Stephen Read - US grants

In this program of research, a series of experiments tests a parallel processing model of social perception and social explanation. This model differs sharply from the two-stage, serial processing , models that currently dominate much social psychology. One set of studies seeks to demonstrate that when subjects are combining dispositional and situational information, whether they underadjust for either dispositional or situational factors under high cognitive load, and the extent to which they do so, reflects the impact of attentional focus and causal unit formation on the spread of activation in a conceptual network. Such results would contradict Gilbert's (1989) model of dispositonal inference and would, at a minimum, force a major expansion of Krull's (1993) model. A second set of studies attempts to show that just as individuals frequently make spontaneous situational inferences, so do they frequently make spontaneous situaitonal inferences. These studies also seek to show that the latter influences do not require a goal to make such inferences as Krull (1993) suggests, but rather are under the control of the stimulus configuration. Several factors are investigated that may influence the likelihood of spontaneous situational inferences: (1) individualist vs. collectivist beliefs; (2) proximity of the situational causal context to the target behavior; and (3) salience of the situational causal context. A third set of studies examines whether situational and dispositional information can be quickly and spontaneously integrated, in parallel, to make a spontaneous dispositional inference, thereby arguing against models that propose a two step process for the integration of dispositional and situational information. A fourth set of studies will test the hypothesis that factors, such as cognitive load and salience which should reduce the spread of activation from explanations to behavior identifications, will reduce the impact of explanatory hypotheses on the id entification of ambiguous behaviors. This program of research has the potential to replace several special-purpose 'mini' theories of social explanation with a general connectionist model that can handle a wide variety of phenomena. Figuring out the characteristics of others is central to successfully negotiating everyday life. But doing so is surprisingly complicated. This program of research tests a model which seeks to explain how people do this. A central claim of this model is that when people make inferences about the causes of behavior, such as "Sheila was furious", the available information is integrated simultaneously into a limited capacity working memory rather than being processed serially. The implication of this parallel processing of information is that the causal explanation that a person favors (e.g., "Sheila is short tempered" or ""Sheila was insulted") will depend upon things that influence information integration, such as the person's focus of attention, the strength of pre-existing causal links among potential causes and effects, and how much demand is being placed on the person's cognitive capacities by other ongoing tasks. The results will have important implications for our understanding of biases in social perception.

Abstract
SES-0080424
Simon, Dan
Read, Stephen
University of Southern California

Theories of human reasoning are heavily influenced by a number of assumptions derived from formal accounts of deductive logic. A central assumption of these models is that the flow of inferences is unidirectional. The syllogistic, unidirectional nature of the reasoning processes rules out "reverse" inferences in which a person's conclusions might lead to a change in the evaluation of the premises and evidence. Violations of this assumption are viewed as signs of the frailty of human reasoning. In this project, we explore an alternative conception of reasoning and decision-making, one based on a theoretical paradigm called constraint satisfaction mechanisms. Our preliminary research has shown that reasoning entails bi-directional influences among the participating pieces of evidence, premises and conclusions, and that the changes occur mostly without awareness.

This project is a novel attempt to introduce this emerging model of cognition to decision making, particularly in the legal domain. First, we intend to apply it to the issue of evidence integration in the fact-finding phase. We will examine whether the process of evidence integration leads to changes in the evaluation of the individual pieces of evidence. In particular, we will examine cognitive effects on judgments of defendants' mental states, a determination that is crucial to adjudication in tort and criminal law (mens rea). Other studies will examine why decision makers encounter problems with ignoring inadmissible evidence.

The making of a decision can be a difficult and daunting task, as is often manifested both before and after the decision is made, yet at the time of making the decision people generally feel confident, even overconfident. In the second part of the project we intend to explore this relationship among pre-decisional conflict, confident decisions, and post-decisional regret. This issue is especially pertinent to the legal domain, since a central feature of legal culture is that decisions are taken very seriously. Contract law, for example, is based on a concept of reliance, and a failure to fulfill an obligation is considered a breach. There is even less flexibility when it comes to adjudication, wherein decisions announced by judges and jurors are treated as virtually immutable. Given the weightiness of the issues and the closeness of the vying positions often involved in legal transactions and disputes, it is important that we gain a better understanding of these seemingly paradoxical phenomena of conflict, confidence and regret.

The objective of this proposal is to study the cognitive processes that enable effective decision making in a category of tasks that require discrete choices in the face of variables that are numerous, contradictory, ambiguous and incommensurate. Decisions of this kind are encountered in everyday life when we choose a job, purchase a house, or condemn a person to prison. The proposed theoretical framework, termed "coherence-based decision making," posits that throughout the decision making process, the mental representation of the task undergoes gradual change, ultimately shifting towards a state of coherence with either one of the decision alternatives. At the culmination of the process, the decision maker's mental model is skewed towards a state of coherence, with one alternative dominating its rival; the decision follows easily and confidently from this perception of the task.
In this proposal the Investigators plan to buttress and extend their previous work on this theory. The fourteen studies included in this proposal are intended to examine theoretical questions and to provide prescriptions with respect to improving people's ability to respond appropriately to incoming information; better understanding failures to ignore information; reducing the effects of group polarization; improving the process of group deliberation; reducing self-serving biases; taking into consideration the influence of need states on biased judgments; and more. The project is intended also to provide specific prescriptions for decision making in a number of legal contexts, including suggesting ways to better structure legal tasks; better handle exposure to impermissible evidence; reduce jury polarization and improve jury deliberation; provide means for gauging and reducing pre-trial optimistic overconfidence; and provide critical insight into policy questions regarding the regulation of gambling.

