimulation of the fornix modulates the activity of brain memory circuits, including the hippocampus and NAc within the dopaminergic pathway.

Approaches to closed-loop deep brain stimulation for movement disorders

OBJECTIVE Deep brain stimulation (DBS) is a safe and effective therapy for movement disorders, such as Parkinson's disease (PD), essential tremor (ET), and dystonia. There is considerable interest in developing "closed-loop" DBS devices capable of modulating stimulation in response to sensor feedback. In this paper, the authors review related literature and present selected approaches to signal sources and approaches to feedback being considered for deployment in closed-loop systems. METHODS A literature search using the keywords "closed-loop DBS" and "adaptive DBS" was performed in the PubMed database. The search was conducted for all articles published up until March 2018. An in-depth review was not performed for publications not written in the English language, nonhuman studies, or topics other than Parkinson's disease or essential tremor, specifically epilepsy and psychiatric conditions. RESULTS The search returned 256 articles. A total of 71 articles were primary studies in humans, of which 50 focused on treatment of movement disorders. These articles were reviewed with the aim of providing an overview of the features of closed-loop systems, with particular attention paid to signal sources and biomarkers, general approaches to feedback control, and clinical data when available. CONCLUSIONS Closed-loop DBS seeks to employ biomarkers, derived from sensors such as electromyography, electrocorticography, and local field potentials, to provide real-time, patient-responsive therapy for movement disorders. Most studies appear to focus on the treatment of Parkinson's disease. Several approaches hold promise, but additional studies are required to determine which approaches are feasible, efficacious, and efficient.

Analysis of Carbon-Based Microelectrodes for Neurochemical Sensing

The comprehensive microscopic, spectroscopic, and in vitro voltammetric analysis presented in this work, which builds on the well-studied properties of carbon-based materials, facilitates potential ways for improvement of carbon fiber microelectrodes (CFMs) for neuroscience applications. Investigations by both, scanning electron microscopy (SEM) and confocal Raman spectroscopy, confirm a higher degree of structural ordering for the fibers exposed to carbonization temperatures. An evident correlation is also identified between the extent of structural defects observed from SEM and Raman results with the CFM electrochemical performance for dopamine detection. To improve CFM physico-chemical surface stability and increase its mechanical resistance to the induced compressive stress during anticipated in vivo tissue penetration, successful coating of the carbon fiber with boron-doped diamond (BDD) is also performed and microspectroscopically analyzed here. The absence of spectral shifts of the diamond Raman vibrational signature verifies that the growth of an unstrained BDD thin film was achieved. Although more work needs to be done to identify optimal parameter values for improved BDD deposition, this study serves as a demonstration of foundational technology for the development of more sensitive electrochemical sensors, that may have been impractical previously for clinical applications, due to limitations in either safety or performance.

Closed-Loop Implantable Therapeutic Neuromodulation Systems Based on Neurochemical Monitoring

Closed-loop or intelligent neuromodulation allows adjustable, personalized neuromodulation which usually incorporates the recording of a biomarker, followed by implementation of an algorithm which decides the timing (when?) and strength (how much?) of stimulation. Closed-loop neuromodulation has been shown to have greater benefits compared to open-loop neuromodulation, particularly for therapeutic applications such as pharmacoresistant epilepsy, movement disorders and potentially for psychological disorders such as depression or drug addiction. However, an important aspect of the technique is selection of an appropriate, preferably neural biomarker. Neurochemical sensing can provide high resolution biomarker monitoring for various neurological disorders as well as offer deeper insight into neurological mechanisms. The chemicals of interest being measured, could be ions such as potassium (K⁺), sodium (Na⁺), calcium (Ca²⁺), chloride (Cl⁻), hydrogen (H⁺) or neurotransmitters such as dopamine, serotonin and glutamate. This review focusses on the different building blocks necessary for a neurochemical, closed-loop neuromodulation system including biomarkers, sensors and data processing algorithms. Furthermore, it also highlights the merits and drawbacks of using this biomarker modality.

