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.

Investigation of daily patterns for smartphone keystroke dynamics based on loneliness and social isolation.

This study examined the relationship between loneliness levels and daily patterns of mobile keystroke dynamics in healthy individuals. Sixty-six young healthy Koreans participated in the experiment. Over five weeks, the participants used a custom Android keyboard. We divided the participants into four groups based on their level of loneliness (no loneliness, moderate loneliness, severe loneliness, and very severe loneliness). The very severe loneliness group demonstrated significantly higher typing counts during sleep time than the other three groups (one-way ANOVA, F = 3.75, p < 0.05). In addition, the average cosine similarity value of weekday and weekend typing patterns in the very severe loneliness group was higher than that in the no loneliness group (Welch's t-test, t = 2.27, p < 0.05). This meant that the no loneliness group's weekday and weekend typing patterns varied, whereas the very severe loneliness group's weekday and weekend typing patterns did not. Our results indicated that individuals with very high levels of loneliness tended to use mobile keyboards during late-night hours and did not significantly change their smartphone usage behavior between weekdays and weekends. These findings suggest that mobile keystroke dynamics have the potential to be used for the early detection of loneliness and the development of targeted interventions.

Techniques for Measurement of Serotonin: Implications in Neuropsychiatric Disorders and Advances in Absolute Value Recording Methods.

Serotonin (5-HT) is a monoamine neurotransmitter in the peripheral, enteric, and central nervous systems (CNS). Within the CNS, serotonin is principally involved in mood regulation and reward-seeking behaviors. It is a critical regulator in CNS pathologies such as major depressive disorder, addiction, and schizophrenia. Consequently, in vivo serotonin measurements within the CNS have emerged as one of many promising approaches to investigating the pathogenesis, progression, and treatment of these and other neuropsychiatric conditions. These techniques vary in methods, ranging from analyte sampling with microdialysis to voltammetry. Provided this diversity in approach, inherent differences between techniques are inevitable. These include biosensor size, temporal/spatial resolution, and absolute value measurement capabilities, all of which must be considered to fit the prospective researcher's needs. In this review, we summarize currently available methods for the measurement of serotonin, including novel voltammetric absolute value measurement techniques. We also detail serotonin's role in various neuropsychiatric conditions, highlighting the role of phasic and tonic serotonergic neuronal firing within each where relevant. Lastly, we briefly review the present clinical application of these techniques and discuss the potential of a closed-loop monitoring and neuromodulation system utilizing deep brain stimulation (DBS).

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.

Deep brain stimulation alleviates tics in Tourette syndrome via striatal dopamine transmission.

Tourette syndrome is a childhood-onset neuropsychiatric disorder characterized by intrusive motor and vocal tics that can lead to self-injury and deleterious mental health complications. While dysfunction in striatal dopamine neurotransmission has been proposed to underlie tic behaviour, evidence is scarce and inconclusive. Deep brain stimulation (DBS) of the thalamic centromedian parafascicular complex (CMPf), an approved surgical interventive treatment for medical refractory Tourette syndrome, may reduce tics by affecting striatal dopamine release. Here, we use electrophysiology, electrochemistry, optogenetics, pharmacological treatments and behavioural measurements to mechanistically examine how thalamic DBS modulates synaptic and tonic dopamine activity in the dorsomedial striatum. Previous studies demonstrated focal disruption of GABAergic transmission in the dorsolateral striatum of rats led to repetitive motor tics recapitulating the major symptom of Tourette syndrome. We employed this model under light anaesthesia and found CMPf DBS evoked synaptic dopamine release and elevated tonic dopamine levels via striatal cholinergic interneurons while concomitantly reducing motor tic behaviour. The improvement in tic behaviour was found to be mediated by D2 receptor activation as blocking this receptor prevented the therapeutic response. Our results demonstrate that release of striatal dopamine mediates the therapeutic effects of CMPf DBS and points to striatal dopamine dysfunction as a driver for motor tics in the pathoneurophysiology of Tourette syndrome.

Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo.

