P224 Four-compartment model of dopamine dynamics at the nigrostriatal synaptic site

Alex G. O'Hare*1, 2, Catalina Vich1, 2, Jonathan E. Rubin3, 4, Timothy Verstynen3, 5

1Dept. de Matemátiques i Informática, Universitat de les Illes Balears, Palma, Illes Balears, Spain
2Institute of Applied Computing and Community Code, Palma, Illes Balears, Spain
3Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States of America
4Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
5Department of Psychology & Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America

*Email: alex-gwyn.o-hare@uib.cat
Introduction

The traditional model of dopamine (DA) dynamics [1] posits that the level of extrasynaptic (tonic) DA modulates the effect of phasic burst firing which occurs in the event of a reward [2]. It is supposed that tonic DA, although present in low concentrations, has the capacity to activate DA synthesis and release modulating autoreceptors of the pre-synaptic DA neuron. Taking into account this traditional model as well as recent findings which demonstrate the capacity of tonic DA to also affect both D1 and D2 postsynaptic receptors [3], we develop a biologically realistic, yet computationally efficient 4-compartment model (see Fig.1) of DA action at the synaptic site, to elucidate the impact of DA dynamics on receptor occupancy and tonic DA levels.
Methods
DA is synthesised in the terminal of the presynaptic substantia nigra pars compacta (SNc) neuron, DAter, and released into the synaptic cleft, DAsyn at a rate dependent on DAter and the membrane voltage of the SNc neuron. From the synaptic cleft, DA is occupied by D1 or D2 receptors, the quantity of which is occupied we consider as the third compartment, DAocc. DAocc impacts the excitability and plasticity of postsynaptic spiny projection neuron (SPN) which receives inputs from a cortical neuron. DA is removed from DAsyn by reuptake into DAter and via diffusion to the extrasynaptic space, DAext. DA in DAsyn affects release via autoreceptors. DA in DAext affects synthesis autoreceptors and is removed from the system via diffusion.
Results
Preliminary symbolic analysis of the system in a supposed quasi-steady-state determined by setting the rate of synthesis equal to the rate of removal from DAext and letting the firing rate of the presynaptic neuron be constant, reveals a stable system according to the Routh-Hurwitz criterion, with either damped or no oscillations. Building on prior work [4] in which we developed an STDP model for cortico-striatal plasticity, we incorporate a presynaptic SNc neuron to analyse the effect of variations in parameters (limited within ranges of empirical data and using latin hypercube sampling) of the DA model on plasticity.
Discussion
Our four-compartment model of nigrostriatal dopamine dynamics bridges the gap between purely phenomenoligcal models which lack biological realism and more complex models which take into account a high degree of biological detail and are computationally expensive, thereby providing a solution for incorporating the effect of DA on corticostriatal plasticity in large scale spiking neural networks. In particular, our model may be of utility for simulations of dopaminergic reinforcement learning, such as in n-choice tasks, and simulations of DA-related pathologies which require explicit consideration of postsynaptic receptor occupation and extrasynaptic DA levels.



Figure 1. 4-compartment model of dopamine (DA) at the synaptic site. DAter: presynaptic terminal, DAsyn: synaptic cleft, DAocc: occupied postsynaptic receptors, DAext: extrasynaptic space. Pointed arrows indicate the transfer of DA from one compartment to another, with constants ki indicating the rate of transfer. Dotted arrows denote the modulatory effect of synthesis and release modulating autoreceptors.
Acknowledgements.
References
1. https://doi.org/10.1016/0376-8716(94)01066-t
2. https://doi.org/10.1126/science.275.5306.1593
3. https://doi.org/10.1523/jneurosci.1951-19.2019
4. https://doi.org/10.1016/j.cnsns.2019.105048