Neurodynamics of Decision-Making—A Computational Approach

Abstract

Decision-making is a complex process that normally seems to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC), and lateral prefrontal cortex (LPFC) seem to be essential in human decision-making, where both emotional and cognitive aspects are taken into consideration. In this paper, we present a stochastic population model representing the neural information processing of decision-making, from perception to behavioral activity. We model the population dynamics of the three neural structures significant in the decision-making process (amygdala, OFC, and LPFC), as well as their interaction. In our model, amygdala and OFC represent the neural correlates of secondary emotion, while the activity of OFC neural populations represents the outcome expectancy of alternatives, and the cognitive aspect of decision-making is controlled by LPFC. The results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on climate change.

Published in

Advances in cognitive neurodynamics
2016, number: 5, pages: 41-47
Title: Advances in Cognitive Neurodynamics (V)
Publisher: Springer

SLU Authors

• Liljenström, Hans

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    

• Hassannejad, Nazir Azadeh

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    

Global goals (SDG)

SDG13 Climate action

UKÄ Subject classification

Information Science

Publication identifier

• DOI: https://doi.org/10.1007/978-981-10-0207-6_7
• ISBN: 978-981-10-0205-2

Permanent link to this page (URI)

https://res.slu.se/id/publ/73833