Curiosity evolves as information unfolds.

When people feel curious, they often seek information to resolve their curiosity. Reaching resolution, however, does not always occur in a single step but instead may follow the accumulation of information over time. Here, we investigated changes in curiosity over a dynamic information-gathering process and how these changes related to affective and cognitive states as well as behavior. Human participants performed an Evolving Line Drawing Task, during which they reported guesses about the drawings' identities and made choices about whether to keep watching. In Study 1, the timing of choices was predetermined and externally imposed, while in Study 2, participants had agency in the timing of guesses and choices. Using this dynamic paradigm, we found that even within a single information-gathering episode, curiosity evolved in concert with other emotional states and with confidence. In both studies, we showed that the relationship between curiosity and confidence depended on stimulus entropy (unique guesses across participants) and on guess accuracy. We demonstrated that curiosity is multifaceted and can be experienced as either positive or negative depending on the state of information gathering. Critically, even when given the choice to alleviate uncertainty immediately (i.e., view a spoiler), higher curiosity promoted continuing to engage in the information-gathering process. Collectively, we show that curiosity changes over information accumulation to drive engagement with external stimuli, rather than to shortcut the path to resolution, highlighting the value inherent in the process of discovery.

Beyond money: Risk preferences across both economic and non-economic contexts predict financial decisions.

Important decisions about risk occur in wide-ranging contexts, from investing to healthcare. While an underlying, domain-general risk attitude has been identified across contexts, it remains unclear what role it plays in shaping behavior relative to more domain-specific risk attitudes. Clarifying the relationship between domain-general and domain-specific risk attitudes would inform decision-making theories and the construction of decision aids. The present research assessed the relative contribution of domain-general and domain-specific risk attitudes to financial risk taking. We examined risk attitudes across different decision domains, as revealed through a well-validated measure, the Domain-Specific Risk-Taking Scale (DOSPERT). Confirmatory factor analysis indicated that a domain-general risk attitude shaped responses across multiple domains, and structural equation modeling showed that this domain-general risk attitude predicted observed behavioral risk premiums in a financial decision-making task better than domain-specific financial risk attitudes. Thus, assessments of risk attitudes that include both economic and non-economic domains improve predictions of financial risk taking due to the enhanced insight they provide into underlying, domain-general risk preferences.

Transient Motion Classification Through Turbid Volumes via Parallelized Single-Photon Detection and Deep Contrastive Embedding.

Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical settings. One of the primary optical techniques used is diffuse correlation spectroscopy (DCS), whose classical implementation uses a single or few single-photon detectors, resulting in poor spatial localization accuracy and relatively low temporal resolution. Here, we propose a technique termed C lassifying R apid decorrelation E vents via P arallelized single photon d E tection (CREPE), a new form of DCS that can probe and classify different decorrelating movements hidden underneath turbid volume with high sensitivity using parallelized speckle detection from a 32 × 32 pixel SPAD array. We evaluate our setup by classifying different spatiotemporal-decorrelating patterns hidden beneath a 5 mm tissue-like phantom made with rapidly decorrelating dynamic scattering media. Twelve multi-mode fibers are used to collect scattered light from different positions on the surface of the tissue phantom. To validate our setup, we generate perturbed decorrelation patterns by both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as well as a vessel phantom containing flowing fluid. Along with a deep contrastive learning algorithm that outperforms classic unsupervised learning methods, we demonstrate our approach can accurately detect and classify different transient decorrelation events (happening in 0.1-0.4 s) underneath turbid scattering media, without any data labeling. This has the potential to be applied to non-invasively monitor deep tissue motion patterns, for example identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates within a compact and static detection probe.

Gaze-dependent evidence accumulation predicts multi-alternative risky choice behaviour.

