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GrangerCausality

Namespace: CONNECTIVITYLIB  ·  Library: Connectivity Library

Python equivalent

mne_connectivity.spectral_connectivity_epochs (method='gc') in MNE-Python.

#include <connectivity/granger_causality.h>

class CONNECTIVITYLIB::GrangerCausality

Spectral Granger Causality estimator (Geweke 1982 formulation).

For every ordered channel pair ``(j -> i) the estimator fits an MVAR model to the trial-concatenated time series via [MvarModel](/docs/api/connectivity/mvar-model) and evaluates the log ratio of the unconditional and conditional spectra of X_i, GC_{j->i}(f) = ln( S_{ii}(f) / ( S_{ii}(f) - (Sigma_{jj} - Sigma_{ij}^2 / Sigma_{ii}) * |H_{ij}(f)|^2 ) ). The resulting [Network](/docs/api/connectivity/network) is directional and stores the band-averaged GC value as edge weight.

Spectral Granger Causality estimator; directional, MVAR-based.

Inheritance​

Public Methods​

GrangerCausality()​

Constructs a GrangerCausality object.

Static Methods​

calculate(connectivitySettings)​

Calculates spectral Granger causality between all channel pairs.

Parameters:

Returns:

  • Network — The connectivity information in form of a network structure.

Authors of this file​