1
|
Kandimalla M, Lim S, Thakkar J, Dewan S, Kang D, In MH, Jo HJ, Jang DP, Nedelska Z, Lapid MI, Shu Y, Cheon-Pyung, Cogswell PM, Lowe VJ, Lee J, Min HK. Cardiorespiratory dynamics in the brain: Review on the significance of cardiovascular and respiratory correlates in functional MRI signal. Neuroimage 2025; 306:121000. [PMID: 39753161 DOI: 10.1016/j.neuroimage.2024.121000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 12/17/2024] [Accepted: 12/31/2024] [Indexed: 01/11/2025] Open
Abstract
Cardiorespiratory signals have long been treated as "noise" in functional magnetic resonance imaging (fMRI) research, with the goal of minimizing their impact to isolate neural activity. However, there is a growing recognition that these signals, once seen as confounding variables, provide valuable insights into brain function and overall health. This shift reflects the dynamic interaction between the cardiovascular, respiratory, and neural systems, which together support brain activity. In this review, we explore the role of cardiorespiratory dynamics-such as heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and changes in blood flow, oxygenation, and carbon dioxide levels-embedded within fMRI signals. These physiological signals reflect critical aspects of neurovascular coupling and are influenced by factors such as physiological stress, breathing patterns, and age-related changes. We also discuss the complexities of distinguishing these signals from neuronal activity in fMRI data, given their significant contribution to signal variability and interactions with cerebrospinal fluid (CSF). Recognizing the influence of these cardiorespiratory dynamics is crucial for improving the interpretation of fMRI data, shedding light on heart-brain and respiratory-brain connections, and enhancing our understanding of circulation, oxygen delivery, and waste elimination within the brain.
Collapse
|
2
|
Kim HG, Song S, Cho BH, Jang DP. Deep learning-based stress detection for daily life use using single-channel EEG and GSR in a virtual reality interview paradigm. PLoS One 2024; 19:e0305864. [PMID: 38959272 PMCID: PMC11221693 DOI: 10.1371/journal.pone.0305864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 06/04/2024] [Indexed: 07/05/2024] Open
Abstract
This research aims to establish a practical stress detection framework by integrating physiological indicators and deep learning techniques. Utilizing a virtual reality (VR) interview paradigm mirroring real-world scenarios, our focus is on classifying stress states through accessible single-channel electroencephalogram (EEG) and galvanic skin response (GSR) data. Thirty participants underwent stress-inducing VR interviews, with biosignals recorded for deep learning models. Five convolutional neural network (CNN) architectures and one Vision Transformer model, including a multiple-column structure combining EEG and GSR features, showed heightened predictive capabilities and an enhanced area under the receiver operating characteristic curve (AUROC) in stress prediction compared to single-column models. Our experimental protocol effectively elicited stress responses, observed through fluctuations in stress visual analogue scale (VAS), EEG, and GSR metrics. In the single-column architecture, ResNet-152 excelled with a GSR AUROC of 0.944 (±0.027), while the Vision Transformer performed well in EEG, achieving peak AUROC values of 0.886 (±0.069) respectively. Notably, the multiple-column structure, based on ResNet-50, achieved the highest AUROC value of 0.954 (±0.018) in stress classification. Through VR-based simulated interviews, our study induced social stress responses, leading to significant modifications in GSR and EEG measurements. Deep learning models precisely classified stress levels, with the multiple-column strategy demonstrating superiority. Additionally, discreetly placing single-channel EEG measurements behind the ear enhances the convenience and accuracy of stress detection in everyday situations.
Collapse
|
3
|
Jang J, Cho HU, Hwang S, Kwak Y, Kwon H, Heien ML, Bennet KE, Oh Y, Shin H, Lee KH, Jang DP. Understanding the different effects of fouling mechanisms on working and reference electrodes in fast-scan cyclic voltammetry for neurotransmitter detection. Analyst 2024; 149:3008-3016. [PMID: 38606455 PMCID: PMC11648937 DOI: 10.1039/d3an02205f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
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.
Collapse
|
4
|
Lim S, Kim C, Cho BH, Choi SH, Lee H, Jang DP. Investigation of daily patterns for smartphone keystroke dynamics based on loneliness and social isolation. Biomed Eng Lett 2024; 14:235-243. [PMID: 38374905 PMCID: PMC10874350 DOI: 10.1007/s13534-023-00337-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 10/16/2023] [Accepted: 11/06/2023] [Indexed: 02/21/2024] Open
Abstract
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.