Choices are influenced by gaze allocation during deliberation, so that fixating an alternative longer leads to increased probability of choosing it. Gaze-dependent evidence accumulation provides a parsimonious account of choices, response times and gaze-behaviour in many simple decision scenarios. Here, we test whether this framework can also predict more complex context-dependent patterns of choice in a three-alternative risky choice task, where choices and eye movements were subject to attraction and compromise effects. Choices were best described by a gaze-dependent evidence accumulation model, where subjective values of alternatives are discounted while not fixated. Finally, we performed a systematic search over a large model space, allowing us to evaluate the relative contribution of different forms of gaze-dependence and additional mechanisms previously not considered by gaze-dependent accumulation models. Gaze-dependence remained the most important mechanism, but participants with strong attraction effects employed an additional similarity-dependent inhibition mechanism found in other models of multi-alternative multi-attribute choice.

Peer presence increases the prosocial behavior of adolescents by speeding the evaluation of outcomes for others.

Peer presence can elicit maladaptive adolescent decision-making, potentially by increasing sensitivity to the rewards one receives. It remains unknown whether peer presence also increases adolescents' sensitivity to others' outcomes, which could have an adaptive effect in contexts allowing pro-social behaviors. Here, we combine social utility modeling and real-time decision process modeling to characterize how peer presence alters adolescents' processing of self and other outcomes. We found that adolescents behaved selfishly when privately allocating monetary rewards for themselves and a peer in an incentive-compatible task. In peer presence, however, adolescents became more altruistic. Real-time decision process estimates collected using computer mouse tracking showed that altruistic behavior was associated with relatively earlier influence of peer-outcomes relative to self-outcomes, and that peer presence sped the influence of peer-outcomes without altering the time at which self-outcomes began to influence the decision process. Our results indicate a mechanism through which peer presence prompts greater prosocial behavior by altering how adolescents process prosocial outcomes.

Shuffle the Decks: Children Are Sensitive to Incidental Nonrandom Structure in a Sequential-Choice Task.

As children age, they can learn increasingly complex features of environmental structure-a key prerequisite for adaptive decision-making. Yet when we tested children (N = 304, 4-13 years old) in the Children's Gambling Task, an age-appropriate variant of the Iowa Gambling Task, we found that age was negatively associated with performance. However, this paradoxical effect of age was found only in children who exhibited a maladaptive deplete-replenish bias, a tendency to shift choices after positive outcomes and repeat choices after negative outcomes. We found that this bias results from sensitivity to incidental nonrandom structure in the canonical, deterministic forms of these tasks-and that it would actually lead to optimal outcomes if the tasks were not deterministic. Our results illustrate that changes in decision-making across early childhood reflect, in part, increasing sensitivity to environmental structure.

The hidden cost of humanization: Individuating information reduces prosocial behavior toward in-group members.

This paper reports robust experimental evidence that humanization-in the form of individuating information about another's personal preferences-leads to decreased prosocial behavior toward in-group members. Previous research shows that this information increases prosocial behavior toward dehumanized out-group members. The consequences for in-group members, however, are less well understood. Using methods from social psychology and behavioral economics, four experiments show that individuating information decreases pro-social behavior toward in-group members in a variety of settings (charitable giving, altruistic punishment, and trust games). Moreover, this effect results from decreased reliance on group membership labels, and not from other potential explanations like the induction of new group identities. Understanding these effects sheds light on the motives behind intergroup conflict, which may not result from a difference in social perception (i.e., humanized in-groups and dehumanized out-groups), but rather from biases associated with group membership (i.e. in-group favoritism and out-group discrimination) that are eliminated by individuating information. Together, these results indicate that humanization carries a hidden cost for in-group members by disrupting group identities that would otherwise make them targets of altruistic actions.

Disruptions of Sustained Spatial Attention Can Be Resistant to the Distractor's Prior Reward Associations.

