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Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0
Published on: June 5, 2017
Neurobiological model of stimulated dopamine neurotransmission to interpret fast-scan cyclic voltammetry data
Rashed Harun1, Christine M Grassi2, Miranda J Munoz3
1Center for Neuroscience, University of Pittsburgh, 453 Fifth and Ruskin Avenue, Langley Hall, Suite A210, Pittsburgh, PA 15260, USA; Department of Physical Medicine & Rehabilitation, University of Pittsburgh, School of Medicine, 3471 Fifth Avenue, Kaufmann Building, Suite 202, Pittsburgh, PA 15213, USA; Safar Center for Resuscitation Research, University of Pittsburgh, 3434 Fifth Avenue Hill Building, Pittsburgh, PA 15213, USA.
Abstract:
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.
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