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.
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.
Fast-scan cyclic voltammetry along with its background subtraction method has been widely used for detecting neurotransmitters in the brain. The most common application of FSCV is measuring phasic changes of dopamine (DA) in the brain evoked by an external stimulus. The background subtraction method has greatly improved FSCV’s application to the neuroscience field. However, tonic dopamine concentration, which is as vital as phasic change, cannot be measured even though the background is subtracted. In this study, we developed a tailoring FSCV technique which can manipulate the background current by modifying a waveform’s voltage points. By using the technique, the last background current generated by multiple waveform application is tailored to the front background current. As a result, background current is cancelled out by subtracting the tailored (last) voltammagram from the front voltammagram. Therefore, only the DA oxidation/reduction pattern still remained between front and last voltammogram, so that, tailoring FSCV can detect tonic DA concentration without background subtraction method. The tailoring technique is evaluated by comparing it with commercialized enzyme-linked immunosorbent assay (ELISA) kits. By measuring endogenously released DA from DAergic cells, the tailoring method showed a significant correlation with ELISA results.
Fast scan cyclic voltammetry (FSCV) is a technique that measures the concentrations of neurotransmitters in vivo or in vitro. Conventional FSCV uses a triangle waveform, which starts from -0.4V, sweeps to +1.3V and returns to -0.4V. It makes not only a large background signal, but also a small signal from oxidation and reduction of a neurotransmitter. These large background signals can be removed by a background subtraction technique which extracts only the oxidation and reduction signals. After that, analyze the subtracted signal to estimate the concentration of the neurotransmitter. It has a limit in detecting low-level concentration of neurotransmitter because a large quantization error comes from the wide range of analog-to-digital convertor (ADC). To measure low-level concentrations of a neurotransmitter, the range of the ADC was decreased to lower the quantization error. Even though using a narrow range of ADC has a low quantization error, it cannot measure the whole voltammagram. For this reason, the waveform is changed for the background signal to become flat, where the oxidation signal arises, and move these flat sections to ADC-range using hardware subtraction. Eventually, we can measure the oxidation signal in a narrow range with low quantization error.
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