Differential Response Patterns in the Striatum and Orbitofrontal Cortex to Financial Reward in Humans: A Parametric Functional Magnetic Resonance Imaging Study

TLDR

Functional imaging studies show that monetary reward activates brain regions overlapping with those for primary reinforcers, and money is an objectively quantifiable reinforcer. The study uses a parametric fMRI design to examine how neural responses vary with systematically changing reward values. Twelve healthy volunteers performed a rewarded target‑detection task while undergoing fMRI, with reward values changing across blocks. The study identified three distinct response patterns: reward‑presence–responsive regions (amygdala, striatum, dopaminergic midbrain), a premotor cortex that increased linearly with reward value, and medial/lateral orbitofrontal foci that responded nonlinearly, peaking at low and high values, indicating functional differentiation within the reward system.

Abstract

Responses to monetary reward in humans have been assessed in a number of recent functional imaging studies, and it is clear that the neuronal substrates of financial reinforcement overlap extensively with regions responding to primary reinforcers, such as food. Money has the practical advantage of being an objectively quantifiable reinforcer. In this study, we exploit this advantage using a parametric functional magnetic resonance imaging design to look at the patterns of responding to systematically varying reward values. Twelve healthy volunteers were scanned during performance of a rewarded target detection task, in which the reward value varied between task blocks. We observed three distinct patterns of responding in different regions. Amygdala, striatum, and dopaminergic midbrain responded to the presence of rewards, regardless of value. In contrast, premotor cortex showed a linear increase in response with increasing reward value. Finally, medial and lateral foci of orbitofrontal cortex responded nonlinearly, such that response was enhanced for the lowest and highest reward values relative to the midrange. These results suggest functional distinction in response patterns within a distributed reward system.