Fast Cyclic Square-Wave Voltammetry To Enhance Neurotransmitter Selectivity and Sensitivity

Although fast-scan cyclic voltammetry (FSCV) has been widely used for in vivo neurochemical detection, the sensitivity and selectivity of the technique can be further improved. In this study, we develop fast cyclic square-wave voltammetry (FCSWV) as a novel voltammetric technique that combines large-amplitude cyclic square-wave voltammetry (CSWV) with background subtraction. A large-amplitude, square-shaped potential was applied to induce cycling through multiple redox reactions within a square pulse to increase sensitivity and selectivity when combined with a two-dimensional voltammogram. As a result, FCSWV was significantly more sensitive than FSCV ( n = 5 electrodes, two-way ANOVA, p = 0.0002). In addition, FCSWV could differentiate dopamine from other catecholamines (e.g., epinephrine and norepinephrine) and serotonin better than conventional FSCV. With the confirmation that FCSWV did not influence local neuronal activity, despite the large amplitude of the square waveform, it could monitor electrically induced phasic changes in dopamine release in rat striatum before and after injecting nomifensine, a dopamine reuptake inhibitor.

Integrity Assessment of a Hybrid DBS Probe that Enables Neurotransmitter Detection Simultaneously to Electrical Stimulation and Recording

Deep brain stimulation (DBS) is a successful medical therapy for many treatment resistant neuropsychiatric disorders such as movement disorders; e.g., Parkinson's disease, Tremor, and dystonia. Moreover, DBS is becoming more and more appealing for a rapidly growing number of patients with other neuropsychiatric diseases such as depression and obsessive compulsive disorder. In spite of the promising outcomes, the current clinical hardware used in DBS does not match the technological standards of other medical applications and as a result could possibly lead to side effects such as high energy consumption and others. By implementing more advanced DBS devices, in fact, many of these limitations could be overcome. For example, a higher channels count and smaller electrode sites could allow more focal and tailored stimulation. In addition, new materials, like carbon for example, could be incorporated into the probes to enable adaptive stimulation protocols by biosensing neurotransmitters in the brain. Updating the current clinical DBS technology adequately requires combining the most recent technological advances in the field of neural engineering. Here, a novel hybrid multimodal DBS probe with glassy carbon microelectrodes on a polyimide thin-film device assembled on a silicon rubber tubing is introduced. The glassy carbon interface enables neurotransmitter detection using fast scan cyclic voltammetry and electrophysiological recordings while simultaneously performing electrical stimulation. Additionally, the presented DBS technology shows no imaging artefacts in magnetic resonance imaging. Thus, we present a promising new tool that might lead to a better fundamental understanding of the underlying mechanism of DBS while simultaneously paving our way towards better treatments.

Comparative Computational and Experimental Detection of Adenosine Using Ultrasensitive Surface-Enhanced Raman Spectroscopy

To better understand detection and monitoring of the important neurotransmitter adenosine at physiological levels, this study combines quantum chemical density functional modeling and ultrasensitive surface-enhanced Raman spectroscopic (SERS) measurements. Combined simulation results and experimental data for an analyte concentration of about 10-11 molar indicate the presence of all known molecular forms resulting from adenosine's complex redox-reaction. Detailed analysis presented here, besides assessing potential Raman signatures of these adenosinic forms, also sheds light on the analytic redox process and voltammetric detection. Examples of adenosine Raman fingerprints for different molecular orientations with respect to the SERS substrate are the vibrational line around 920 ± 10 cm-1 for analyte physisorption through the carbinol moiety and around 1600 ± 20 cm-1 for its fully oxidized form. However, both hydroxyl/oxygen sites and NH₂/nitrogen sites contribute to molecule's interaction with the SERS environment. Our results also reveal that contributions of partially oxidized adenosine forms and of the standard form are more likely to be detected with the first recorded voltammetric oxidation peak. The fully oxidized adenosine form contributes mostly to the second peak. Thus, this comparative theoretical⁻experimental investigation of adenosine's vibrational signatures provides significant insights for advancing its detection, and for future development of opto-voltammetric biosensors.

