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Author Lowe, Robert J. ♦ Almer, Alexander ♦ Lindblad, Gustaf ♦ Gander, Pierre ♦ Michael, John ♦ Vesper, Cordula
Source Directory of Open Access Journals (DOAJ)
Content type Text
Publisher Frontiers Media S.A.
File Format HTM / HTML
Date Created 2016-10-04
Copyright Year ©2016
Language English
Subject Domain (in LCC) RC321-571
Subject Keyword Neuropsychiatry ♦ Biological psychiatry ♦ Minimal Architectures ♦ Joint Action ♦ Neurosciences ♦ Social Aff-ATP Hypothesis ♦ Associative Two-Process Theory ♦ Social Value Computation ♦ Emotions ♦ Internal medicine ♦ Medicine
Abstract Joint Action is typically described as social interaction that requires coordination among two or more co-actors in order to achieve a common goal. In this article, we put forward a hypothesis for the existence of a neural-computational mechanism of affective valuation that may be critically exploited in Joint Action. Such a mechanism would serve to facilitate coordination between co-actors permitting a reduction of required information. Our hypothesized affective mechanism provides a value function based implementation of Associative Two-Process theory that entails the classification of external stimuli according to outcome expectancies. This approach has been used to describe animal and human action that concerns differential outcome expectancies. Until now it has not been applied to social interaction. We describe our Affective Associative Two-Process (ATP) model as applied to social learning consistent with an ‘extended common currency’ perspective in the social neuroscience literature. We contrast this to an alternative mechanism that provides an example implementation of the so-called social-specific value perspective. In brief, our Social-Affective ATP mechanism builds upon established formalisms for reinforcement learning (temporal difference learning models) nuanced to accommodate expectations (consistent with ATP theory) and extended to integrate non-social and social cues for use in Joint Action.
ISSN 16625188
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2016-08-01
e-ISSN 16625188
Journal Frontiers in Computational Neuroscience
Volume Number 10

Source: Directory of Open Access Journals (DOAJ)