Categorical encoding of decision variables in orbitofrontal cortex

A fundamental and recurrent question in systems neuroscience is that of assessing what variables are encoded by a given population of neurons. Such assessments are often challenging because neurons in one brain area may encode multiple variables, and because neuronal representations might be categorical (different neurons encoding different variables) or mixed (individual neurons encoding a combination of variables). These issues are particularly pertinent to the representation of decision variables in the orbitofrontal cortex (OFC) – an area implicated in economic choices. Here we present a new algorithm to assess whether a neuronal representation is categorical or mixed, and to identify the encoded variables if the representation is indeed categorical. The algorithm is based on two clustering procedures, one variable-independent and the other variable-based. The two partitions are then compared through adjusted mutual information. The present algorithm overcomes limitations of previous approaches and is widely applicable. We tested the algorithm on synthetic data and then used it to examine neuronal data recorded in the primate OFC during economic decisions. Confirming previous assessments, we found the neuronal representation in OFC to be categorical in nature. We also found that neurons in this area encode the value of individual offers, the binary choice outcome and the chosen value. In other words, during economic choice, neurons in the primate OFC encode decision variables in a categorical way. Author Summary Mental functions such as sensory perception or decision making ultimately rely on the activity of neuronal populations in different brain regions. Much research in neuroscience is devoted to understanding how different groups of neurons support specific brain functions by representing behaviorally relevant variables. In this respect, one important question is whether individual neurons represent single variables, or linear combination of variables. Here we developed a new algorithm to assess this general issue. We then used the algorithm to examine neurons in the orbitofrontal cortex (OFC) recorded while non-human primates performed economic decisions. We found that different neurons represent different variables (categorical encoding). Specifically, neurons in the OFC encoded the value of individual offers, the binary choice outcome, and the chosen value. The present results support the hypothesis that economic decisions are formed within the OFC.