EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes

Z.G. Doborjeh, M. Doborjeh, N. Kasabov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)


This paper proposes a method utilising spiking neural networks (SNN) for modelling, visualising and comparing the brain data under complex mental states. The method was applied to a cognitive task performed by 23 participants while they were making decision on a moral dilemma situation-related task. An SNN evolving spatiotemporal data architecture is used to learn and visualise the neural activity across different brain regions. The model developed allows for studying the patterns of electrical activity of neurons elicited during complex decision making processes such as moral-related tasks. This could be used for predictive analysis of various aspects of human behavior during decision making and for other related cognitive tasks.
Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
ISBN (Electronic)978-1-5090-6014-6
Publication statusPublished (in print/issue) - 12 Jun 2018


  • EEG
  • decision making
  • pattern recognition

Cite this