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Computational neuroscience across the lifespan: Promises and pitfalls

van den Bos, Wouter and Bruckner, Rasmus and Nassar, Matthew R. and Mata, Rui and Eppinger, Ben. (2017) Computational neuroscience across the lifespan: Promises and pitfalls. Developmental Cognitive Neuroscience.

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Official URL: http://edoc.unibas.ch/56521/

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Abstract

In recent years, the application of computational modeling in studies on age-related changes in decision making and learning has gained in popularity. One advantage of computational models is that they provide access to latent variables that cannot be directly observed from behavior. In combination with experimental manipulations, these latent variables can help to test hypotheses about age-related changes in behavioral and neurobiological measures at a level of specificity that is not achievable with descriptive analysis approaches alone. This level of specificity can in turn be beneficial to establish the identity of the corresponding behavioral and neurobiological mechanisms. In this paper, we will illustrate applications of computational methods using examples of lifespan research on risk taking, strategy selection and reinforcement learning. We will elaborate on problems that can occur when computational neuroscience methods are applied to data of different age groups. Finally, we will discuss potential targets for future applications and outline general shortcomings of computational neuroscience methods for research on human lifespan development.
Faculties and Departments:07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Sozial-, Wirtschafts- und Entscheidungspsychologie > Cognitive and Decision Sciences (Mata)
UniBasel Contributors:Mata, Rui
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Elsevier
ISSN:1878-9293
e-ISSN:1878-9307
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:17 Nov 2017 12:14
Deposited On:17 Nov 2017 12:14

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