Collapse
|
5
|
Rojas Cabrera JM, Oesterle TS, Rusheen AE, Goyal A, Scheitler KM, Mandybur I, Blaha CD, Bennet KE, Heien ML, Jang DP, Lee KH, Oh Y, Shin H. Techniques for Measurement of Serotonin: Implications in Neuropsychiatric Disorders and Advances in Absolute Value Recording Methods. ACS Chem Neurosci 2023; 14:4264-4273. [PMID: 38019166 PMCID: PMC10739614 DOI: 10.1021/acschemneuro.3c00618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/10/2023] [Accepted: 11/14/2023] [Indexed: 11/30/2023] Open
Abstract
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).
Collapse
|
6
|
Kwak Y, Lim S, Cho HU, Sim J, Lee S, Jeong S, Jeon SJ, Im CH, Jang DP. Effect of temporal interference electrical stimulation on phasic dopamine release in the striatum. Brain Stimul 2023; 16:1377-1383. [PMID: 37716638 DOI: 10.1016/j.brs.2023.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 09/10/2023] [Accepted: 09/13/2023] [Indexed: 09/18/2023] Open
Abstract
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.
Collapse
|
7
|
Goyal A, Hwang S, Rusheen AE, Blaha CD, Bennet KE, Lee KH, Jang DP, Oh Y, Shin H. Software for near-real-time voltammetric tracking of tonic neurotransmitter levels in vivo. Front Neurosci 2022; 16:899436. [PMID: 36213749 PMCID: PMC9537688 DOI: 10.3389/fnins.2022.899436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 08/30/2022] [Indexed: 11/26/2022] Open
Abstract
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.
Collapse
|
8
|
Lee S, Park J, Choi DS, Lim S, Kwak Y, Jang DP, Kim DH, Ji HB, Choy YB, Im CH. Feasibility of epidural temporal interference stimulation for minimally invasive electrical deep brain stimulation: simulation and phantom experimental studies. J Neural Eng 2022; 19. [PMID: 36066021 DOI: 10.1088/1741-2552/ac8503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 07/28/2022] [Indexed: 11/11/2022]
Abstract
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.
Collapse
|
9
|
Choi H, Shin H, Cho HU, Blaha CD, Heien ML, Oh Y, Lee KH, Jang DP. Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study. ACS Chem Neurosci 2022; 13:2288-2297. [PMID: 35876751 DOI: 10.1021/acschemneuro.2c00069] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
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.
Collapse
|
10
|
Min Park Y, Park J, Young Kim I, Koo Kang J, Pyo Jang D. Interhemispheric Theta Coherence in the Hippocampus for Successful Object-Location Memory in Human Intracranial Encephalography. Neurosci Lett 2022; 786:136769. [DOI: 10.1016/j.neulet.2022.136769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/23/2022] [Accepted: 06/30/2022] [Indexed: 10/17/2022]
|
11
|
Song S, Park J, Park YM, Kim IY, Jang DP. The influence of object-location binding mental load effects on the visual N1 and N2 Event-related Potentials. BMC Res Notes 2022; 15:217. [PMID: 35739605 PMCID: PMC9219235 DOI: 10.1186/s13104-022-06086-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 05/24/2022] [Indexed: 11/25/2022] Open
Abstract
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.
Collapse
|
12
|
Yang SM, Shim JH, Cho HU, Jang TM, Ko GJ, Shim J, Kim TH, Zhu J, Park S, Kim YS, Joung SY, Choe JC, Shin JW, Lee JH, Kang YM, Cheng H, Jung Y, Lee CH, Jang DP, Hwang SW. Hetero-Integration of Silicon Nanomembranes with 2D Materials for Bioresorbable, Wireless Neurochemical System. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2108203. [PMID: 35073597 DOI: 10.1002/adma.202108203] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/14/2022] [Indexed: 06/14/2023]
Abstract
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.
Collapse
|
13
|
Shin H, Goyal A, Barnett JH, Rusheen AE, Yuen J, Jha R, Hwang SM, Kang Y, Park C, Cho HU, Blaha CD, Bennet KE, Oh Y, Heien ML, Jang DP, Lee KH. Tonic Serotonin Measurements In Vivo Using N-Shaped Multiple Cyclic Square Wave Voltammetry. Anal Chem 2021; 93:16987-16994. [PMID: 34855368 DOI: 10.1021/acs.analchem.1c02131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
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.
Collapse
|
14
|
Kang Y, Goyal A, Hwang S, Park C, Cho HU, Shin H, Park J, Bennet KE, Lee KH, Oh Y, Jang DP. Enhanced Dopamine Sensitivity Using Steered Fast-Scan Cyclic Voltammetry. ACS OMEGA 2021; 6:33599-33606. [PMID: 34926907 PMCID: PMC8675016 DOI: 10.1021/acsomega.1c04475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 11/16/2021] [Indexed: 05/09/2023]
Abstract
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.
