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Individual Differences in Reward-Based Learning Predict Fluid Reasoning Abilities

Cognitive Science, ISSN: 1551-6709, Vol: 45, Issue: 2, Page: e12941
2021
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If you’ve ever got stuck trying to solve a puzzle only to back up and start over, that’s your brain recognizing that your current strategy isn’t working, and that you need a new way to solve the problem, according to new research. With the help of about 200 puzzle-takers, a computer model, and functional MRI (fMRI) images, researchers have learned more about the processes of reasoning and decision

Article Description

The ability to reason and problem-solve in novel situations, as measured by the Raven's Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task performance and real-world outcomes. Here we provide evidence that RAPM performance depends on the ability to reallocate attention in response to self-generated feedback about progress. We propose that such an ability is underpinned by the basal ganglia nuclei, which are critically tied to both reward processing and cognitive control. This hypothesis was implemented in a neurocomputational model of the RAPM task, which was used to derive novel predictions at the behavioral and neural levels. These predictions were then verified in one neuroimaging and two behavioral experiments. Furthermore, an effective connectivity analysis of the neuroimaging data confirmed a role for the basal ganglia in modulating attention. Taken together, these results suggest that individual differences in a neural circuit related to reward processing underpin human fluid reasoning abilities.

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