The GLHMM toolbox provides facilities to fit a variety of Hidden Markov models (HMM) based on the Gaussian distribution, which we generalise as the Gaussian-Linear HMM. Crucially, the toolbox has a focus on finding associations at various levels between brain data (EEG, MEG, fMRI, ECoG, etc) and non-brain data, such as behavioural or physiological variables.

Important links

• Official source code repo: https://github.com/vidaurre/glhmm
• GLHMM documentation: https://glhmm.readthedocs.io/en/latest/index.html

Dependencies

The required dependencies to use glhmm are:

• Python >= 3.6

• NumPy

• numba

• scikit-learn

• scipy

• matplotlib

• seaborn

• cupy (only when using GPU acceleration; requires manual install)

Installation

• To install the latest development version from the repository, use the following command:

pip install git+https://github.com/vidaurre/glhmm

• Alternatively, to install the latest stable release from PyPI, use the command:

pip install glhmm