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, Turkey, 24 - 26 April 2019 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2019.8806456
  • City: Sivas
  • Country: Turkey


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.