Stefan Appelhoff
95672092f3
add derivatives
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2 years ago | |
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| .. | ||
| (None, 0)-(0.3, 0.7) | 2 years ago | |
| README | 2 years ago | |
README
folder names are `f"{baseline}-{mean_times}"`, where:
- baseline is a tuple (start, stop)
- mean_times is a tuple (start, stop)
- baseline is a tuple (start, stop)
- mean_times is a tuple (start, stop)
| datacite.yml | |
|---|---|
| Title | The mpib_ecomp_derivatives dataset |
| Authors |
Appelhoff,Stefan;Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0001-8002-0877
Hertwig,Ralph;Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0002-9908-9556 Spitzer,Bernhard;Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0001-9752-932X |
| Description | This dataset contains derived data. See the README.md file for further information. |
| License | Open Data Commons Public Domain Dedication and License (PDDL) v1.0 (https://opendatacommons.org/licenses/pddl/1-0/) |
| References |
Appelhoff, S., Hertwig, R. & Spitzer, B. EEG-representational geometries and psychometric distortions in approximate numerical judgment. (2022) doi:10.1101/2022.03.31.486560 [doi:10.1101/2022.03.31.486560] (IsSupplementTo)
Appelhoff, Stefan. (2022). eComp Experiment Code (2022.1.0). Zenodo. https://doi.org/10.5281/zenodo.6411319 [doi:10.5281/zenodo.6411313] (IsReferencedBy) Appelhoff, Stefan. (2022). eComp Analysis Code (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.6411288 [doi:10.5281/zenodo.6411287] (IsSupplementTo) https://gin.g-node.org/sappelhoff/mpib_ecomp_dataset [] (IsReferencedBy) https://gin.g-node.org/sappelhoff/mpib_ecomp_sourcedata [] (IsReferencedBy) |
| Funding |
Max Planck Institute for Human Development
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| Keywords |
cognitive neuroscience
decision-making numerical cognition sequential sampling value distortions compression anti-compression EEG electroencephalography eyetracking representational similarity analysis RSA multivariate pattern analysis MVPA computational modeling |
| Resource Type |
Dataset |