Adaptive Training and Collective Decision Support Based on Man-Machine Interface
Abstract
The existence of grandmother cells, i.e. hypothetical cells that respond to specific entities with high specificity, have long been theorized. The objective of this project was to develop non-traditional techniques for assessment of cognition and training effectiveness of mixed expertise, collaborative teams. This effort comprised of three specific aims: 1) to develop a portable wireless, real-time f-EEG system for measurement and assessment of cognitive function in response to visual stimuli; 2) to develop algorithms and strategies for detecting significant events to improve situational awareness; and 3) to combine aims 1 and 2 to propose a strategy for collective decision support for mixed expertise, collaborative teams. Through the 8-month STIR duration, the CUA team designed, developed and tested the function of a portable, real-time f-EEG system (Aim 1) and conducted preliminary trials to develop algorithms and strategies to detect significant events in response to visual stimuli and to study the existence of grandmother cells (Aim 2). Preliminary results show that strong and significant personal identification with visual stimuli exhibit unique transmission dynamics and response as compared to viewing generic images. This provides evidence to support the grandmother neuron and may have high potential for providing quantitative assessment of training effectiveness.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 02, 2016
- Accession Number
- AD1010406
Entities
People
- Binh Q. Tran
Organizations
- The Catholic University of America