Local pattern classification differentiates processes of economic valuation.

Published

Journal Article

For effective decision making, individuals must be able to form subjective values from many types of information. Yet, the neural mechanisms that underlie potential differences in value computation across different decision scenarios are incompletely understood. Here, we used functional magnetic resonance imaging (fMRI), in conjunction with the machine learning technique of support vector machines (SVM), to identify brain regions that contain unique local information associated with different types of valuation. We used a combinatoric approach that evaluated the unique contributions of different brain regions to model generalization strength. Local voxel patterns in left posterior parietal cortex contained unique information differentiating probabilistic and intertemporal valuation, a result that was not accessible using standard fMRI analyses. We conclude that the early valuation phases for these reward types differ on a fine spatial scale, suggesting the existence of computational topographies along the value construction pathway.

Full Text

Duke Authors

Cited Authors

  • Clithero, JA; Carter, RM; Huettel, SA

Published Date

  • May 2009

Published In

Volume / Issue

  • 45 / 4

Start / End Page

  • 1329 - 1338

PubMed ID

  • 19349244

Pubmed Central ID

  • 19349244

Electronic International Standard Serial Number (EISSN)

  • 1095-9572

International Standard Serial Number (ISSN)

  • 1053-8119

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2008.12.074

Language

  • eng