EEG Many Pipelines
Title: EEG Many Pipelines
SNIC Project: LiU-compute-2022-18
Project Type: LiU Compute
Principal Investigator: Carine Signoret <carine.signoret@liu.se>
Affiliation: Linköpings universitet
Duration: 2022-04-22 – 2022-07-01
Classification: 50101
Keywords:

Abstract

EEGManyPipelines: "This project is inspired by other recent projects involving many independent analysis teams to investigate how different analysts approach a given data set and how analysis approaches affect the obtained results (e.g., Silberzahn et al., 2015; Botvinik-Nezer et al., 2020). The aim of this project is to extend this novel initiative to EEG research. We believe this to be particularly important in the case of EEG data, as compared to other neuroimaging research, analysis pipelines are less standardized (e.g. see Cohen, 2017) and have more degrees of freedom. EEG is the most widespread tool in human neuroscience research with significant impact on research in all fields of psychology and cognitive neuroscience, which, we believe, makes the EEGManyPipelines project a timely and crucial endeavor that we hope will benefit a large part of the cognitive neuroscience community. Participants in this project will get access to an EEG dataset and are invited to analyze the data with an analysis pipeline they deem sensible and representative of their own research. Participants will then report their results and a detailed description of the analysis pipeline back to us. We will use these reports to map the diversity of analysis pipelines and the effect of pipeline parameters on obtained results." I have created a team participating in this project and have EEG datasets to analyse.