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Abstract Expectations are often dynamic: sports fans know that expectations are rapidly updated as games unfold. Yet expectations have traditionally been studied as static. Here we present behavioral and electrophysiological evidence of sub-second changes in expectations using slot machines as a case study. In Study 1, we demonstrate that EEG signal before the slot machine stops varies based on proximity to winning. Study 2 introduces a behavioral paradigm to measure dynamic expectations via betting, and shows that expectation trajectories vary as a function of winning proximity. Notably, these expectation trajectories parallel Study 1’s EEG activity. Studies 3 (EEG) and 4 (behavioral) replicate these findings in the loss domain. These four studies provide compelling evidence that dynamic sub-second updates in expectations can be behaviorally and electrophysiologically measured. Our research opens promising avenues for understanding the dynamic nature of reward expectations and their impact on cognitive processes.

Summary: Social decision making requires the integration of reward valuation and social cognition systems, both dependent on the orbitofrontal cortex (OFC). How these two OFC functions interact is largely unknown. We recorded intracranial activity from the OFC of ten patients making choices in a social context where reward inequity with a social counterpart varied and could be either advantageous or disadvantageous. We find that OFC high-frequency activity (HFA; 70–150 Hz) encodes self-reward, consistent with previous reports. We also observe encoding of the social counterpart’s reward, as well as the type of inequity being experienced. Additionally, we find evidence of inequity-dependent reward encoding: depending on the type of inequity, electrodes rapidly and reversibly switch between different reward-encoding profiles. These results provide direct evidence for encoding of self- and other rewards in the human OFC and highlight the dynamic nature of encoding in the OFC as a function of social context.

The verbal fluency task, where participants name as many instances of a specific semantic or phonemic category as possible in a certain time limit, is widely used to probe language and memory retrieval functions in research and clinical settings. More recently, interests in using longitudinal observations in verbal fluency to examine changes over the lifespan have grown, in part due to the increasing availability of such datasets, yet quantitative methods for comparing repeated measures of verbal fluency responses remain scarce. As a result, existing studies tend to focus only on the number of unique words produced and how this metric changes over time, overlooking changes in other important features in the data, such as the identity of the words and the order in which they are produced. Here, we provide an example of how the literature of recurrence analysis, which aims to visualize and analyze non-linear time series, may present useful visualization and analytical approaches for this problem. Drawing on this literature, we introduce a novel metric (the “distance from diagonal,” or DfD) to quantify semantic fluency data that incorporates analysis of the sequence order and changes between two lists. As a demonstration, we apply these methods to a longitudinal dataset of semantic fluency in people with Alzheimer’s disease and age-matched controls. We show that DfD differs significantly between healthy controls and Alzheimer’s disease patients, and that it complements common existing metrics in diagnostic prediction. Our visualization method also allows incorporation of other less common metrics—including the order that words are recalled, repetitions of words within a list, and out-of-category intrusions. Additionally, we show that these plots can be used to visualize and compare aggregate recall data at the group level. These methods can improve understanding of verbal fluency deficits observed in various neuropsychiatric and neurological disorders.

Social and decision-making deficits are often the first symptoms of neuropsychiatric disorders. In recent years, economic games, together with computational models of strategic learning, have been increasingly applied to the characterization of individual differences in social behavior, as well as their changes across time due to disease progression, treatment, or other factors. At the same time, the high dimensionality of these data poses an important challenge to statistical estimation of these models, potentially limiting the adoption of such approaches in patients and special populations. We introduce a hierarchical Bayesian implementation of a class of strategic learning models, experience-weighted attraction (EWA), that is widely used in behavioral game theory. Importantly, this approach provides a unified framework for capturing between- and within-participant variation, including changes associated with disease progression, comorbidity, and treatment status. We show using simulated data that our hierarchical Bayesian approach outperforms representative agent and individual-level estimation methods that are commonly used in extant literature, with respect to parameter estimation and uncertainty quantification. Furthermore, using an empirical dataset, we demonstrate the value of our approach over competing methods with respect to balancing model fit and complexity. Consistent with the success of hierarchical Bayesian approaches in other areas of behavioral science, our hierarchical Bayesian EWA model represents a powerful and flexible tool to apply to a wide range of behavioral paradigms for studying the interplay between complex human behavior and biological factors.

Neuroimaging evidence implicates basal ganglia (BG) in social decision-making, yet causal evidence remains lacking. Here, the authors show that learning in strategic (but not non-strategic) games is spared in patients with BG damage, suggesting social decision making is not fully reliant on the BG.

