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Site Navigation
Overview
Installation
API Reference
Examples
GitHub
Twitter
Section Navigation
Tutorials
Estimate the Dynamic Functional Connectivity
Statistical analysis of a stimulus-specific network
Multi-subjects dataset
Define an electrophysiological dataset using MNE-Python structures
Build an electrophysiological dataset
Define an electrophysiological dataset using Xarray
Group-level statistics on measures of information
MI between two continuous variables conditioned by a discret one
MI between a continuous and a discret variables
MI between two continuous variables
Compute MI across time and frequencies
Investigate relation of order
Compute a conjunction analysis on mutual-information
Mutual-information at the contact level
Information-based estimators
Trial-resampling: correcting for unbalanced designs
Defining a custom estimator
Estimator comparison
Connectivity and Information Transfer
FIT: Feature specific information transfer
PID: Decomposing the information carried by pairs of brain regions
Estimate dynamic functional connectivity
Estimate interaction information
Estimate comodulations between brain areas
Lag estimation between delayed times-series using the cross-correlation
Estimate the covariance-based Granger Causality
Autoregressive model
AR : pairwise illustration
AR : simulate common driving input
AR : conditional covariance based Granger Causality
Utility
Define temporal windows
Statistics
Compare within-subjects statistics when computing mutual information
Compare between-subjects statistics when computing mutual information
Estimate the empirical confidence interval
Simulations
Generate random electrophysiological data
Generate spatio-temporal ground-truths
Performance
Comparison between tensor and vector based computations
Xarray
Xarray : Saving the results
Xarray : Quick tour
Examples
Utility
Utility
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Illustration of utility functions.
Define temporal windows
Define temporal windows