This dashboard provides comprehensive analysis of dataset citations within the NEMAR ecosystem, revealing collaboration patterns, research trends, and the impact of open neuroscience data sharing on the research community.
This is a data visualization dashboard for exploring the Healthy Brain Network EEG dataset. Features age and sex distributions, task availability metrics, mental health correlations, and per-release analysis across 11 dataset releases with over 3,600 participants.
We present a comprehensive framework that standardizes sensor placement in human movement and physiological monitoring applications. Through precise definitions of anatomical landmarks, coordinate systems, and placement protocols, our framework enables reproducible sensor positioning across different applications and laboratories. The system provides quantifiable levels of placement precision and is compatible with existing data-sharing standards like BIDS and HED. This standardization addresses the critical need for consistent sensor placement across applications ranging from clinical biomechanics to consumer wearables, enhancing data quality, reproducibility, and interoperability in human biosensing research.
The Healthy Brain Network EEG Datasets (HBN-EEG) includes 11 dataset releases containing EEG, behavioral data, and rich event annotations from participants aged 5-21 years, supporting large-scale analyses and machine-learning research on mental health.
The HBN-EEG dataset provides a comprehensive collection of high-density EEG recordings from the Healthy Brain Network project, formatted in the Brain Imaging Data Structure (BIDS) standard. This dataset includes annotated behavioral and task-condition events, making it ready for various types of analysis without the need for extensive preprocessing. With data from over 2,600 participants, the HBN-EEG dataset supports the development and validation of EEG analysis methods, including machine learning and deep learning approaches. Additionally, it aims to facilitate the creation of EEG-based biomarkers for psychiatric disorders, offering valuable insights into brain function and mental health.
The Lab Streaming Layer (LSL) presents a software-based solution for synchronizing data streams across multiple instruments in neurophysiological research. Utilizing per-sample time stamps and LAN-based time synchronization, LSL ensures accurate, continuous recording despite varying device clocks. It automatically corrects for network delays and jitters, maintaining data integrity through disruptions. Supporting over 150 device classes and compatible with numerous programming languages, LSL has become a vital tool for integrating diverse data acquisition systems. Its robustness and adaptability have extended its application beyond research, into art, performance, and commercial realms, making it a cornerstone for multimodal data collection and synchronization.