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pyMOU

Light package for simulation and connectivity estimation using the multivariate Ornstein-Uhlenbeck process (MOU)

This Python library relies on the MOU process to simulate network activity and estimate connectivity from observed activity (Gilson et al. PLoS Comput Biol 2016; Gilson et al Net Neurosci 2020).

NEW IN THIS VERSION

There is no more minimum bound imposed on the estimated weights by default. If you want to estimate positive weights, use min_C=0 in the fit method!

Quick install using pip

The installer pip comes with Anaconda and most Python distribution. Just run:

$ pip install git+https://github.com/mb-BCA/pyMOU.git@master

How to use?

Check the Python notebooks in examples.

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Light package for connectivity estimation and analysis of neuroimaging data (e.g. fMRI). It relies on the multivariate Ornstein-Uhlenbeck process (MOU).

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