No abstract

To achieve a goal, animals procure immediately available rewards, escape from aversive events, or endure the absence of rewards. The neuronal substrates for these goal-directed actions include the limbic system and the basal ganglia. In the striatum, tonically active neurons (TANs), presumed cholinergic interneurons, were originally shown to respond to reward-associated stimuli and to evolve their activity through learning. Subsequent studies revealed that they also respond to aversive event-associated stimuli such as an airpuff on the face and that they are less selective to whether the stimuli instruct reward or no reward. To address this paradox, we designed a set of experiments in which macaque monkeys performed a set of visual reaction time tasks while expecting a reward, during escape from an aversive event, and in the absence of a reward. We found that TANs respond to instruction stimuli associated with motivational outcomes (312 of 390; 80%) but not to unassociated ones (51 of 390; 13%), and that they mostly differentiate associated instructions (217 of 312; 70%). We also found that a higher percentage of TANs in the caudate nucleus respond to stimuli associated with motivational outcomes (118 of 128; 92%) than in the putamen (194 of 262; 74%), whereas a higher percentage of TANs in the putamen respond to go signals for the lever release (112 of 262; 43%) than in the caudate nucleus (27 of 128; 21%), especially for an action expecting a reward. These findings suggest a distinct, pivotal role of TANs in the caudate nucleus and putamen in encoding instructed motivational contexts for goal-directed action planning and learning.

Animals monitor the outcome of their choice and adjust subsequent choice behavior using the outcome information. Together with the anterior cingulate cortex (ACC), the lateral habenula (LHb) has recently attracted attention for its crucial role in monitoring negative outcome. To investigate their contributions to subsequent behavioral adjustment, we recorded single-unit activity from the LHb and ACC in monkeys performing a reversal learning task. The monkey was required to shift a previous choice to the alternative if the choice had been repeatedly unrewarded in past trials. We found that ACC neurons stored outcome information from several past trials, whereas LHb neurons detected the ongoing negative outcome with shorter latencies. ACC neurons, but not LHb neurons, signaled a behavioral shift in the next trial. Our findings suggest that, although both the LHb and the ACC represent signals associated with negative outcome, these structures contribute to subsequent behavioral adjustment in different ways.

Experimental economic techniques have been widely used to evaluate human risk attitudes, but how these measured attitudes relate to overall individual wealth levels is unclear. Previous noneconomic work has addressed this uncertainty in animals by asking the following: (i) Do our close evolutionary relatives share both our risk attitudes and our degree of economic rationality? And (ii) how does the amount of food or water one holds (a nonpecuniary form of "wealth") alter risk attitudes in these choosers? Unfortunately, existing noneconomic studies have provided conflicting insights from an economic point of view. We therefore used standard techniques from human experimental economics to measure monkey risk attitudes for water rewards as a function of blood osmolality (an objective measure of how much water the subjects possess). Early in training, monkeys behaved randomly, consistently violating first-order stochastic dominance and monotonicity. After training, they behaved like human choosers-technically consistent in their choices and weakly risk averse (i.e., risk averse or risk neutral on average)-suggesting that well-trained monkeys can serve as a model for human choice behavior. As with attitudes about money in humans, these risk attitudes were strongly wealth dependent; as the animals became "poorer," risk aversion increased, a finding incompatible with some models of wealth and risk in human decision making. utility | satietyWhat We Know About Humans. Significant headway has been made toward understanding human choice behavior under risk. At a theoretical level, any logically consistent chooser behaves as if he consults a continuous monotonic internal representation of utility. Choice is then the process of maximizing utility (see ref.1 for a review). At an empirical level, consistent human choosers are typically somewhat risk averse, maximizing a weakly compressive utility function. Logically inconsistent choosers do not reflect such a maximization process (2-5), in principle.Less headway has been made in understanding how wealth level affects risk attitudes. Although a consensus view is that choosers should become less risk averse as wealth levels increase (6-8), solid empirical data have been difficult to obtain because wealth levels are hard to systematically manipulate in humans.What We Know About Animals. The risk attitudes of many species have been assessed, both with and without confirmation that choosers are logically consistent (9-11), with variable and sometimes controversial results (12). Caraco and colleagues (13), for example, found that sparrows were risk averse over food choices in a manner similar to that of humans, but that this depended on how many calories the subjects had already stored internally-a form of primitive consumption-related "wealth" shared by all animals and premonetary humans. When the birds were heavily food deprived (low caloric stores for future consumption or wealth), they became risk seeking. However, later studies in starlings challenged this conclusion, suggestin...