TY - JOUR
T1 - EEGManyPipelines
T2 - A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild
AU - Trübutschek, Darinka
AU - Yang, Yu-Fang
AU - Gianelli, Claudia
AU - Cesnaite, Elena
AU - Fischer, Nastassja L
AU - Vinding, Mikkel C
AU - Marshall, Tom R
AU - Algermissen, Johannes
AU - Pascarella, Annalisa
AU - Puoliväli, Tuomas
AU - Vitale, Andrea
AU - Busch, Niko A
AU - Nilsonne, Gustav
N1 - © 2023 Massachusetts Institute of Technology.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project and how it might have a lasting impact on the field.
AB - The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project and how it might have a lasting impact on the field.
KW - Electroencephalography
KW - Humans
KW - Reproducibility of Results
KW - Research Design
UR - http://www.scopus.com/inward/record.url?scp=85183200214&partnerID=8YFLogxK
U2 - 10.1162/jocn_a_02087
DO - 10.1162/jocn_a_02087
M3 - Journal article
C2 - 38010291
SN - 0898-929X
VL - 36
SP - 217
EP - 224
JO - Journal of Cognitive Neuroscience
JF - Journal of Cognitive Neuroscience
IS - 2
ER -