Novel Computational Methods for Predicting Transitions in Spatiotemporal Neurodynamics between Attention and Mind wandering
Abstract
We aim to build an explorative and predictive model of the brain that is sensitive to the transitions between sustained attention and mind wandering behaviors. Such a predictive model potentially has applications in tracking attention during critical tasks as well as being of medical and diagnostic relevance. Towards this goal, we will develop novel methods for characterizing and predicting the spatio temporal dynamics of the brain. The work will be carried out by applying computational and machine intelligence methods to an existing data set for which prior ethical approval for secondary analysis has been obtained. The methods developed will serve directly in (1) predicting the transitions between attention and mind wandering in terms of neurodynamics, but will also (2) contribute to the general foundation for using neuroscience algortihmics in human machine interface, operator attention monitoring, and (3) may generalize to underpin better understanding and prediction of the patterning of brain activity dynamics in a variety of human activities.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 14, 2022
- Source ID
- FA95501917034
Entities
People
- Chrystopher Nehaniv
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Hertfordshire