Model-based Brain Connectivity Analysis

NetDynFlow

A package to study complex networks based on the temporal evolution of their Dynamic Communicability and Flow.

SiReNetA_Tutorials

SiReNetA

Stimulus-Response Network Analysis

pyMOU

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

notebooks_review2019

These Python notebooks reproduce some figures in the following preprint using the libraries pyMOU and NetDynFlow: https://www.biorxiv.org/content/10.1101/531830v2

Notebooks_EC_Collab

Showcase Jupyter Notebooks for integration of EC estimation methods in EBRAINS

EITN2020_BrainConn_Tutorial

Materials and Notebooks for the tutorial "Analysis of Brain Connectivity" to be held during the EITN Spring School in Computational Neuroscience, Paris, March 4 - 13, 2020.

dummy

Testbed for Git(Hub) hocus pocus