Browsing by Subject "Decision making"

Causal inference methods are commonly used across domains to aid high-stakes decision-making. The validity of causal studies often relies on strong assumptions that might not be realistic in high-stakes scenarios. Inferences based on incorrect assumptions frequently result in sub-optimal decisions with high penalties and long-term consequences. Unlike prediction or machine learning methods, it is particularly challenging to evaluate the performance of causal methods using just the observed data because the ground truth causal effects are missing for all units. My research presents frameworks to enable validation of causal inference methods in one of the following three ways: (i) auditing the estimation procedure by a domain expert, (ii) studying the performance using synthetic data, and (iii) using placebo tests to identify biases. This work enables decision-makers to reason about the validity of the estimation procedure by thinking carefully about the underlying assumptions. Our Learning-to-Match framework is an auditable-and-accurate approach that learns an optimal distance metric for estimating heterogeneous treatment effects. We augment Learning-to-Match framework with pharmacological mechanistic knowledge to study the long-term effects of untreated seizure-like brain activities in critically ill patients. Here, the auditability of the estimator allowed neurologists to qualitatively validate the analysis via a chart-review. We also propose Credence, a synthetic data based framework to validate causal inference methods. Credence simulates data that is stochastically indistinguishable from the observed data while allowing for user-designed treatment effects and selection biases. We demonstrate Credence's ability to accurately assess the relative performance of causal estimation techniques in an extensive simulation study and two real-world data applications. We also discuss an approach to combines experimental and observational studies. Our approach provides a principled approach to test for the violations of no-unobserved confounder assumption and estimate treatment effects under this violation.

One of the outstanding goals of neuroscience is to understand how neural circuits are assembled to produce context appropriate behavior. In an ever changing environment, it is critical for animals to be able to flexibly respond to different stimuli to optimize their behavioral responses accordingly. Oviposition, or the process of choosing where to lay eggs, is an important behavior for egg-laying animals, yet the neural mechanisms of this behavior are still not completely understood. Here, we use the genetically tractable organism, Drosophila melanogaster, to investigate how the brain decides which substrates are best for egg deposition. We show that flies prefer to lay eggs away from UV light and that induction egg-laying correlates with increased movement away from UV. Both egg-laying and movement aversion of UV are mediated through R7 photoreceptors, but only movement aversion is mediated through Dm8 amacrine neurons. We then identify octopaminergic neurons as being potential modulators of egg-laying output. Collectively, this work reveals new insights into the neural mechanisms that govern Drosophila egg-laying behavior.

Humans are able to make adaptive decisions with the goal of obtaining a goal, earning a reward, or avoiding punishment. While much is known about the behavior and corresponding underlying neural mechanism relating to this aspect of decision-making, the field of cognitive neuroscience has focused almost exclusively on how these types of decisions are made in discrete choices where the set of possible actions is comparatively much smaller. We know much less about how human brains are able to make similar types of goal-directed decisions in continuous contexts which are more akin to the types of choices humans make in real-life. Further, how these processes are modified by the presence of other humans whose goals might influence one's own future behavior is currently unknown. Across three empirical studies, I address some of these gaps in the literature by studying human competitive decision-making in a dynamic, control paradigm in which humans interacted with both social and non-social opponents (Chapter 2 and Chapter 4). In Chapter 3, I show that brain regions heavily implicated in social cognition and value-based decision-making also play a role in tracking continuous decision metrics involved in monitoring instantaneous coupling between opponents, advantageous decision timing, and constructing social context. Collectively, the results in this dissertation demonstrate the utility in studying decision-making in less-constrained paradigms with the overall goal of gaining further understanding of how humans make complex, goal-directed decisions closer to real-world conditions.

