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dc.contributor.authorMerchan-Clavellino, Ana
dc.contributor.authorSalguero-Alcañiz, María P.
dc.contributor.authorBarbosa, Fernando
dc.contributor.authorAlameda-Bailén, Jose R.
dc.contributor.otherPsicologíaen_US
dc.date.accessioned2019-12-12T08:08:58Z
dc.date.available2019-12-12T08:08:58Z
dc.date.issued2019-10
dc.identifier.issn1664-1078
dc.identifier.urihttp://hdl.handle.net/10498/21977
dc.description.abstractBased on the somatic marker hypothesis (Damasio, 1994), many studies have examined whether or not physiological responses are “somatic markers” that implicitly guide the decision making process. Vegetative or motor reactions that are produced by negative or positive stimuli generate a series of somatic markers. So, when a similar stimuli is encountered in the future, these somatic marks will facilitate favorable decisions and inhibit the disadvantageous ones (Martínez-Selva et al., 2006). The most widely studied physiological responses, as indicators of these markers, are heart rate and the skin conductance response (Damasio, 1994; Bechara et al., 1996). The Iowa Gambling Task (IGT) has been the most widely used tool in this research. The common IGT protocol for psychophysiological studies comprises limited inter-trial intervals, and does not distinguish participants as a function of relevant physiological traits, such as the anticipatory skin conductance response (aSCR). The objectives of this work were to determine whether “somatic markers” guide the decision making process without time restrictions and to examine the effects of opposite aSCR profiles on this process. Participants were 29 healthy subjects, divided into two groups according to positive (C) and negative (􀀀) aSCR. Two different data analysis strategies were applied: firstly, gambling indices were computed and, secondly, we examined the parameters of the probabilistic Prospect Valence Learning (PVL) model in three versions: maximum likelihood estimation (MLE), PVL-Delta and PVL-Decay simulations with Hierarchical Bayesian analysis (HBA) for parameter estimation. The results show a significant group effect in gambling indices, with the aSCRC group presenting lower risk in the decision making process than the aSCR􀀀 group. Significant differences were also observed in the Utility parameter of MLE-PVL, with the aSCR􀀀 group have low sensitivity to feedback outcomes, than aSRCC group. However, data from the PVL simulations do not show significant group differences and, in both cases, the utility value denotes low sensitivity to feedback outcomes.en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.publisherFRONTIERS MEDIA SAen_US
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceFrontiers in Psychology 10:2237en_US
dc.subjectdecision– makingen_US
dc.subjectiowa gambling tasken_US
dc.subjectprospect valence learning modelen_US
dc.subjectpositive anticipatory skin conductanceen_US
dc.subjectnegative anticipatory skin conductanceen_US
dc.titleDecision Making Profile of Positive and Negative Anticipatory Skin Conductance Responders in an Unlimited-Time Version of the IGTen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.identifier.doi10.3389/fpsyg.2019.02237


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Atribución 4.0 Internacional
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