Disambiguating ambiguity: influence of various levels of uncertainty on neural systems mediating choice

2011 Fall.Includes bibliographical references.Previous studies have dissociated two types of uncertainty in decision making: risk and ambiguity. However, many of these studies have categorically defined ambiguity as a complete lack of information regarding outcome probabilities, thereby precluding the study of how various neural substrates may acknowledge and track levels of ambiguity. The present study provided a novel paradigm designed to address how decisions are made under varying states of uncertainty, ranging from risk to ambiguity. More important, the present study was designed to address limitations of previous studies looking at decision making under uncertainty: explore neural regions sensitive to hidden but searchable information by parametrically controlling the amount of information hidden from the subject by using different levels of ambiguity manipulations instead of just the one, as used in previous studies, and allowed subjects to freely choose the best option. Participants were asked to play one of two lotteries, one uncertain and one certain. Throughout the task, the certain lottery offered to participants was always a 100% chance of winning $1. This was contrasted by the uncertain lottery in which various probabilities of winning (20%, 33%, 50 % or 80%) were combined with different potential gains (2$, 3$, 5$, or 8$) so that expected values ranged from being better, equal or worse than the expected value of the certain lottery. In our lotteries, the probability of winning or losing any given amount of money was indicated along the borders of the wheel, increasing from 0% to 100% in a clockwise direction starting at the 12 o'clock position. For some uncertain lotteries and all certain lotteries, a "dial" explicitly indicated the probability of winning. For some uncertain lotteries, there was no dial to indicate a specific probability. Instead, a blinder that covered a portion of the wheel occluded the dial. This occlusion represented the possible range of percentages in which the actual probability of winning lay. Finally, the blinder covered 15%, 33%, 66%, 80% or 100% of the wheel in order to vary the level of ambiguity. By manipulating the level of ambiguity, we were able to explore neural responses to different types of uncertainty ranging from risk to full ambiguity. Participants completed this task while BOLD contrast images were collected using a 3T MR scanner. Here, we show that both risk and ambiguity share a common network devoted to uncertainty processing in general. Moreover, we found support for the hypothesis that regions of the DLPFC might subserve contextual analysis when search of hidden information is both necessary and meaningful in order to optimize behavior in a decision making task; activation in the DLPFC peaked when the degraded information could be resolved by additional cognitive processing. Our results help to underscore the importance of studying varying degrees of uncertainty, as we found evidence for different neural responses for intermediate and high levels of ambiguity that are easy to ignore depending on how ambiguity is defined. Additionally, our results help reconcile two different accounts of brain activity during ambiguous decision making, one suggesting that uncertainty increases linearly and another suggesting ambiguity processing is greater at intermediate levels. The graded coding of uncertainty we reported may reflect a unified neural treatment of risk and ambiguity as limiting cases of a general system evaluating uncertainty mediated by the DLPFC which then recruits different regions of the prefrontal cortex as well as other valuation and learning systems according to the inherent difficulty of a decision