Understanding the different effects of fouling mechanisms on working and reference electrodes in fast-scan cyclic voltammetry for neurotransmitter detection.

Fast-scan cyclic voltammetry (FSCV) is a widely used technique for detecting neurotransmitters. However, electrode fouling can negatively impact its accuracy and sensitivity. Fouling refers to the accumulation of unwanted materials on the electrode surface, which can alter its electrochemical properties and reduce its sensitivity and selectivity. Fouling mechanisms can be broad and may include biofouling, the accumulation of biomolecules on the electrode surface, and chemical fouling, the deposition of unwanted chemical species. Despite individual studies discussing fouling effects on either the working electrode or the reference electrode, no comprehensive study has been conducted to compare the overall fouling effects on both electrodes in the context of FSCV. Here, we examined the effects of biofouling and chemical fouling on the carbon fiber micro-electrode (CFME) as the working electrode and the Ag/AgCl reference electrode with FSCV. Both fouling mechanisms significantly decreased the sensitivity and caused peak voltage shifts in the FSCV signal with the CFME, but not with the Ag/AgCl reference electrode. Interestingly, previous studies have reported peak voltage shifts in FSCV signals due to the fouling of Ag/AgCl electrodes after implantation in the brain. We noticed in a previous study that energy-dispersive spectroscopy (EDS) spectra showed increased sulfide ion concentration after implantation. We hypothesized that sulfide ions may be responsible for the peak voltage shift. To test this hypothesis, we added sulfide ions to the buffer solution, which decreased the open circuit potential of the Ag/AgCl electrode and caused a peak voltage shift in the FSCV voltammograms. Also, EDS analysis showed that sulfide ion concentration increased on the surface of the Ag/AgCl electrodes after 3 weeks of chronic implantation, necessitating consideration of sulfide ions as the fouling agent for the reference electrodes. Overall, our study provides important insights into the mechanisms of electrode fouling and its impact on FSCV measurements. These findings could inform the design of FSCV experiments, with the development of new strategies for improving the accuracy and reliability of FSCV measurements in vivo.

Effect of temporal interference electrical stimulation on phasic dopamine release in the striatum.

BACKGROUND: Temporal interference stimulation (TIS) is a neuromodulation technique that could stimulate deep brain regions by inducing interfering electrical signals based on high-frequency electrical stimulations of multiple electrode pairs from outside the brain. Despite numerous TIS studies, however, there has been limited investigation into the neurochemical effects of TIS. OBJECTIVE: We performed two experiments to investigate the effect of TIS on the medial forebrain bundle (MFB)-evoked phasic dopamine (DA) response. METHODS: In the first experiment, we applied TIS next to a carbon fiber microelectrode (CFM) to examine the modulation of the MFB-evoked phasic DA response in the striatum (STr). Beat frequencies and intensities of TIS were 0, 2, 6, 10, 20, 60, 130 Hz and 0, 100, 200, 300, 400, 500 µA. In the second experiment, we examined the effect of TIS with a 2 Hz beat frequency (based on the first experiment) on MFB-evoked phasic DA release when applied above the cortex (with a simulation-based stimulation site targeting the striatum). We employed 0 Hz and 2 Hz beat frequencies and a control condition without stimulation. RESULTS: In the first experiment, TIS with a beat frequency of 2 Hz and an intensity of 400 µA or greater decreased MFB-evoked phasic DA release by roughly 40%, which continued until the experiment's end. In contrast, TIS at beat frequencies other than 2 Hz and intensities less than 400 µA did not affect MFB-evoked phasic DA release. In the second experiment, TIS with a 2 Hz beat frequency decreased only the MFB-evoked phasic DA response, but the reduction in DA release was not sustained. CONCLUSIONS: STr-applied and cortex-applied TIS with delta frequency dampens evoked phasic DA release in the STr. These findings demonstrate that TIS could influence the neurochemical modulation of the brain.

Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.

Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From measurements using fast scan cyclic voltammetry (FSCV), one of the main tools used to detect synaptic efflux of neurochemicals in vivo, principal component regression (PCR), has been commonly used to predict the identity and concentrations of neurotransmitters. However, the sensitivity and discrimination performance of PCR have room for improvement, especially for analyzing mixtures of similar oxidizable neurochemicals. Deep learning may be able to address these challenges. To date, there have been a few studies to apply machine learning to FSCV, but no attempt to apply deep learning to neurotransmitter mixture discrimination and no comparative study have been performed between PCR and deep learning methods to demonstrate which is more accurate for FSCV analysis so far. In this study, we compared the neurochemical identification and concentration estimation performance of PCR and deep learning in an analysis of FSCV recordings of catecholamine and indolamine neurotransmitters. Both analysis methods were tested on in vitro FSCV data with a single or mixture of neurotransmitters at the desired concentration. In addition, the estimation performance of PCR and deep learning was compared in incorporation with in vivo experiments to evaluate the practical usage. Pharmacological tests were also conducted to see whether deep learning would track the increased amount of catecholamine levels in the brain. Using conventional FSCV, we used five electrodes and recorded in vitro background-subtracted cyclic voltammograms from four neurotransmitters, dopamine, epinephrine, norepinephrine, and serotonin, with five concentrations of each substance, as well as various mixtures of the four analytes. The results showed that the identification accuracy errors were reduced 5-20% by using deep learning compared to using PCR for mixture analysis, and the two methods were comparable for single analyte analysis. The applied deep-learning-based method demonstrated not only higher identification accuracy but also better discrimination performance than PCR for mixtures of neurochemicals and even for in vivo testing. Therefore, we suggest that deep learning should be chosen as a more reliable tool to analyze FSCV data compared to conventional PCR methods although further work is still needed on developing complete validation procedures prior to widespread use.

Hetero-Integration of Silicon Nanomembranes with 2D Materials for Bioresorbable, Wireless Neurochemical System.

Although neurotransmitters are key substances closely related to evaluating degenerative brain diseases as well as regulating essential functions in the body, many research efforts have not been focused on direct observation of such biochemical messengers, rather on monitoring relatively associated physical, mechanical, and electrophysiological parameters. Here, a bioresorbable silicon-based neurochemical analyzer incorporated with 2D transition metal dichalcogenides is introduced as a completely implantable brain-integrated system that can wirelessly monitor time-dynamic behaviors of dopamine and relevant parameters in a simultaneous mode. An extensive range of examinations of molybdenum/tungsten disulfide (MoS2 /WS2 ) nanosheets and catalytic iron nanoparticles (Fe NPs) highlights the underlying mechanisms of strong chemical and target-specific responses to the neurotransmitters, along with theoretical modeling tools. Systematic characterizations demonstrate reversible, stable, and long-term operational performances of the degradable bioelectronics with excellent sensitivity and selectivity over those of non-dissolvable counterparts. A complete set of in vivo experiments with comparative analysis using carbon-fiber electrodes illustrates the capability for potential use as a clinically accessible tool to associated neurodegenerative diseases.

Enhanced Dopamine Sensitivity Using Steered Fast-Scan Cyclic Voltammetry.

Fast-scan cyclic voltammetry (FSCV) is a technique for measuring phasic release of neurotransmitters with millisecond temporal resolution. The current data are captured by carbon fiber microelectrodes, and non-Faradaic current is subtracted from the background current to extract the Faradaic redox current through a background subtraction algorithm. FSCV is able to measure neurotransmitter concentrations in vivo down to the nanomolar scale, making it a very robust and useful technique for probing neurotransmitter release dynamics and communication across neural networks. In this study, we describe a technique that can further lower the limit of detection of FSCV. By taking advantage of a "waveform steering" technique and by amplifying only the oxidation peak of dopamine to reduce noise fluctuations, we demonstrate the ability to measure dopamine concentrations down to 0.17 nM. Waveform steering is a technique to dynamically alter the input waveform to ensure that the background current remains stable over time. Specifically, the region of the input waveform in the vicinity of the dopamine oxidation potential (∼0.6 V) is kept flat. Thus, amplification of the input waveform will amplify only the Faradaic current, lowering the existing limit of detection for dopamine from 5.48 to 0.17 nM, a 32-fold reduction, and for serotonin, it lowers the limit of detection from 57.3 to 1.46 nM, a 39-fold reduction compared to conventional FSCV. Finally, the applicability of steered FSCV to in vivo dopamine detection was also demonstrated in this study. In conclusion, steered FSCV might be used as a neurochemical monitoring tool for enhancing detection sensitivity.

