This package contains a set of reaction-diffusion models to simulate the dynamics of fluorescent dyes and neuropeptides in the brain extracellular space. The models are encoded in Python using the reaction-diffusion module of the NEURON simulator and its recently developed extracellular reaction-diffusion simulator (McDougal et al. 2013, Newton et al. 2018).
extracellular-models installs as the extmodels Python package. It is tested with Python 3.9.
Note that extmodels has the following core dependencies:
You can install extmodels with pip sourced from the GitHub repo:
pip install -e git+https://github.com/NTBEL/extracellular-models#egg=extmodels
extracellular-models currently contains 4 models:
extmodels.calcein- Model of calcein diffusion in the brain extracellular space after photorelease from gold-coated nanovesicles.extmodels.somatostatin- Model of somatostatin diffusion and loss (degradation, clearance, etc.) in the brain extracellular space after photorelease from gold-coated nanovesicles.extmodels.dynophin- Model of dynorphin A diffusion and binding to the kLight receptor-based fluorescent sensor in the brain extracellular space after photorelease from gold-coated nanovesicles.extmodels.core_satellite- Model of somatostatin (SST) release, diffusion, and loss with core-satellite based sensing clusters. The sensing clusters are simplified models of the core-satellite CNiFERs clusters setup used in Xiong et al. 2021 bioRxiv.extmodels.calcein_pointsource- Model of calcein diffusion in the brain extracellular space that approximates release from an instantaneous point source.extmodels.dynorphin_pointsource- Model of dynorphin A diffusion and binding to the kLight receptor-based fluorescent sensor in the brain extracellular space after photorelease from a point-source.extmodels.calcein_pointsource_asymm- Model of asymmetric calcein diffusion in the brain extracellular space after release from an approximate instantaneous point source. The two-sides of the simulation domain along the x-axis have different tortuosities so calcein diffuses asymmetrically.
To facilitate reusability and allow models to be importable they have been encapsulated as Python class objects and defined within separate modules.
Models can be imported from their respective modules. For example,
from extmodels.calcein import modelwill import the initialized instance of the calcein model.
To simulate the model you can call the simulate function. For example,
time_step = 10 # time step in milliseconds
n_steps = 100 # run for 100 time steps.
out_frequency = 10 # compute model observables every 10 time steps.
model.simulate(time_step, n_steps, out_frequency)will run the model simulation for total simulated time of 1 second (time_step*n_step) and store model observables at intervals of every 10 time steps. The observables and corresponding simulated times are accessible through the properteries observables and times; for example:
model_observables = model.observables
times = model.timesThe NEURON rxd.Extracellular object that is used to define the extracellular space and its parameters (e.g., volume fraction and tortuosity) currently doesn't support modifying the parameters (such as volume fraction or tortuosity) after it has been initialized in the model. If you want to use a particular model but want, for example, a different tortuosity, you can import the Model class and then create a custom instance:
from extmodels.calcein import Model
# Initialize the calcein model but with a tortuosity of 2 instead of the default
# 1.7 used for extmodels.calcein.model.
model = Model(tortuosity=2.0)The examples folder contains some example application scripts using the models and saving outputs. Note that most of these require the tifffile library to save 2d z-projections as .tiff image trajectory files.
Please open a GitHub Issue to report any problems/bugs or make any comments, suggestions, or feature requests.
This project is licensed under the MIT License - see the LICENSE file for detail
See: CHANGELOG
If any of these models are useful in your research, please cite this GitHub repo: https://github.com/NTBEL/extracellular-models