It has been proposed that whenever an animal faces several action choices, their neural representations are processed in parallel in frontoparietal cortex and compete in a manner biased by any factor relevant to the decision. We tested this hypothesis by recording single-unit activity in dorsal premotor cortex (PMd) while a monkey performed two delayed center-out reaching tasks. In the one-target task, a single target was presented and its border style indicated its reward value. The two-target task was the same except two targets were presented and the value of each was varied. During the delay period of the one-target task, directionally tuned PMd activity showed no modulation with value. In contrast, during the two-target task, the same neurons showed strong effects of the value associated with their preferred target, always in relation to the value of the other target. Furthermore, the competition between action choices was strongest when targets were furthest apart. This angular distance effect appeared in neural activity as soon as cells became tuned, while modulation by relative value appeared much later. All of these findings can be reproduced by a computational model which suggests that decisions between actions are made through a biased competition taking place within a sensorimotor map of potential actions.

Neurophysiological studies of decision-making have focused primarily on elucidating the mechanisms of classic economic decisions, for which the relevant variables are the values of expected outcomes and action is simply the means of reporting the selected choice. By contrast, here we focus on the particular challenges of embodied decision-making faced by animals interacting with their environment in real time. In such scenarios, the choices themselves as well as their relative costs and benefits are defined by the momentary geometry of the immediate environment and change continuously during ongoing activity. To deal with the demands of embodied activity, animals require an architecture in which the sensorimotor specification of potential actions, their valuation, selection and even execution can all take place in parallel. Here, we review behavioural and neurophysiological data supporting a proposed brain architecture for dealing with such scenarios, which we argue set the evolutionary foundation for the organization of the mammalian brain.

Revealed preference theory provides axiomatic tools for assessing whether individuals make observable choices "as if" they are maximizing an underlying utility function. The theory evokes a tradeoff between goods whereby individuals improve themselves by trading one good for another good to obtain the best combination. Preferences revealed in these choices are modeled as curves of equal choice (indifference curves) and reflect an underlying process of optimization. These notions have far-reaching applications in consumer choice theory and impact the welfare of human and animal populations. However, they lack the empirical implementation in animals that would be required to establish a common biological basis. In a design using basic features of revealed preference theory, we measured in rhesus monkeys the frequency of repeated choices between bundles of two liquids. For various liquids, the animals' choices were compatible with the notion of giving up a quantity of one good to gain one unit of another good while maintaining choice indifference, thereby implementing the concept of marginal rate of substitution. The indifference maps consisted of nonoverlapping, linear, convex, and occasionally concave curves with typically negative, but also sometimes positive, slopes depending on bundle composition. Out-of-sample predictions using homothetic polynomials validated the indifference curves. The animals' preferences were internally consistent in satisfying transitivity. Change of option set size demonstrated choice optimality and satisfied the Weak Axiom of Revealed Preference (WARP). These data are consistent with a version of revealed preference theory in which preferences are stochastic; the monkeys behaved "as if" they had well-structured preferences and maximized utility.marginal rate of substitution | optimal choice | reward | transitivity | axiom T o function properly, the body acquires particular substances contained in objects that are conceptualized as rewards in biology and goods in economics. Even the simplest drinks and foods contain multiple constituents such as amino acids, fats, and carbohydrates and attributes such as taste, color, and temperature. Water has taste and temperature. Beer has famously hundreds of components produced by fermentation. Sandwiches are composed of such constituents as bread, meat, and cheese. Components that can be varied individually may become tradable goods. For a balanced diet, the ancient farmer goes to the market and trades 5 lb of potatoes, of which he has plenty, against 1 lb of meat, of which he has little. Thus, considering biological rewards as multicomponent objects marks the transition to tradable economic goods. Revealed preference theory achieves exactly that: Each reward constitutes a bundle of tradable goods and is formally a vector.In trading, one gives up some quantity of one good to obtain one unit of the other good. As the farmer gives up the minimal amount of potatoes for that 1 lb of meat, he expresses his preference for the two goods. In trying to ob...

Economic choice options contain multiple components and constitute vectorial bundles. The question arises how they are represented by single-dimensional, scalar neuronal signals that are suitable for economic decision-making. Revealed Preference Theory provides formalisms for establishing preference relations between such bundles, including convenient graphic indifference curves. During stochastic choice between bundles with the same two juice components, we identified neuronal signals for vectorial, multi-component bundles in the orbitofrontal cortex of monkeys. A scalar signal integrated the values from all bundle components in the structured manner of the Theory; it followed the behavioral indifference curves within their confidence limits, was indistinguishable between differently composed but equally revealed preferred bundles, predicted bundle choice and complied with an optimality axiom. Further, distinct signals in other neurons coded the option components separately but followed indifference curves as a population. These data demonstrate how scalar signals represent vectorial, multi-component choice options.

Previous studies have shown that neural activity in primate dorsal premotor cortex (PMd) can simultaneously represent multiple potential movement plans, and that activity related to these movement options is modulated by their relative subjective desirability. These findings support the hypothesis that decisions about actions are made through a competition within the same circuits that guide the actions themselves. This hypothesis further predicts that the very same cells that guide initial decisions will continue to update their activities if an animal changes its mind. For example, if a previously selected movement option suddenly becomes unavailable, the correction will be performed by the same cells that selected the initial movement, as opposed to some different group of cells responsible for online guidance. We tested this prediction by recording neural activity in the PMd of a monkey performing an instructed-delay reach selection task. In the task, two targets were simultaneously presented and their border styles indicated whether each would be worth 1, 2, or 3 juice drops. In a random subset of trials (FREE), the monkey was allowed a choice while in the remaining trials (FORCED) one of the targets disappeared at the time of the GO signal. In FORCED-LOW trials the monkey was forced to move to the less valuable target and started moving either toward the new target (Direct) or toward the target that vanished and then curved to reach the remaining one (Curved). Prior to the GO signal, PMd activity clearly reflected the monkey's subjective preference, predicting his choices in FREE trials even with equally valued options. In FORCED-LOW trials, PMd activity reflected the switch of the monkey's plan as early as 100 ms after the GO signal, well before movement onset (MO). This confirms that the activity is not related to feedback from the movement itself, and suggests that PMd continues to participate in action selection even when the animal changes its mind on-line. These findings were reproduced by a computational model suggesting that switches between action plans can be explained by the same competition process responsible for initial decisions.