mne.minimum_norm.source_induced_power#
- mne.minimum_norm.source_induced_power(epochs, inverse_operator, freqs, label=None, lambda2=0.1111111111111111, method='dSPM', nave=1, n_cycles=5, decim=1, use_fft=False, pick_ori=None, baseline=None, baseline_mode='logratio', pca=True, n_jobs=None, zero_mean=False, prepared=False, method_params=None, use_cps=True, verbose=None)[source]#
Compute induced power and phase lock.
Computation can optionally be restricted in a label.
- Parameters:
- epochsinstance of
Epochs
The epochs.
- inverse_operatorinstance of
InverseOperator
The inverse operator.
- freqs
array
Array of frequencies of interest.
- label
Label
Restricts the source estimates to a given label.
- lambda2
float
The regularization parameter of the minimum norm.
- method“MNE” | “dSPM” | “sLORETA” | “eLORETA”
Use minimum norm, dSPM (default), sLORETA, or eLORETA.
- nave
int
The number of averages used to scale the noise covariance matrix.
- n_cycles
float
|array
offloat
Number of cycles. Fixed number or one per frequency.
- decim
int
Temporal decimation factor.
- use_fft
bool
Do convolutions in time or frequency domain with FFT.
- pick_ori
None
| “normal” If “normal”, rather than pooling the orientations by taking the norm, only the radial component is kept. This is only implemented when working with loose orientations.
- baseline
None
(default) ortuple
of length 2 The time interval to apply baseline correction. If None do not apply it. If baseline is (a, b) the interval is between “a (s)” and “b (s)”. If a is None the beginning of the data is used and if b is None then b is set to the end of the interval. If baseline is equal to (None, None) all the time interval is used.
- baseline_mode‘mean’ | ‘ratio’ | ‘logratio’ | ‘percent’ | ‘zscore’ | ‘zlogratio’
Perform baseline correction by
subtracting the mean of baseline values (‘mean’)
dividing by the mean of baseline values (‘ratio’)
dividing by the mean of baseline values and taking the log (‘logratio’)
subtracting the mean of baseline values followed by dividing by the mean of baseline values (‘percent’)
subtracting the mean of baseline values and dividing by the standard deviation of baseline values (‘zscore’)
dividing by the mean of baseline values, taking the log, and dividing by the standard deviation of log baseline values (‘zlogratio’)
- pca
bool
If True, the true dimension of data is estimated before running the time-frequency transforms. It reduces the computation times e.g. with a dataset that was maxfiltered (true dim is 64).
- n_jobs
int
|None
The number of jobs to run in parallel. If
-1
, it is set to the number of CPU cores. Requires thejoblib
package.None
(default) is a marker for ‘unset’ that will be interpreted asn_jobs=1
(sequential execution) unless the call is performed under ajoblib.parallel_backend()
context manager that sets another value forn_jobs
.- zero_mean
bool
Make sure the wavelets are zero mean.
- prepared
bool
If True, do not call
prepare_inverse_operator()
.- method_params
dict
|None
Additional options for eLORETA. See Notes of
apply_inverse()
.- use_cps
bool
Whether to use cortical patch statistics to define normal orientations for surfaces (default True).
Only used when the inverse is free orientation (
loose=1.
), not in surface orientation, andpick_ori='normal'
.New in version 0.20.
- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- epochsinstance of
- Returns:
- power
array
The induced power.
- power
Examples using mne.minimum_norm.source_induced_power
#
Compute power and phase lock in label of the source space