Mathematical resolution of mixed in vivo voltammetry signals: Models, equipment, assessment by simultaneous microdialysis sampling

Abstract

A microcomputer-assisted curve-fitting procedure was developed for the quantitative estimation of the components of the mixed “catechol peak” recorded with differential normal pulse voltammetry (DNPV) at electrochemically pretreated carbon fiber microelectrodes in the living brain. The contribution of each of the relevant electroactive species is fitted by a normal probability function, the parameters of which are previously determined in vitro for each electrode and substance. The voltammogram is thus modeled as a mixture of normal curves corresponding to the individual oxidizable substances plus a low order polynomial approximating the baseline. In a former approach the function was solved by linear least squares techniques. As a further improvement, we now propose a non-linear model of the voltammogram and a Gauss-Newton iterative algorithm with stepwise regression for parameter estimation. This report shows the application of the method for the resolution of the dopamine (DA) and dihydroxyphenylacetic acid (DOPAC) components of the DNPV signal recorded from the striatum of freely moving animals in response to amphetamine and pargyline. The method was validated by the chemical assay of contralateral microdialysates collected simultaneously. The changes detected by both methodologies were closely parallel, with highly significant correlation coefficients (0.87 and 0.99 for DA and DOPAC, respectively, P < 0.001). This study further illustrates that the in vivo voltammetry methodology can be improved substantially by incorporating a suitable mathematical treatment of the electrochemical signals.