Human Neocortical Neurosolver (HNN) is a software for interpreting the neural origin of macroscale magneto-/electro-encephalography (MEG/EEG) data using biophysically-detailed microcircuit simulations. HNN can be run through a user-friendly graphical user interface or through a Python interface HNN-core.
Mailing list(s): https://groups.google.com/g/hnnsolver
Goal: The aim of this project is to build a new GUI with the same functionality as the current HNN, using the HNN-core API and following best practices in open source software design.
- Run HNN-GUI tutorials with old as well as new GUI to identify and implement functionality that missing
- Build new GUI components based on identified weaknesses in new GUI. This includes implementing dialog boxes for optimization, displaying waveforms from previous simulations
- Write tests for the GUI using “fake clicks” and incorporate them in continuous integration
- Extra credit: Test GUI over remote cluster connection, incorporate new API elements in GUI such as viewing connectivity matrices and modifying connectivity
Duration: 350 hours (full time)
Skills: Some experience in GUI development such as matplotlib, ipywidgets or PySimpleGUI may be helpful but not necessary. Experience in neuroscience is also helpful but not required.
Tech keywords: Python, GUI