mne.connectivity.phase_slope_index¶

mne.connectivity.phase_slope_index(data, indices=None, sfreq=6.283185307179586, mode='multitaper', fmin=None, fmax=inf, tmin=None, tmax=None, mt_bandwidth=None, mt_adaptive=False, mt_low_bias=True, cwt_frequencies=None, cwt_n_cycles=7, block_size=1000, n_jobs=1, verbose=None)

Compute the Phase Slope Index (PSI) connectivity measure

The PSI is an effective connectivity measure, i.e., a measure which can give an indication of the direction of the information flow (causality). For two time series, and one computes the PSI between the first and the second time series as follows

indices = (np.array([0]), np.array([1])) psi = phase_slope_index(data, indices=indices, ...)

A positive value means that time series 0 is ahead of time series 1 and a negative value means the opposite.

The PSI is computed from the coherency (see spectral_connectivity), details can be found in [1].

Parameters: data : array-like, shape=(n_epochs, n_signals, n_times) Can also be a list/generator of array, shape =(n_signals, n_times); list/generator of SourceEstimate; or Epochs. The data from which to compute connectivity. Note that it is also possible to combine multiple signals by providing a list of tuples, e.g., data = [(arr_0, stc_0), (arr_1, stc_1), (arr_2, stc_2)], corresponds to 3 epochs, and arr_* could be an array with the same number of time points as stc_*. indices : tuple of arrays | None Two arrays with indices of connections for which to compute connectivity. If None, all connections are computed. sfreq : float The sampling frequency. mode : str Spectrum estimation mode can be either: ‘multitaper’, ‘fourier’, or ‘cwt_morlet’. fmin : float | tuple of floats The lower frequency of interest. Multiple bands are defined using a tuple, e.g., (8., 20.) for two bands with 8Hz and 20Hz lower freq. If None the frequency corresponding to an epoch length of 5 cycles is used. fmax : float | tuple of floats The upper frequency of interest. Multiple bands are dedined using a tuple, e.g. (13., 30.) for two band with 13Hz and 30Hz upper freq. tmin : float | None Time to start connectivity estimation. tmax : float | None Time to end connectivity estimation. mt_bandwidth : float | None The bandwidth of the multitaper windowing function in Hz. Only used in ‘multitaper’ mode. mt_adaptive : bool Use adaptive weights to combine the tapered spectra into PSD. Only used in ‘multitaper’ mode. mt_low_bias : bool Only use tapers with more than 90% spectral concentration within bandwidth. Only used in ‘multitaper’ mode. cwt_frequencies : array Array of frequencies of interest. Only used in ‘cwt_morlet’ mode. cwt_n_cycles: float | array of float Number of cycles. Fixed number or one per frequency. Only used in ‘cwt_morlet’ mode. block_size : int How many connections to compute at once (higher numbers are faster but require more memory). n_jobs : int How many epochs to process in parallel. verbose : bool, str, int, or None If not None, override default verbose level (see mne.verbose). psi : array Computed connectivity measure(s). The shape of each array is either (n_signals, n_signals, n_bands) mode: ‘multitaper’ or ‘fourier’ (n_signals, n_signals, n_bands, n_times) mode: ‘cwt_morlet’ when “indices” is None, or (n_con, n_bands) mode: ‘multitaper’ or ‘fourier’ (n_con, n_bands, n_times) mode: ‘cwt_morlet’ when “indices” is specified and “n_con = len(indices[0])”. freqs : array Frequency points at which the connectivity was computed. times : array Time points for which the connectivity was computed. n_epochs : int Number of epochs used for computation. n_tapers : int The number of DPSS tapers used. Only defined in ‘multitaper’ mode. Otherwise None is returned.

References

[1] Nolte et al. “Robustly Estimating the Flow Direction of Information in Complex Physical Systems”, Physical Review Letters, vol. 100, no. 23, pp. 1-4, Jun. 2008.