Todd Anthony Hare

Late childhood and adolescence are marked by substantial reorganization of the brain’sfunctional connectome and the emergence of many mental health problems. Although resting-state functional connectivity (rsFC) has been widely used to predict mental health and relatedbehavioral phenotypes, it remains unclear whether such models generalize across developmentor instead reflect age-specific brain-behavior mappings. Here, we tested the developmentalgeneralizability of whole-brain rsFC-based predictive models of mental health and cognitiveability across three timepoints spanning ages 9-14 years in the Adolescent Brain CognitiveDevelopment Study. Using out-of-sample prediction and cross-timepoint model transfer, wefound that rsFC significantly predicted concurrent mental health and cognitive ability withineach age group, but models trained at one age often generalized poorly to data acquired 2-4years earlier or later, particularly for mental health. In addition to this limited transfer, wedemonstrate developmental shifts in the associations between individual functionalconnections and mental health and cognitive ability. These changes occurred alongside broaderreorganization of the functional connectome, including age-related differences in globalcovariance structure and cortical network segregation. Together, our findings indicate thatbrain-behavior mappings of mental health are highly dynamic across late childhood andadolescence and may challenge the assumption that predictive models or candidate neuralbiomarkers for mental health disorders derived at a single age remain valid across development.

Have you ever seen someone look disappointed after an outcome—whether a gift, a grade, or a rejection? Rich emotional reactions, such as disappointment, readily inform social inference (e.g., that the other person expected more). Yet real-world emotional reactions are not always rich, as they can take the form of simple indications of feeling good (e.g., feeling 8/10) or bad. Are such simplified affective reactions sufficient for social inference? Research on experienced affect and reinforcement learning suggests simple reports of feeling good or bad (i.e., valence) contain rich information: (i) people feel better when outcomes exceed expectations and worse when they fall short; and (ii) how people feel after an outcome predicts their subsequent choices. This raises the possibility that observed simple affective valence is already sufficient for social inference. Across four preregistered experiments (N = 783), participants observed two hypothetical demonstrators react to lottery outcomes via continuous valence reports. From these affective cues, observers correctly inferred which demonstrator expected more, while tracking trial-by-trial updating over time. Inferences generalised beyond the lottery context: demonstrators with higher expectations were rated as more dominant but less fair and likable, based solely on their reported feelings. Observers also adjusted their behaviour accordingly. They shared less with high-expectation demonstrators when generosity was voluntary, but offered more to them when rejection was possible. Together, our results establish simple affective valence as a sufficient signal for systematic social inference.

People are often faced with choices whose outcomes will affect other individuals in addition to themselves. Being responsible for deciding on behalf of others alters choice behavior and increases delegation rates in decisions involving risk and ambiguity. However, it is unknown whether the influence of social responsibility on decision-making acts primarily or directly on risk, loss, and ambiguity attitudes versus more general aspects of cognition. We report a series of experiments on objective magnitude judgments that demonstrate that the influences of responsibility on cognition and behavior extend beyond risk or ambiguity and act at the metacognitive level. Specifically, responsibility for others changes metacognitive biases, leading to a decrease in decision confidence without affecting choice accuracy. Last, we propose and empirically test a normative computational framework based on decision confidence that can explain decisions to assume or delegate responsibility for others without needing to assume changes in risk preferences.

Intertemporal choices balance immediate rewards against future outcomes across various life domains. This chapter explores temporal discounting, where future rewards are devalued compared to immediate ones. This chapter examines the usefulness and shortcomings of common temporal discounting functions. It also investigates how attribute-based models, which consider specific features of rewards complement process-tracing methods and other neuroeconomic tools. I discuss how the clarity and certainty of future rewards, along with individual differences in time perception, influence intertemporal choices. I also discuss the role of self-control in intertemporal choices, questioning whether selecting a smaller, sooner reward necessarily indicates a lack of self-control. The chapter highlights recent work on the psychology and neurobiology of intertemporal choice, highlighting its complexity and the need for nuanced interpretations.

Do people learn to predict their feelings over time, and do such predictions manifest in behavior? Feeling ratings track with what we do. Understanding their properties may thus elucidate behavior. Inspired by reinforcement learning, differences between expected and experienced feelings—affective prediction errors—have recently entered the toolkit of behavioral prediction. But the extent of the analogy between affective prediction errors and conventional prediction errors about outcomes in the environment is unknown. Across reanalyzes of existing data (N = 4607) and four pre-registered experiments (N = 1806; U.S. online samples), we probe affective prediction errors to document and dissect a core analogy: Learning reflected in decreasing (affective) prediction errors over time. We found that decreases in affective prediction errors depended on introspection, as prior experience with a task absent affective reports did not yield the same decreases (Experiment 1). A task manipulation forcing participants to alter their choices showed increased affective prediction errors, ruling out simple response alignment (i.e., to report feeling “as predicted”; Experiment 2). Decreases in affective prediction errors transferred across structurally similar tasks (i.e., stealing versus giving money; Experiment 3) and affective measures (i.e., from pride or guilt to valence; Experiment 4). Although affective prediction errors often tracked with social choice behavior overall, their absolute decrease over time did not. In sum, we present evidence for convergence (i.e., learning and transfer) and divergence (i.e., introspection dependence and predictive epiphenomenality) between affective prediction errors and conventional prediction errors. Implications for affective measures as a proxy for subjective value are discussed.