Attention can be involuntarily biased toward reward-associated distractors (value-driven attentional capture, VDAC). Yet past work has primarily demonstrated this distraction phenomenon during a particular set of circumstances: transient attentional orienting to potentially relevant stimuli occurring in our visual environment. Consequently, it is not well-understood if reward-based attentional capture can occur under other circumstances, such as during sustained visuospatial attention. Using EEG, we investigated whether associating transient distractors with reward value would increase their distractibility and lead to greater decrements in concurrent sustained spatial attention directed elsewhere. Human participants learned to associate three differently colored, laterally presented squares with rewards of varying magnitude (zero, small, and large). These colored squares were then periodically reintroduced as distractors at the same lateral locations during a demanding sustained-attention rapid-serial-visual-presentation (RSVP) task at the midline. Behavioral and neural evidence indicated that participants had successfully learned and maintained the reward associations to the distractors. During the RSVP task, consistent with prior work, we found that the distractors generated dips in the instantaneous amplitude of the steady-state visual evoked potentials (SSVEPs) elicited by the midline RSVP stimuli, indicating that the distractors were indeed transiently disrupting sustained spatial attention. Contrary to our hypotheses, however, the magnitude of this dip did not differ by the magnitude of the distractor's reward associations. These results indicate that while sustained spatial attention can be impaired by the introduction of distractors at another location, the main distraction process is resistant to the distractors' reward associations, thus providing evidence of an important boundary condition to value-driven attentional capture.

Healthful choices depend on the latency and rate of information accumulation.

The drift diffusion model provides a parsimonious explanation of decisions across neurobiological, psychological and behavioural levels of analysis. Although most drift diffusion model implementations assume that only a single value guides decisions, choices often involve multiple attributes that could make separable contributions to choice. Here we fit incentive-compatible dietary choices to a multi-attribute, time-dependent drift diffusion model, in which taste and health could differentially influence the evidence accumulation process. We find that these attributes shaped both the relative value signal and the latency of evidence accumulation in a manner consistent with participants' idiosyncratic preferences. Moreover, by using a dietary prime, we showed how a healthy choice intervention alters multi-attribute, time-dependent drift diffusion model parameters that in turn predict prime-dependent choices. Our results reveal that different decision attributes make separable contributions to the strength and timing of evidence accumulation, providing new insights into the construction of interventions to alter the processes of choice.

Hypoactivation in the precuneus and posterior cingulate cortex during ambiguous decision making in individuals with HIV.

People with human immunodeficiency virus (HIV) often have neurocognitive impairment. People with HIV make riskier decisions when the outcome probabilities are known, and have abnormal neural architecture underlying risky decision making. However, ambiguous decision making, when the outcome probabilities are unknown, is more common in daily life, but the neural architecture underlying ambiguous decision making in people with HIV is unknown. Eighteen people with HIV and 20 controls completed a decision making task while undergoing functional magnetic resonance imaging scanning. Participants chose between a certain reward and uncertain reward with a known (risky) or unknown (ambiguous) probability of winning. There were three levels of risk: high, medium, and low. Ambiguous > risky brain activity was compared between groups. Ambiguous > risky brain activity was correlated with emotional/psychiatric functioning in people with HIV. Both groups were similarly ambiguity-averse. People with HIV were more risk-averse than controls and chose the high-risk uncertain option less often. People with HIV had hypoactivity in the precuneus, posterior cingulate cortex (PCC), and fusiform gyrus during ambiguous > medium risk decision making. Ambiguous > medium risk brain activity was negatively correlated with emotional/psychiatric functioning in individuals with HIV. To make ambiguous decisions, people with HIV underrecruit key regions of the default mode network, which are thought to integrate internally and externally derived information to come to a decision. These regions and related cognitive processes may be candidates for interventions to improve decision-making outcomes in people with HIV.

Voter Preferences Reflect a Competition Between Policy and Identity.

Canonical rational choice models of voter preferences assume that voters select candidates whose policy positions most closely match their own. Yet, much of the electorate often appears to prioritize identity variables (e.g., social categories, group membership) over policy considerations. Here, we report an empirical test of policy-identity interactions using surveys of likely voters conducted in the 24 hours before the 2016 United States presidential election and the 2018 United States senatorial elections. Each respondent indicated not only their policy preferences but also key social group identities and how those identities would be reinforced by voting. We observed striking evidence for a competition between policy and social group identification: For voters who exhibited the maximal effects of identity, policy positions were essentially irrelevant to their candidate preferences. These results account for dissociations between voters' stated policy preferences and their voting behavior, while linking empirical observations of political behavior to new models derived from psychology and neuroscience.

Neural sensitivity to risk in adults with co-occurring HIV infection and cocaine use disorder.

