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Numerical methods for the analysis of in vivo voltammetry signals
DIFFERENTIAL JULIAN MILLAR Department
RAMP VOLT~MMETRY
- A NEW VOLTA~IETRIC
TECHNIQUE
& GRAHA~M V. WILLIAMS
of Physiology,
The London Hospital
Medical
College,
Turner
Street,
London
El 2AD
Fast Cyclic Voltammetry (FCV) (Armstrong-James & Millar 1984, Millar & Barnett 1988) has now become established as a major tool for the investigation of the detailed time course of dopamine release and re-uptake in the rat striatum (Stamford, Kruk & Millar 1986). However, it has not proved possible to measure basal levels of dopamine or its metabolites with this technique, due to problems in the stability of the large charging current which is an inevitable by-product of FCV. We have now developed a modification of FCV which is called Differential Ramp Voltammetry (DRV) which overcomes many of the problems of FCV and appears to be sufficiently stable and sensitive enough to measure basal levels of electroactive materials in the striatum. The DRV technique uses two FCV scans at an interval of 20 ms, the second scan being offset 200mV negative from the first. The signals obtained in the two scans are then stored and digitally subtracted. The charging currents in the two scans cancel out but the Faradaic signals are preserved, albeit in a differentiated form. Detection of dopamine release in the striatum by electrical stimulation of the median forebrain bundle is possible at levels of considerably less than 10-7 M with this technique. It has also been possible to monitor changes in p02 in the spinal cord correlated with neuronal activity from stimulation of peripheral receptive fields. (Millar & Williams 1989). References Armstrong-James, >I. & Millar, J. (1984) In: Measurement of neurotransmitter Ed., Marsden, C.A. (J. Wiley Interscience, IBRO Handbook series). Millar, J. & Barnett, T.G. (1988) J. Neurosci. Meth. 25 p91. Millar, J. & Williams, G.V. (1989) J. Physiol. (in press). Stamford, J.A. Kruk, Z.L. & Millar, J. (1986) Brain Res. 381 p351-355. This work was supported
by the Parkinson's
Disease
release
in-vivo.
Society.
NUMERICAL METHODS FOR THE ANALYSIS OF IN VIVO VOLTAMMETRY SIGNALS M. MAS, J. L. GONZALEZ-MORA, A. SANCHEZ-BRUNO. Department of Physiology.
University of La Laguna. Tenerife. Spain
Numerical analysis techniques have long been used for the resolution of overlapping peaks in a wide variety of physico-chemical and biological fields. We have applied this methodology to analyze the mixed electrochemical signals recorded from the living brain. This paper shows its aplication for separating the dopamine (DA) and DOPAC components of the "catechol peak" recorded in the rat striatum by Differential Normal Pulse Voltammetry (DNPV) with electrochemically pretreated carbon fiber microelectrodes. The contribution of each of the relevant electroactive species is fitted by a normal probability function whose parameters, for each electrode and substance, can be determined by in vitro calibration. The brain volta~nogram is thus modelled as a sum of normal curves corresponding to the individual oxidizable substances plus a low order polynomial accounting for the baseline. In a first approach the parameters corresponding to each substance were determined independently and kept at fixed values throughout the study . This expression was approximated by linear least squares techniques and the resulting multiple system of normal equations solved by gaussian elimination. In vitro testing and i n vivo studies with drugs having well-known effects on DA release and metabolism were used to assess performance (Gonzalez-Mora et al, Neurosci. Lett. 86: 61 , 1988). We have now refined this numerical methodology by defining the oxidation potential of each of the electroactive species as its distance from an "external reference " peak , such as ascorbic acid. The resulting function is solved by a non-linear iterative Gauss-Newton procedure with stepwise regression. The relative merits of each method will be discussed. Briefly, the non-linear approach, while requiring more computing power, shows better performance in several aspects. Thus, (a) is less influenced by noisy baselines (b) the required difference between the oxidation potential of two substances in order to be efficiently resolved is decreased to about 5 mV,and (c) it makes feasible the resolution of more than two substances within the same peak. The method has been validated by simultaneous microdialysis sampling. These computational procedures can be extended to the analysis signals, such as the indole/uric acid peak of DPV. Likewise, combination with other voltammetry techniques based on differentiation to increase their analytical power.
