Kay A. Robbins

Capturing the nature of events and event context using Hierarchical Event Descriptors (HED)

The paper introduces HED for event annotation in neuroimaging data, demonstrating its application to a BIDS dataset and providing best practices for event design and annotation.

EEG-Beats: Automated analysis of heart rate variability (HVR) from EEG-EKG

EEG-Beats automatically detects interbeat intervals and calculates HRV metrics from EEG-EKG signals, providing artifact-robust and synchronized HRV analysis.

How Sensitive are EEG Results to Preprocessing Methods: A Benchmarking Study

This study benchmarks EEG preprocessing methods by analyzing their impact on signal and event-related measures across multiple studies.

Automated EEG mega-analysis I: Spectral and amplitude characteristics across studies

This paper performs a large-scale EEG mega-analysis across 18 studies, showing that automated processing and consistent metadata enable channel- and source-level insights into spectral and amplitude characteristics.

Automated EEG mega-analysis II: Cognitive aspects of event related features

This paper performs a large-scale EEG analysis across 17 studies to identify cognitive aspects of event-related responses using HED tags and RSA, showing significant similarities in annotated features across diverse conditions.