Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0.

Central dopaminergic (DAergic) pathways have an important role in a wide range of functions, such as attention, motivation, and movement. Dopamine (DA) is implicated in diseases and disorders including attention deficit hyperactivity disorder, Parkinson's disease, and traumatic brain injury. Thus, DA neurotransmission and the methods to study it are of intense scientific interest. In vivo fast-scan cyclic voltammetry (FSCV) is a method that allows for selectively monitoring DA concentration changes with fine temporal and spatial resolution. This technique is commonly used in conjunction with electrical stimulations of ascending DAergic pathways to control the impulse flow of dopamine neurotransmission. Although the stimulated DA neurotransmission paradigm can produce robust DA responses with clear morphologies, making them amenable for kinetic analysis, there is still much debate on how to interpret the responses in terms of their DA release and clearance components. To address this concern, a quantitative neurobiological (QN) framework of stimulated DA neurotransmission was recently developed to realistically model the dynamics of DA release and reuptake over the course of a stimulated DA response. The foundations of this model are based on experimental data from stimulated DA neurotransmission and on principles of neurotransmission adopted from various lines of research. The QN model implements 12 parameters related to stimulated DA release and reuptake dynamics to model DA responses. This work describes how to simulate DA responses using QNsim1.0 and also details principles that have been implemented to systematically discern alterations in the stimulated dopamine release and reuptake dynamics.

Fast-scan cyclic voltammetry demonstrates that L-DOPA produces dose-dependent, regionally selective bimodal effects on striatal dopamine kinetics in vivo.

Parkinson's disease (PD) is a debilitating condition that is caused by a relatively specific degeneration of dopaminergic (DAergic) neurons of the substantia nigra pars compacta. L-DOPA was introduced as a viable treatment option for PD over 40 years ago and still remains the most common and effective therapy for PD. Though the effects of L-DOPA to augment striatal DA production are well known, little is actually known about how L-DOPA alters the kinetics of DA neurotransmission that contribute to its beneficial and adverse effects. In this study, we examined the effects of L-DOPA administration (50 mg/kg carbidopa + 0, 100, and 250 mg/kg L-DOPA) on regional electrically stimulated DA response kinetics using fast-scan cyclic voltammetry in anesthetized rats. We demonstrate that L-DOPA enhances DA release in both the dorsal striatum (D-STR) and nucleus accumbens (NAc), but surprisingly causes a delayed inhibition of release in the D-STR. In both regions, L-DOPA progressively attenuated reuptake kinetics, predominantly through a decrease in Vmax . These findings have important implications on understanding the pharmacodynamics of L-DOPA, which may be informative for understanding its therapeutic effects and also common side effects like L-DOPA-induced dyskinesias (LID). L-DOPA is commonly used to treat Parkinsonian symptoms, but little is known about how it affects presynaptic DA neurotransmission. Using in vivo fast-scan cyclic voltammetry, we show L-DOPA inhibits DA reuptake in a region-specific and dose-dependent manner, and L-DOPA has paradoxical effects on release. These findings may be important when considering mechanisms for L-DOPA's therapeutic benefits and adverse side-effects.

Neurobiological model of stimulated dopamine neurotransmission to interpret fast-scan cyclic voltammetry data.

Fast-scan cyclic voltammetry (FSCV) is an electrochemical method that can assess real-time in vivo dopamine (DA) concentration changes to study the kinetics of DA neurotransmission. Electrical stimulation of dopaminergic (DAergic) pathways can elicit FSCV DA responses that largely reflect a balance of DA release and reuptake. Interpretation of these evoked DA responses requires a framework to discern the contribution of DA release and reuptake. The current, widely implemented interpretive framework for doing so is the Michaelis-Menten (M-M) model, which is grounded on two assumptions- (1) DA release rate is constant during stimulation, and (2) DA reuptake occurs through dopamine transporters (DAT) in a manner consistent with M-M enzyme kinetics. Though the M-M model can simulate evoked DA responses that rise convexly, response types that predominate in the ventral striatum, the M-M model cannot simulate dorsal striatal responses that rise concavely. Based on current neurotransmission principles and experimental FSCV data, we developed a novel, quantitative, neurobiological framework to interpret DA responses that assumes DA release decreases exponentially during stimulation and continues post-stimulation at a diminishing rate. Our model also incorporates dynamic M-M kinetics to describe DA reuptake as a process of decreasing reuptake efficiency. We demonstrate that this quantitative, neurobiological model is an extension of the traditional M-M model that can simulate heterogeneous regional DA responses following manipulation of stimulation duration, frequency, and DA pharmacology. The proposed model can advance our interpretive framework for future in vivo FSCV studies examining regional DA kinetics and their alteration by disease and DA pharmacology.