Tonic extracellular neurotransmitter concentrations are important modulators of central network homeostasis. Disruptions in these tonic levels are thought to play a role in neurologic and psychiatric disease. Therefore, ways to improve their quantification are actively being investigated. Previously published voltammetric software packages have implemented FSCV, which is not capable of measuring tonic concentrations of neurotransmitters in vivo. In this paper, custom software was developed for near-real-time tracking (scans every 10 s) of neurotransmitters' tonic concentrations with high sensitivity and spatiotemporal resolution both in vitro and in vivo using cyclic voltammetry combined with dynamic background subtraction (M-CSWV and FSCAV). This software was designed with flexibility, speed, and user-friendliness in mind. This software enables near-real-time measurement by reducing data analysis time through an optimized modeling algorithm, and efficient memory handling makes long-term measurement possible. The software permits customization of the cyclic voltammetric waveform shape, enabling experiments to detect a specific analyte of interest. Finally, flexibility considerations allow the user to alter the fitting parameters, filtering characteristics, and size and shape of the analyte kernel, based on data obtained live during the experiment to obtain accurate measurements as experimental conditions change. Herein, the design and advantages of this near-real-time voltammetric software are described, and its use is demonstrated in in vivo experiments.

Feasibility of epidural temporal interference stimulation for minimally invasive electrical deep brain stimulation: simulation and phantom experimental studies.

Objective. Temporal interference stimulation (TIS) has shown the potential as a new method for selective stimulation of deep brain structures in small animal experiments. However, it is challenging to deliver a sufficient temporal interference (TI) current to directly induce an action potential in the deep area of the human brain when electrodes are attached to the scalp because the amount of injection current is generally limited due to safety issues. Thus, we propose a novel method called epidural TIS (eTIS) to address this issue; in this method, the electrodes are attached to the epidural surface under the skull.Approach. We employed finite element method (FEM)-based electric field simulations to demonstrate the feasibility of eTIS. We first optimized the electrode conditions to deliver maximum TI currents to each of the three different targets (anterior hippocampus, subthalamic nucleus, and ventral intermediate nucleus) based on FEM, and compared the stimulation focality between eTIS and transcranial TIS (tTIS). Moreover, we conducted realistic skull-phantom experiments for validating the accuracy of the computational simulation for eTIS.Main results. Our simulation results showed that eTIS has the advantage of avoiding the delivery of TI currents over unwanted neocortical regions compared with tTIS for all three targets. It was shown that the optimized eTIS could induce neural action potentials at each of the three targets when a sufficiently large current equivalent to that for epidural cortical stimulation is injected. Additionally, the simulated results and measured results via the phantom experiments were in good agreement.Significance. We demonstrated the feasibility of eTIS, facilitating more focalized and stronger electrical stimulation of deep brain regions than tTIS, with the relatively less invasive placement of electrodes than conventional deep brain stimulation via computational simulation and realistic skull phantom experiments.

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.

The influence of object-location binding mental load effects on the visual N1 and N2 Event-related Potentials.

OBJECTIVE: This study aimed to analyze the effect of object-location binding on the visual working memory workload. For this study, thirty healthy subjects were recruited, and they performed the "What was where" task, which was modified to evaluated object-location binding memory. We analyzed their ERP and behavior response. RESULTS: Object memory and location memory were preserved during the task, but binding memory decreased significantly when more than four objects were presented. These results indicate that the N1 amplitude is related to the object-only load effect, and the posterior N2 amplitude is a binding-dependent ERP component.

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.

Non-human primate epidural ECoG analysis using explainable deep learning technology.