~tA~
of more complex electrochemical they could also be used in potential ramps and current
RAMP VOLT~MMETRY
- A NEW VOLTA~IETRIC
TECHNIQUE
& GRAHA~M V. WILLIAMS
of Physiology,
The London Hospital
Medical
College,
Turner
Street,
London
El 2AD
Fast Cyclic Voltammetry (FCV) (Armstrong-James & Millar 1984, Millar & Barnett 1988) has now become established as a major tool for the investigation of the detailed time course of dopamine release and re-uptake in the rat striatum (Stamford, Kruk & Millar 1986). However, it has not proved possible to measure basal levels of dopamine or its metabolites with this technique, due to problems in the stability of the large charging current which is an inevitable by-product of FCV. We have now developed a modification of FCV which is called Differential Ramp Voltammetry (DRV) which overcomes many of the problems of FCV and appears to be sufficiently stable and sensitive enough to measure basal levels of electroactive materials in the striatum. The DRV technique uses two FCV scans at an interval of 20 ms, the second scan being offset 200mV negative from the first. The signals obtained in the two scans are then stored and digitally subtracted. The charging currents in the two scans cancel out but the Faradaic signals are preserved, albeit in a differentiated form. Detection of dopamine release in the striatum by electrical stimulation of the median forebrain bundle is possible at levels of considerably less than 10-7 M with this technique. It has also been possible to monitor changes in p02 in the spinal cord correlated with neuronal activity from stimulation of peripheral receptive fields. (Millar & Williams 1989). References Armstrong-James, >I. & Millar, J. (1984) In: Measurement of neurotransmitter Ed., Marsden, C.A. (J. Wiley Interscience, IBRO Handbook series). Millar, J. & Barnett, T.G. (1988) J. Neurosci. Meth. 25 p91. Millar, J. & Williams, G.V. (1989) J. Physiol. (in press). Stamford, J.A. Kruk, Z.L. & Millar, J. (1986) Brain Res. 381 p351-355. This work was supported
by the Parkinson's
Disease
release
in-vivo.
Society.
NUMERICAL METHODS FOR THE ANALYSIS OF IN VIVO VOLTAMMETRY SIGNALS M. MAS, J. L. GONZALEZ-MORA, A. SANCHEZ-BRUNO. Department of Physiology.
University of La Laguna. Tenerife. Spain
Numerical analysis techniques have long been used for the resolution of overlapping peaks in a wide variety of physico-chemical and biological fields. We have applied this methodology to analyze the mixed electrochemical signals recorded from the living brain. This paper shows its aplication for separating the dopamine (DA) and DOPAC components of the "catechol peak" recorded in the rat striatum by Differential Normal Pulse Voltammetry (DNPV) with electrochemically pretreated carbon fiber microelectrodes. The contribution of each of the relevant electroactive species is fitted by a normal probability function whose parameters, for each electrode and substance, can be determined by in vitro calibration. The brain volta~nogram is thus modelled as a sum of normal curves corresponding to the individual oxidizable substances plus a low order polynomial accounting for the baseline. In a first approach the parameters corresponding to each substance were determined independently and kept at fixed values throughout the study . This expression was approximated by linear least squares techniques and the resulting multiple system of normal equations solved by gaussian elimination. In vitro testing and i n vivo studies with drugs having well-known effects on DA release and metabolism were used to assess performance (Gonzalez-Mora et al, Neurosci. Lett. 86: 61 , 1988). We have now refined this numerical methodology by defining the oxidation potential of each of the electroactive species as its distance from an "external reference " peak , such as ascorbic acid. The resulting function is solved by a non-linear iterative Gauss-Newton procedure with stepwise regression. The relative merits of each method will be discussed. Briefly, the non-linear approach, while requiring more computing power, shows better performance in several aspects. Thus, (a) is less influenced by noisy baselines (b) the required difference between the oxidation potential of two substances in order to be efficiently resolved is decreased to about 5 mV,and (c) it makes feasible the resolution of more than two substances within the same peak. The method has been validated by simultaneous microdialysis sampling. These computational procedures can be extended to the analysis signals, such as the indole/uric acid peak of DPV. Likewise, combination with other voltammetry techniques based on differentiation to increase their analytical power.
~tA~
of more complex electrochemical they could also be used in potential ramps and current