Collapse
|
15
|
Park C, Hwang S, Kang Y, Sim J, Cho HU, Oh Y, Shin H, Kim DH, Blaha CD, Bennet KE, Lee KH, Jang DP. Feasibility of Applying Fourier Transform Electrochemical Impedance Spectroscopy in Fast Cyclic Square Wave Voltammetry for the In Vivo Measurement of Neurotransmitters. Anal Chem 2021; 93:15861-15869. [PMID: 34839667 DOI: 10.1021/acs.analchem.1c02308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
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.
Collapse
|
16
|
Choi H, Lim S, Min K, Ahn KH, Lee KM, Jang DP. Non-human primate epidural ECoG analysis using explainable deep learning technology. J Neural Eng 2021; 18. [PMID: 34695809 DOI: 10.1088/1741-2552/ac3314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 10/25/2021] [Indexed: 11/12/2022]
Abstract
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.
Collapse
|
17
|
Choi Y, Park C, Kang Y, Muya JT, Jang DP, Chang J. Temporally Resolved Electrochemical Interrogation for Stochastic Collision Dynamics of Electrogenerated Single Polybromide Droplets. Anal Chem 2021; 93:8336-8344. [PMID: 34075746 DOI: 10.1021/acs.analchem.1c01366] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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.
Collapse
|
18
|
Kim J, Barath AS, Rusheen AE, Rojas Cabrera JM, Price JB, Shin H, Goyal A, Yuen JW, Jondal DE, Blaha CD, Lee KH, Jang DP, Oh Y. Automatic and Reliable Quantification of Tonic Dopamine Concentrations In Vivo Using a Novel Probabilistic Inference Method. ACS OMEGA 2021; 6:6607-6613. [PMID: 33748573 PMCID: PMC7970470 DOI: 10.1021/acsomega.0c05217] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/19/2021] [Indexed: 05/04/2023]
Abstract
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.
Collapse
|
19
|
Barath AS, Rusheen AE, Rojas Cabrera JM, Price JB, Owen RL, Shin H, Jang DP, Blaha CD, Lee KH, Oh Y. Hypoxia-Associated Changes in Striatal Tonic Dopamine Release: Real-Time in vivo Measurements With a Novel Voltammetry Technique. Front Neurosci 2020; 14:869. [PMID: 32973432 PMCID: PMC7461928 DOI: 10.3389/fnins.2020.00869] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 07/27/2020] [Indexed: 11/13/2022] Open
Abstract
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.
Collapse
|
20
|
Kim E, Kim CK, Kim HS, Jang DP, Kim IY, Hwang J. Histogram analysis from stretched exponential model on diffusion-weighted imaging: evaluation of clinically significant prostate cancer. Br J Radiol 2020; 93:20190757. [PMID: 31899654 DOI: 10.1259/bjr.20190757] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE To evaluate the usefulness of histogram analysis of stretched exponential model (SEM) on diffusion-weighted imaging in evaluating clinically significant prostate cancer (CSC). METHODS A total of 85 patients with prostate cancer underwent 3 T multiparametric MRI, followed by radical prostatectomy. Histogram parameters of the tumor from the SEM [distributed diffusion coefficient (DDC) and α] and the monoexponential model [MEM; apparent diffusion coefficient (ADC)] were evaluated. The associations between parameters and Gleason score or Prostate Imaging Reporting and Data System v. 2 were evaluated. The area under the receiver operating characteristics curve was calculated to evaluate diagnostic performance of parameters in predicting CSC. RESULTS The values of histogram parameters of DDC and ADC were significantly lower in patients with CSC than in patients without CSC (p < 0.05), except for skewness and kurtosis. The value of the 25th percentile of α was significantly lower in patients with CSC than in patients without CSC (p = 0.014). Histogram parameters of ADC and DDC had significant weak to moderate negative associations with Gleason score or Prostate Imaging Reporting and Data System v. 2 (p < 0.001), except for skewness and kurtosis. For predicting CSC, the area under the curves of mean ADC (0.856), 50th percentile DDC (0.852), and 25th percentile α (0.707) yielded the highest values compared to other histogram parameters from each group. CONCLUSION Histogram analysis of the SEM on diffusion-weighted imaging may be a useful quantitative tool for evaluating CSC. However, the SEM did not outperform the MEM. ADVANCES IN KNOWLEDGE Histogram parameters of SEM may be useful for evaluating CSC.
Collapse
|
21
|
Shin H, Oh Y, Park C, Kang Y, Cho HU, Blaha CD, Bennet KE, Heien ML, Kim IY, Lee KH, Jang DP. Sensitive and Selective Measurement of Serotonin in Vivo Using Fast Cyclic Square-Wave Voltammetry. Anal Chem 2019; 92:774-781. [PMID: 31789495 DOI: 10.1021/acs.analchem.9b03164] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
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.
