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2
A computational model of the Cambridge gambling task with applications to substance use disorders.
Drug Alcohol Depend. 2020 Jan 1;206:107711. doi: 10.1016/j.drugalcdep.2019.107711. Epub 2019 Nov 3.
3
What the Future Holds and When: A Description-Experience Gap in Intertemporal Choice.
Psychol Sci. 2019 Aug;30(8):1218-1233. doi: 10.1177/0956797619858969. Epub 2019 Jul 18.
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Three gaps and what they may mean for risk preference.
Philos Trans R Soc Lond B Biol Sci. 2019 Feb 18;374(1766):20180140. doi: 10.1098/rstb.2018.0140.
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Impulsivities and addictions: a multidimensional integrative framework informing assessment and interventions for substance use disorders.
Philos Trans R Soc Lond B Biol Sci. 2019 Feb 18;374(1766):20180137. doi: 10.1098/rstb.2018.0137.
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Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications.
Philos Trans R Soc Lond B Biol Sci. 2019 Feb 18;374(1766):20180128. doi: 10.1098/rstb.2018.0128.
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The Outcome-Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling Task.
Cogn Sci. 2018 Nov;42(8):2534-2561. doi: 10.1111/cogs.12688. Epub 2018 Oct 5.
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Modeling Individual Differences in the Go/No-go Task with a Diffusion Model.
Decision (Wash D C ). 2018 Jan;5(1):42-62. doi: 10.1037/dec0000065. Epub 2016 Aug 15.
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A meta-analytic review of two modes of learning and the description-experience gap.
Psychol Bull. 2018 Feb;144(2):140-176. doi: 10.1037/bul0000115. Epub 2017 Dec 14.
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Factor analysis linking functions for simultaneously modeling neural and behavioral data.
Neuroimage. 2017 Jun;153:28-48. doi: 10.1016/j.neuroimage.2017.03.044. Epub 2017 Mar 22.

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