Browsing by Subject "Decision-making"

Humans make decisions in highly complex physical, economic and social environments. In order to adaptively choose, the human brain has to learn about- and attend to- sensory cues that provide information about the potential outcome of different courses of action. Here I present three event-related potential (ERP) studies, in which I evaluated the role of the interactions between attention and reward learning in economic decision-making. I focused my analyses on three ERP components (Chap. 1): (1) the N2pc, an early lateralized ERP response reflecting the lateralized focus of visual; (2) the feedback-related negativity (FRN), which reflects the process by which the brain extracts utility from feedback; and (3) the P300 (P3), which reflects the amount of attention devoted to feedback-processing. I found that learned stimulus-reward associations can influence the rapid allocation of attention (N2pc) towards outcome-predicting cues, and that differences in this attention allocation process are associated with individual differences in economic decision performance (Chap. 2). Such individual differences were also linked to differences in neural responses reflecting the amount of attention devoted to processing monetary outcomes (P3) (Chap. 3). Finally, the relative amount of attention devoted to processing rewards for oneself versus others (as reflected by the P3) predicted both charitable giving and self-reported engagement in real-life altruistic behaviors across individuals (Chap. 4). Overall, these findings indicate that attention and reward processing interact and can influence each other in the brain. Moreover, they indicate that individual differences in economic choice behavior are associated both with biases in the manner in which attention is drawn towards sensory cues that inform subsequent choices, and with biases in the way that attention is allocated to learn from the outcomes of recent choices.

Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. To mitigate these pressures, people satisfice, foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and “good-enough” decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the manner in which satisficing is spontaneously triggered and accomplished. The aim of this dissertation, therefore, is to characterize cognitive and neural mechanisms underlying human satisficing behavior via tasks that closely model real-life challenges in decision making. Specifically, the empirical studies presented here examine how people solve a novel multi-cue probabilistic classification task under various external and internal pressures, using a set of strategy analyses based on variational Bayesian inference, which can track and quantify shifts in strategies. Results from these behavioral and computational approaches are then applied to model human functional magnetic resonance imaging (fMRI) data to investigate neural correlates of satisficing. The findings indicate that the human cognitive apparatus copes with uncertainty and various pressures by adaptively employing a “Drop-the-Worst” heuristic that minimizes cognitive time and effort investment while preserving the consideration of the most diagnostic cue information.

Financial decision-making in a complex and dynamic world poses many challenges including which information to use, how to filter out distractions, and how to arrive at a decision strategy that balances effort and accuracy in the face of imperfect information and cognitive constraints. Traditional financial education methods that provide more information to consider and thus require expending additional time and energy have had limited efficacy in improving long-term decision-making capacity. The research presented here takes a different approach by exploring the influence of context on the construction of value to elucidate mechanisms in consumer choice that underlie individual differences in decision-making. This approach uses computational modeling to identify the component parts of decision-making, eye tracking to measure attentional processes and information gathering strategies during choice, and functional neuroimaging (fMRI) to characterize how social networks modulate value representations in the brain. Characterizing the underpinnings of decision-making can help pinpoint which individual differences in the decision process lead to different choices. The research presented reveals that patience in intertemporal choice results from rapid, attribute-wise comparison of amounts with minimal attention paid to time information, whereas impatience results from slower integration of time and amount within options. Furthermore, measuring attention in purchasing behavior shows that budget size can influence the value of items through a comparison process with price. Finally, a public social context influences motivation for rewards for self but does not affect motivation to earn for charity. This mechanistic approach to understanding value construction and evidence accumulation in choice can help offer strategies grounded in human cognition for people to better adapt to their financial situation, hopefully increasing the likelihood of longer-term impact.

Public health data show that many everyday reckless behaviors reach a developmental peak in adolescence, with adolescents engaging in more reckless behaviors than both children and adults. In contrast, most studies of decision-making across development do not find laboratory risk-taking to peak in adolescence. Here, I focus on two factors that contribute to the discrepancy between public health and laboratory findings: ambiguity and social context. Everyday decisions tend to involve ambiguous decisions (choices with unknown probabilities), while previous laboratory studies have largely focused on risky decisions (choices with known probabilities). Consequently, little is known about the ambiguity preferences of young children. Across three behavioral studies, I show that ambiguity aversion is absent in 5-year-old children (Chapter 2) and 8- and 9-year-old children (Chapter 3) but present in 15- to 18-year-old adolescents (Chapter 4) and adults (Chapters 2 to 4). The results of Chapters 2 through 4 indicate that the willingness to take ambiguous gambles, like the willingness to take risky gambles, does not peak in adolescence. Everyday decisions also often occur in social contexts when friends are present and outcomes can be shared, whereas most laboratory studies occur in social isolation. In Chapter 5, I use functional magnetic resonance imaging to show that neural response to reward for self and for friend are similar in a sample of young adults (ages 18 to 28), and that neural response to reward linearly decreases with age when participants are watched by their friends but not when they are alone. In Chapter 6, I use behavioral modeling to show that adults value rewards similarly for themselves and for their friend. Adolescents, in contrast, value their own rewards more than those of their friend, but the presence of their friend reduces this valuation difference. The results of Chapters 5 and 6 indicate that the presence of friends prompts adolescents and young adults to engage in behavior that benefits both themselves and their friends. Collectively, the results in this dissertation demonstrate the need to consider contextual influences on decision-making in order to better capture everyday decision behavior in the laboratory.