Making decisions is fundamental to everything we do, yet it can be impaired in various disorders and conditions. While research into the neural basis of decision-making has flourished in recent years, many questions remain about how decisions are instantiated in the brain. Here we explored how primates make abstract decisions and decisions in social contexts, as well as one way to non-invasively modulate the brain circuits underlying decision-making. We used rhesus macaques as our model organism. First we probed numerical decision-making, a form of abstract decision-making. We demonstrated that monkeys are able to compare discrete ratios, choosing an array with a greater ratio of positive to negative stimuli, even when this array does not have a greater absolute number of positive stimuli. Monkeys’ performance in this task adhered to Weber’s law, indicating that monkeys—like humans—treat proportions as analog magnitudes. Next we showed that monkeys’ ordinal decisions are influenced by spatial associations; when trained to select the fourth stimulus from the bottom in a vertical array, they subsequently selected the fourth stimulus from the left—and not from the right—in a horizontal array. In other words, they begin enumerating from one side of space and not the other, mirroring the human tendency to associate numbers with space. These and other studies confirmed that monkeys’ numerical decision-making follows similar patterns to that of humans, making them a good model for investigations of the neurobiological basis of numerical decision-making.

We sought to develop a system for exploring the neuronal basis of the cognitive and behavioral effects observed following transcranial magnetic stimulation, a relatively new, non-invasive method of brain stimulation that may be used to treat clinical disorders. We completed a set of pilot studies applying offline low-frequency repetitive transcranial magnetic stimulation to the macaque posterior parietal cortex, which has been implicated in numerical processing, while subjects performed a numerical comparison and control color comparison task, and while electrophysiological activity was recorded from the stimulated region of cortex. We found tentative evidence in one paradigm that stimulation did selectively impair performance in the number task, causally implicating the posterior parietal cortex in numerical decisions. In another paradigm, however, we manipulated the subject’s reaching behavior but not her number or color comparison performance. We also found that stimulation produced variable changes in neuronal firing and local field potentials. Together these findings lay the groundwork for detailed investigations into how different parameters of transcranial magnetic stimulation can interact with cortical architecture to produce various cognitive and behavioral changes.

Finally, we explored how monkeys decide how to behave in competitive social interactions. In a zero-sum computer game in which two monkeys played as a shooter or a goalie during a hockey-like “penalty shot” scenario, we found that shooters developed complex movement trajectories so as to conceal their intentions from the goalies. Additionally, we found that neurons in the dorsolateral and dorsomedial prefrontal cortex played a role in generating this “deceptive” behavior. We conclude that these regions of prefrontal cortex form part of a circuit that guides decisions to make an individual less predictable to an opponent.

Everyday, animals make decisions that require balancing tradeoffs like time delays, uncertainty, and physical effort demands with the prospect of rewards like food or money. The tendency to devalue rewards according to these tradeoffs is also known as discounting and depends on how much subjective value an animal places on a reward. These discounting decisions are supported by different neural systems. The influence of dopamine signaling is well-characterized as a modulator of motivation and decision making. However, the role of dopamine as a marker of interindividual differences of reward sensitivity and valuation is less clearly understood. Using a combination of neuroimaging techniques (functional magnetic resonance imaging and positron emission tomography), behavioral experiments, and meta-analyses, this dissertation identifies how trait-like variation in dopamine function explains the way people differ in their preferences and neural computations of value. Overall, the findings indicate that while dopamine may exert acute influence over reward discounting behavior, these associations may not extend to trait-like differences. Specifically, individual differences in dopamine receptor availability are related to discounting behavior in clinical populations but not healthy adults. Nevertheless, individual differences in dopamine are related to functional brain activation associated with the subjective valuation of rewards—the input to choice behavior. These results highlight that interindividual variation in dopamine is more directly linked to neural computations than observed behaviors and that dopamine-mediated psychopathology does not precisely map on to acute pharmacodynamics.

