Abstract
In recent literature from Neuroscience, the adaptive role of the effects of stress on decision making is highlighted. In this chapter, it is addressed how that role can be modelled computationally using a reified adaptive temporal-causal network architecture. The presented network model addresses the so-called disconnect-reconnect adaptation principle. In the first phase of the acute stress suppression of the existing network connections takes place (disconnect), and then in a second phase after some time there is a relaxation of the suppression. This gives room to quickly get rid of old habits that are not applicable anymore in the new stressful situation and start new learning (reconnect) of better decision making, more adapted to this new stress-triggering context.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barsegyan, A., Mackenzie, S.M., Kurose, B.D., McGaugh, J.L., Roozendaal, B.: Glucocorticoids in the prefrontal cortex enhance memory consolidation and impair working memory by a common neural mechanism. Proc. Natl. Acad. Sci. USA 107, 16655–16660 (2010)
de Kloet, E.R., Joëls, M., Holsboer, F.: Stress and the brain: from adaptation to disease. Nat. Rev. Neurosci. 6, 463–475 (2005)
Etkin, A., Prater, K.E., Hoeft, F., Menon, V., Schatzberg, A.F.: Failure of anterior cingulate activation and connectivity with amygdala during implicit regulation of emotional processing in generalized anxiety disorder. Am. J. Psychiatry 167, 545–554 (2010). https://doi.org/10.1176/ajp.2009.09070931 PMID: 201123913
Glass, D.C., Reim, B., Singer, J.E.: Behavioral consequences of adaptation to controllable and uncontrollable noise. J. Exp.Soc. Psychol. 7, 244–257 (1971)
Gok, K., Atsan, N.: Decision-making under stress and its implications for managerial decision-making: a review of literature. Int. J. Bus. Soc. Res. 6(3), 38–47 (2016)
Hermans, E.J., Hencknes, M.J.A.G., Joels, M.: Guillen Fernandes: dynamic adaption of large-scale brain networks in response to acute stressors, Trends Neurosci. 37(6), 304–14 (2014). https://doi.org/10.1016/j.tins.2014.03.006. Epub
Johnstone, T., van Reekum, C.M., Ury, H.L., Klain, N.H., Davidson, R.J.: Failure to regulate: counterproductive recruitment of top-down prefrontal-subcortical circuitry in major depression. J. Neurosci. 27, 8877–8884 (2007). PMID: 17699669
Quaedflieg, C.W.E.M., van de Ven, V., Meyer, T., Siep, N., Merckelbach, H., Smeets, T.: Temporal dynamics of stress-induced alternations of intrinsic amygdala connectivity and neuroendocrine levels. PLoS ONE 10(5), e0124141 (2015). https://doi.org/10.1371/journal.pone.0124141
Radley, J., Morrison, J.: Repeated stress and structural plasticity in the brain. Ageing Res. Rev. 4, 271–287 (2005)
Reser, J.E.: Chronic stress, cortical plasticity and neuroecology. Behave Process. (2016). https://doi.org/10.1016/j.beproc.2016.06.010. Epub
Robinson, B.L., Harper, N.S., McAlpine, D.: Meta-adaptation in the auditory midbrain under cortical influence. Nat. Commun. 7, 13442 (2016)
Sousa, N., Almeida, O.F.X.: Disconnection and reconnection: the morphological basis of (mal)adaptation to stress. Trends in Neurosci. 35(12), 742–51 (2012). https://doi.org/10.1016/j.tins.2012.08.006. Epub 2012 Sep 21
Treur, J.: Verification of temporal-causal network models by mathematical analysis. Vietnam J. Comput. Sci. 3, 207–221 (2016a)
Treur, J.: Network-Oriented Modeling: Addressing Complexity of Cognitive, Affective and Social Interactions. Springer Publishers, Berlin (2016b)
Treur, J.: Network reification as a unified approach to represent network adaptation principles within a network. In: Proceedings of the 7th International Conference on Natural Computing. Lecture Notes in Computer Science, vol. 11324, pp. 344–358. Springer Publishers, Berlin (2018a)
Treur, J.: Multilevel network reification: representing higher order adaptivity in a network. In: Proceedings of the 7th International Conference on Complex Networks and their Applications, ComplexNetworks’18, vol. 1. Studies in Computational Intelligence, vol. 812, pp. 635–651, Springer Publishers, Berlin (2018b)
Treur, J., Mohammadi Ziabari, S.S.: An adaptive temporal-causal network model for decision making under acute stress. In: Nguyen, N.T., Trawinski, B., Pimenidis, E., Khan, Z. (eds.) Computational Collective Intelligence: Proceedings of the 10th International Conference, ICCCI’18, vol. 2. Lecture Notes in Computer Science, vol. 11056, pp. 13–25. Springer Publishers, Berlin (2018)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Treur, J. (2020). A Reified Network Model for Adaptive Decision Making Based on the Disconnect-Reconnect Adaptation Principle. In: Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models. Studies in Systems, Decision and Control, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-31445-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-31445-3_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31444-6
Online ISBN: 978-3-030-31445-3
eBook Packages: EngineeringEngineering (R0)