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Abstract or Description

In this chapter we discuss how the ACT-R cognitive architecture can be used in combination with fMRI data. ACT-R is a cognitive architecture that can provide a description of the processes from perception through to action for a wide range of cognitive tasks. It has a computational implementation that can be used to create models of specific tasks, which yield exact predictions in the form of response times and accuracy measures. In the last decade, researchers have extended the predictive capabilities of ACT-R to fMRI data. Since ACT-R provides a model of all the components in task performance it can address brain-wide activation patterns. fMRI data can now be used to inform and constrain the architecture, and, on the other hand, the architecture can be used to interpret fMRI data in a principled manner. In the following sections we first introduce cognitive architectures, and ACT-R in particular. Then, on the basis of an example dataset, we explain how ACT-R can be used to create fMRI predictions. In the third and fourth section of this chapter we discuss two ways in which these predictions can be used: region-ofinterest and model-based fMRI analysis, and how the results can be used to inform the architecture and to interpret fMRI data



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Published In

An Introduction to Model-Based Cognitive Neuroscience, B.U. Forstmann, & E.-J. Wagenmakers (Eds.), III, 339-352.