mne_connectivity.phase_slope_index#

mne_connectivity.phase_slope_index(data, names=None, indices=None, sfreq='', mode='multitaper', fmin=None, fmax=inf, tmin=None, tmax=None, mt_bandwidth=None, mt_adaptive=False, mt_low_bias=True, cwt_freqs=None, cwt_n_cycles=7, block_size=1000, n_jobs=1, verbose=None)[source]#

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_epochs()), details can be found in [1].

Parameters:

dataarray_like, shape (n_epochs, n_signals, n_times) | Epochs | generator: Can also be a list/generator of arrays, shape (n_signals, n_times); list/generator of mne.SourceEstimate; or mne.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_*.
namesarray_like | None: The names of the nodes of the dataset used to compute connectivity. If None (default), then names will be a list of integers from 0 to n_nodes. If a list of names, then it must be equal in length to n_nodes.
indicestuple of array_like | None: Two array-likes with indices of connections for which to compute connectivity. If None, all connections are computed. See Notes of spectral_connectivity_epochs() for details.
sfreqfloat | None: The sampling frequency. Default is an empty string for 2*np.pi in 0.8, but will change to None in 0.9. Set it explicitly when data is an array-like to avoid a warning.
mode'multitaper' | 'fourier' | 'cwt_morlet': Spectrum estimation mode.
fminfloat | tuple of float: The lower frequency of interest. Multiple bands are defined using a tuple, e.g., (8., 20.) for two bands with 8 Hz and 20 Hz lower freq. If None the frequency corresponding to an epoch length of 5 cycles is used.
fmaxfloat | tuple of float: The upper frequency of interest. Multiple bands are defined using a tuple, e.g., (13., 30.) for two bands with 13 Hz and 30 Hz upper freq.
tminfloat | None: Time to start connectivity estimation.
tmaxfloat | None: Time to end connectivity estimation.
mt_bandwidthfloat | None: The bandwidth of the multitaper windowing function in Hz. Only used in 'multitaper' mode.
mt_adaptivebool: Use adaptive weights to combine the tapered spectra into PSD. Only used in 'multitaper' mode.
mt_low_biasbool: Only use tapers with more than 90 percent spectral concentration within bandwidth. Only used in 'multitaper' mode.
cwt_freqsarray_like: Array-like of frequencies of interest. Only used in 'cwt_morlet' mode.
cwt_n_cyclesfloat | array_like: Number of cycles. Fixed number or one per frequency. Only used in 'cwt_morlet' mode.
block_sizeint: How many connections to compute at once (higher numbers are faster but require more memory).
n_jobsint: How many epochs to process in parallel.
verbosebool | str | int | None: If not None, override default verbose level (see mne.verbose() for more info). If used, it should be passed as a keyword-argument only.

Returns:

conninstance of SpectralConnectivity or SpectroTemporalConnectivity

Computed connectivity measure(s). Either a SpectralConnectivity, or SpectroTemporalConnectivity container. The shape of each array is:

(n_cons, n_bands) for 'multitaper' or 'fourier' modes
(n_cons, n_bands, n_times) for 'cwt_morlet' mode
n_cons = n_signals ** 2 when indices=None
n_cons = len(indices[0]) when indices is supplied

Examples using `mne_connectivity.phase_slope_index`#

Comparison of coherency-based methods

Compute Phase Slope Index (PSI) in source space for a visual stimulus

mne_connectivity.phase_slope_index#

Examples using mne_connectivity.phase_slope_index#

Examples using `mne_connectivity.phase_slope_index`#