Persons with co-occurring HIV infection and cocaine use disorder tend to engage in riskier decision-making. However, the neural correlates of sensitivity to risk are not well-characterized in this population. The purpose of this study was to examine the neural interaction effects of HIV infection and cocaine use disorder to sensitivity to risk. The sample included 79 adults who differed on HIV status and cocaine use disorder. During functional magnetic resonance imaging (fMRI), participants completed a Wheel of Fortune (WoF) task that assessed neural activation in response to variations of monetary risk (i.e., lower probability of winning a larger reward). Across groups, neural activation to increasing risk was in cortical and subcortical regions similar to previous investigations using the WoF in nondrug-using populations. Our analyses showed that there was a synergistic effect between HIV infection and cocaine use in the left precuneus/posterior cingulate cortex and hippocampus, and right postcentral gyrus, lateral occipital cortex, cerebellum, and posterior parietal cortex. HIV+ individuals with cocaine use disorder displayed neural hyperactivation to increasing risk that was not observed in the other groups. These results support a synergistic effect of co-occurring HIV infection and cocaine dependence in neural processing of risk probability that may reflect compensation. Future studies can further investigate and validate how neural activation to increasing risk is associated with risk-taking behavior.

Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior.

Understanding how humans make competitive decisions in complex environments is a key goal of decision neuroscience. Typical experimental paradigms constrain behavioral complexity (e.g. choices in discrete-play games), and thus, the underlying neural mechanisms of dynamic social interactions remain incompletely understood. Here, we collected fMRI data while humans played a competitive real-time video game against both human and computer opponents, and then, we used Bayesian non-parametric methods to link behavior to neural mechanisms. Two key cognitive processes characterized behavior in our task: (i) the coupling of one's actions to another's actions (i.e. opponent sensitivity) and (ii) the advantageous timing of a given strategic action. We found that the dorsolateral prefrontal cortex displayed selective activation when the subject's actions were highly sensitive to the opponent's actions, whereas activation in the dorsomedial prefrontal cortex increased proportionally to the advantageous timing of actions to defeat one's opponent. Moreover, the temporoparietal junction tracked both of these behavioral quantities as well as opponent social identity, indicating a more general role in monitoring other social agents. These results suggest that brain regions that are frequently implicated in social cognition and value-based decision-making also contribute to the strategic tracking of the value of social actions in dynamic, multi-agent contexts.

Sleep deprivation, effort allocation and performance.

Sleep deprivation causes physiological alterations (e.g., decreased arousal, intrusion of micro-sleeps), that negatively affect performance on a wide range of cognitive domains. These effects indicate that cognitive performance relies on a capacity-limited system that may be more challenged in the absence of sleep. Additionally, sleep loss can result in a lower willingness to exert effort in the pursuit of performance goals. Such deficits in motivation may interact with the effects of capacity limitations to further stifle cognitive performance. When sleep-deprived, cognitive performance is experienced as more effortful, and intrinsic motivation to perform dwindles. On the other hand, increasing motivation extrinsically (e.g., by monetary incentives) can inspire individuals to allocate more task-related effort, and can partially counter performance deficits associated with sleep deprivation. In this chapter, we review current research on the interplay between sleep deprivation, effort and performance. We integrate these findings into an effort-based decision-making framework in which sleep-related performance impairments may result from a voluntary decision to withdraw effort. We conclude with practical implications of this framework for performance in healthy populations (e.g., work productivity) and clinical conditions.

Developmental Maturation of the Precuneus as a Functional Core of the Default Mode Network.