Multi-waveform fast-scan cyclic voltammetry mapping of adsorption/desorption kinetics of biogenic amines and their metabolites

Fast-scan cyclic voltammetry (FSCV) is an effective method for investigating electro-active neurochemical species. In recent years, FSCV has been used to measure electro-active neurotransmitters in a variety of neuroscience studies. We previously reported on the use of paired-pulse voltammetry (PPV) that enables FSCV to differentiate various analytes and minimize confounding factors by taking advantage of the adsorption characteristics of the analyte on carbon fiber microelectrodes. In spite of a number of studies regarding adsorption/desorption characteristics of neurotransmitters, the difference in adsorption/desorption properties among neurotransmitters has yet to be fully explored. To calculate adsorption/desorption constants for neurotransmitters, we propose the use of multi-waveform FSCV (M-FSCV), which consists of decade triangular waveforms in a single scan. Within the multiple waveforms, the voltammetric response of dopamine decayed exponentially because of the decreased adsorption time period. The decay pattern was mathematically described using adsorption/desorption characteristics and two additional initial points: an exponential decay constant (K) and an initial quantity (A), which were extracted from the decay equation. Using this method, we were able to quantify the decay constant (K-map) and an initial quantity (A-map) color plot in addition to a conventional pseudo color plot. M-FSCV was evaluated with two biogenic amine groups (catecholamines and indolamines) to characterize their inherent adsorption/desorption constants. As a result, the A-map showed a high correlation with concentration and the K-map for each group to be significantly differentiated. These results demonstrate that M-FSCV has the potential to be a useful technique for acquiring additional adsorption/desorption information regarding neurotransmitters.

Early changes in transient adenosine during cerebral ischemia and reperfusion injury

Adenosine is an important neuromodulator in the central nervous system, and tissue adenosine levels increase during ischemic events, attenuating excitotoxic neuronal injury. Recently, our lab developed an electrochemical fast-scan cyclic voltammetry (FSCV) method that identified rapid, spontaneous changes in adenosine concentrations that last only about 3 seconds. Here, we investigated the effects of cerebral ischemia and reperfusion on the concentration and frequency of transient adenosine release in the caudate-putamen. In anesthetized rats, data were collected for four hours: two hours of normoxia, 30 min of cerebral ischemia induced by bilateral common carotid artery occlusion, and 90 min of reperfusion. Transient adenosine release was increased during the cerebral ischemia period and remained elevated during reperfusion. The total number of adenosine transients increased by 52% during cerebral ischemia and reperfusion compared to normoxia. The concentration of adenosine per event did not increase but the cumulative adenosine concentration during cerebral ischemia and reperfusion increased by 53% because of the higher frequency of events. Further, we evaluated the role of A_2A antagonist, SCH442416, a putative neuroprotective agent to affect adenosine transients. SCH442416 significantly decreased the transient frequency during cerebral ischemia-reperfusion by 27% and the cumulative concentration by 31%. Our results demonstrate that this mode of rapid adenosine release increases during early cerebral ischemia-reperfusion injury. Rapid adenosine release could provide fast, local neuromodulation and neuroprotection during cerebral ischemia.

Microfabricated Probes for Studying Brain Chemistry: A Review

Probe techniques for monitoring in vivo chemistry (e.g., electrochemical sensors and microdialysis sampling probes) have significantly contributed to a better understanding of neurotransmission in correlation to behaviors and neurological disorders. Microfabrication allows construction of neural probes with high reproducibility, scalability, design flexibility, and multiplexed features. This technology has translated well into fabricating miniaturized neurochemical probes for electrochemical detection and sampling. Microfabricated electrochemical probes provide a better control of spatial resolution with multisite detection on a single compact platform. This development allows the observation of heterogeneity of neurochemical activity precisely within the brain region. Microfabricated sampling probes are starting to emerge that enable chemical measurements at high spatial resolution and potential for reducing tissue damage. Recent advancement in analytical methods also facilitates neurochemical monitoring at high temporal resolution. Furthermore, a positive feature of microfabricated probes is that they can be feasibly built with other sensing and stimulating platforms including optogenetics. Such integrated probes will empower researchers to precisely elucidate brain function and develop novel treatments for neurological disorders.

