Abstract
The Damasio's somatic marker hypothesis focuses on the possible influence of the emotional states on the decision making processes. An assessment tool derived form this theory is the Iowa Gambling Task (IGT). The aim of this study was to detect decision-making alterations in relation to the cognitive impairment associated to age (GDS 2). The data analysis was conducted from two perspectives: quantitative, by computing the advantageous versus disadvantageous choices; and qualitative, according to the PVL model parameters. Two groups were analyzed: one consisting of elderly women with cognitive impairment, and another, with no impairment. Regarding the quantitative analysis, the results show significant differences between both groups, indicating that women with cognitive impairment have less advantageous choices than women without impairment; however, from a qualitative point of view, the results show no significant differences between groups in any of the four parameters of the PVL, indicating that execution of women with and without cognitive impairment are similar. In conclusion, it can be argued that the decision-making processes in women with and without cognitive impairment are quantitatively different but qualitatively similar.
Highlights
Cognitive mechanisms of decision making in older women
The Damasio's somatic marker hypothesis focuses on the possible influence of the emotional states on the decision making processes
The aim of this study was to detect decision-making alterations in relation to the cognitive impairment associated to age (GDS 2)
Summary
La hipótesis del marcador somático de Damasio se centra en la influencia que los estados emocionales pueden ejercer sobre los procesos de toma de decisiones. Desde la teoría del marcador somático, se ha empleado como instrumento para evaluar los procesos de toma de decisiones la tarea denominada Iowa Gambling Task (IGT) (Bechara et al, 1994). El rendimiento en esta prueba se analiza a partir del cómputo de elecciones ventajosas frente a desventajosas, mediante los conocidos como Índices Gambling (IG), lo que permite averiguar las diferencias cuantitativas entre sujetos o grupos de sujetos en los procesos de toma de decisiones. Entre los modelos computacionales destaca el Prospective Valence Learning (Ahn, Busemeyer, Wagenmakers y Stout, 2008), (PVL), que define la ejecución de la IGT en base a los siguientes cuatro parámetros (Tabla 1): Utilidad subjetiva (α), controla la curvatura de la función de utilidad y tiene un valor comprendido entre 0 y 1 (0
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