The network architecture of value learning

Marcelo G. Mattar, Sharon L. Thompson-Schill, Danielle S. Bassett

Research output: Contribution to journalArticlepeer-review


Value guides behavior. With knowledge of stimulus values and action consequences, behaviors that maximize expected reward can be selected. Prior work has identified several brain structures critical for representing both stimuli and their values. Yet, it remains unclear how these structures interact with one another and with other regions of the brain to support the dynamic acquisition of value-related knowledge. Here, we use a network neuroscience approach to examine how BOLD functional networks change as 20 healthy human subjects learn the values of novel visual stimuli over the course of four consecutive days. We show that connections between regions of the visual, frontal, and cingulate cortices become stronger as learning progresses, with some of these changes being specific to the type of feedback received during learning. These results demonstrate that functional networks dynamically track behavioral improvement in value judgments, and that interactions between network communities form predictive biomarkers of learning.

Original languageEnglish (US)
Pages (from-to)128-149
Number of pages22
JournalNetwork Neuroscience
Issue number2
StatePublished - Jan 1 2018


  • Behavioral adaptability
  • Brain networks
  • Cognitive systems
  • Functional connectivity
  • Reinforcement learning
  • Valuation system

ASJC Scopus subject areas

  • General Neuroscience
  • Computer Science Applications
  • Artificial Intelligence
  • Applied Mathematics


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