Value signals in the prefrontal cortex predict individual preferences across reward categories

Jörg Gross, Eva Woelbert, Jan Zimmermann, Sanae Okamoto-Barth, Arno Riedl, R. Goebel

Research output: Contribution to journal/periodicalArticleScientificpeer-review

222 Downloads (Pure)

Abstract

Humans can choose between fundamentally different options, such as watching a movie or going out for dinner. According to the utility concept, put forward by utilitarian philosophers and widely used in economics, this may be accomplished by mapping the value of different options onto a common scale, independent of specific option characteristics (Fehr and Rangel, 2011; Levy and Glimcher, 2012). If this is the case, value-related activity patterns in the brain should allow predictions of individual preferences across fundamentally different reward categories. We analyze fMRI data of the prefrontal cortex while subjects imagine the pleasure they would derive from items belonging to two distinct reward categories: engaging activities (like going out for drinks, daydreaming, or doing sports) and snack foods. Support vector machines trained on brain patterns related to one category reliably predict individual preferences of the other category and vice versa. Further, we predict preferences across participants. These findings demonstrate that prefrontal cortex value signals follow a common scale representation of value that is even comparable across individuals and could, in principle, be used to predict choice.

Original languageEnglish
Pages (from-to)7580-6
Number of pages7
JournalThe Journal of neuroscience : the official journal of the Society for Neuroscience
Volume34
Issue number22
DOIs
Publication statusPublished - 28 May 2014

Keywords

  • Adult
  • Choice Behavior
  • Female
  • Forecasting
  • Humans
  • Imagination
  • Individuality
  • Magnetic Resonance Imaging
  • Male
  • Prefrontal Cortex
  • Reward

Fingerprint

Dive into the research topics of 'Value signals in the prefrontal cortex predict individual preferences across reward categories'. Together they form a unique fingerprint.

Cite this