Plebe A. Neurocomputational model of moral behaviour.
BIOLOGICAL CYBERNETICS 2015;
109:685-699. [PMID:
26585964 DOI:
10.1007/s00422-015-0669-z]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Accepted: 11/07/2015] [Indexed: 06/05/2023]
Abstract
Our understanding of human morality has dramatically improved in the last decades, thanks to efforts carried out with scientific methods, in addition to the traditional speculative approach. Substantial contributions and relevant empirical data have come from neuroscience, psychology, genetics, comparative ethology, anthropology, and the social sciences. In this fruitful synergy, one useful approach is still missing: computational modeling. More precisely, a neurocomputational model aimed at simulating forms of moral behavior, to our knowledge, has not yet been designed. The purpose of this work is to start filling this gap, proposing MOral Neural Engine (MONE), a model that simulates the emergence of moral cognition. The neural engine in this model is assumed to be based in frontal areas, specifically the orbitofrontal and the ventromedial prefrontal cortex, and in connections to limbic areas involved in emotions and reward, such as the ventral striatum and the amygdala. Moral cognition is probably the result of a collection of several different neural processes, activated depending on the type of moral problem, each associated with a variety of emotions. This model, in its first implementation, deals with only a single moral situation: stealing someone's food, a transgression that typically elicits guilt, learned in the model from the angry facial expressions of the victim.
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