DESCRIPTION (provided by applicant): HIV cases continue to rise among men who have sex with men (MSM) with methamphetamine (METH) use contributing. But, we lack understanding of the neural processes underlying MSM's decisions. How might the neural circuitry differ for sexually risky vs. non-sexually risky MSM? How might chronic METH use modify it? We aim to address this gap, using the resulting knowledge to develop novel interventions to reduce risk-taking. Three key neural systems are hypothesized to play a central role in risky decision making: (1) an amygdala- striatal (dopamine-dependent) neural system, which promotes cue-induced habitual behaviors; (2) a prefrontal cortex neural system, which subserves decision-making, executive functioning, and impulse control capacities; and (3) an insular cortex system, which responds to homeostatic and interoceptive signals triggered by states of deprivation, or by exposure to environmental cues that elicit craving. The resulting urge may exacerbate the hypersensitivity of the amygdala-striatal system, or weaken the inhibitory function of the prefrontal system. Magnetic Resonance Imaging techniques applied to decisions, often in virtual environments, in conjunction with computational modeling afford an innovative mix of technologies to systematically investigate, in more realistic contexts, the decision-making processes of METH and non-METH using MSM who chronically engage in risky sex. The volume and gray/white matter density of brain areas in the proposed neural circuit will be quantified for each subject from high resolution MRI scans. DTI (diffusion tensor imaging) will be used to map out the connectivity among the target regions. In addition, the fMRI BOLD responses of these regions will be measured when subjects perform both standard decision-making tasks and make risky sexual decisions in a virtual environment. We will compare: (1) sexually risky MSM who use METH, (2) sexually risky MSM who do not use METH, and (3) non-risky MSM. We will sample from Caucasian, African-American, and Latino MSM. The overarching aim of this proposal is to develop a model of the brain systems involved in risky sexual decision-making for MSM and to understand how dysfunctions in those systems may be related to increases in sexually risky decision-making by both METH using and non-METH using MSM. Our main hypotheses are: H1: Sexually risky MSM will show differential functioning in the dopaminergic, habitual system compared to non-sexually risky men: (H1a) they will take longer to acquire negative contingencies to risky behavior (e.g., money loss or shock) and more quickly acquire positive contingencies, and (H1b) show a tendency to overvalue rewards and underweight risks. H2: Sexual risk takers will show greater activation in the insular cortex (and greater craving or urgency) in response to rewarding stimuli and especially sexual stimuli. H3: Sexual risk takers will show dysfunctions in inhibitory control and executive functioning. Our results on gray/white matter density and connectivity will corroborate those differences between groups. H4: METH use will increase risky sexual decision-making and impact each of the three components of the decision-making circuitry.

DESCRIPTION (provided by applicant): Risky decision-making leads to pervasive negative health outcomes (e.g., alcohol and drug abuse, risky sexual decisions, accidents). One central characteristic of such individuals (e.g., risky men who have sex with men (MSM)) is that they continue to engage in behaviors with very rewarding short-term consequences, but extremely negative long-term consequences, including medical, social and legal problems. Why do they have such difficulties making the right choices? A growing body of research suggests that motivated human decision-making is the result of a dynamic interplay among three systems: (1) a relatively automatic appetitive system, which has been called the Impulsive System, (2) an executive control system, which has been called the Reflective System[11], and (3) a neural system that translates interoceptive signals into what one experiences as a feeling of desire, or urge [5,12] that may help propel individuals towards reward, and inhibit cognitive resources needed for self-control. Unfortunately, we lack a systematic understanding of how these complex neural systems interact with each other and with various social and contextual factors to produce risk-taking, when, for whom, and why. This gap impedes more rapid advancements in prevention and intervention science. Adequate computational tools could help address this critical barrier, and better advance a cumulative science, but they are currently lacking. This project aims to address this gap by developing generalizable computational tools: A validated neurobiologically based, neural network model of the interaction of these systems could transform our ability to advance theory and effective interventions. To this end, a team of social scientists, neuroscientists, and computational neuroscientists will (a) develop biologically-based computational models that leverage and integrate existing neural network models that view behavior as emergent from approach and avoid motivational structures[13,14] and, at a different level of scale, neural network models that simulate the underlying biological basis of incentive processing and learning, executive function, and decision-making [15,16]; (b) test, validate, and refine the model by predicting the neural and behavioral responses of a subsample from 180 young MSM (sexually risky, sexually risky methamphetamine users, and non-risky) from a completed NIDA imaging study on risky decision-making; (c) assess its generalizability via focused tests, and cross validate with additional NIDA data subsamples; and (d) conduct exploratory computational analyses aimed at concurrently predicting MSM's sequential neural and behavioral dynamics in a virtual date simulation over time, and using the model to explore what interventions, when, and for whom might more effectively reduce risk-taking. A deeper understanding of these neural systems and their interactions, will transform our ability to advance theory, design effective risk-reduction interventions and enhance societal health and well-being, while reducing economic costs.