Year: 2023
Type: preprint
Abstract: The brain is a complex dynamic system whose current state is inextricably coupled to awareness of current threats and opportunities, bodily sensations, and behavioral goals and decisions in an ever-changing sensory and behavioral context unfolding on multiple time scales. Neuroimaging experiments seek to isolate and focus on individual aspects of these complex dynamics to better understand how human experience, cognition, behavior, and health are supported by brain activity. Here we consider an approach to modeling brain dynamics, experience, and behavior in terms of events in context. We explore the strengths and limitations of this conceptual framework applied to a range of neuroimaging experiment designs including rest, cognitive task performance, behavioral / multimodal, social interactive, and in-the-wild. We discuss the ways that events in neuroimaging experiments have been, are currently, and should best be modeled and recorded, as well as the importance of event context in understanding the nature of the associated brain dynamic processes. We consider the problem of how to model and capture the temporal architecture of neuroimaging experiments so as to discern innate relationships between neurodynamics, behavior, and experience, and suggest how Hierarchical Event Descriptors (HED; hedtags.org) can best be used to model the role of events and evolving event context in neuroimaging research. We describe how the using the HED system can make this information accessible for neuroimaging data analysis, meta-analysis, and mega-analysis, and discuss ways in which the HED system must continue to evolve to serve the evolving needs of neuroimaging research.
Authors: Scott Makeig, Kay Robbins
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4386640507