Food insecurity is associated with many poor health outcomes yet is not routinely addressed in clinical settings. The purpose of this study was to implement a food insecurity screening and referral program in Student-run Free Clinics (SRFC) and to document the prevalence of food insecurity screening in this low-income patient population. All patients seen in three SRFC sites affiliated with one institution in San Diego, California were screened for food insecurity using the 6-item United States Department of Agriculture (USDA) Food Security Survey between January and July 2015 and referred to appropriate resources. The percentage of patients who were food insecure was calculated. The screening rate was 92.5% (430/463 patients), 74.0% (318/430) were food insecure, including 30.7% (132/430) with very low food security. A food insecurity registry and referral tracking system revealed that by January 2016, 201 participants were receiving monthly boxes of food onsite, 66 used an off-site food pantry, and 64 were enrolled in the Supplemental Nutrition Assistance Program (SNAP). It is possible to implement a food insecurity screening and referral program into SRFCs. The prevalence of food insecurity in this population was remarkably high yet remained largely unknown until this program was implemented. Other health care settings, particularly those with underserved patient populations, should consider implementing food insecurity screening and referral programs.

Erotic imagery is one highly salient emotional signal that exists everywhere in daily life. The impact of sexual stimuli on human decision-making, however, has rarely been investigated. This study examines the impact of sexual stimuli on financial decision-making under risk. In each trial, either a sexual or neutral image was presented in a picture categorization task before a gambling task. Thirty-four men made gambling decisions while their physiological arousal, measured by skin conductance responses (SCRs), was recorded. Behaviorally, the proportion of gambling decisions did not differ between the sexual and neutral image trials. Physiologically, participants had smaller arousal differences, measured in micro-siemen per dollar, between losses and gains in the sexual rather than in the neutral image trials. Moreover, participants' SCRs to losses relative to gains predicted the proportion of gambling decisions in the neutral image trials but not in the sexual image trials. The results were consistent with the hypothesis that the presence of emotionally salient sexual images reduces attentional and arousal-related responses to gambling losses. Our results are consistent with the theory of loss attention involving increased cognitive investment in losses compared to gains. The findings also have potential practical implications for our understanding of the specific roles of sexual images in human financial decision making in everyday life, such as gambling behaviors in the casino.

TABLE OF CONTENTS INTRODUCTION 1139 I. RACIALIZED CITIZENSHIP 1140 A. Time One (1790-1868): American Means White Persons 1143 B. Time Two (1868-1952): American Means Black and White Persons 1144 C. [...], In The "Free White Person" Clause of the Naturalization Act of 1790 as Super-Statute, Gabriel Jack Chin and Paul Finkelman argue that racist results in naturalization have arisen despite, or maybe because of, the race neutral interpretation. This happened in a manner that could have been predicted by the federal government's attitudes toward non-White persons in the Naturalization Act of 1790 and the nearly unbroken chain of legal developments. This leads them to think of the law as a "super-statute." While I agree that this is the path actually taken in history, I view the mid-1960s civil rights era as a "critical juncture" when the U.S. government could have taken a counterfactual path that was less racist. The counterfactual path would have required legal interpretations of Constitutional equality and statutory nondiscrimination that remained cognizant of racial implications of purportedly race neutral laws, which was briefly captured in language rights and voting rights statutes in the late 1960s to 1970s. But the egalitarian interpretations unraveled due to contradictions within the liberal national ideology that permitted a post-racial pragmatism about colorblindness that stalled the political incorporation of some non-White immigrants--Asian, Latino/a, Arab--due to their racialization as perpetual foreigners (racialized foreigners).

Deception is a universal human behavior. Yet longstanding skepticism about the validity of measures used to characterize the biological mechanisms underlying deceptive behavior has relegated such studies to the scientific periphery. Here, we address these fundamental questions by applying machine learning methods and functional magnetic resonance imaging (fMRI) to signaling games capturing motivated deception in human participants. First, we develop an approach to test for the presence of confounding processes and validate past skepticism by showing that much of the predictive power of neural predictors trained on deception data comes from processes other than deception. Specifically, we demonstrate that discriminant validity is compromised by the predictor's ability to predict behavior in a control task that does not involve deception. Second, we show that the presence of confounding signals need not be fatal and that the validity of the neural predictor can be improved by removing confounding signals while retaining those associated with the task of interest. To this end, we develop a "dual-goal tuning" approach in which, beyond the typical goal of predicting the behavior of interest, the predictor also incorporates a second compulsory goal that enforces chance performance in the control task. Together, these findings provide a firmer scientific foundation for understanding the neural basis of a neglected class of behavior, and they suggest an approach for improving validity of neural predictors. [ABSTRACT FROM AUTHOR]