Neuroblox: Neurotransmitter Cycling Model

Test potential drug targets in silico and compare simulations with experiments.

Examine how brain levels of excitatory and inhibitory neurotransmitters are influenced by medical conditions, metabolic interventions, and pharmacological treatments.
Test your own hypotheses or check out the examples: 


What is this model for? The main purpose of this model is to simulate neurotransmitter levels in the brain, focusing on glutamate and gamma-aminobutyric acid (GABA). Use this tool to test how different interventions – provided they correspond to one of the modeled reactions – impact Glu/GABA levels.

Mechanism: MRS and traditional neurochemical studies have demonstrated a linear relationship between the synthesis rates of the neurotransmitters glutamate and GABA and neuronal glucose metabolism (Rothman et al. 2019). This relationship is mechanistically grounded in the pseudo malate-aspartate shuttle model (PMAS) (Sibson et al. 1998, Rothman et al. 2024). According to this model, glutamate synthesis from glutamine in neurons is directly coupled to glucose oxidation via the malate-aspartate shuttle. Building upon this connection between neurotransmitter cycling rates and energy substrates, we developed a computational model that simulates the dynamics of neurotransmitter cycling in the brain.

The dynamics of neurotransmitter cycling were simulated using differential equations representing reactions within a connected system of excitatory neurons, inhibitory neurons, and astrocytes. Key reaction pathways involved in neurotransmitter cycling were identified via mass balance analysis in a previous work (Rothman et al. 2024). Using the principle of metabolic control (Fell 1992), we determined which reactions required dynamic representations for accurate simulation, while reactions exerting minimal control over system dynamics were modeled as simple flow-throughs. Reaction equations were parameterized using 13C MRS measurements and enzyme database entries.

The corresponding work will be published as a preprint​​​​​​​ soon!

References: - detailed references coming soon!
● Rothman, Douglas L., et al. "In vivo 13C and 1H‐[13C] MRS studies of neuroenergetics and neurotransmitter cycling, applications to neurological and psychiatric disease and brain cancer." NMR in Biomedicine 32.10 (2019): e4172.
● Sibson, Nicola R., et al. "Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity. Proceedings of the National Academy of Sciences95.1 (1998): 316-321.
● Rothman, Douglas L., Kevin L. Behar, and Gerald A. Dienel. "Mechanistic stoichiometric relationship between the rates of neurotransmission and neuronal glucose oxidation: Reevaluation of and alternatives to the pseudo‐malate‐aspartate shuttle model." Journal of Neurochemistry168.5 (2024): 555-591.
● Fell, David A. "Metabolic control analysis: a survey of its theoretical and experimental development." Biochemical Journal 286.Pt 2 (1992): 313.


● The Model tab displays the reactions and their reactants, with the equations for the reaction rates shown below.
● Adjust reaction parameters to test your hypotheses by selecting parameters from the dropdown menu in the Parameters tab and entering their values. You can simultaneously modify as many parameters as you wish.
● You can simulate two conditions ( Condition 1 and Condition 2) simultaneously to facilitate easy comparison between a test and a reference condition. You can modify the parameters of either condition by selecting it using the toggle switch.
● Under the Initial Conditions tab, you can modify the starting concentrations of your simulations.
● The model will automatically simulate using the updated values.
● To restore default parameters, click the Reset Settings button.
● To display all adjustable parameters, click the Full Model button.
● Define your own simulation length. Use this option to ensure the simulation runs long enough to reach a new steady state.
● There are two options for displaying the results. Dynamics shows the time series for the full simulation, while End-points displays only the final concentrations as bar plots.
● Select the variables you want to plot, and the graphs will update accordingly.
● Enable Percentage Change to visualize relative changes compared to initial values instead of absolute concentrations.
● To download a plot, hover over it with your cursor to access the Download plot as a png option.
● To download the simulation results as an excel file, click the Dowload Results button within the Dynamics tab.


GLN: glutamine
GLU: glutamate
GABA: gamma-aminobutyric acid
LAC: lactate
BHB: beta-hydroxybutyrate
Vmax: maximum reaction rate
Km: Michaelis-Menten constant
CMRglc: cerebral metabolic rate of glucose
MAS: pseudo malate aspartate shuttle
PAG: phosphate-activated glutaminase
GS: glutamine synthetase
GT: GABA transaminase
GAD65/67: glutamate decarboxylase 65/67_e: excitatory neuronal
​​​​​​​
_e: excitatory neuronal
​​​​​​​ _i: inhibitory neuronal
_a: astrocytic
_s: vesicula
_cyc: cycling
_e0, _i0, _a0: baseline level/rate
_pmas: GLU-specific fraction of MAS
_gtmas: GABA-specific fraction of MAS

Default parameter set represents a healthy young adult's brain.

Default initial conditions correspond to steady-state concentrations given the default parameter set. 

Use the toggle below to switch between modifying conditions 1 and 2:

Final Concentrations:

This model is part of Neuroblox. Visit at www.neuroblox.org. Contact: botond.antal(at)stonybrook.edu