I investigate people's degree of preference for "blinding" in decision-making: purposefully restricting the information one sees in order to try to form a more accurate evaluation. For example, when grading her students’ papers, a professor might choose to "blind" herself to students’ names by anonymizing them, and thus evaluate the papers on content alone. I propose a theoretical framework of individual-level blinding preferences, outlining various factors that may drive evaluators’ choices to see or blind themselves to potentially biasing information in an impending evaluation. Next, I discuss 8 studies (N = 5,350) and associated replications (N = 3,720) that (a) explore individuals’ preferences for blinding and outline consequences for bias, (b) test the mechanisms driving blinding decisions proposed in my theoretical framework, and (c) explore the efficacy of multiple interventions to encourage a choice to blind one’s judgment. I find that people often choose to see potentially biasing information rather than be blind to it, even though they acknowledge they should be blind and that seeing such information will likely bias their evaluations. I also find that interventions that facilitate deliberative reflection before a blinding choice is made can encourage a choice to be blind. I discuss contributions of these studies to research on mental contamination, inequality reduction in organizations, and social perception, as well as implications of these studies for groups concerned with members’ decision bias.

Issue voting, where citizens select candidates based on their own policy preferences, exists as an ideal form of candidate selection in a representative democracy, with politicians being elected because they match the policy preferences of their constituencies. But, in practice, how much of voter decision-making is driven by political issue information? Much of the literature on this topic has narrowly debated whether the mass public uses issues at all, with influential work concluding that citizens seem largely unable or unwilling to do so. If true, this has important implications for our understanding of democratic accountability and the design of institutions. In this dissertation, I argue the debate of how voters decide is a false dichotomy and that pitting issue voting against non-issue voting has limited our understanding of political decision-making. Through a series of original survey experiments and analysis of multiple panel datasets, I show that voters, hindered by the same cognitive and motivational constraints used by critics to argue against the existence of issue voting, can and do use policy information to inform their vote choice. The results of this dissertation imply that the American voter falls between the ideal issue voter from classical theories of voting and the non-issue voter of recent work in political psychology, promoting guarded optimism toward the public’s ability to maintain ideal democratic principles.

An animal's ability to make adaptive choices is key to its fitness. Thus, the process of determining options, making a decision, evaluating outcomes, and learning from those outcomes to adjust future behavior is a central function of our nervous system. Determining the neural mechanisms of these cognitive processes is a crucial goal. One brain region, the posterior cingulate cortex (CGp), a central hub within the default mode network, is prominently dysregulated in Alzheimer's Disease and schizophrenia. Despite its clinical importance, the posterior cingulate cortex remains an enigmatic nexus of attention, memory, and motivation, all pointing to a role in decision-making. This dissertation is concerned with the role of this brain region in the learning and valuation processes involved in making adaptive choices. Specifically, I used rhesus macaques (Macaca mulatta) to examine the neural activity in posterior cingulate associated with specific learning and valuation -related variables. In the first experiment, I showed that posterior cingulate neurons track decision salience--the degree to which an option differs from a standard--but not the subjective value of a decision. To do this, I recorded the spiking activity of CGp neurons in monkeys choosing between options varying in reward-related risk, delay to reward, and social outcomes, each of which varied in level of decision salience. Firing rates were higher when monkeys chose the risky option, consistent with their risk-seeking preferences, but were also higher when monkeys chose the delayed and social options, contradicting their preferences. Thus, across decision contexts, neuronal activity was uncorrelated with how much monkeys valued a given option, as inferred from choice. Instead, neuronal activity signaled the deviation of the chosen option from the standard, independently of how it differed. The observed decision salience signals suggest a role for CGp in the flexible allocation of neural resources to motivationally significant information, akin to the role of attention in selective processing of sensory inputs. This pointed to a role for CGp in learning rather than subjective value signaling, and the second set of experiments aimed to test the role of CGp in associative learning. I recorded from single CGp neurons in monkeys performing a simple conditional motor association task while varying stimulus familiarity and motivation. CGp neurons responded phasically following commission of errors, and this error signal was modulated by motivation and stimulus novelty. Moreover, slow variations in firing rates tracked variations in learning rate over the course of sessions. Silencing these signals with muscimol impaired learning in low motivational states but spared learning in high motivational states, and spared recall of familiar associations as well. These findings endorse a role for CGp in performance and environment monitoring to regulate learning rate. Collectively, these experiments reshape our understanding of the role of posterior cingulate cortex in cognition, integrate default mode and value-based theories of CGp function, and provide a potential foundation for a circuit-level explication of Alzheimer's Disease and schizophrenia.

