Computing connectivity in electrophysiological data
FieldTrip has a consistent set of low-level functions for the computation of connectivity, i.e. estimating a bivariate or multivariate quantity from electrophysiological data, both on the sensor level and on the source level.
The objective of supplying these low-level functions as a separate module/toolbox are to
- facilitate the reuse of these functions in other open-source projects (e.g. EEGLAB, SPM)
- facilitate the implementation and support for new inverse methods, esp. for external users/contributors
- facilitate the implementation of advanced features
Please note that if you are an end-user interested in analyzing experimental EEG/MEG/ECoG data, you will probably will want to use the high-level FieldTrip functions. The functions such as ft_preprocessing, ft_timelockanalysis, ft_sourceanalysis, ft_mvaranalysis, ft_freqanalysis, ft_connectivityanalysis and ft_networkanalysis provide a user-friendly interface that take care of all relevant analysis steps and the data bookkeeping.
Supported connectivity metrics
- directed transfer function
- granger causality, spectrally resolved
- imaginary part of coherency
- instantaneous causality
- pairwise phase consistency
- partial coherence
- partial correlation
- partial directed coherence
- phase locking value
- phase slope index
- total interdependence
- weighted phase lag index
Definition of the function-calls (API)
The functions should be called as
outputdata = ft_connectivity_bct (inputdata, 'key1', value1, 'key2', value2, ....); outputdata = ft_connectivity_corr(inputdata, 'key1', value1, 'key2', value2, ....); outputdata = ft_connectivity_dtf (inputdata, 'key1', value1, 'key2', value2, ....); outputdata = ft_connectivity_ppc (inputdata, 'key1', value1, 'key2', value2, ....); outputdata = ft_connectivity_psi (inputdata, 'key1', value1, 'key2', value2, ....); outputdata = ft_connectivity_wpli(inputdata, 'key1', value1, 'key2', value2, ....);
The inputdata consists of a matrix of one of the following dimensionalities:
- Nrpt x Nchan x Nchan (x Nfreq) (x Ntime)
- Nrpt x Nchancmb (x Nfreq) (x Ntime)
where Nrpt can be singleton. Additional arguments come in key-value pairs and depend on the function and the required functionality. The current functions only take inputdata which is already in a bivariate representation. In FieldTrip this is ensured by the calling function ft_connectivityanalysis.
One exception to the API described above is:
outputdata = ft_connectivity_granger(H, Z, S, key1, value1, ...);
Spectrally resolved granger causality is a function of both the spectral transfer function (H) and the covariance of the noise (Z). For computational reasons, the cross-spectral density is also a required input argument for the function.
The literature references to the implemented methods are given here.
Tutorial material for connectivity analysis:
|2011/06/08 11:25||Jan-Mathijs Schoffelen|
|2013/02/21 21:03||Eelke Spaak|
|2015/09/15 14:44||Robert Oostenveld|
|2014/10/29 09:37||Tzvetan Popov|