STOCHASTIC SYNAPSE

Introducing STOCHASTIC SYNAPSE, a computational platform for exploring neurotransmitter diffusion and receptor activation in the crowded, probabilistic environment of the brain extracellular space.

STOCHASTIC SYNAPSE simulates the release, Brownian diffusion, and uptake of neurotransmitter molecules among realistic nanoscopic obstacles, and computes the resulting activation of synaptic and extrasynaptic receptors. It captures how the stochastic geometry of the neuropil and glutamate–transporter interactions shape signalling at and beyond the synaptic cleft, on the scale from nanometers to microns.

Key Features

• Monte Carlo diffusion: tracks thousands of individual neurotransmitter molecules undergoing Brownian motion in a three-dimensional extracellular space.
• Realistic stochastic environment: neuronal and astroglial processes are represented as overlapping nanoscopic obstacles, with a tunable extracellular volume fraction and astroglial coverage.
• Stochastic transporter kinetics: glutamate binding, unbinding, and uptake by astroglial transporters are modelled probabilistically, including glutamate–transporter unbinding.
• Receptor activation maps: computes spatial and temporal maps of neurotransmitter concentration and of AMPA and NMDA receptor activation as a function of distance and time.
• Interactive exploration: a graphical interface lets you set parameters, run the diffusion, and view concentration and receptor-activation figures in one window.

Background

STOCHASTIC SYNAPSE implements the modelling framework developed in a series of studies by Savtchenko, Rusakov and colleagues (see Publications below). Together these works show how the stochastically shaped tissue geometry, glutamate buffering and uptake by astroglial transporters, and glutamate–transporter unbinding jointly shape the escape of neurotransmitter and the activation of synaptic and distant extrasynaptic receptors.

Publications

The STOCHASTIC SYNAPSE framework is based on the following studies:

• Savtchenko LP, Rusakov DA. Glutamate–transporter unbinding in probabilistic synaptic environment facilitates activation of distant NMDA receptors. Cells 12 (12), 1610 (2023).
• Savtchenko LP, Rusakov DA. Increased extrasynaptic glutamate escape in stochastically shaped probabilistic synaptic environment. Biomedicines 10 (10), 2406 (2022).
• Savtchenko LP, Zheng K, Rusakov DA. Buffering by transporters can spare geometric hindrance in controlling glutamate escape. Frontiers in Cellular Neuroscience 15, 707813 (2021).

Downloads

Two ready-to-run implementations are provided:

• Python package (with graphical interface): Python.zip
• MATLAB version: MatLab.zip

Documentation and Support

For guidance and questions, please consult our Support Page and join the discussion on the Neuroalgebra Forum.