Value and choice as separable, stable representations in orbitofrontal cortex

Abstract

Value-based decision-making operates on multiple variables--including offer value, choice, expected outcome, and recent history--each functioning at different times in the decision process. Orbitofrontal cortex (OFC) has long been implicated in value-based decision-making, but it is unclear how downstream circuits might read out complex OFC responses into separate representations of the relevant variables to support different cognitive functions at specific times. We recorded from single neurons in OFC while macaque monkeys made cost-benefit decisions to juice offers. Using a novel analysis--optimal targeted dimensionality reduction--we discovered orthogonal, static dimensions (i.e. linear combinations of neurons) that selectively represented the value, choice, and expected reward of the present and, separately, previous offers. The neural composition of most representations was stable over discrete time periods that aligned to concurrent cognitive demands. We applied a new set of statistical methods to determine that the sensitivity, specificity and stability of the representations were greater than expected from the low-level features--dimensionality and temporal smoothness--of the responses alone. The separability and stability of OFC representations suggest a mechanism by which downstream circuits can read out specific task-relevant variables at appropriate times.