A Materials Roadmap to Functional Neural Interface Design

Advancement in neurotechnologies for electrophysiology, neurochemical sensing, neuromodulation, and optogenetics are revolutionizing scientific understanding of the brain while enabling treatments, cures, and preventative measures for a variety of neurological disorders. The grand challenge in neural interface engineering is to seamlessly integrate the interface between neurobiology and engineered technology, to record from and modulate neurons over chronic timescales. However, the biological inflammatory response to implants, neural degeneration, and long-term material stability diminish the quality of interface overtime. Recent advances in functional materials have been aimed at engineering solutions for chronic neural interfaces. Yet, the development and deployment of neural interfaces designed from novel materials have introduced new challenges that have largely avoided being addressed. Many engineering efforts that solely focus on optimizing individual probe design parameters, such as softness or flexibility, downplay critical multi-dimensional interactions between different physical properties of the device that contribute to overall performance and biocompatibility. Moreover, the use of these new materials present substantial new difficulties that must be addressed before regulatory approval for use in human patients will be achievable. In this review, the interdependence of different electrode components are highlighted to demonstrate the current materials-based challenges facing the field of neural interface engineering.

Deep brain stimulation induces sparse distributions of locally modulated neuronal activity

Deep brain stimulation (DBS) therapy is a potent tool for treating a range of brain disorders. High frequency stimulation (HFS) patterns used in DBS therapy are known to modulate neuronal spike rates and patterns in the stimulated nucleus; however, the spatial distribution of these modulated responses are not well understood. Computational models suggest that HFS modulates a volume of tissue spatially concentrated around the active electrode. Here, we tested this theory by investigating modulation of spike rates and patterns in non-human primate motor thalamus while stimulating the cerebellar-receiving area of motor thalamus, the primary DBS target for treating Essential Tremor. HFS inhibited spike activity in the majority of recorded cells, but increasing stimulation amplitude also shifted the response to a greater degree of spike pattern modulation. Modulated responses in both categories exhibited a sparse and long-range spatial distribution within motor thalamus, suggesting that stimulation preferentially affects afferent and efferent axonal processes traversing near the active electrode and that the resulting modulated volume strongly depends on the local connectome of these axonal processes. Such findings have important implications for current clinical efforts building predictive computational models of DBS therapy, developing directional DBS lead technology, and formulating closed-loop DBS strategies.

Glial responses to implanted electrodes in the brain

The use of implants that can electrically stimulate or record electrophysiological or neurochemical activity in nervous tissue is rapidly expanding. Despite remarkable results in clinical studies and increasing market approvals, the mechanisms underlying the therapeutic effects of neuroprosthetic and neuromodulation devices, as well as their side effects and reasons for their failure, remain poorly understood. A major assumption has been that the signal-generating neurons are the only important target cells of neural-interface technologies. However, recent evidence indicates that the supporting glial cells remodel the structure and function of neuronal networks and are an effector of stimulation-based therapy. Here, we reframe the traditional view of glia as a passive barrier, and discuss their role as an active determinant of the outcomes of device implantation. We also discuss the implications that this has on the development of bioelectronic medical devices.

Advances in closed-loop deep brain stimulation devices

BACKGROUND

Millions of patients around the world are affected by neurological and psychiatric disorders. Deep brain stimulation (DBS) is a device-based therapy that could have fewer side-effects and higher efficiencies in drug-resistant patients compared to other therapeutic options such as pharmacological approaches. Thus far, several efforts have been made to incorporate a feedback loop into DBS devices to make them operate in a closed-loop manner.

METHODS

This paper presents a comprehensive investigation into the existing research-based and commercial closed-loop DBS devices. It describes a brief history of closed-loop DBS techniques, biomarkers and algorithms used for closing the feedback loop, components of the current research-based and commercial closed-loop DBS devices, and advancements and challenges in this field of research. This review also includes a comparison of the closed-loop DBS devices and provides the future directions of this area of research.

RESULTS

Although we are in the early stages of the closed-loop DBS approach, there have been fruitful efforts in design and development of closed-loop DBS devices. To date, only one commercial closed-loop DBS device has been manufactured. However, this system does not have an intelligent and patient dependent control algorithm. A closed-loop DBS device requires a control algorithm to learn and optimize the stimulation parameters according to the brain clinical state.

CONCLUSIONS

The promising clinical effects of open-loop DBS have been demonstrated, indicating DBS as a pioneer technology and treatment option to serve neurological patients. However, like other commercial devices, DBS needs to be automated and modernized.

