Working Memory in Children Predicts Performance on a Gambling Task

REFERENCES

• Baddeley, A. (1986). Working memory. New York, NY: Clarendon Press/Oxford University Press.
   Google Scholar
• Bechara, A., Damasio, A.R., Damasio, H., & Anderson, S.W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15.
   PubMed Web of Science ®Google Scholar
• Bechara, A., Damasio, H., Tranel, D., & Anderson, S.W. (1998). Dissociation of working memory from decision making within the human prefrontal cortex. The Journal of Neuroscience, 18, 428–437.
   PubMed Web of Science ®Google Scholar
• Busemeyer, J.R., Koling, A., Cox, C.R., & Davis, H. (2005). Older adults as adaptive decision makers: Evidence From the Iowa gambling task. Psychology and Aging, 20, 220–225.
   PubMed Web of Science ®Google Scholar
• Busemeyer, J.R., & Stout, J.C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253–262.
   PubMed Web of Science ®Google Scholar
• Cassotti, M., Houdé, O., & Moutier, S. (2011). Developmental changes of win-stay and loss-shift strategies in decision making. Child Neuropsychology, 17, 400–411.
   PubMed Web of Science ®Google Scholar
• Courage, M.L., & Cowan, N. (2009). The development of memory in infancy and childhood ( 2nd ed.). New York, NY: Psychology Press.
   Google Scholar
• Cowan, N. (1999). An embedded-processes model of working memory. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control. (pp. 62–101). New York, NY: Cambridge University Press.
   Google Scholar
• Cragg, L., & Nation, K. (2007). Self-ordered pointing as a test of working memory in typically developing children. Memory, 15, 526–535.
   PubMed Web of Science ®Google Scholar
• Crone, E.A., Bunge, S.A., Latenstein, H., & van der Molen, M.W. (2005). Characterization of children's decision making: Sensitivity to punishment frequency, not task complexity. Child Neuropsychology, 11, 245–263.
   PubMed Web of Science ®Google Scholar
• Crone, E.A., & van der Molen, M.W. (2004). Developmental changes in real life decision making: Performance on a gambling task previously shown to depend on the ventromedial prefrontal cortex. Developmental Neuropsychology, 25, 251–279.
   PubMed Web of Science ®Google Scholar
• Crone, E.A., & van der Molen, M.W. (2007). Development of decision making in school-aged children and adolescents: Evidence from heart rate and skin conductance analysis. Child Development, 78, 1288–1301.
   PubMed Web of Science ®Google Scholar
• Damasio, A. (1998). The somatic marker hypothesis and the possible functions of the prefrontal cortex. In A.C. Roberts, T.W. Robbins, & L. Weiskrantz (Eds.), The prefrontal cortex: Executive and cognitive functions (pp. 36–50). New York, NY: Oxford University Press.
   Google Scholar
• Dretsch, M.N., & Tipples, J. (2008). Working memory involved in predicting future outcomes based on past experiences. Brain and Cognition, 66, 83–90.
   PubMed Web of Science ®Google Scholar
• Gao, S., Wei, Y., Bai, J., Lin, C., & Li, H. (2009). Young children's affective decision-making in a gambling task: Does difficulty in learning the gain/loss schedule matter? Cognitive Development, 24, 183–191.
   Web of Science ®Google Scholar
• Hinson, J.M., Jameson, T.L., & Whitney, P. (2002). Somatic markers, working memory, and decision making. Cognitive, Affective & Behavioral Neuroscience, 2, 341–353.
   PubMed Web of Science ®Google Scholar
• Hongwanishkul, D., Happaney, K.R., Lee, W.S. C., & Zelazo, P.D. (2005). Assessment of hot and cool executive function in young children: Age-related changes and individual differences. Developmental Neuropsychology, 28, 617–644.
   PubMed Web of Science ®Google Scholar
• Hooper, C.J., Luciana, M., Conklin, H.M., & Yarger, R.S. (2004). Adolescents’ performance on the Iowa gambling task: Implications for the development of decision making and ventromedial prefrontal cortex. Developmental Psychology, 40, 1148–1158.
   PubMed Web of Science ®Google Scholar
• Jacobs, J.E., & Klaczynski, P.A. (2002). The development of judgment and decision making during childhood and adolescence. Current Directions in Psychological Science, 11, 145–149.
