Value and choice as separable and stable representations in orbitofrontal cortex

Abstract

Value-based decision-making requires different variables—including offer value, choice, expected outcome, and recent history—at different times in the decision process. Orbitofrontal cortex (OFC) is implicated in value-based decision-making, but it is unclear how downstream circuits read out complex OFC responses into separate representations of the relevant variables to support distinct functions at specific times. We recorded from single OFC neurons while macaque monkeys made cost-benefit decisions. Using a novel analysis, we find separable neural dimensions that selectively represent the value, choice, and expected reward of the present and previous offers. The representations are generally stable during periods of behavioral relevance, then transition abruptly at key task events and between trials. Applying new statistical methods, we show that the sensitivity, specificity and stability of the representations are greater than expected from the population’s low-level features—dimensionality and temporal smoothness—alone. The separability and stability suggest a mechanism—linear summation over static synaptic weights—by which downstream circuits can select for specific variables at specific times.