Events in context-The HED framework for the study of brain, experience and behavior.

Area of Science:

• Neuroscience
• Cognitive Science
• Data Science

Background:

• The brain is a complex dynamic system influenced by past, present, and future experiences.
• Brain activity is driven by continuous sensory and internal experiences across multiple timescales.
• Neuroimaging aims to understand how brain activity supports human experience, cognition, behavior, and health.

Purpose of the Study:

• To introduce an event-related data modeling approach for neuroimaging.
• To highlight the significance of modeling both events and their context for interpreting brain dynamics.
• To demonstrate how Hierarchical Event Descriptors (HED) can enhance data annotation and analysis.

Main Methods:

• Distinguishing between event processes and event markers in time-delimited data.
• Utilizing text annotation of time series neuroimaging data.
• Applying the Hierarchical Event Descriptors (HED) system for event and context modeling.

Main Results:

• Event-related data modeling allows parsing of experience and behavior into discrete events.
• Precise event descriptions enable interpretation of participant experience within event context.
• HED annotation models events and context more effectively than current practices, facilitating analysis.

Conclusions:

• Accurate modeling of events and context is crucial for interpreting neuroimaging data.
• The Hierarchical Event Descriptors (HED) system offers a robust method for annotating neuroimaging data.
• Continued expansion of HED is necessary to meet the evolving demands of neuroimaging research.