Humans are natural politicians. We obsessively collect social information that is both observable (e.g., about third-party relationships) and unobservable (e.g., about others’ psychological states), and we strategically employ that information to manage our cooperative and competitive relationships. To what extent are these abilities unique to our species, and how did they evolve? The present dissertation seeks to contribute to these two questions. To do so, I take a comparative perspective, investigating social decision-making in humans’ closest living relatives, bonobos and chimpanzees. In Chapter 1, I review existing literature on theory of mind—or the ability to understand others’ psychological states—in these species. I also present a theoretical framework to guide further investigation of social cognition in bonobos and chimpanzees based on hypotheses about the proximate and ultimate origins of their species differences. In Chapter 2, I experimentally investigate differences in the prosocial behavior of bonobos and chimpanzees, revealing species-specific prosocial motivations that appear to be less flexible than those exhibited by humans. In Chapter 3, I explore through decision-making experiments bonobos’ ability to evaluate others based on their prosocial or antisocial behavior during third-party interactions. Bonobos do track the interactions of third-parties and evaluate actors based on these interactions. However, they do not exhibit the human preference for those who are prosocial towards others, instead consistently favoring an antisocial individual. The motivation to prefer those who demonstrate a prosocial disposition may be a unique feature of human psychology that contributes to our ultra-cooperative nature. In Chapter 4, I investigate the adaptive value of social cognition in wild primates. I show that the recruitment behavior of wild chimpanzees at Gombe National Park, Tanzania is consistent with the use of third-party knowledge, and that those who appear to use third-party knowledge receive immediate proximate benefits. They escape further aggression from their opponents. These findings directly support the social intelligence hypothesis that social cognition has evolved in response to the demands of competing with one’s own group-mates. Thus, the studies presented here help to better characterize the features of social decision-making that are unique to humans, and how these abilities evolved.

A hallmark of human behavior is serial decision-making, in which decisions are linked across time: the choices we make are informed by our past decisions and, in turn, influence our future decisions. Flexible, accurate goal-directed behavior breaks down when decisions become inconsistent with previous decisions and their outcomes. Such impairments contribute to the difficulty that people with schizophrenia and other psychiatric disorders have functioning in society. While there has been a large amount of research investigating the behavioral and neuronal mechanisms responsible for making individual decisions, there is a dearth of research on serial decision-making. The goal of my work has been to establish the formal study of serial decision-making and provide a psychophysical, computational, and neural foundation for future work. In Study 1, we showed that rhesus monkeys, a prime animal model for decision-making, can perform serial decision-making in a novel rule-selection task. The animals selected behavioral rules rationally and used those rules to flexibly discriminate between complex visual stimuli. In Study 2, we had human and monkey subjects perform variations on the rule-selection task to study how behavioral strategies for serial decision-making are dependent on task characteristics. We developed a set of normative probabilistic behavioral models and used Bayesian model selection to determine which model features best explained the observed behavioral data. Specifically, we found that whether or not humans use sensory information (in addition to reward information) to guide their future decisions is dependent on the lower-level features of the task. In Study 3, we investigated the role of one particular brain region, the supplementary eye field (SEF), in serial decision-making. The SEF is part of frontal cortex and sits at the intersection of oculomotor function and broader cognition, and previous studies have implicated it in linking sequences of decisions. We found that neuronal activity in the SEF encoded the rules used for decisions, predicted the outcomes of future decisions, and reacted to the outcomes of past decisions. The two outcome-related signals match what we expect of control signals necessary for flexibly and adaptively updating stimulus values in accordance with past decisions. Taken together, these three studies demonstrate that serial decision-making strategies are dependent on decision context and that the SEF may contribute to serial decision-making in dynamic environments.