Objective.With the development in the field of neural networks,explainable AI(XAI), is being studied to ensure that artificial intelligence models can be explained. There are some attempts to apply neural networks to neuroscientific studies to explain neurophysiological information with high machine learning performances. However, most of those studies have simply visualized features extracted from XAI and seem to lack an active neuroscientific interpretation of those features. In this study, we have tried to actively explain the high-dimensional learning features contained in the neurophysiological information extracted from XAI, compared with the previously reported neuroscientific results.Approach. We designed a deep neural network classifier using 3D information (3D DNN) and a 3D class activation map (3D CAM) to visualize high-dimensional classification features. We used those tools to classify monkey electrocorticogram (ECoG) data obtained from the unimanual and bimanual movement experiment.Main results. The 3D DNN showed better classification accuracy than other machine learning techniques, such as 2D DNN. Unexpectedly, the activation weight in the 3D CAM analysis was high in the ipsilateral motor and somatosensory cortex regions, whereas the gamma-band power was activated in the contralateral areas during unimanual movement, which suggests that the brain signal acquired from the motor cortex contains information about both contralateral movement and ipsilateral movement. Moreover, the hand-movement classification system used critical temporal information at movement onset and offset when classifying bimanual movements.Significance.As far as we know, this is the first study to use high-dimensional neurophysiological information (spatial, spectral, and temporal) with the deep learning method, reconstruct those features, and explain how the neural network works. We expect that our methods can be widely applied and used in neuroscience and electrophysiology research from the point of view of the explainability of XAI as well as its performance.

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.

Cocaine-Induced Changes in Tonic Dopamine Concentrations Measured Using Multiple-Cyclic Square Wave Voltammetry in vivo.

For over 40 years, in vivo microdialysis techniques have been at the forefront in measuring the effects of illicit substances on brain tonic extracellular levels of dopamine that underlie many aspects of drug addiction. However, the size of microdialysis probes and sampling rate may limit this technique's ability to provide an accurate assessment of drug effects in microneural environments. A novel electrochemical method known as multiple-cyclic square wave voltammetry (M-CSWV), was recently developed to measure second-to-second changes in tonic dopamine levels at microelectrodes, providing spatiotemporal resolution superior to microdialysis. Here, we utilized M-CSWV and fast-scan cyclic voltammetry (FSCV) to measure changes in tonic or phasic dopamine release in the nucleus accumbens core (NAcc) after acute cocaine administration. Carbon-fiber microelectrodes (CFM) and stimulating electrodes were implanted into the NAcc and medial forebrain bundle (MFB) of urethane anesthetized (1.5 g/kg i.p.) Sprague-Dawley rats, respectively. Using FSCV, depths of each electrode were optimized by determining maximal MFB electrical stimulation-evoked phasic dopamine release. Changes in phasic responses were measured after a single dose of intravenous saline or cocaine hydrochloride (3 mg/kg; n = 4). In a separate group, changes in tonic dopamine levels were measured using M-CSWV after intravenous saline and after cocaine hydrochloride (3 mg/kg; n = 5). Both the phasic and tonic dopamine responses in the NAcc were augmented by the injection of cocaine compared to saline control. The phasic and tonic levels changed by approximately x2.4 and x1.9, respectively. These increases were largely consistent with previous studies using FSCV and microdialysis. However, the minimal disruption/disturbance of neuronal tissue by the CFM may explain why the baseline tonic dopamine values (134 ± 32 nM) measured by M-CSWV were found to be 10-fold higher when compared to conventional microdialysis. In this study, we demonstrated phasic dopamine dynamics in the NAcc with acute cocaine administration. M-CSWV was able to record rapid changes in tonic levels of dopamine, which cannot be achieved with other current voltammetric techniques. Taken together, M-CSWV has the potential to provide an unprecedented level of physiologic insight into dopamine signaling, both in vitro and in vivo, which will significantly enhance our understanding of neurochemical mechanisms underlying psychiatric conditions.

Temporally Resolved Electrochemical Interrogation for Stochastic Collision Dynamics of Electrogenerated Single Polybromide Droplets.

