bidsaid.events.PresentationBlockExtractor.extract_mean_reaction_times

PresentationBlockExtractor.extract_mean_reaction_times(response_map=None, response_type='all', response_trial_names=None)[source]

Extract mean reaction times for each block.

Parameters

response_mapdict[str, int] or None, default=None: A dictionary mapping response codes, from “Stim Type” column (ie. “hit”, “miss”, “other”, “false alarm”, “incorrect”), to accuracy values (0 for incorrect, 1 for correct). Use float("NaN") to exclude a response code from the computation. Required when response_type is “correct” or “incorrect”. When provided with response_type="all", responses mapped to float("NaN") are excluded from the mean reaction time computation.
response_typeLiteral["correct", "incorrect", "all"], default=”all”: Whether to compute mean RT for correct, incorrect, or all trials. When “all”, response_map is not needed.
response_trial_namesIterable[str] or None, default=None: The stimulus trial names within each block to include for the reaction_time computation.

Important

If split_cue_from_block is True, trial types are excluded from this parameter.

Returns

list[float]: A list of mean reaction times for each block.

Note

The reaction time is computed for the first response only. Also, if cue is split from the block, NaN will be assigned for its reaction time.

Example

>>> # Mean RT for all trials with a response
>>> mean_reaction_times = extractor.extract_mean_reaction_times()
>>> # Mean RT for correct trials only
>>> response_map = {"hit": 1, "miss": 0}
>>> mean_reaction_times = extractor.extract_mean_reaction_times(
...     response_map=response_map,
...     response_type="correct",
... )