Accession Number : AD1020806

Title :   Computational Cognitive Neuroscience Modeling of Sequential Skill Learning

Descriptive Note : Technical Report,01 Jul 2015,30 Jun 2016

Corporate Author : The University of Texas at Austin Austin United States

Personal Author(s) : Schnyer,David S ; Ashby,Gregory F ; Maddox,Todd

Full Text :

Report Date : 21 Sep 2016

Pagination or Media Count : 8

Abstract : The overall aim of this grant proposal was to build a computational cognitive neuroscience model of how the feedback can be optimized in order to influence learning of complex sequential skills. The model was then tested with a rich set of empirical data from aggregate feedback settings that was used to test the model and to facilitate further model development. The impact of the work is broad as it has the potential to change the way that we think about the learning of complex sequential skills that are ubiquitous in the day-to-day lives of military personnel, and it has the potential to lead to the development of training protocols that optimize the learning of sequential skills.

Descriptors :   cognitive science , neurosciences , computational modeling , learning , feedback , brain , Neurobiology

Distribution Statement : APPROVED FOR PUBLIC RELEASE