Attentional processes are critical aspects of the neural, cognitive, and computational mechanisms of decision-making. However, the role of such processes is often not given much focus in decision-making research, especially for studies involving economic decision-making. Here, I present three studies that evaluated the role of attention during decision making. Study 1 evaluated the role of attentional control, such as top-down and bottom-up control, in mediating conflict between internal and external demands on attention to promote optimal task performance in a discrimination decision task. Results from Study 1 provided novel neural insights into the role of attentional control in processing and resolving conflict between internal representations and external stimuli during everyday decision-making. Studies 2 and 3 evaluated the role of selective attention, namely online feature-based selective attention, underlying mechanisms of delay and effort discounting in economic decision-making. Results from these two studies demonstrated the importance of measuring (online and parametrically) and utilizing feature-based selective attention during comparative decision-making tasks to better quantify the cognitive and computational mechanisms underlying behavior and preferences. Taken together, results from all three studies provide important quantitative and qualitative implications for understanding mechanisms of decision-making through the lens of attention.

Humans make a variety of choices every day. Some of these choices are pretty mundane like whether to eat pancakes or oatmeal for breakfast. Others cost a little more, have a little bit of a longer impact, like which vacuum cleaner to buy on Amazon. And finally, there are choices that we don’t make very often—maybe even just once, that have enormous consequences in our lives like whether to choose Duke for graduate school. Deciding to choose one option over a set of alternatives involves imagining the future value that could be obtained by making those choices. Research on value-based decision making has recently begun to assess the impact of memory-related processes in making prospective decisions. Given that remembering the past and imagining the future rely on the same cognitive and neural mechanisms, researchers have investigated how imagining the future and remembering the past shift choice behavior. However, much of this research has focused on relatively abstract choices made in a laboratory setting rather than potentially more impactful long-term decisions that we make in everyday life. Overall, it is unclear to what extent memory-related systems impact a range of choices that humans make in everyday life from minor financial transactions to consequential life choices. Across three studies, I examine the role of the constructive memory process of imagination in decisions between shorter-term monetary rewards available at different temporal delays as well as longer-term consequential life choices like career decisions. Chapter 1 provides a general overview of past research on the role of constructive memory processes in making decisions. In chapter 2 (Study 1), after rehearsal of hypothetical imagined future events, younger adults and older adults made choices between larger-later and smaller-sooner monetary rewards. Some of the trials included a cue that invoked the imagined future event whereas other trials did not include a cue. Younger adults were more likely to choose larger, delayed monetary rewards on trials where the imagined future event was cued compared to trials without a cue. However, older adults did not show an effect of cued imagination. Across age groups, functional neuroimaging data revealed that trials with an imagination cue elicited greater engagement of regions that are part of the default mode network including the posterior cingulate cortex, angular gyrus, and medial prefrontal cortex. This network is commonly engaged during thinking about past memories as well as imagining the future in many studies that did not focus on decision making. Interestingly, this difference in neural activity did not vary across age groups even though the behavioral effect of the cue was limited to younger adults. In Chapter 3, I explore the effects of imagining previous successes and failures on choices between larger-later and smaller-sooner monetary rewards (Studies 2a & 2b). I find no conclusive evidence of differences in decisions based on whether people imagined successes or failures, even when comparing to a non-imagined, emotionally neutral control condition. Finally, in chapter 4, I extend this work into more complex career decision making. In a pilot study (Study 3), greater enjoyment of an imagined future career was associated with increased preference for that career option. Given the small and variable effects of imagining the future on decision making in Studies 1-3, two additional studies (Study 4a & 4b) evaluated the effects on decision making of an individual’s ability to vividly visualize, a different cognitive measure potentially relevant to thinking about and imagining the future. Using multivariate analyses, we found that vividness of visual imagery along with a set of individual difference measures related to future time perspective, self-efficacy, and well-being were associated with a set of variables crucial to career decision making. Together, these studies qualify our understanding of the role of imagination and visual imagery in decision making from choices between small rewards in the laboratory and consequential life choices. Overall various forms of imagination had relatively small and inconsistent effects on both laboratory-based and real-world decisions, whereas visual imagery had a moderate and consistent shared effect on real world decisions. The findings have broad implications for guiding prospective decisions in humans across the life span. For example, educational institutions currently have little to no focus on imagination and imagery in guiding developing students toward their future lives. There are critical opportunities in higher education to integrate imagination and imagery into living and learning communities to support students in their transitions to independent and rewarding careers.

