In a multi-agent environment, where the outcomes of one's actions change dynamically because they are related to the behavior of other beings, it becomes difficult to make an optimal decision about how to act. Although game theory provides normative solutions for decision making in groups, how such decision-making strategies are altered by experience is poorly understood. These adaptive processes might resemble reinforcement learning algorithms, which provide a general framework for finding optimal strategies in a dynamic environment. Here we investigated the role of prefrontal cortex (PFC) in dynamic decision making in monkeys. As in reinforcement learning, the animal's choice during a competitive game was biased by its choice and reward history, as well as by the strategies of its opponent. Furthermore, neurons in the dorsolateral prefrontal cortex (DLPFC) encoded the animal's past decisions and payoffs, as well as the conjunction between the two, providing signals necessary to update the estimates of expected reward. Thus, PFC might have a key role in optimizing decision-making strategies.

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Although economic theories based on utility maximization account for a range of choice behaviors, utilities must be estimated through experience. Dynamics of this learning process may account for certain discrepancies between the predictions of economic theories and real choice behaviors of humans and other animals. To understand the neural mechanisms responsible for such adaptive decision making, we trained rhesus monkeys to play a simulated matching pennies game. Small but systematic deviations of the animal's behavior from the optimal strategy were consistent with the predictions of reinforcement learning theory. In addition, individual neurons in the dorsolateral prefrontal cortex (DLPFC) encoded 3 different types of signals that can potentially influence the animal's future choices. First, activity modulated by the animal's previous choices might provide the eligibility trace that can be used to attribute a particular outcome to its causative action. Second, activity related to the animal's rewards in the previous trials might be used to compute an average reward rate. Finally, activity of some neurons was modulated by the computer's choices in the previous trials and may reflect the process of updating the value functions. These results suggest that the DLPFC might be an important node in the cortical network of decision making.

Activity of the neurons in the lateral intraparietal cortex (LIP) displays a mixture of sensory, motor, and memory signals. Moreover, they often encode signals reflecting the accumulation of sensory evidence that certain eye movements might lead to a desirable outcome. However, when the environment changes dynamically, animals are also required to combine the information about its previously chosen actions and their outcomes appropriately to update continually the desirabilities of alternative actions. Here, we investigated whether LIP neurons encoded signals necessary to update an animal's decision-making strategies adaptively during a computer-simulated matchingpennies game. Using a reinforcement learning algorithm, we estimated the value functions that best predicted the animal's choices on a trial-by-trial basis. We found that, immediately before the animal revealed its choice, ϳ18% of LIP neurons changed their activity according to the difference in the value functions for the two targets. In addition, a somewhat higher fraction of LIP neurons displayed signals related to the sum of the value functions, which might correspond to the state value function or an average rate of reward used as a reference point. Similar to the neurons in the prefrontal cortex, many LIP neurons also encoded the signals related to the animal's previous choices. Thus, the posterior parietal cortex might be a part of the network that provides the substrate for forming appropriate associations between actions and outcomes.

This exploratory qualitative study was conducted to examine the meaning of career and related concepts for adult American Indians. Eighteen Northern Plains American Indians were interviewed, and the resulting data were analyzed using consensual qualitative research strategies (C. E. Hill, B. J. Thompson, & E. N. Williams, 1997). Five major topic areas emerged from the data: the meaning of career, definitions of success, supportive factors, obstacles, and living in 2 worlds. Within these domains, several categories emerged, with differences noted between those participants with postsecondary education and those with secondary education in 3 of the domains. Following discussion of and comparison of the categories across the 2 groups, implications for future research and theory development are presented. American Indians have long been recognized as having minority status in Western society. In fact, LaFromboise (1998) noted that American Indians have essentially been "aliens in their own land" (p. 138) for the past 100 years. Like other minority status groups, they experience limited access to the educational and occupational opportunities available to members of the dominant culture. This limited access is clearly reflected in employment statistics. American Indian people, as a group, have the highest rate of unemployment and the lowest levels of education in the nation. The U.S. Bureau of the Census (1990) reported that 31% of Native peoples, including American Indian, Eskimo, and Aleut populations, lived below the poverty level (compared with 13% nationally). The Bureau of Indian Affairs (BIA; 1997) offered an even more serious report on the employment situation of American Indians living on or near reservations. Of more than 1.5 million American Indians represented in BIA service areas, more than 760,000 are available for the work force. Of that number, a full 50% are unemployed. Among the 380,000 who are employed, 30% are earning wages below poverty guidelines.