Multifunctional System for Observing, Measuring and Analyzing Stimulation-Evoked Neurochemical Signaling

The ability to measure neurotransmitter activity using implanted electrochemical sensors offers researchers a potent technique for analyzing neural activity across specific neural circuitry. We have developed a wirelessly controlled device, WINCS Harmoni, to observe and measure neurotransmitter dynamics at up to four separate sensors, with high temporal and spatial resolution. WINCS Harmoni also incorporates a versatile neurostimulator that can be synchronized with electrochemical recording. The WINCS Harmoni platform is thus optimally suited for probing the neurochemical effects of neurostimulation, and may in turn enable the development of personalized therapies for multiple brain disorders.

Dopamine Release in the Nonhuman Primate Caudate and Putamen Depends upon Site of Stimulation in the Subthalamic Nucleus

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for medically refractory Parkinson's disease. Although DBS has recognized clinical utility, its biologic mechanisms are not fully understood, and whether dopamine release is a potential factor in those mechanisms is in dispute. We tested the hypothesis that STN DBS-evoked dopamine release depends on the precise location of the stimulation site in the STN and the site of recording in the caudate and putamen. We conducted DBS with miniature, scaled-to-animal size, multicontact electrodes and used functional magnetic resonance imaging to identify the best dopamine recording site in the brains of nonhuman primates (rhesus macaques), which are highly representative of human brain anatomy and circuitry. Real-time stimulation-evoked dopamine release was monitored using in vivo fast-scan cyclic voltammetry. This study demonstrates that STN DBS-evoked dopamine release can be reduced or increased by redirecting STN stimulation to a slightly different site.

SIGNIFICANCE STATEMENT

Electrical stimulation of deep structures of the brain, or deep brain stimulation (DBS), is used to modulate pathological brain activity. However, technological limitations and incomplete understanding of the therapeutic mechanisms of DBS prevent personalization of this therapy and may contribute to less-than-optimal outcomes. We have demonstrated that DBS coincides with changes in dopamine neurotransmitter release in the basal ganglia. Here we mapped relationships between DBS and changes in neurochemical activity. Importantly, this study shows that DBS-evoked dopamine release can be reduced or increased by refocusing the DBS on a slightly different stimulation site.

WINCS Harmoni: Closed-loop dynamic neurochemical control of therapeutic interventions

There has been significant progress in understanding the role of neurotransmitters in normal and pathologic brain function. However, preclinical trials aimed at improving therapeutic interventions do not take advantage of real-time in vivo neurochemical changes in dynamic brain processes such as disease progression and response to pharmacologic, cognitive, behavioral, and neuromodulation therapies. This is due in part to a lack of flexible research tools that allow in vivo measurement of the dynamic changes in brain chemistry. Here, we present a research platform, WINCS Harmoni, which can measure in vivo neurochemical activity simultaneously across multiple anatomical targets to study normal and pathologic brain function. In addition, WINCS Harmoni can provide real-time neurochemical feedback for closed-loop control of neurochemical levels via its synchronized stimulation and neurochemical sensing capabilities. We demonstrate these and other key features of this platform in non-human primate, swine, and rodent models of deep brain stimulation (DBS). Ultimately, systems like the one described here will improve our understanding of the dynamics of brain physiology in the context of neurologic disease and therapeutic interventions, which may lead to the development of precision medicine and personalized therapies for optimal therapeutic efficacy.

Monitoring In Vivo Changes in Tonic Extracellular Dopamine Level by Charge-Balancing Multiple Waveform Fast-Scan Cyclic Voltammetry

