Modeling and Decoding Complex Problem Solving Process by Artificial Neural Networks


Akan A. K. , Kivilcim B. B. , AKBAŞ E. , Newman S. D. , YARMAN VURAL F. T.

27th Signal Processing and Communications Applications Conference (SIU), Sivas, Türkiye, 24 - 26 Nisan 2019 identifier identifier

Özet

It is hypothesized that the process of complex problem solving in human brain consists of two basic phases, namely, planning and execution. In this study, we propose a computational model in order to verify this hypothesis. For this purpose, we develop a holistic approach for decoding the planning and execution phases of complex problem solving, using the functional magnetic resonance imaging data (fMRI), recorded when the subjects play the Tower of London (TOL) game.