Efforts to map the functional architecture of the developing human brain have shown that connectivity between and within functional neural networks changes from childhood to adulthood. Although prior work has established that the adult precuneus distinctively modifies its connectivity during task versus rest states [Utevsky, A. V., Smith, D. V., & Huettel, S. A. Precuneus is a functional core of the default-mode network. Journal of Neuroscience, 34, 932-940, 2014], it remains unknown how these connectivity patterns emerge over development. Here, we use fMRI data collected at two longitudinal time points from over 250 participants between the ages of 8 and 26 years engaging in two cognitive tasks and a resting-state scan. By applying independent component analysis to both task and rest data, we identified three canonical networks of interest-the rest-based default mode network and the task-based left and right frontoparietal networks (LFPN and RFPN, respectively)-which we explored for developmental changes using dual regression analyses. We found systematic state-dependent functional connectivity in the precuneus, such that engaging in a task (compared with rest) resulted in greater precuneus-LFPN and precuneus-RFPN connectivity, whereas being at rest (compared with task) resulted in greater precuneus-default mode network connectivity. These cross-sectional results replicated across both tasks and at both developmental time points. Finally, we used longitudinal mixed models to show that the degree to which precuneus distinguishes between task and rest states increases with age, due to age-related increasing segregation between precuneus and LFPN at rest. Our results highlight the distinct role of the precuneus in tracking processing state, in a manner that is both present throughout and strengthened across development.

Exploring common changes after acute mental stress and acute tryptophan depletion: Resting-state fMRI studies.

Stress and low serotonin levels are important biological factors in depression and anxiety etiologies. Although studies indicate that low serotonin levels, stress, and other factors may interact in depression/anxiety psychopathology, few studies have investigated the potentially shared neural substrates. We conducted resting-state fMRI scans pre- and post-stress task, and under control and tryptophan depletion condition, to explore the common changes induced by acute mental stress (AMS) and acute tryptophan depletion (ATD). The present study targeted regions within core brain networks - default mode network, salience network, executive control network, and emotion network - reported altered in AMS and ATD, and used regional homogeneity (ReHo) and functional connectivity (FC) analyses to explore their overlapped effects. We additionally examined the relationships among core neural networks - operationalized as an index of resource allocation bias that quantifies the shift from internal to external modes of processing. We found both manipulations induced increased ReHo of the amygdala and decreased ReHo of the posterior cingulate cortex (PCC). The PCC-amygdala FC was negatively correlated with the change of negative affect, whereas the right dorsolateral prefrontal cortex and right anterior insula FC was positively associated with anxiety level. In addition, we found that a greater shift to an external mode was correlated with higher anxiety level under both conditions. Common changes induced by acute mental stress and acute tryptophan depletion confirmed our hypothesis that AMS and ATD induce changes in common neural pathways, which in turn might mark vulnerability to depression and anxiety.

Amount and time exert independent influences on intertemporal choice.

Intertemporal choices involve trade-offs between the value of rewards and the delay before those rewards are experienced. Canonical intertemporal choice models such as hyperbolic discounting assume that reward amount and time until delivery are integrated within each option prior to comparison1,2. An alternative view posits that intertemporal choice reflects attribute-wise processes in which amount and time attributes are compared separately3-6. Here, we use multi-attribute drift diffusion modelling (DDM) to show that attribute-wise comparison represents the choice process better than option-wise comparison for intertemporal choice in a young adult population. We find that, while accumulation rates for amount and time information are uncorrelated, the difference between those rates predicts individual differences in patience. Moreover, patient individuals incorporate amount earlier than time into the decision process. Using eye tracking, we link these modelling results to attention, showing that patience results from a rapid, attribute-wise process that prioritizes amount over time information. Thus, we find converging evidence that distinct evaluation processes for amount and time determine intertemporal financial choices. Because intertemporal decisions in the lab have been linked to failures of patience ranging from insufficient saving to addiction7-13, understanding individual differences in the choice process is important for developing more effective interventions.

Bayesian nonparametric models characterize instantaneous strategies in a competitive dynamic game.

Previous studies of strategic social interaction in game theory have predominantly used games with clearly-defined turns and limited choices. Yet, most real-world social behaviors involve dynamic, coevolving decisions by interacting agents, which poses challenges for creating tractable models of behavior. Here, using a game in which humans competed against both real and artificial opponents, we show that it is possible to quantify the instantaneous dynamic coupling between agents. Adopting a reinforcement learning approach, we use Gaussian Processes to model the policy and value functions of participants as a function of both game state and opponent identity. We found that higher-scoring participants timed their final change in direction to moments when the opponent's counter-strategy was weaker, while lower-scoring participants less precisely timed their final moves. This approach offers a natural set of metrics for facilitating analysis at multiple timescales and suggests new classes of experimental paradigms for assessing behavior.