Psychological research on aging typically characterizes it as a period of decline. Numerous studies have reported age-related deficits in episodic memory, sensory perception, and fluid intelligence. These reports only add to society’s negative views of aging, which inevitably have a detrimental impact on older adults’ cognition, health, and general well-being. However, there are several other domains of cognition that remain stable or improve during healthy aging. For example, emotional functioning increases with age: older adults can better regulate their emotions and resist their desires compared to younger adults. Older adults are also more skilled at solving interpersonal problems and display intact implicit and procedural memory. This dissertation highlights two other areas that show improvement with age (i.e., decision making and knowledge) and considers how we can use these positive aspects to offset the negative aspects of aging. Chapter 2 investigates heuristic decision making. While some work suggests that older adults are more reliant on these shortcuts, there is little evidence to support this claim. To clarify this issue, participants from across the adult lifespan solved decision scenarios that tapped each of the following classic heuristics: anchoring, availability, recognition, representativeness, and sunk cost fallacy. Chapter 3 further explores knowledge. While the literature confirms that knowledge increases across the lifespan, it is unclear 1) if people are generally aware of this increase and 2) whether they hold expectations about the scope of younger vs. older adults' knowledge. To address these questions, younger and older participants predicted the knowledge of hypothetical younger and older adults. Chapter 4 focuses on application. While many studies have demonstrated that negative aging stereotypes negatively impact older adults’ memory performance, research on positive aging stereotypes’ influence is still inconclusive. In order to address this gap, older participants demonstrated their memory performance before and after viewing a neutral intervention or positive stereotype intervention about their knowledge advantage. Altogether, I find that older adults continue to use cognitively efficient decision strategies; they are not more reliant on classic heuristics and use them to the same degree as younger adults. Furthermore, I demonstrate that adults of all ages recognize that older individuals have a knowledge advantage over younger individuals, regardless of the difficulty of the information. Critically, if older adults are reminded of this advantage, they remember more words during a memory test. Taken together, this body of work sheds light on the cognitive improvements that accompany healthy aging and considers ways to leverage these positive aspects, with the goal of offsetting age-related deficits and promoting positive self-perceptions of aging.

A key debate in nutrition research is whether highly processed foods uniquely reinforce consumption and if, in being uniquely reinforcing, highly processed foods cause overeating and obesity. To that end, overarching goal of my dissertation was to examine the mechanisms through which food motivates appetitive behavior and how relative differences in these processes predict differences in eating behavior.

Here we cover three studies where participants are asked to make choices to earn food rewards. In each study, we examine how participants form action-reward contingency estimations and reward magnitude estimations through learning and how their choices reflect differences in the underlying decision processes. In chapter two, we show that when you reinforce behavior with a food rather than money, differences in reward magnitude estimation predict differences in behavior. Our results demonstrate that a key feature of natural reinforcers like food – that reward magnitude diminishes as a function of consumption due to changes in internal state – is observable in participants’ decision-making. In chapter three, we find that a large subset of children, whose choices appear as if they are trying to lose, were using a choice strategy that would be nearly optimal given a plausible (albeit false) assumption about the experimental environment. Our results indicate that children can form computationally complex models of their environment; however, their choices can be maladaptive if those models are incorrect. In chapter four, we examined how individual differences in action-reward contingency estimation and estimated reward magnitude for food rewards predicted differences on validated clinical measures associated with weight gain in children. We show preliminary evidence that overall reward magnitude for snack foods, as well as change in reward magnitude, are associated with outcomes on the Child Eating Behavior Questionnaire and the Eating in the Absence of Hunger Task.