Objective: Parenting behaviors significantly impact children's development, including thematuration of emotion regulation (ER) skills and associated brain regions (e.g., amygdala,hippocampus and prefrontal cortex [PFC]). Adaptive and maladaptive parenting behaviorshave been associated with ER brain structures of children/adolescents; however, longitudinalstudies of parenting behaviors with links to neural correlates remain scarce. Methods: Datafrom two cohorts are analyzed with parenting measures and neuroimaging during childhood(cohort 1; N=40) and repeated-measures parenting reports from childhood to adolescence (7-17 years of age) and neuroimaging at age 22 (cohort 2; repeated-measures report for N=1482;neuroimaging for n=134). Changes in parenting behaviors, parent-child alignment onparenting-behaviors reports at age 11, and associations between early parenting behaviors andER brain structures (volume/cortical thickness) during childhood (cohort 1) and during youngadulthood (cohort 2) were assessed using linear mixed effect models, regressions andcorrelational analyses. Results: Adaptive parenting behaviors (involvement, positiveparenting) and most maladaptive behaviors (inconsistent discipline, corporal punishment)decreased, while poor monitoring increased with children’s age. Parents’ and children’s reportsat age 11 were positively correlated. Positive parenting behaviors during childhood wereassociated with larger amygdala volume in children but smaller amygdala volume in a separate,matched young adults cohort. Corporal punishment was associated with reduced leftdorsolateral PFC thickness in children. Conclusion: In line with past evidence, adaptiveparenting behaviors were positively associated with ER brain structures, while maladaptiveparenting behaviors (i.e., corporal punishment) had opposite effects. Our findings indicate thateven in community samples variations in positive parenting matter. Supportive parentingbehaviors tend to foster healthy brain development. Such findings support the need for earlyfamily programs enabling children to thrive.

People often need to take responsibility for others, with widespread and lasting impacts on both themselves and those affected by the choice outcomes. Responsibility for others has been shown to alter behaviour in decisions involving risk and ambiguity, and increase delegation rates. Our work demonstrates that the influence of responsibility extends beyond risky choices and acts at the metacognitive level. Responsibility for others changes metacognitive biases leading to a decrease in decision confidence. We propose and empirically test a normative computational framework based on decision confidence to explain delegation behaviours with social responsibility.

Do people have well-defined social preferences waiting to be applied when making decisions? Or do they have to construct social decisions on the spot? If the latter, how are those decisions influenced by the way in which information is acquired and evaluated? These temporal dynamics are fundamental to understanding how people trade off selfishness and prosociality in organizations and societies. Here, we investigate how the temporal dynamics of the choice process shape social decisions in three studies using response times and mouse tracking. In the first study, participants made binary decisions in mini-dictator games with and without time constraints. Using mouse trajectories and a starting time drift diffusion model, we find that, regardless of time constraints, selfish participants were delayed in processing others’ payoffs, whereas the opposite was true for prosocial participants. The independent mouse trajectory and computational modeling analyses identified consistent measures of the delay between considering one’s own and others’ payoffs (self-onset delay, SOD). This measure correlated with individual differences in prosociality and predicted heterogeneous effects of time constraints on preferences. We confirmed these results in two additional studies, one a purely behavioral study in which participants made decisions by pressing computer keys, and the other a replication of the mouse-tracking study. Together, these results indicate that people preferentially process either self or others’ payoffs early in the choice process. The intrachoice dynamics are crucial in shaping social preferences and might be manipulated via nudge policies (e.g., manipulating the display order or saliency of self and others’ outcomes) for behavior in managerial or other contexts. This paper was accepted by Yan Chen, behavioral economics and decisions analysis. Funding: F. Chen acknowledges support from the National Natural Science Foundation of China [Grants 71803174 and 72173113]. Z. Zhu acknowledges support from the Ministry of Science and Technology [Grant STI 2030-Major Projects 2021ZD0200409]. Q. Shen acknowledges support from the National Natural Science Foundation of China [Grants 71971199 and 71942004]. I. Krajbich acknowledges support from the U.S. National Science Foundation [Grant 2148982]. This work was also supported by the James McKeen Cattell Fund. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4732 .

Suggestions about hunger can generate placebo effects on hunger experiences. But, the underlying neurocognitive mechanisms are unknown. Here, we show in 255 women that hunger expectancies, induced by suggestion-based placebo interventions, determine hunger sensations and economic food choices. Functional magnetic resonance imaging in a subgroup (n = 57/255) provides evidence that the strength of expecting the placebo to decrease hunger moderates medial prefrontal cortex activation at the time of food choice and attenuates ventromedial prefrontal cortex (vmPFC) responses to food value. Dorsolateral prefrontal cortex activation linked to interference resolution formally mediates the suggestion-based placebo effects on hunger. A drift-diffusion model characterizes this effect by showing that the hunger suggestions bias participants’ food choices and how much they weigh tastiness against the healthiness of food, which further moderates vmPFC–dlPFC psychophysiological interactions when participants expect decreased hunger. Thus, suggestion-induced beliefs about hunger shape hunger addressing economic choices through cognitive regulation of value computation within the prefrontal cortex.