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.

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

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 twodimensional 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.

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 signal to noise ratio, a HPF with a low cutoff frequency was applied to temporal data set at each voltage point to remove background drift. As a result, the HPF utilizing cutoff frequencies between 0.001 Hz to 0.01 Hz could be effectively used to a set of FSCV data for removing 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 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 unstable background.

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.

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

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.

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