Primates in the wild face complex foraging decisions where they must assess the most valuable of different potential resources to exploit, as well recall the location of options that can be widely distributed. While differences in diet and ecology have long been thought to be an important factor influencing brain evolution in primates, it is less well understood what psychological abilities animals actually use when making foraging decisions. This dissertation examines cognitive domains that play a crucial role in supporting foraging behaviors--spatial memory and decision-making--by integrating both psychological and biological approaches to behavior. In particular, the research presented here examines multiple species of primates to address the cognitive skills that different animals use to solve foraging problems (at the proximate level of analysis), as well as why some species appear to solve such problems differently than other species (at the ultimate level of analysis).

The first goal of the dissertation is to compare closely-related species that vary in ecological characteristics, in order to illuminate how evolution shapes the cognitive skills used in foraging contexts. This component focuses on comparisons between chimpanzees (Pan troglodytes) and bonobos (Pan paniscus), humans' closest extant relatives. In addition, this component reports comparisons amongst strepsirrhines (Lemur catta, Eulemur mongoz, Propithecus coquereli, and Varecia subsp.) to model cognitive evolution in a taxonomic group with greater ecological diversity than Pan. The first two chapters test the hypothesis that more frugivorous species exhibit more accurate spatial memory skills, first by comparing apes' spatial memory abilities (Chapter 2), and then by comparing four species of lemurs on a related set of spatial memory tasks (Chapter 3). In subsequent chapters, I examine apes' decision-making strategies to test the hypothesis that chimpanzees are more willing to pay decision-making costs than are bonobos, due to differences in their feeding ecology. I focus on preferences about the timing of payoffs (Chapter 4); preferences about risk, or the variability in payoffs (Chapters 4 and 5); and preferences about ambiguity, or knowledge about available options (Chapter 6).

The second goal of the dissertation is to compare the psychological mechanisms that human and nonhuman great apes use for foraging, in order to identify potentially human-unique cognitive abilities. In terms of spatial memory, I examine whether other apes also exhibit human-like patterns of spatial memory development (Chapter 2). In terms of decision-making, I examine whether apes exhibit a suite of human-like biases when making value-based choices. In particular, I test whether emotional and motivational processes, which are critical components of human decision-making, also play a role in apes' choices (Chapters 4); whether apes are sensitive to social context when making economic decisions (Chapter 5); and whether apes are sensitive to their degree of knowledge when making choices under uncertainty (Chapter 6). Finally, I directly compare human and ape preferences on a matched task to assess whether humans use any unique psychological abilities when making decisions about risk (Chapter 7). In sum, this dissertation links studies of mechanism with hypotheses about function in order to illuminate the evolutionary roots of human's unique cognitive phenotype.

The goal of this dissertation is to articulate specific modes and mechanisms by which the process of an individual choosing an organization is shaped by (1) the status of the organization, and (2) the attributes of the chooser. I do this with three types of chooser attributes: individual demographics, neighborhood context, and cultural values; and in two settings: choosing a hospital for cancer treatment, and choosing a church to attend and contribute to financially. Chapters 1 and 2 use data from the SEER-Medicare linked database to demonstrate the relationship between chooser (patient) demographics, at both the individual and neighborhood levels, on the likelihood of choosing a "high-status" cancer hospital in California. Chapter 1 does this in multiple ways. First, it shows that a patient's propensity to seek treatment for their cancer is a function of the patient's race, sex, and age, and by the racial makeup of a patient's neighborhood. Second, it shows that a patient's propensity to leave California for treatment is a function of both patient attributes and attributes of the hospitals they choose. Finally, it shows that patient choice of high-status cancer hospitals is moderated by the educational level of the patient's neighborhood. Chapter 2 shows that patient choice of high-status cancer hospitals is moderated by both individual-level race and the racial composition of the patient's neighborhood. Chapter 3 uses data from multiple sources to describe the ways that congregants' cultural values interact with organizational status (denomination) in the church choice process. Specifically, I use the National Congregations study to demonstrate the organization-level returns to nondenominational status on both legitimacy (attendees) and performance (tithes). Nondenominational churches are uniquely successful, even when compared only to conservative churches. I then use over 45,000 individual-level responses from the nationally-representative Religious Landscape/Faith in Flux Survey and Congregational Life Studies to demonstrate the individual-level valuative mechanisms behind organizational returns to categorical ambiguity. Though the settings and attributes differ across the three chapters, they all point to a similar conclusion: candidate choice processes are shaped by attributes of both candidates and choosers, and a neglect of chooser attributes misses important stratification in the choice process.