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Updated: Mar 26, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
The neural dynamics of reward value and risk coding in the human orbitofrontal cortex
Yansong Li1, Giovanna Vanni-Mercier1, Jean Isnard2
11 Neuroeconomics, Reward and Decision-making Team, Cognitive Neuroscience Centre, CNRS UMR 5229, Bron 69675, France 2 Université Claude Bernard Lyon 1, Lyon 69100, France.
Abstract:
The orbitofrontal cortex is known to carry information regarding expected reward, risk and experienced outcome. Yet, due to inherent limitations in lesion and neuroimaging methods, the neural dynamics of these computations has remained elusive in humans. Here, taking advantage of the high temporal definition of intracranial recordings, we characterize the neurophysiological signatures of the intact orbitofrontal cortex in processing information relevant for risky decisions. Local field potentials were recorded from the intact orbitofrontal cortex of patients suffering from drug-refractory partial epilepsy with implanted depth electrodes as they performed a probabilistic reward learning task that required them to associate visual cues with distinct reward probabilities. We observed three successive signals: (i) around 400 ms after cue presentation, the amplitudes of the local field potentials increased with reward probability; (ii) a risk signal emerged during the late phase of reward anticipation and during the outcome phase; and (iii) an experienced value signal appeared at the time of reward delivery. Both the medial and lateral orbitofrontal cortex encoded risk and reward probability while the lateral orbitofrontal cortex played a dominant role in coding experienced value. The present study provides the first evidence from intracranial recordings that the human orbitofrontal cortex codes reward risk both during late reward anticipation and during the outcome phase at a time scale of milliseconds. Our findings offer insights into the rapid mechanisms underlying the ability to learn structural relationships from the environment.
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