Dopamine (DA) modulates central neuronal activity through both phasic (second to second) and tonic (minutes to hours) terminal release. Conventional fast-scan cyclic voltammetry (FSCV), in combination with carbon fiber microelectrodes, has been used to measure phasic DA release in vivo by adopting a background subtraction procedure to remove background capacitive currents. However, measuring tonic changes in DA concentrations using conventional FSCV has been difficult because background capacitive currents are inherently unstable over long recording periods. To measure tonic changes in DA concentrations over several hours, we applied a novel charge-balancing multiple waveform FSCV (CBM-FSCV), combined with a dual background subtraction technique, to minimize temporal variations in background capacitive currents. Using this method, in vitro, charge variations from a reference time point were nearly zero for 48 h, whereas with conventional background subtraction, charge variations progressively increased. CBM-FSCV also demonstrated a high selectivity against 3,4-dihydroxyphenylacetic acid and ascorbic acid, two major chemical interferents in the brain, yielding a sensitivity of 85.40 ± 14.30 nA/μM and limit of detection of 5.8 ± 0.9 nM for DA while maintaining selectivity. Recorded in vivo by CBM-FSCV, pharmacological inhibition of DA reuptake (nomifensine) resulted in a 235 ± 60 nM increase in tonic extracellular DA concentrations, while inhibition of DA synthesis (α-methyl-dl-tyrosine) resulted in a 72.5 ± 4.8 nM decrease in DA concentrations over a 2 h period. This study showed that CBM-FSCV may serve as a unique voltammetric technique to monitor relatively slow changes in tonic extracellular DA concentrations in vivo over a prolonged time period.

Neuroadhesive L1 coating attenuates acute microglial attachment to neural electrodes as revealed by live two-photon microscopy

Implantable neural electrode technologies for chronic neural recordings can restore functional control to paralysis and limb loss victims through brain-machine interfaces. These probes, however, have high failure rates partly due to the biological responses to the probe which generate an inflammatory scar and subsequent neuronal cell death. L1 is a neuronal specific cell adhesion molecule and has been shown to minimize glial scar formation and promote electrode-neuron integration when covalently attached to the surface of neural probes. In this work, the acute microglial response to L1-coated neural probes was evaluated in vivo by implanting coated devices into the cortex of mice with fluorescently labeled microglia, and tracking microglial dynamics with multi-photon microscopy for the ensuing 6 h in order to understand L1's cellular mechanisms of action. Microglia became activated immediately after implantation, extending processes towards both L1-coated and uncoated control probes at similar velocities. After the processes made contact with the probes, microglial processes expanded to cover 47.7% of the control probes' surfaces. For L1-coated probes, however, there was a statistically significant 83% reduction in microglial surface coverage. This effect was sustained through the experiment. At 6 h post-implant, the radius of microglia activation was reduced for the L1 probes by 20%, shifting from 130.0 to 103.5 μm with the coating. Microglia as far as 270 μm from the implant site displayed significantly lower morphological characteristics of activation for the L1 group. These results suggest that the L1 surface treatment works in an acute setting by microglial mediated mechanisms.

Technological Advances in Deep Brain Stimulation

Functional and stereotactic neurosurgery has always been regarded as a subspecialty based on and driven by technological advances. However until recently, the fundamentals of deep brain stimulation (DBS) hardware and software design had largely remained stagnant since its inception almost three decades ago. Recent improved understanding of disease processes in movement disorders as well clinician and patient demands has resulted in new avenues of development for DBS technology. This review describes new advances both related to hardware and software for neuromodulation. New electrode designs with segmented contacts now enable sophisticated shaping and sculpting of the field of stimulation, potentially allowing multi-target stimulation and avoidance of side effects. To avoid lengthy programming sessions utilising multiple lead contacts, new user-friendly software allows for computational modelling and individualised directed programming. Therapy delivery is being improved with the next generation of smaller profile, longer-lasting, re-chargeable implantable pulse generators (IPGs). These include IPGs capable of delivering constant current stimulation or personalised closed-loop adaptive stimulation. Post-implantation Magnetic Resonance Imaging (MRI) has long been an issue which has been partially overcome with 'MRI conditional devices' and has enabled verification of DBS lead location. Surgical technique is considering a shift from frame-based to frameless stereotaxy or greater role for robot assisted implantation. The challenge for these contemporary techniques however, will be in demonstrating equivalent safety and accuracy to conventional methods. We also discuss potential future direction utilising wireless technology allowing for miniaturisation of hardware.