Collapse
|
22
|
Shin H, Lee SY, Cho HU, Oh Y, Kim IY, Lee KH, Jang DP, Min HK. Fornix Stimulation Induces Metabolic Activity and Dopaminergic Response in the Nucleus Accumbens. Front Neurosci 2019; 13:1109. [PMID: 31708723 PMCID: PMC6821687 DOI: 10.3389/fnins.2019.01109] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Accepted: 10/01/2019] [Indexed: 12/27/2022] Open
Abstract
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.
Collapse
|
23
|
Park YM, Park J, Baek JH, Kim SI, Kim IY, Kang JK, Jang DP. Differences in theta coherence between spatial and nonspatial attention using intracranial electroencephalographic signals in humans. Hum Brain Mapp 2019; 40:2336-2346. [PMID: 30648326 DOI: 10.1002/hbm.24526] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2018] [Revised: 12/23/2018] [Accepted: 01/07/2019] [Indexed: 11/09/2022] Open
Abstract
A number of previous studies revealed the importance of the frontoparietal network for attention and preparatory top-down control. Here, we investigated the theta (7-9 Hz) coherence of the right frontoparietal networks to explore the differences in connectivity changes for the right frontoparietal regions during spatial attention (i.e., attention to a specific location rather than a specific feature) and nonspatial attention (i.e., attention to a specific feature rather than a specific location) tasks. The theta coherence in both tasks was primarily maintained at a preparatory state, decreases after stimulus onset, and recovers to the level of the preparatory state after the response time. However, the theta coherence of the frontoparietal network during spatial attention was immediately maintained after cue-onset, whereas for the case of nonspatial attention, it was immediately decreased after cue-onset. In addition, the connectivity of the right frontoparietal network, including the middle frontal gyrus and superior parietal lobe, were significantly higher for spatial attention rather than for nonspatial attention, suggesting that the dorsal parts of right frontoparietal network are more engaged in spatial-specific attention from the preparatory state. These findings also suggest that these two attention systems involve the use of different regional connectivity patterns, not only in the cognitive state, but in the preparatory state as well.
Collapse
|
24
|
DeWaele M, Oh Y, Park C, Kang YM, Shin H, Blaha CD, Bennet KE, Kim IY, Lee KH, Jang DP. A baseline drift detrending technique for fast scan cyclic voltammetry. Analyst 2018; 142:4317-4321. [PMID: 29063091 DOI: 10.1039/c7an01465a] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Fast scan cyclic voltammetry (FSCV) has been commonly used to measure extracellular neurotransmitter concentrations in the brain. Due to the unstable nature of the background currents inherent in FSCV measurements, analysis of FSCV data is limited to very short amounts of time using traditional background subtraction. In this paper, we propose the use of a zero-phase high pass filter (HPF) as the means to remove the background drift. Instead of the traditional method of low pass filtering across voltammograms to increase the signal to noise ratio, a HPF with a low cutoff frequency was applied to the temporal dataset at each voltage point to remove the background drift. As a result, the HPF utilizing cutoff frequencies between 0.001 Hz and 0.01 Hz could be effectively used to a set of FSCV data for removing the drifting patterns while preserving the temporal kinetics of the phasic dopamine response recorded in vivo. In addition, compared to a drift removal method using principal component analysis, this was found to be significantly more effective in reducing the drift (unpaired t-test p < 0.0001, t = 10.88) when applied to data collected from Tris buffer over 24 hours although a drift removal method using principal component analysis also showed the effective background drift reduction. The HPF was also applied to 5 hours of FSCV in vivo data. Electrically evoked dopamine peaks, observed in the nucleus accumbens, were clearly visible even without background subtraction. This technique provides a new, simple, and yet robust, approach to analyse FSCV data with an unstable background.
Collapse
|
25
|
Oh Y, Heien ML, Park C, Kang YM, Kim J, Boschen SL, Shin H, Cho HU, Blaha CD, Bennet KE, Lee HK, Jung SJ, Kim IY, Lee KH, Jang DP. Tracking tonic dopamine levels in vivo using multiple cyclic square wave voltammetry. Biosens Bioelectron 2018; 121:174-182. [PMID: 30218925 PMCID: PMC6775780 DOI: 10.1016/j.bios.2018.08.034] [Citation(s) in RCA: 65] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 08/13/2018] [Accepted: 08/16/2018] [Indexed: 01/02/2023]
Abstract
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 ± 18 nM (n = 7 rats, ± 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.
Collapse
|