Tonic Serotonin Measurements In Vivo Using N-Shaped Multiple Cyclic Square Wave Voltammetry.

Here, we present the development of a novel voltammetric technique, N-shaped multiple cyclic square wave voltammetry (N-MCSWV) and its application in vivo. It allows quantitative measurements of tonic extracellular levels of serotonin in vivo with mitigated fouling effects. N-MCSWV enriches the electrochemical information by generating high dimensional voltammograms, which enables high sensitivity and selectivity against 5-hydroindoleacetic acid (5-HIAA), dopamine, 3,4-dihydroxyphenylacetic acid (DOPAC), histamine, ascorbic acid, norepinephrine, adenosine, and pH. Using N-MCSWV, in combination with PEDOT:Nafion-coated carbon fiber microelectrodes, a tonic serotonin concentration of 52 ± 5.8 nM (n = 20 rats, ±SEM) was determined in the substantia nigra pars reticulata of urethane-anesthetized rats. Pharmacological challenges with dopaminergic, noradrenergic, and serotonergic synaptic reuptake inhibitors supported the ability of N-MCSWV to selectively detect tonic serotonin levels in vivo. Overall, N-MCSWV is a novel voltammetric technique for analytical quantification of serotonin. It offers continuous monitoring of changes in tonic serotonin concentrations in the brain to further our understanding of the role of serotonin in normal behaviors and psychiatric disorders.

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 (Rct), solution-resistance (Rs), and double-layer capacitance (Cdl) voltammograms were constructed and investigated in the phasic changes in dopamine (DA) concentrations. As a result, all Rct, Rs, and Cdl voltammograms showed different DA redox patterns and linear trends for the DA concentration (R2 > 0.99). Furthermore, the Rct 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, Cdl 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.

Redefining differential roles of MAO-A in dopamine degradation and MAO-B in tonic GABA synthesis.

Monoamine oxidase (MAO) is believed to mediate the degradation of monoamine neurotransmitters, including dopamine, in the brain. Between the two types of MAO, MAO-B has been believed to be involved in dopamine degradation, which supports the idea that the therapeutic efficacy of MAO-B inhibitors in Parkinson's disease can be attributed to an increase in extracellular dopamine concentration. However, this belief has been controversial. Here, by utilizing in vivo phasic and basal electrochemical monitoring of extracellular dopamine with fast-scan cyclic voltammetry and multiple-cyclic square wave voltammetry and ex vivo fluorescence imaging of dopamine with GRABDA2m, we demonstrate that MAO-A, but not MAO-B, mainly contributes to striatal dopamine degradation. In contrast, our whole-cell patch-clamp results demonstrated that MAO-B, but not MAO-A, was responsible for astrocytic GABA-mediated tonic inhibitory currents in the rat striatum. We conclude that, in contrast to the traditional belief, MAO-A and MAO-B have profoundly different roles: MAO-A regulates dopamine levels, whereas MAO-B controls tonic GABA levels.

Sensitive and Selective Measurement of Serotonin in Vivo Using Fast Cyclic Square-Wave Voltammetry.