Neurochemostat: A Neural Interface SoC With Integrated Chemometrics for Closed-Loop Regulation of Brain Dopamine

This paper presents a 3.3×3.2 mm(2) system-on-chip (SoC) fabricated in AMS 0.35 μm 2P/4M CMOS for closed-loop regulation of brain dopamine. The SoC uniquely integrates neurochemical sensing, on-the-fly chemometrics, and feedback-controlled electrical stimulation to realize a "neurochemostat" by maintaining brain levels of electrically evoked dopamine between two user-set thresholds. The SoC incorporates a 90 μW, custom-designed, digital signal processing (DSP) unit for real-time processing of neurochemical data obtained by 400 V/s fast-scan cyclic voltammetry (FSCV) with a carbon-fiber microelectrode (CFM). Specifically, the DSP unit executes a chemometrics algorithm based upon principal component regression (PCR) to resolve in real time electrically evoked brain dopamine levels from pH change and CFM background-current drift, two common interferents encountered using FSCV with a CFM in vivo. Further, the DSP unit directly links the chemically resolved dopamine levels to the activation of the electrical microstimulator in on-off-keying (OOK) fashion. Measured results from benchtop testing, flow injection analysis (FIA), and biological experiments with an anesthetized rat are presented.

A Diamond-Based Electrode for Detection of Neurochemicals in the Human Brain

Deep brain stimulation (DBS), a surgical technique to treat certain neurologic and psychiatric conditions, relies on pre-determined stimulation parameters in an open-loop configuration. The major advancement in DBS devices is a closed-loop system that uses neurophysiologic feedback to dynamically adjust stimulation frequency and amplitude. Stimulation-driven neurochemical release can be measured by fast-scan cyclic voltammetry (FSCV), but existing FSCV electrodes rely on carbon fiber, which degrades quickly during use and is therefore unsuitable for chronic neurochemical recording. To address this issue, we developed durable, synthetic boron-doped diamond-based electrodes capable of measuring neurochemical release in humans. Compared to carbon fiber electrodes, they were more than two orders-of-magnitude more physically-robust and demonstrated longevity in vitro without deterioration. Applied for the first time in humans, diamond electrode recordings from thalamic targets in patients (n = 4) undergoing DBS for tremor produced signals consistent with adenosine release at a sensitivity comparable to carbon fiber electrodes. (Clinical trials # NCT01705301).

Fornix deep brain stimulation circuit effect is dependent on major excitatory transmission via the nucleus accumbens

INTRODUCTION

Deep brain stimulation (DBS) is a circuit-based treatment shown to relieve symptoms from multiple neurologic and neuropsychiatric disorders. In order to treat the memory deficit associated with Alzheimer's disease (AD), several clinical trials have tested the efficacy of DBS near the fornix. Early results from these studies indicated that patients who received fornix DBS experienced an improvement in memory and quality of life, yet the mechanisms behind this effect remain controversial. It is known that transmission between the medial limbic and corticolimbic circuits plays an integral role in declarative memory, and dysfunction at the circuit level results in various forms of dementia, including AD. Here, we aimed to determine the potential underlying mechanism of fornix DBS by examining the functional circuitry and brain structures engaged by fornix DBS.

METHODS

A multimodal approach was employed to examine global and local temporal changes that occur in an anesthetized swine model of fornix DBS. Changes in global functional activity were measured by functional MRI (fMRI), and local neurochemical changes were monitored by fast scan cyclic voltammetry (FSCV) during electrical stimulation of the fornix. Additionally, intracranial microinfusions into the nucleus accumbens (NAc) were performed to investigate the global activity changes that occur with dopamine and glutamate receptor-specific antagonism.

RESULTS

Hemodynamic responses in both medial limbic and corticolimbic circuits measured by fMRI were induced by fornix DBS. Additionally, fornix DBS resulted in increases in dopamine oxidation current (corresponding to dopamine efflux) monitored by FSCV in the NAc. Finally, fornix DBS-evoked hemodynamic responses in the amygdala and hippocampus decreased following dopamine and glutamate receptor antagonism in the NAc.

CONCLUSIONS

The present findings suggest that fornix DBS modulates dopamine release on presynaptic dopaminergic terminals in the NAc, involving excitatory glutamatergic input, and that the medial limbic and corticolimbic circuits interact in a functional loop.