Taken together, our results demonstrate that highly processed foods could affect how people make reward magnitude estimations and ultimately make decisions about what and how much to eat. However, the extent to which decision processes affect clinical outcomes like risk for weight gain is unclear. We show that while differences in reward magnitude estimation may not affect cognitive processes underlying the choice of when to stop eating, it may affect choices about portion. Highly processed foods could meaningfully affect portion size selection by altering expectations about how consumption affects internal state. Given the strong association between portion sizes and overall consumption, this suggests a that highly processed foods could trigger meaningful differences in caloric intake by changing what and how much people put on their plates.

Individuals have the tendency to believe that they have complete information when making decisions. In many contexts this propensity allows for swift, efficient, and generally effective decision making. However, individuals cannot always see a representative picture of the world in which they operate. This paper examines judgment in censored environments where a constraint, the censorship point, systematically distorts the sample observed by a decision maker. Random instances beyond the censorship point are observed at the censorship point, while instances below the censorship point are observed at their true value. Many important managerial decisions occur in censored environments, such as inventory, risk-taking, and employee evaluation decisions. This empirical work demonstrates a censorship bias - individuals tend to rely too heavily on the observed censored sample, biasing their beliefs about the underlying population. Further, the censorship bias is exacerbated for higher rates of censorship, higher variance in the population, and higher variability in the censorship points. Evidence from four studies demonstrates how the censorship bias can cause managers to underestimate demand for their goods, over-estimate risk in their environments, and underappreciate the capabilities of their employees, which can lead to undesirable outcomes for organizations.

Humans must integrate information to make decisions. This thesis is concerned with studying neural mechanisms of decision making, and combines tools from economics, psychology, and neuroscience. I employ a neuroeconomic approach to understand the processing of reward information and motivation in the brain, utilizing neural data from functional magnetic resonance imaging (fMRI) to make connections between cognitive neuroscience and economics.

Chapter 1 lays the groundwork for the thesis and provides background on neuroscience, fMRI, and neuroeconomics. Chapter 2 sketches the central challenges of using neuroscience to address economic questions. The first half of the chapter discusses familiar arguments against the integration of neuroscience and economics: behavioral sufficiency and emergent phenomenon. The second half constructs principles for interdisciplinary research linking mechanistic (neuroscience) data to behavioral (economic) phenomena: mechanistic convergence across experiments and biological plausibility in models.

Chapters 3 and 4 employ a nonstandard analysis technique, multivariate pattern analysis (MVPA), to identify brain regions that contain information associated with different types of economic valuation. Chapter 3 uses a combinatoric approach to evaluate how brain regions uniquely contribute to the ability to predict different types of valuation (probabilistic or intertemporal). MVPA shows that early valuation phases for these rewards differ in posterior parietal cortex and suggests computational topographies for different rewards. Chapter 4 employs within- and cross-participant MVPA, which rely on potentially different sources of neural variability, to identify brain regions that contain information about monetary rewards (cash) and social rewards (images of faces). Cross-participant analyses reveal systematic changes in predictive power across multiple brain regions, and individual differences in statistical discriminability in ventromedial prefrontal cortex relate to differences in reward preferences. MVPA thus facilitates mapping behavior to both individual-specific functional organization and general organization of the brain across individuals.

Chapter 5 employs a reward anticipation task to measure variation in relative motivation without observing choices between rewards (money and candy). A reaction-time index captures individual differences in motivation, and heterogeneity in this index maps onto variability in two brain regions: nucleus accumbens and anterior insula. Further, the nucleus accumbens activation mediates the predictive effects of anterior insula. These results show that idiosyncrasies in reward efficacy persist in the absence of a choice environment.

