Background Signal as an in Situ Predictor of Dopamine Oxidation Potential: Improving Interpretation of Fast-Scan Cyclic Voltammetry Data

Abstract

Background-subtracted fast-scan cyclic voltammetry (FSCV) has emerged as a powerful analytical technique for monitoring sub-second molecular fluctuations in live brain tissue. Despite increasing utilization of FSCV, efforts to improve the accuracy of quantification have been limited due to the complexity of the technique and the dynamic recording environment. It is clear that variable electrode performance renders calibration necessary for accurate quantification; however, the nature of in vivo measurements can make conventional post-calibration difficult, or even impossible. Analyte-specific voltammograms and scaling factors that are critical for quantification can shift or fluctuate in vivo. This is largely due to impedance changes, and the effects of impedance on these measurements have not been characterized. We have previously reported that the background current can be used to predict electrode-specific scaling factors in situ. In this work, we employ model circuits to investigate the impact of impedance on FSCV measurements. Additionally, we take another step toward in situ electrode calibration by using the oxidation potential of quinones on the electrode surface to accurately predict the oxidation potential for dopamine at any point in an electrochemical experiment, as both are dependent on impedance. The model, validated both in adrenal slice and live brain tissue, enables information encoded in the shape of the background voltammogram to determine electrochemical parameters that are critical for accurate quantification. This improves data interpretation and provides a significant next step toward more automated methods for in vivo data analysis.

Fast-Scan Cyclic Voltammetry: Chemical Sensing in the Brain and Beyond

“…To begin to address these issues, a recent study systematically evaluated how shifts in system impedance alter the position of peak redox current generated when using FSCV. 106 This important study demonstrates that the background voltammograms that are normally subtracted and discarded in FSCV contain a wealth of information that can be leveraged to enhance quantification. There is a critical need for a robust and user-friendly method of drift compensation in order to enhance accuracy in both the identification and quantification of chemical species using FSCV, particularly in longitudinal studies.…”

Fast serotonin voltammetry as a versatile tool for mapping dynamic tissue architecture: I. Responses at carbon fibers describe local tissue physiology

“…As such, subtle alterations in the function of these modulators are thought to underlie the phenotypes of many disorders of the brain (Owens and Nemeroff ; Abi‐Dargham et al ; Volkow and Fowler ; Oades ; Muller et al ). To better understand the functional importance of messengers like serotonin in the brain, analytical measurements of neurotransmitters is a thriving and rapidly evolving field (Meunier et al ; Johnson et al ; Shen et al ). To this end, we have thus far focused on pioneering in vivo measurements of evoked and ambient serotonin using fast‐scan cyclic voltammetry (FSCV) and fast‐scan controlled adsorption voltammetry (FSCAV) at carbon fiber microelectrodes (CFMs) (Hashemi et al ; Abdalla et al ).…”

Real-Time Fast Scan Cyclic Voltammetry Detection and Quantification of Exogenously Administered Melatonin in Mice Brain

“…Recent works from the Sombers' group have suggested that the FSCV current can be used as a predictor of electrode fouling and sensitivity to multiple analytes in situ (Roberts et al, 2013;Meunier et al, 2017). Furthermore, EIS has been considered a valuable technique to probe electrode conditions and biofouling (Wilks et al, 2012;Alba et al, 2015), as well as predict electrochemical FSCV performance, using equivalent circuit models of the electrode/solution interface (Roberts et al, 2013;Meunier et al, 2020).…”