Although N-shaped fast scan cyclic voltammetry (N-FSCV) is well-established as an electroanalytical method to measure extracellular serotonin concentrations in vivo, it is in need of improvement in both sensitivity and selectivity. Based on our previous studies using fast cyclic square-wave voltammetry (FCSWV) for in vivo dopamine measurements, we have modified this technique to optimize the detection of serotonin in vivo. A series of large amplitude square-shaped potentials was superimposed onto an N-shaped waveform to provide cycling through multiple redox reactions within the N-shaped waveform to enhance the sensitivity and selectivity to serotonin measurement when combined with a two-dimensional voltammogram. N-Shaped fast cyclic square-wave voltammetry (N-FCSWV) showed significantly higher sensitivity to serotonin compared to conventional N-FSCV. In addition, N-FCSWV showed better performance than conventional N-shaped FSCV in differentiating serotonin from its major interferents, dopamine and 5-hydroxyindoleascetic acid (5-HIAA). It was also confirmed that the large amplitude of the square waveform did not influence local neuronal activity, and it could monitor electrical stimulation evoked phasic release of serotonin in the rat substantia nigra pars reticulata (SNr) before and after systemic injection of escitalopram (ESCIT, 10 mg/kg i.p.), a serotonin selective reuptake inhibitor.

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.

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.

Tracking tonic dopamine levels in vivo using multiple cyclic square wave voltammetry.

For over two decades, fast-scan cyclic voltammetry (FSCV) has served as a reliable analytical method for monitoring dopamine release in near real-time in vivo. However, contemporary FSCV techniques have been limited to measure only rapid (on the order of seconds, i.e. phasic) changes in dopamine release evoked by either electrical stimulation or elicited by presentation of behaviorally salient stimuli, and not slower changes in the tonic extracellular levels of dopamine (i.e. basal concentrations). This is because FSCV is inherently a differential method that requires subtraction of prestimulation tonic levels of dopamine to measure phasic changes relative to a zeroed baseline. Here, we describe the development and application of a novel voltammetric technique, multiple cyclic square wave voltammetry (M-CSWV), for analytical quantification of tonic dopamine concentrations in vivo with relatively high temporal resolution (10 s). M-CSWV enriches the electrochemical information by generating two dimensional voltammograms which enable high sensitivity (limit of detection, 0.17 nM) and selectivity against ascorbic acid, and 3,4-dihydroxyphenylacetic acid (DOPAC), including changes in pH. Using M-CSWV, a tonic dopamine concentration of 120 ±â€¯18 nM (n = 7 rats, ±â€¯SEM) was determined in the striatum of urethane anethetized rats. Pharmacological treatments to elevate dopamine by selectively inhibiting dopamine reuptake and to reduce DOPAC by inhibition of monoamine oxidase supported the selective detection of dopamine in vivo. Overall, M-CSWV offers a novel voltammetric technique to quantify levels and monitor changes in tonic dopamine concentrations in the brain to further our understanding of the role of dopamine in normal behavior and neuropsychiatric disorders.

Ultrafast charge and discharge biscrolled yarn supercapacitors for textiles and microdevices.

Flexible, wearable, implantable and easily reconfigurable supercapacitors delivering high energy and power densities are needed for electronic devices. Here we demonstrate weavable, sewable, knottable and braidable yarns that function as high performance electrodes of redox supercapacitors. A novel technology, gradient biscrolling, provides fast-ion-transport yarn in which hundreds of layers of conducting-polymer-infiltrated carbon nanotube sheet are scrolled into ~20 µm diameter yarn. Plying the biscrolled yarn with a metal wire current collector increases power generation capabilities. The volumetric capacitance is high (up to ~179 F cm(-3)) and the discharge current of the plied yarn supercapacitor linearly increases with voltage scan rate up to ~80 V s(-1) and ~20 V s(-1) for liquid and solid electrolytes, respectively. The exceptionally high energy and power densities for the complete supercapacitor, and high cycle life that little depends on winding or sewing (92%, 99% after 10,000 cycles, respectively) are important for the applications in electronic textiles.