NeurIPS 2025 EEG Foundation Challenge Now Open

Wed, 10 Sep 2025 00:00:00 +0000

The NeurIPS 2025 EEG Foundation Challenge is now open for submissions! As one of the organizers, I’m excited to invite the global research community to participate in this groundbreaking competition focused on advancing cross-task and cross-subject EEG decoding.

Challenge Overview

This challenge aims to push the boundaries of EEG analysis by developing foundation models capable of generalizing across different tasks and subjects. Participants will work with large-scale EEG datasets to create models that can:

Decode EEG signals across multiple cognitive tasks
Generalize to new subjects without extensive retraining
Handle the inherent variability in EEG data

Key Dates

Challenge Opens: September 2025
Submission Deadline: November 2025
Winners Announced: December 2025 at NeurIPS

Why Participate?

This challenge represents a unique opportunity to:

Contribute to advancing EEG analysis methodologies
Work with unprecedented large-scale EEG datasets
Compete for prizes and recognition at NeurIPS 2025
Collaborate with leading researchers in neuroscience and machine learning

Get Involved

For more information and to register, visit the official challenge website. We look forward to seeing innovative approaches that will shape the future of EEG analysis and brain-computer interfaces.

HBN-EEG: The FAIR implementation of the Healthy Brain Network (HBN) electroencephalography dataset

Thu, 03 Oct 2024 00:00:00 +0000

Download & Explore

📄 Paper - Full research publication
📊 HBN Dataset Portal - Access all 11 dataset releases with technical documentation
📈 Data Dashboard - Explore demographics, mental health patterns, and data quality metrics

Abstract

The Child Mind Institute (CMI) Healthy Brain Network (HBN) project has recorded phenotypic, behavioral, and neuroimaging data from ~5,000 children and young adults between the ages of 5 and 21. Here, we present “analysis-ready” data from its high-density (128-channel) electroencephalographic (EEG) recording sessions formatted as Brain Imaging Data Structure (BIDS) datasets (HBN-EEG) with behavioral and task-condition events annotated using Hierarchical Event Descriptors (HED), making it analysis-ready for many purposes, without ‘forensic’ search for unreported details. We also ensured individual data files data and event integrity and marked inconsistencies. HBN-EEG sessions include six tasks, three with no participant behavioral input and three including button press responses following task instructions. Openly available participant information includes age, gender, and four psychopathology dimensions (internalizing, externalizing, attention, and p-factor) derived from bifactor model of questionnaire data. Currently, HBN-EEG data from more than 3,000 participants is freely available on NEMAR (nemar.org) and OpenNeuro in the form of eleven dataset releases, with further dataset releases to follow. The HBN-EEG dataset is intended to support the development and validation of EEG analysis methods, including machine learning and deep learning approaches, and to facilitate the development of EEG-based biomarkers for psychiatric disorders.

The number of subjects per HBN-EEG dataset release

Citation

@ARTICLE{Shirazi2024-ye,
  title    = "{HBN}-{EEG}: The {FAIR} implementation of the Healthy Brain
              Network ({HBN}) electroencephalography dataset",
  author   = "Shirazi, Seyed Yahya and Franco, Alexandre and Hoffmann, Mauricio
              Scopel and Esper, Nathalia and Truong, Dung and Delorme, Arnaud
              and Milham, Michael and Makeig, Scott",
  journal  = "bioRxiv",
  pages    = "2024.10.03.615261",
  month    =  "3~" # oct,
  year     =  2024,
  doi      = "10.1101/2024.10.03.615261",
  language = "en"
}

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