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An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency.

Frontiers in psychology

Dai J, Kerestes R, Upton DJ, Busemeyer JR, Stout JC.
PMID: 25814963
Front Psychol. 2015 Mar 12;6:229. doi: 10.3389/fpsyg.2015.00229. eCollection 2015.

The Iowa Gambling Task (IGT) and the Soochow Gambling Task (SGT) are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning (EVL) model and the prospect valence learning (PVL)...

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Dai J, Kerestes R, Upton DJ, et al. An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency. Front Psychol. 2015;6:229doi: 10.3389/fpsyg.2015.00229.
Dai, J., Kerestes, R., Upton, D. J., Busemeyer, J. R., & Stout, J. C. (2015). An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency. Frontiers in psychology, 6229. https://doi.org/10.3389/fpsyg.2015.00229
Dai, Junyi, et al. "An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency." Frontiers in psychology vol. 6 (2015): 229. doi: https://doi.org/10.3389/fpsyg.2015.00229
Dai J, Kerestes R, Upton DJ, Busemeyer JR, Stout JC. An improved cognitive model of the Iowa and Soochow Gambling Tasks with regard to model fitting performance and tests of parameter consistency. Front Psychol. 2015 Mar 12;6:229. doi: 10.3389/fpsyg.2015.00229. eCollection 2015. PMID: 25814963; PMCID: PMC4357250.
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Challenges and promises for translating computational tools into clinical practice.

Current opinion in behavioral sciences

Ahn WY, Busemeyer JR.
PMID: 27104211
Curr Opin Behav Sci. 2016 Oct 01;11:1-7. doi: 10.1016/j.cobeha.2016.02.001.

Computational modeling and associated methods have greatly advanced our understanding of cognition and neurobiology underlying complex behaviors and psychiatric conditions. Yet, no computational methods have been successfully translated into clinical settings. This review discusses three major methodological and practical...

Cite
Ahn WY, Busemeyer JR. Challenges and promises for translating computational tools into clinical practice. Curr Opin Behav Sci. 2016;11:1-7doi: 10.1016/j.cobeha.2016.02.001.
Ahn, W. Y., & Busemeyer, J. R. (2016). Challenges and promises for translating computational tools into clinical practice. Current opinion in behavioral sciences, 111-7. https://doi.org/10.1016/j.cobeha.2016.02.001
Ahn, Woo-Young, and Busemeyer, Jerome R. "Challenges and promises for translating computational tools into clinical practice." Current opinion in behavioral sciences vol. 11 (2016): 1-7. doi: https://doi.org/10.1016/j.cobeha.2016.02.001
Ahn WY, Busemeyer JR. Challenges and promises for translating computational tools into clinical practice. Curr Opin Behav Sci. 2016 Oct 01;11:1-7. doi: 10.1016/j.cobeha.2016.02.001. PMID: 27104211; PMCID: PMC4834893.
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