Shubham Pandey
Sessions
The field of cognitive neuroscience has accumulated a vast amount of EEG data, yet new studies often prioritize fresh data collection over utilizing these existing resources. Repurposing publicly available EEG datasets presents a cost-effective and efficient way to explore novel hypotheses. However, EEG analysis involves complex preprocessing and interpretation steps, where subjective decisions, such as artifact rejection, filtering techniques, and statistical methods, can significantly impact results. To enhance transparency and reliability, a collaborative framework in which more than one researcher independently analyses the same EEG dataset and identifies robust findings can be a significant step forward. This approach not only mitigates individual biases but also promotes best practices in EEG research within the open science movement. In this talk, we highlight the potential of existing EEG datasets, discuss strategies for fostering community-driven EEG analysis, and call for collective collaboration in this endeavor.
The FORRT community has prepared 200+ summaries of Open and Reproducible Science literature. The purpose of these summaries is to reduce some of the burden on educators looking to incorporate open and reproducible research principles into their teaching as well as facilitate the edification of anyone wishing to learn or disseminate open and reproducible science tenets. In this hackathon, we invite you to review the summaries, i.e., checking that the content of the summary faithfully represents the original article and improving the text to your best capacity. Contributors will be acknowledged on the website and those who fulfil our requirements (i.e., 10 reviews) will be invited to co-author any resulting manuscripts. The summaries will serve as a valuable resource for those with limited time or access, promoting educational equity.