P113 Baseline firing rate of dopaminergic neurons modulates the dopamine response to stimuli
M. Duc Hoang*1, Andrea R. Hamilton2,Timothy J. Lewis1, Stephen L. Cowen3,4and M. Leandro Heien2
1Department of Mathematics, University of California, Davis, Davis, CA, USA 2Department of Chemistry & Biochemistry, University of Arizona, Tucson, AZ, USA 3Department of Psychology, University of Arizona, Tucson, AZ, USA 4Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
*Email: mdhoang@ucdavis.edu
Introduction
Electrical brain stimulation (EBS) targeting dopaminergic (DA) neurons is a valuable tool for investigating dopamine circuits and treating diseases such as Parkinson's disease [1]. However, our understanding of how the temporal structure of stimuli interacts with the firing dynamics of DA neurons to regulate dopamine release remains limited. In this study, we experimentally measure changes in dopamine concentration in response to stimulation of the medial forebrain bundle and develop a data-driven mathematical model to describe this stimulus-evoked dopamine response. Our results demonstrate that the baseline firing rate (BFR) of DA neurons prior to electrical stimulation can strongly modulate the DA response.
Methods In this study, we use fast-scan cyclic voltammetry (FSCV) to measure changes in dopamine (DA) concentration in the nucleus accumbens (NAc) in response to stimulation of the medial forebrain bundle (MFB) in anesthetized rats [2]. We then implement a modification of the Montague et al. model [3] of DA response to electrical stimulation of DA axons in the MFB. The model includes synaptic facilitation and depression, as well as feedback inhibition through D2 autoreceptors (D2AR). We fit model parameters to the FSCV data from multiple stimulation patterns simultaneously. Importantly, we account for the unknown baseline DA levels in our parameter fits. We also validate the model with additional experimental data sets. Results We observe a high degree of variability in the dopamine response in the NAc when the MFB is subjected to identical 20 Hz stimuli across several trials. Specifically, the peak change in DA concentration differs by ~40% between trials (Fig. 1A). Simulations of our model show a similarly large variation in peak DA concentration in response to 20 Hz stimulation when the baseline firing rate (BFR) of simulated DA neurons is varied from 0 to 6 Hz, even though the corresponding variation in baseline DA concentration is below 0.02M (Fig. 1B). We use phase-plane analysis to elucidate the mechanism underlying this phenomenon and describe how the phenomenon is influenced by BFR, dopamine reuptake, and D2AR inhibition. Discussion Our experimental and modeling results suggest that small fluctuations in baseline DA concentrations in the NAc due to changes in BFR of DA neurons, D2AR levels, or DA reuptake rates can significantly alter the DA response to MFB stimulation. Analysis of the model reveals that the underlying mechanism of this phenomenon involves the interplay of the firing rate of DA neurons, DA reuptake dynamics, and synaptic depression. These findings underscore the importance of BFR in modulating dopamine release during EBS, suggesting that BFR may influence the efficacy of EBS in treating disorders such as Parkinson’s disease, depression, and schizophrenia. This insight could inform the optimization of EBS protocols for therapeutic applications.
Figure 1. The baseline firing rate (BFR) leads to substantial variation in DA response to identical stimulation. A: The change in DA in the NAc in response to a 20 Hz periodic stimulation applied to the MFB. 3 trials are shown of the same stimulus. B: DA concentration profiles predicted by the modified Montague et al. model in response to 20 Hz stimulation for 5 different BFRs (0-6 Hz). Acknowledgements Funding for this project is provided by the National Institutes of Health (R01 NS123424-01). A.R.H. was funded by T32 GM008804. References [1] https://doi.org/10.3171/2019.4.JNS181761 [2] https://doi.org/10.1021/acschemneuro.4c00115 [3] https://doi.org/10.1523/JNEUROSCI.4279-03.2004