   Web of Science ®Google Scholar
• Jameson, T.L., Hinson, J.M., & Whitney, P. (2004). Components of working memory and somatic markers in decision making. Psychonomic Bulletin & Review, 11, 515–520.
   PubMed Web of Science ®Google Scholar
• Kerr, A., & Zelazo, P.D. (2004). Development of « hot » executive function: The children's gambling task. Brain and Cognition, 55, 148–157.
   PubMed Web of Science ®Google Scholar
• Lee, K., & Karmiloff-Smith, A. (2002). Macro- and microdevelopmental research: Assumptions, research strategies, constraints, and utilities. In N. Granott & J. Parziale (Eds.), Microdevelopment: Transition processes in development and learning: Cambridge studies in cognitive perceptual development (pp. 243–292). New York, NY: Cambridge University Press.
   Google Scholar
• Manes, F., Sahakian, B., Clark, L., Rogers, R., Antoun, N., Aitken, M., & Robbins, T. (2002). Decision-making processes following damage to the prefrontal cortex. Brain, 125, 624–639.
   PubMed Web of Science ®Google Scholar
• Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., & Howerter, A. (2000). The unity and diversity of executive functions and their contributions to complex « frontal lobe » tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100.
   PubMed Web of Science ®Google Scholar
• Nesselroade, J.R. (1991). The warp and the woof of the developmental fabric. In R.M. Downs, L.S. Liben, & D.S. Palermo (Eds.), Visions of aesthetics, the environment & development: The legacy of Joachim F. Wohlwill. (pp. 213–240). Hillsdale, NJ: Erlbaum.
   Google Scholar
• Newell, K.M., Mayer-Kress, G., Hong, S.L., & Liu, Y.-T. (2010). Decomposing the performance dynamics of learning through time scales. In P.C. M. Molenaar & K.M. Newell (Eds.), Individual pathways of change: Statistical models for analyzing learning and development. (p. 71–86). Washington, DC: American Psychological Association.
   Google Scholar
• Pecchinenda, A., Dretsch, M., & Chapman, P. (2006). Working memory involvement in emotion-based processes underlying choosing advantageously. Experimental Psychology, 53, 191–197.
   PubMed Web of Science ®Google Scholar
• Petrides, M., & Milner, B. (1982). Deficits on subject-ordered tasks after frontal- and temporal-lobe lesions in man. Neuropsychologia, 20, 249–262.
   PubMed Web of Science ®Google Scholar
• R Core Team. (2012). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
   Google Scholar
• Raftery, A.E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163.
   Web of Science ®Google Scholar
• Reimann, M., & Bechara, A. (2010). The somatic marker framework as a neurological theory of decision-making: Review, conceptual comparisons, and future neuroeconomics research. Journal of Economic Psychology, 31, 767–776.
   Web of Science ®Google Scholar
• Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461–464.
   Web of Science ®Google Scholar
• Siegler, R.S. (1995). How does change occur: A microgenetic study of number conservation. Cognitive Psychology, 28, 225–273.
   PubMed Web of Science ®Google Scholar
• Smith, D.G., Xiao, L., & Bechara, A. (2012). Decision making in children and adolescents: Impaired Iowa Gambling Task performance in early adolescence. Developmental Psychology, 48, 1180–1187.
   PubMed Web of Science ®Google Scholar
• Turnbull, O.H., Evans, C.E. Y., Bunce, A., Carzolio, B., & O’Connor, J. (2005). Emotion-based learning and central executive resources: An investigation of intuition and the Iowa gambling task. Brain and Cognition, 57, 244–247.
   PubMed Web of Science ®Google Scholar
• Van Duijvenvoorde, A.C. K., Jansen, B.R. J., Bredman, J.C., & Huizenga, H.M. (2012). Age-related changes in decision making: Comparing informed and noninformed situations. Developmental Psychology, 48, 192–203.
   PubMed Web of Science ®Google Scholar
• Wainwright, P.E., Leatherdale, S.T., & Dubin, J.A. (2007). Advantages of mixed effects models over traditional ANOVA models in developmental studies: A worked example in a mouse model of fetal alcohol syndrome. Developmental Psychobiology, 49, 664–674.
   PubMed Web of Science ®Google Scholar
• Wetzels, R., Vandekerckhove, J., Tuerlinckx, F., & Wagenmakers, E.-J. (2010). Bayesian parameter estimation in the expectancy valence model of the Iowa gambling task. Journal of Mathematical Psychology, 54, 14–27.
   Web of Science ®Google Scholar