Chapters 6 and 7 conclude the thesis. Chapter 6 complements discussions of neuroeconomics with text analysis of an exhaustive corpus from top economics journals and references from a large set of review articles. The analysis shows a mismatch between topics of importance to economics and prominent concepts in neuroeconomics. I show how neuroeconomics can grow by employing cognitive neuroscience to identify biologically plausible and generalizable models of a broader class of behaviors.

Hypoxic ischemic encephalopathy (HIE) is a serious birth complication of full term infants; 40-60% of affected infants die by 2 years or have severe disabilities. Infants with HIE often have a normal gestation and parents anticipate a healthy birth. HIE can be managed with aggressively with moderate hypothermia < 6 hours of life, cardiopulmonary support, and seizure management. Experimental interventions such as moderate hypothermia > 6 hours of life and umbilical cord stem cell transplant are also available. Additional decision-making for these infants may include long-term developmental therapy, nutritional support, and respiratory support. However, who makes these decisions, what factors influence decision-making and the long-term impact of decision-making on parents and health care providers remains unknown. Therefore, the purpose of this study was to explore parental and health care provider decision-making for infants with HIE.

A longitudinal case study design was used to study 11 cases of infants with HIE. Each case included the infant, the parent, and the infant's providers. Infant medical record data, interviews and questionnaires were used to collect data from infant birth through 6 months of age. Content analysis was used to analyze the interviews. Descriptive statistics were used with the questionnaires. Visualization techniques were used to search for patterns and trends in the assembled data.

All infants required resuscitation and their treatment plans included aggressive care or aggressive and experimental care. The level of parental participation varied with in the first week of life depending on whether the infant was enrolled in experimental interventions plus aggressive care or only aggressive care. Parental hopefulness was lower in parents of infants who received experimental interventions, but the infants receiving experimental interventions were less critically ill than infants who received aggressive care only. Parental stress was also lower among parents of infants who received experimental interventions over the first 2 months of life.

Parents were concerned about the short and long-term impact of HIE, few parents understood that even though their infant had appropriate developmental outcomes at 6-months that did mean that neurological damage occurred. However in one case of an infant, the neurological development became central to the parental decision-making for the infant. Parents became less hopeful as diagnostic examinations continued find more complex conditions that were individually not problematic for the parents, but when the complexity of the infant's illnesses continued to unfold, parents feared that too many complications existed for their daughter to have an acceptable quality of life. Yet, when parents broached the topic of transitioning from aggressive care to palliative care with providers, they were told that withholding/withdrawing treatment was not appropriate for the infant. Not discussing withholding or withdrawing treatment ultimately created conflict between parents and providers due to differences in opinions about the predicted neurological outcomes for the infant. The conflict led to distrust and parents regretted most decisions they made for their infant.

Parental and provider decision-making is complex and many of the decisions within the 6-month trajectory were made within the first 6 hours of birth. Parents felt that the decision-making was appropriate in most cases, but the extent of the infant's injury remains unknown. How parents will evaluate the decision-making when the infant begins to miss developmental milestones is unknown. Results from this dissertation suggest that decision-making is a trajectory and decisions are not made in isolation. Implications for practice include discussing and educating parents during the first 6 months and later about developmental milestones and the importance of continuing therapy, even when the infant appears normal. Providers can also acknowledge to parents, up front, that the extent of the neurological injury is unknown and different providers may have different opinions about the long-term effects. By acknowledging these differences, providers can begin discussing the treatment options with parents and educating them about the specific needs of their infant.

Nudging people towards healthier dietary choices is an important policy tool for treating and preventing obesity. However, most studies of nudging interventions fail to identify how cognitive processes change in response to alterations in choice architecture. Over four experiments, the analysis of choices, response times, eye movements, and Drift Diffusion Modeling revealed that a) health priming alters food attribute weighting, b) word options require more decision processing time than image options, and c) word-induced increases in response time are associated with greater stimulus encoding and accuracy demands. Additional experiments with independent samples largely reproduce the results of these investigations, providing high confidence in the replicated findings and achieving a gold standard in growing scientific replication norms.

