{"repo":"kesslerr/m4d","free":true,"listed":false,"github":"https://github.com/kesslerr/m4d","clone":"git clone https://github.com/kesslerr/m4d.git","description":"How EEG preprocessing shapes decoding performance","language":"Jupyter Notebook","stars":17,"topics":["decoding","eeg","erp","multiverse","preprocessing"],"license":"CC-BY-4.0","category":"dashboards-admin","readme_excerpt":"How EEG preprocessing shapes decoding performance Working title: Multiverse 4 Decoding (m4d) Kessler et al., 2025 , How EEG preprocessing shapes decoding performance. Communications Biology . https://rdcu.be/evH5m - Read article here - Supplementary Information - Read previous versions here - GitHub repository https://github.com/kesslerr/m4d - Zenodo repository (large result files) https://zenodo.org/records/14223514 - An interactive dashboard to explore the impact of changing single preprocessing steps on decoding performance can be found on streamlit. Abstract : EEG preprocessing varies widely between studies, but its impact on classification performance remains poorly understood. To address this gap, we analyzed seven experiments with 40 participants drawn from the public ERP CORE dataset. We systematically varied key preprocessing steps, such as filtering, referencing, baseline interval, detrending, and multiple artifact correction steps, all of which implemented in MNE-Python. Then we performed trial-wise binary classification (i.e., decoding) using neural networks (EEGNet), or time-resolved logistic regressions. Our findings demonstrate that preprocessing choices influenced decoding performance considerably. All artifact correction steps reduced decoding performance across experiments and models, while higher high-pass filter cutoffs consistently increased decoding performance. For EEGNet, baseline correction further increased decoding performance, and for time-resolved","default_branch":null,"files":null,"tree":[],"storefront":"/r/kesslerr","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/kesslerr/m4d/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}