mne.io.read_raw_eyelink#
- mne.io.read_raw_eyelink(fname, *, create_annotations=True, apply_offsets=False, find_overlaps=False, overlap_threshold=0.05, verbose=None)[source]#
Reader for an Eyelink .asc file.
- Parameters:
- fnamepath-like
Path to the eyelink file (.asc).
- create_annotations
bool
|list
(defaultTrue
) Whether to create mne.Annotations from occular events (blinks, fixations, saccades) and experiment messages. If a list, must contain one or more of [‘fixations’, ‘saccades’,’ blinks’, messages’]. If True, creates mne.Annotations for both occular events and experiment messages.
- apply_offsets
bool
(defaultFalse
) Adjusts the onset time of the mne.Annotations created from Eyelink experiment messages, if offset values exist in the ASCII file.
- find_overlaps
bool
(defaultFalse
) Combine left and right eye
mne.Annotations
(blinks, fixations, saccades) if their start times and their stop times are both not separated by more than overlap_threshold.- overlap_threshold
float
(default 0.05) Time in seconds. Threshold of allowable time-gap between both the start and stop times of the left and right eyes. If the gap is larger than the threshold, the
mne.Annotations
will be kept separate (i.e."blink_L"
,"blink_R"
). If the gap is smaller than the threshold, themne.Annotations
will be merged and labeled as"blink_both"
. Defaults to0.05
seconds (50 ms), meaning that if the blink start times of the left and right eyes are separated by less than 50 ms, and the blink stop times of the left and right eyes are separated by less than 50 ms, then the blink will be merged into a singlemne.Annotations
.- 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.
- Returns:
- rawinstance of RawEyelink
A Raw object containing eyetracker data.
See also
mne.io.Raw
Documentation of attribute and methods.
Notes
It is common for SR Research Eyelink eye trackers to only record data during trials. To avoid frequent data discontinuities and to ensure that the data is continuous so that it can be aligned with EEG and MEG data (if applicable), this reader will preserve the times between recording trials and annotate them with
'BAD_ACQ_SKIP'
.