Human Decision Making  When the medical doctor diagnoses a patient, they are making a decision. When the deer determines whether that sound was due to a hunter approaching or a gust of wind, they are making a decision. All organisms make hundreds of these decisions daily and often are remarkably accurate. Accurate decision making requires knowledge of the category structures (e.g., the symptoms associated with each disease category), knowledge of the base-rates (the prevalence of each disease in the general population), and the costs and benefits of correct and incorrect decisions. Our lab studies human decision-making by manipulating category structures, category base-rates, and the costs and benefits of various decisions, and attempts to determine the underlying brain mechanisms. A fruitful approach has been to compare the decisions made by humans with those made by the "optimal" decision maker. The optimal decision maker is a hypothetical device that maximizes long-run reward, and is very sensitive to category structure, category base-rate, and cost-benefit information. Our studies suggest that each of these factors has a powerful effect on human decision making performance, but that the effects of each are often different from one another. Some interesting findings are that human decision-makers perform better when base-rates are manipulated, and perform less well when costs and benefits are manipulated. In addition, human decision makers tend to have more difficulty when the cost of an incorrect response is large, and have less difficulty when the costs are small. Our lab also studies the effects of different types of feedback on the optimality of decision making in hopes of developing better decision-making training procedures. Several other directions are currently being pursued.   [main page]