load_metacognition_data#

load_metacognition_data()[source]#

Load the metacognition dataset from a CSV file.

Returns:
pd.DataFrame

A pandas DataFrame containing the metacognition data.

See also

cpm.applications.signal_detection.EstimatorMetaD

Class to estimate metacognitive sensitivity (meta-d’) from confidence ratings and choices.

Notes

The data are from an experiment combining a perceptual decision making task with an additional post-decision component assessing participants’ confidence in their choices (Marzuki et al., 2025; Moses-Payne et al., 2021). The experiment is implemented as a gamified smartphone-compatible application available in the BrainExplorer platform (https://brainexplorer.net/) as the game “Space Observer”. The task is designed to assess aspects of metacognition, i.e., the extent to which one can accurately reflect on and evaluate their own performance, specifically how well one’s confidence is calibrated to their actual performance. For a more thorough description of the experimental procedure, please refer to Marzuki et al. (2025). Briefly, in each trial of the game, participants are presented with a planet in the centre of the screen. On top of the planet, participants are shown 68 differently coloured aliens for 250 ms, overlaying the planet. The aliens are drawn from two distinct categories (S1 and S2), which differ in colour, but are identical in shape. After the 68 aliens disappear, participants are presented with an example of the two differently coloured aliens and asked to choose which of the two had been more abundant on that trial. After each of the trials, they are asked to indicate how confident they are about their decision on a visual analogue scale ranging from “totally guessing” (0) to “totally certain” (100). The scale is not labelled with numbers and participants are not informed about the numerical values associated with their confidence ratings. A staircase procedure (Cornsweet, 1962; García-Pérez, 1998; Levitt, 1971) is used throughout the task to dynamically adjust the stimulus intensity, defined as the difference in aliens required to keep participants’ performance at approximately 70%.

The dataset includes the following columns:

  • participant: the participant number.

  • signal: which alien is more abundant (0 = S1, 1 = S2).

  • stimulus_intensity: absolute difference in number of aliens (i.e., evidence strength).

  • response: participant’s choice (0 = S1, 1 = S2).

  • confidence: participant’s confidence rating for their response.

  • accuracy: accuracy of the participant’s response (0 = incorrect, 1 = correct).

References

Chen, Y., Daly, H. R., Pitt, M. A., & Van Zandt, T. (2024). Assessing the distortions introduced when calculating d’: A simulation approach. Behavior Research Methods. https://doi.org/10.3758/s13428-024-02447-8

Cornsweet, T. (1962). The staircase-method in psychophysics. Am. J. Psychol. 75, 485491. https://doi.org/10.2307/1419876

García-Pérez M.A. (1998). Forced-choice staircases with fixed step sizes: asymptotic and small-sample properties. Vision Res., 38(12), 1861-81. https://doi.org/10.1016/s0042-6989(97)00340-4.

Levitt, H. (1971). Transformed up-down methods in psychoacoustics. Journal of the Acoustical Society of America, 49, 467–477. https://doi.org/10.1121/1.1912375

Marzuki, A., Kosina, L., Dome, L., Hewitt, S., & Hauser, T. (2025). Metacognitive antecedents to states of mental ill-health: Drops in confidence precede symptoms of OCD. Research Square. https://doi.org/10.21203/rs.3.rs-7544256/v1

Moses‐Payne, M. E., Habicht, J., Bowler, A., Steinbeis, N., & Hauser, T. U. (2021). I know better! Emerging metacognition allows adolescents to ignore false advice. Developmental Science, 24(5), e13101. https://doi.org/10.1111/desc.13101

Examples

>>> data = load_metacognition_data()
>>> print(data.head())

See also