Neuroelectronics and Biooptics: Closed-Loop Technologies in Neurological Disorders

Brain-implanted devices are no longer a futuristic idea. Traditionally, therapies for most neurological disorders are adjusted based on changes in clinical symptoms and diagnostic measures observed over time. These therapies are commonly pharmacological or surgical, requiring continuous or irreversible treatment regimens that cannot respond rapidly to fluctuations of symptoms or isolated episodes of dysfunction. In contrast, closed-loop systems provide intervention only when needed by detecting abnormal neurological signals and modulating them with instantaneous feedback. Closed-loop systems have been applied to several neurological conditions (most notably epilepsy and movement disorders), but widespread use is limited by conceptual and technical challenges. Herein, we discuss how advances in experimental closed-loop systems hold promise for improved clinical benefit in patients with neurological disorders.

Real time adenosine fluctuations detected with fast-scan cyclic voltammetry in the rat striatum and motor cortex

BACKGROUND

Adenosine serves many functions within the CNS, including inhibitory and excitatory control of neurotransmission. The understanding of adenosine dynamics in the brain is of fundamental importance. The goal of the present study was to explore subsecond adenosine fluctuations in the rat brain in vivo.

METHOD

Long Evans rats were anesthetized and a carbon fiber electrode was positioned in the motor cortex or dorsal striatum. Real time electrochemical recordings were made at the carbon fiber electrodes every 100ms by applying a triangular waveform (-0.4 to +1.5V, 400V/s). Adenosine spikes were identified by the background-subtracted cyclic voltammogram.

RESULTS

The frequency of detected adenosine spikes was relatively stable in both tested regions, and the time intervals between spikes were regular and lasted from 1 to 5s within an animal. Spike frequency ranged from 0.5 to 1.5Hz in both the motor cortex and the dorsal striatum. Average spike amplitudes were 85±11 and 66±7nM for the motor cortex and the dorsal striatum, respectively.

COMPARISON WITH EXISTING METHODS

The current study established that adenosine signaling can operate on a fast time scale (within seconds) to modulate brain functions.

CONCLUSIONS

This finding suggests that spontaneous adenosine release may play a fast, dynamic role in regulating an organism's response to external events. Therefore, adenosine transmission in the brain may have characteristics similar to those of classical neurotransmitters, such as dopamine and norepinephrine.

Deep Brain Stimulation

High-frequency deep brain stimulation (DBS) is an effective treatment for some movement disorders. Though mechanisms underlying DBS are still unclear, commonly accepted theories include a “functional inhibition” of neuronal cell bodies and the excitation of axonal projections near the electrodes. It is becoming clear, however, that the paradoxical dissociation “local inhibition” and “distant excitation” is far more complex than initially thought. Despite an initial increase in neuronal activity following stimulation, cells are often unable to maintain normal ionic concentrations, particularly those of sodium and potassium. Based on currently available evidence, we proposed an alternative hypothesis. Increased extracellular concentrations of potassium during DBS may change the dynamics of both cells and axons, contributing not only to the intermittent excitation and inhibition of these elements but also to interrupt abnormal pathological activity. In this article, we review mechanisms through which high extracellular potassium may mediate some of the effects of DBS.

Deep brain stimulation for the treatment of resistant hypertension

Hypertension is a leading risk factor for the development of several cardiovascular diseases. As the global prevalence of hypertension increases, so too has the recognition of resistant hypertension. Whilst figures vary, the proportion of hypertensive patients that are resistant to multiple drug therapies have been reported to be as high as 16.4 %. Resistant hypertension is typically associated with elevated sympathetic activity and abnormal homeostatic reflex control and is termed neurogenic hypertension because of its presumed central autonomic nervous system origin. This resistance to conventional pharmacological treatment has stimulated a plethora of medical devices to be investigated for use in hypertension, with varying degrees of success. In this review, we discuss a new therapy for drug-resistant hypertension, deep brain stimulation. The utility of deep brain stimulation in resistant hypertension was first discovered in patients with concurrent neuropathic pain, where it lowered blood pressure and improved baroreflex sensitivity. The most promising central target for stimulation is the ventrolateral periaqueductal gray, which has been well characterised in animal studies as a control centre for autonomic outflow. In this review, we will discuss the promise and potential mechanisms of deep brain stimulation in the treatment of severe, resistant hypertension.