mne_connectivity.phase_slope_index#
- mne_connectivity.phase_slope_index(data, names=None, 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_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)
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_*.
- names
list
|np.ndarray
|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 ton_nodes
.- indices
tuple
ofarray
|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
offloat
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
offloat
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_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_freqs
array
Array of frequencies of interest. Only used in ‘cwt_morlet’ mode.
- cwt_n_cycles
float
|array
offloat
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.
- verbosebool,
str
,int
, orNone
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
Connectivity
Computed connectivity measure(s). Either a
SpectralConnnectivity
, orSpectroTemporalConnectivity
container. The shape of each array is either (n_signals ** 2, n_bands) mode: ‘multitaper’ or ‘fourier’ (n_signals ** 2, 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])”.
- conninstance of
References
Examples using mne_connectivity.phase_slope_index
#
Comparison of coherency-based methods
Compute Phase Slope Index (PSI) in source space for a visual stimulus