In this article, we present electrochemical interrogation for collision dynamics of electrogenerated individual polybromide ionic liquid (PBIL) droplets through chronoamperometry combined with fast scan cyclic voltammetry (CA-FSCV). In the CA mode of CA-FSCV, a Pt ultramicroelectrode (UME) acts as the electrochemical generator for PBIL droplets by holding the oxidation potential for Br- in a given time, while FSCV is repetitively performed at a certain frequency. In the FSCV mode of CA-FSCV, a Pt UME serves as the probe to electrochemically monitor Br3- reduction for an adsorbed PBIL droplet during collision with a high temporal resolution. Based on the newly introduced CA-FSCV, we can estimate the dynamic changes in the following parameters for a short collision time: the contact radius of a PBIL droplet on a Pt UME, the concentration of Br- in the droplet, and the apparent charge transfer rate constant for electro-reduction of Br3- to Br- in the droplet, koapp. Moreover, a computational calculation using molecular dynamics is presented that can explain the change in koapp as a function of time for Br- electrolysis in a PBIL droplet. Based on the quantitative estimation of the above parameters, we suggest a more advanced mechanism for the stochastic electrochemical collision process of a PBIL droplet. These findings are important for understanding QBr2n+1/QBr half redox reactions in aqueous energy storage systems, such as Zn-Br redox flow batteries and Br-related redox enhanced electrochemical capacitors.

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.

Hypoxia-Associated Changes in Striatal Tonic Dopamine Release: Real-Time in vivo Measurements With a Novel Voltammetry Technique.

INTRODUCTION: Striatal tonic dopamine increases rapidly during global cerebral hypoxia. This phenomenon has previously been studied using microdialysis techniques which have relatively poor spatio-temporal resolution. In this study, we measured changes in tonic dopamine during hypoxia (death) in real time with high spatio-temporal resolution using novel multiple cyclic square wave voltammetry (MCSWV) and conventional fast scan cyclic voltammetry (FSCV) techniques. METHODS: MCSWV and FSCV were used to measure dopamine release at baseline and during hypoxia induced by euthanasia, with and without prior alpha-methyl-p-tyrosine (AMPT) treatment, in urethane anesthetized male Sprague-Dawley rats. RESULTS: Baseline tonic dopamine levels were found to be 274.1 ± 49.4 nM (n = 5; mean ± SEM). Following intracardiac urethane injection, the tonic levels increased to a peak concentration of 1753.8 ± 95.7 nM within 3.6 ± 0.6 min (n = 5), followed by a decline to 50.7 ± 21.5 nM (n = 4) at 20 min. AMPT pre-treatment significantly reduced this dopamine peak to 677.9 ± 185.7 nM (n = 3). FSCV showed a significantly higher (p = 0.0079) peak dopamine release of 6430.4 ± 1805.7 nM (n = 5) during euthanasia-induced cerebral hypoxia. CONCLUSION: MCSWV is a novel tool to study rapid changes in tonic dopamine release in vivo during hypoxia. We found a 6-fold increase in peak dopamine levels during hypoxia which was attenuated with AMPT pre-treatment. These changes are much lower compared to those found with microdialysis. This could be due to improved estimation of baseline tonic dopamine with MCSWV. Higher dopamine response measured with FSCV could be due to an increased oxidation current from electroactive interferents.

Aberrant Tonic Inhibition of Dopaminergic Neuronal Activity Causes Motor Symptoms in Animal Models of Parkinson's Disease.

Current pharmacological treatments for Parkinson's disease (PD) are focused on symptomatic relief, but not on disease modification, based on the strong belief that PD is caused by irreversible dopaminergic neuronal death. Thus, the concept of the presence of dormant dopaminergic neurons and its possibility as the disease-modifying therapeutic target against PD have not been explored. Here we show that optogenetic activation of substantia nigra pars compacta (SNpc) neurons alleviates parkinsonism in acute PD animal models by recovering tyrosine hydroxylase (TH) from the TH-negative dormant dopaminergic neurons, some of which still express DOPA decarboxylase (DDC). The TH loss depends on reduced dopaminergic neuronal firing under aberrant tonic inhibition, which is attributed to excessive astrocytic GABA. Blocking the astrocytic GABA synthesis recapitulates the therapeutic effect of optogenetic activation. Consistently, SNpc of postmortem PD patients shows a significant population of TH-negative/DDC-positive dormant neurons surrounded by numerous GABA-positive astrocytes. We propose that disinhibiting dormant dopaminergic neurons by blocking excessive astrocytic GABA could be an effective therapeutic strategy against PD.