mne.minimum_norm.apply_inverse_raw

mne.minimum_norm.apply_inverse_raw(raw, inverse_operator, lambda2, method='dSPM', label=None, start=None, stop=None, nave=1, time_func=None, pick_ori=None, buffer_size=None, prepared=False, method_params=None, use_cps=True, verbose=None)[source]

Apply inverse operator to Raw data.

Parameters
rawRaw object

Raw data.

inverse_operatordict

Inverse operator.

lambda2float

The regularization parameter.

method“MNE” | “dSPM” | “sLORETA” | “eLORETA”

Use minimum norm, dSPM (default), sLORETA, or eLORETA.

labelLabel | None

Restricts the source estimates to a given label. If None, source estimates will be computed for the entire source space.

startint

Index of first time sample (index not time is seconds).

stopint

Index of first time sample not to include (index not time is seconds).

naveint

Number of averages used to regularize the solution. Set to 1 on raw data.

time_funccallable()

Linear function applied to sensor space time series.

pick_oriNone | “normal” | “vector”

Options:

  • None

    Pooling is performed by taking the norm of loose/free orientations. In case of a fixed source space no norm is computed leading to signed source activity.

  • "normal"

    Only the normal to the cortical surface is kept. This is only implemented when working with loose orientations.

  • "vector"

    No pooling of the orientations is done, and the vector result will be returned in the form of a mne.VectorSourceEstimate object. This is only implemented when working with loose orientations.

buffer_sizeint (or None)

If not None, the computation of the inverse and the combination of the current components is performed in segments of length buffer_size samples. While slightly slower, this is useful for long datasets as it reduces the memory requirements by approx. a factor of 3 (assuming buffer_size << data length). Note that this setting has no effect for fixed-orientation inverse operators.

preparedbool

If True, do not call prepare_inverse_operator().

method_paramsdict | None

Additional options for eLORETA. See Notes of apply_inverse().

New in version 0.16.

use_cpsbool

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, and pick_ori='normal'.

New in version 0.20.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns
stcSourceEstimate | VectorSourceEstimate | VolSourceEstimate

The source estimates.

See also

apply_inverse_epochs

Apply inverse operator to epochs object.

apply_inverse

Apply inverse operator to evoked object.

Examples using mne.minimum_norm.apply_inverse_raw