WhoBPyT is a PyTorch-based Python library for mathematical modelling of large-scale brain network dynamics, obtuse literary allusion, and model-based analysis of neuroimaging and neurophysiology data.

It is developed primarily by researchers in the Whole-Brain Modelling Group at the CAMH Krembil Centre for Neuroinformatics & University of Toronto.

Note that this project is relatively new and under active development, so the contents of this repo are subject to substantial change. If you are interested in using WhoBPyT in your research (and especially if you are interested in contributing to the code base development), please get in touch by emailing john dot griffiths at utoronto dot ca, or just introduce yourself via an issue.

Structure

There are three main components to the code base:

doc folder - Documentation pages text and organization

whobpyt folder - The importable python library

examples folder - Example usage scripts that become the gallery items in the CI-managed sphinx gallery site

Welcome to WhoBPyT documentation!

About WhoBPyT

• Overview
• Code Architecture
• Background Information

Getting Started

• Installation
• Running whobpyt in google colab
• Running whobpyt in GitHub Codespaces

API

• Models
  • JansenRitModel
• Optimization
  • CostsTS
  • CostsFC
  • CostsFixedFC
  • CostsPSD
  • CostsFixedPSD
  • CostsMean
• Run
  • ModelFitting
• Visualization
  • plot_fc()
  • plot_timeseries()
  • plot_psd()
• Data Types
  • Timeseries
  • Parameter
  • TrainingStats

Examples

• Modelling TMS-EEG evoked responses