pydentate is a biophysically realistic computational model of the dentate gyrus, a hippocampal brain region associated with memory formation and a computation called pattern separation. We made changes based on new literature and our own experimental findings. Furthermore, we introduced enhancements to study pattern separation.
Open a terminal and clone the pydentate repository
git clone https://github.com/danielmk/pydentate.git
Inside the cloned repository pip install
cd pydentate
ON WINDOWS: You will need to install neuron manually.
pip install -e .The installation is now complete and you can get started by running the example script
python paradigm_pattern_separation_baseline.py
This will take a long time. If no errors are raised your pydentate is working.
pydentate builds on a computational model from this paper: Santhakumar, V., Aradi, I., & Soltesz, I. (2005). Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cell types and axonal topography. Journal of Neurophysiology, 93(1), 437–453. https://doi.org/10.1152/jn.00777.2004 Their model can be found here.
We decribe pydentate in our eLife paper: Braganza, O., Müller-Komorowska, D., Kelly, T., & Beck, H. (2020). Quantitative properties of a feedback circuit predict frequency-dependent pattern separation. ELife, 813188. https://doi.org/10.7554/eLife.53148 You can find a separated repository that is dedicated to reproducing the paper results here.
Daniel Müller-Komorowska - Institute of Experimental Epileptology and Cognition Research
Barış Can Kuru (synaptic_fitting add on) - Institute of Experimental Epileptology and Cognition Research