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The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis

Author(s) / Creator(s)

Paul, Katharina
Short, Cassie Ann
Beauducel, André
Carsten, Hannes Per
Härpfer, Kai
Hennig, Jürgen
Hewig, Johannes
Hildebrandt, Andrea
Kührt, Corinna
Mueller, Erik Malte
Munk, Aisha
Osinsky, Roman
Porth, Elisa
Riesel, Anja
Rodrigues, Johannes
Scheffel, Christoph
Stahl, Jutta
Strobel, Alexander
Wacker, Jan

Abstract / Description

: Despite a plethora of research, associations between individual differences in personality and electroencephalogram (EEG) parameters remain poorly understood due to concerns of low replicability and insufficiently powered data analyses due to relatively small effect sizes. The present article describes how a multi-laboratory team of EEG-personality researchers aims to alleviate this unsatisfactory status quo. In particular, the present article outlines the design and methodology of the project, provides a detailed overview of the resulting large-scale dataset that is available for use by future collaborators, and forms the basis for consistency and depth to the methodology of all resulting empirical articles. Through this article, we aim to inform researchers in the field of Personality Neuroscience of the freely available dataset. Furthermore, we assume that researchers will generally benefit from this detailed example of the implementation of cooperative forking paths analysis.

Keyword(s)

personality neuroscience EEG replicability multiverse analysis cooperative forking paths

Persistent Identifier

Date of first publication

2022-06-08

Journal title

Personality Science

Volume

3

Article number

Article e7177

Publisher

PsychOpen GOLD

Publication status

publishedVersion

Review status

peerReviewed

Is version of

Citation

Paul, K., Short, C. A., Beauducel, A., Carsten, H. P., Härpfer, K., Hennig, J., Hewig, J., Hildebrandt, A., Kührt, C., Mueller, E. M., Munk, A., Osinsky, R., Porth, E., Riesel, A., Rodrigues, J., Scheffel, C., Stahl, J., Strobel, A., & Wacker, J. (2022). The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis. Personality Science, 3, Article e7177. https://doi.org/10.5964/ps.7177
  • Author(s) / Creator(s)
    Paul, Katharina
  • Author(s) / Creator(s)
    Short, Cassie Ann
  • Author(s) / Creator(s)
    Beauducel, André
  • Author(s) / Creator(s)
    Carsten, Hannes Per
  • Author(s) / Creator(s)
    Härpfer, Kai
  • Author(s) / Creator(s)
    Hennig, Jürgen
  • Author(s) / Creator(s)
    Hewig, Johannes
  • Author(s) / Creator(s)
    Hildebrandt, Andrea
  • Author(s) / Creator(s)
    Kührt, Corinna
  • Author(s) / Creator(s)
    Mueller, Erik Malte
  • Author(s) / Creator(s)
    Munk, Aisha
  • Author(s) / Creator(s)
    Osinsky, Roman
  • Author(s) / Creator(s)
    Porth, Elisa
  • Author(s) / Creator(s)
    Riesel, Anja
  • Author(s) / Creator(s)
    Rodrigues, Johannes
  • Author(s) / Creator(s)
    Scheffel, Christoph
  • Author(s) / Creator(s)
    Stahl, Jutta
  • Author(s) / Creator(s)
    Strobel, Alexander
  • Author(s) / Creator(s)
    Wacker, Jan
  • PsychArchives acquisition timestamp
    2023-01-23T14:06:49Z
  • Made available on
    2023-01-23T14:06:49Z
  • Date of first publication
    2022-06-08
  • Abstract / Description
    : Despite a plethora of research, associations between individual differences in personality and electroencephalogram (EEG) parameters remain poorly understood due to concerns of low replicability and insufficiently powered data analyses due to relatively small effect sizes. The present article describes how a multi-laboratory team of EEG-personality researchers aims to alleviate this unsatisfactory status quo. In particular, the present article outlines the design and methodology of the project, provides a detailed overview of the resulting large-scale dataset that is available for use by future collaborators, and forms the basis for consistency and depth to the methodology of all resulting empirical articles. Through this article, we aim to inform researchers in the field of Personality Neuroscience of the freely available dataset. Furthermore, we assume that researchers will generally benefit from this detailed example of the implementation of cooperative forking paths analysis.
    en_US
  • Publication status
    publishedVersion
  • Review status
    peerReviewed
  • Citation
    Paul, K., Short, C. A., Beauducel, A., Carsten, H. P., Härpfer, K., Hennig, J., Hewig, J., Hildebrandt, A., Kührt, C., Mueller, E. M., Munk, A., Osinsky, R., Porth, E., Riesel, A., Rodrigues, J., Scheffel, C., Stahl, J., Strobel, A., & Wacker, J. (2022). The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis. Personality Science, 3, Article e7177. https://doi.org/10.5964/ps.7177
    en_US
  • ISSN
    2700-0710
  • Persistent Identifier
    https://hdl.handle.net/20.500.12034/7998
  • Persistent Identifier
    https://doi.org/10.23668/psycharchives.12457
  • Language of content
    eng
  • Publisher
    PsychOpen GOLD
  • Is version of
    https://doi.org/10.5964/ps.7177
  • Is related to
    https://doi.org/10.23668/psycharchives.6671
  • Is related to
    https://doi.org/10.23668/psycharchives.6672
  • Is related to
    https://osf.io/g6u89/
  • Is related to
    https://osf.io/yq3z7
  • Is related to
    https://osf.io/6b7ke
  • Keyword(s)
    personality neuroscience
    en_US
  • Keyword(s)
    EEG
    en_US
  • Keyword(s)
    replicability
    en_US
  • Keyword(s)
    multiverse analysis
    en_US
  • Keyword(s)
    cooperative forking paths
    en_US
  • Dewey Decimal Classification number(s)
    150
  • Title
    The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis
    en_US
  • DRO type
    article
  • Article number
    Article e7177
  • Journal title
    Personality Science
  • Volume
    3
  • Visible tag(s)
    Version of Record
    en_US