Over the past decade there has been an explosion of interest in exploring how attention and reward value can interact with one another during cognition and behavior. This interdisciplinary work has already provided many critical findings that have revolutionized what have traditionally been isolated fields of study. However, there are still many unexplored aspects by which attention and value can interact with one another. Here I advance upon this interdisciplinary work by investigating several aspects of the dynamic interplay between attention and value. In the first three studies I look at how reward can influence attention and assess its neural impact using EEG. I first detail the neural mechanisms underlying reward-driven salience, a phenomenon that describes how reward-associated items receive higher priority during attentional orienting. These findings provide evidence that value-driven salience generates a unique increase in the strength of attentional orienting. In the second study I investigate whether associating distractors with rewards can lead to larger impairments in sustained spatial attention. Results indicate that sustained spatial attention can be resistant to a distractor’s reward-history, highlighting an important boundary condition for reward-related distraction. The objective of the third study was to investigate the neural processes underlying reward expectation and outcome processing, with a focus on how these reward expectations influence attention and attentional orienting. A core finding from this experiment is that outcome valence modulates the strength of attentional orienting, while uncertain outcomes lead to elongated attentional processing. In the fourth and final study I turn to investigating how attention can influence decision making. A burgeoning body of work has shown that attention can be highly predictive of choice, but it has not yet determined how inattention can influence decision processes. To this end I investigated if and how attentional distractors influence nutritional decision making using a combination of behavioral and eye-tracking measures. The results indicate that distractors can interrupt the decision process but that they do not reset it. Collectively, these studies demonstrate the diverse ways in which attention and reward can interact with one another, and how studying these interactions can help us better understand a number of real-world behaviors and circumstances.

The research studies presented as this dissertation constitute a methodologically diverse and conceptually integrative approach to understanding impulsiveness in the context of cognitive control and decision making. Broadly, these findings address the validity of current conceptions of trait impulsiveness, relationships between those traits and brain or laboratory measures of cognitive control, and links between impulsive traits and economic decisions under conditions of delay or uncertainty. The findings presented in this thesis affirm the multidimensional nature of impulsiveness as a construct, and link individual differences in specific impulsive types to behavioral and neurobiological measures of control function. The nature of motor, attentional, and nonplanning impulsive types are contextualized by reference to evidence supporting a broad theory of behavioral control based on hierarchical organization of action, ranging from concrete acts to abstract plans and strategies. We provide evidence linking concrete forms of urgent/motor impulsiveness to behavior and brain activation during response-related control, and more abstract and future-oriented premedititative/nonplanning impulsiveness to strategic control signals in more rostral PFC. Finally, these findings are complemented by causal evidence from a neurostimulation study linking a contextual control network to risky decision making and attentional impulsiveness.

Judgment and decision-making in a healthcare context often involve complex information and difficult tradeoffs. In order to understand key concepts and receive help with difficult decisions, patients may turn to written materials, like informed consent forms. Unfortunately, these materials can actually increase confusion. This dissertation explores the relationship between written health materials and cognitive processes, specifically comprehension, memory, judgment, and decision-making. The first goal was to investigate how language and design affect cognition for informed consent forms. We developed a Standard informed consent form and two Enhanced versions that had simplified language and modified design, and compared comprehension and memory between the three versions. As written health materials undergo changes to make their content more accessible to readers, they also become more fluent. The second goal was to explore how this fluency affects judgments and decision-making, especially for materials that have a negative valence. This question was studied in the context of two competing fluency theories, the Hedonic Fluency Model and the Fluency Amplification Model. We manipulated the fluency of various materials, including medications, diseases, and risks, and asked participants to make several judgments about the fluent and disfluent materials. Our results highlight the complexities and nuances that characterize fluency’s effects.