This project aims to model the effect of variable acetylcholine levels in the human hippocampus on pattern separation task performance. The underlying hippocampal model is a modified version of the Emergent HPC Model which was based on Ketz et al. (2013). The research accompanying this model can be found here.
These instructions will get you a copy of the project up and running on your local machine.
As the model is written in Golang, please have this installed first: https://golang.org/doc/install
Next, install Emergent (GoGi and Leabra) using these instructions: https://github.com/emer/emergent/wiki/Install
Next, clone this repository to your preferred directory and run it.
Start by cding to your preferred directory.
git clone https://github.com/AlexGordienko/hip-ACh
To run the model with the graphical interface:
cd hip-ACh
go build
./hip-ACh
From here you should see the graphical interface pop up. In this window, click Train to begin. There's lots to do here, so check out the CCN Lab's Textbook to get started learning.
If you want to run the model with a dataset of your choosing from the stimuli folder, begin by installing go-bindata here: https://github.com/shuLhan/go-bindata. Now, make sure you are cd'ed into this project's home directory and run
./go-bindata ./stimuli/[YOUR SELECTED DATASET]/test_ab_ps.tsv ./stimuli/[YOUR SELECTED DATASET]/train_ab_ps.tsv
From here you can
go build
./hip-ACh
as usual.
If you would like to create and run your own dataset on this model, I would recommend building the dataset with this dataset creation tool. You can then place the outputed .tsv files into a folder under stimuli and bind the files as shown above. I would recommend that you conserve the naming convention of train_ab_ps.tsv, test_ab_ps.tsv for your training and testing variants so that you don't need to modify any code to try them out.
- Alex Gordienko - Initial work - Website