This repository contains the data for the "Long-Term Effects of Working Memory Retrieval From Prioritized and Deprioritized" States manuscript.

Frieda Born f0feb61900 correcting format of references 2 weeks ago
Experiment1 1277171cb8 Added data files and codebook for RIDER experiments 3 weeks ago
Experiment2 1277171cb8 Added data files and codebook for RIDER experiments 3 weeks ago
Experiment3 1277171cb8 Added data files and codebook for RIDER experiments 3 weeks ago
codebook 1277171cb8 Added data files and codebook for RIDER experiments 3 weeks ago
.gitignore 1277171cb8 Added data files and codebook for RIDER experiments 3 weeks ago
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README.md c6d10fc225 updating README file with zenodo DOI and license info 3 weeks ago
datacite.yml f0feb61900 correcting format of references 2 weeks ago

README.md

:floppy_disk: Data Repository for the "RIDER1/2/3" Experiments

This repository contains all the data collected and used for the manuscript: Long-Term Effects of Working Memory Retrieval From Prioritized and Deprioritized States. In brief, the repository contains data tables that hold the behavioral data collected in our experiment series. Below is an overview of the motivation of this experiment series, the data structure and the key contents in each folder.

🪁 What are these experiments about? Which factors determine whether information temporarily held in working memory (WM) is transferred to long-term memory (LTM)? Previous work has shown that retrieving (“testing”) memories from LTM can benefit their future LTM recall. Here, we examined the extent to which a benefit for subsequent LTM may also occur after retrieval from WM, depending on whether the WM contents were retrieved from a prioritized or deprioritized state. In three experiments, we combined variants of a novel visual WM paradigm with a subsequent surprise LTM recall test.


:file_folder: Folder Overview

  • 🗄 Experiment1/ This folder contains the data files for the first experiment:
    • :memo: LTM_data.csv: Long-term memory data collected from participants in Experiment 1.
    • :memo: WM_data.csv: Working memory data collected from participants in Experiment 1.
  • 🗄 Experiment2/ This folder holds the data from the second experiment:
    • :memo: LTM_data_RIDER_2.csv: Long-term memory data for RIDER Experiment 2.
    • :memo: WM_data_RIDER_2.csv: Working memory data for RIDER Experiment 2.
  • 🗄 Experiment3/ This folder contains data from the third experiment:
    • :memo: LTM_data_3.csv: Long-term memory data for Experiment 3.
    • :memo: LTM_data_3_second_testing_round.csv: Long-term memory data for Experiment 3 during the second testing round.
    • :memo: WM_data_3.csv: Working memory data for Experiment 3.
    • :memo: WM_data_3_second_testing_round.csv: Working memory data for Experiment 3 during the second testing round.
  • :page_facing_up: codebook/ Contains documentation for understanding the structure and meaning of the data.
    • :book: Codebook.pdf: A comprehensive document explaining the variables and data formats used in the experiments.
  • .gitignore Specifies files and directories that should be ignored by Git, ensuring that only relevant data is tracked in the repository.

:clipboard: Usage Instructions

The data provided in this repository is structured by experiment, with each folder containing the data files related to long-term memory (LTM) and working memory (WM) tasks. You can find the codebook in the codebook/ folder to better understand the data variables and methods.

  1. Download the data from this repository for further analysis.
  2. Refer to codebook/Codebook.pdf for detailed information on the structure and meaning of the variables in the dataset.
  3. Download the analysis scripts of the statistical analysis of our experiments from the zenodo repo listed below, if you wish to re-run the analysis .
  4. Of course, if you want to perform your own analysis, the raw data files should contain everything you need.

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📑 Format

The dataset is structured into two .csv files for each experiment: one for the Working Memory (WM) data and one for the Long-Term Memory (LTM) data. These files contain the raw data that were used in the analysis for the manuscript.

For best results, we recommend using these data files in conjunction with the analysis scripts available in the Zenodo repository for the statistical analysis. The Zenodo repository will provide you with the necessary scripts to reproduce the analyses presented in the manuscript.

👾 Zenodo DOI: [DOI: 10.5281/zenodo.13867139]

:warning: License

This data is made available under the Public Domain Dedication and License v1.0 whose full text can be found at: LICENSE. See also the human readable summary at: summary.

Please see the LICENSE file for details.

📬 Please do not hesitate to contact us (born[at]mpib-berlin.mpg.de) when you have questions about the data or wish to receive them in a different format.

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datacite.yml
Title The RIDER_data
Authors Born,Frieda;Adaptive Memory and Decision Making (AMD), Max Planck Institute for Human Development,Berlin, Germany;ORCID:0009-0002-1214-4864
Spitzer,Bernhard;Adaptive Memory and Decision Making (AMD), Max Planck Institute for Human Development, Berlin, Germany;ORCID:0000-0001-9752-932X
Description Which factors determine whether information temporarily held in working memory (WM) is transferred to long-term memory (LTM)? Previous work has shown that retrieving (“testing”) memories from LTM can benefit their future LTM recall. Here, we examined the extent to which a benefit for subsequent LTM may also occur after retrieval from WM, depending on whether the WM contents were retrieved from a prioritized or deprioritized state. In three experiments, we combined variants of a novel visual WM paradigm with a subsequent surprise LTM recall test.
License Open Data Commons Public Domain Dedication and License (PDDL) v1.0 (https://opendatacommons.org/licenses/pddl/1-0/)
References Born, F., Spitzer, B.: Long-Term Effects of Working Memory Retrieval From Prioritized and Deprioritized States. [doi:tba] (IsSupplementTo)
Born Frieda. (2024). RIDER Analysis Code (v1.0.0) [doi:10.5281/zenodo.13867139] (IsReferencedBy)
Born Frieda. (2024). RIDER Experiment Code (v1.0.0) [doi:10.5281/zenodo.13867798] (IsReferencedBy)
Funding EU; ERC grant ERC-2020-COG-101000972
DFG; 462752742
Keywords cognitive neuroscience
workig memory
long-term memory
attention
behavior
Resource Type Dataset