Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success

Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level. Using an established laboratory food task capturing brain responses in natural and regulatory conditions (N = 123), we demonstrate that regulatory changes of dietary brain states in the gradient space predict individual differences in dietary success. Better regulators required smaller shifts in brain states to achieve larger goal-consistent changes in dietary behaviors, pointing toward efficient network organization. This pattern was most pronounced in individuals with lower weight status (low-BMI, body mass index) but absent in high-BMI individuals. Consistent with prior work, regulatory goals increased activity in frontoparietal brain circuits. However, this shift in brain states alone did not predict variance in dietary success. Instead, regulatory success emerged from combined changes along multiple gradients, showcasing the interplay of different large-scale brain networks subserving dietary control and possible regulatory strategies. Our results provide insights into how the brain might solve the problem of dietary control: Dietary success may be easier for people who adopt modes of large-scale brain activation that do not require significant reconfigurations across contexts and goals.

When expert predictions fail

We examine the opportunities and challenges of expert judgment in the social sciences, scrutinizing the way social scientists make predictions. While social scientists show above-chance accuracy in predicting laboratory-based phenomena, they often struggle to predict real-world societal changes. We argue that most causal models used in social sciences are oversimplified, confuse levels of analysis to which a model applies, misalign the nature of the model with the nature of the phenomena, and fail to consider factors beyond the scientist's pet theory. Taking cues from physical sciences and meteorology, we advocate an approach that integrates broad foundational models with context-specific time series data. We call for a shift in the social sciences towards more precise, daring predictions and greater intellectual humility.

On the accuracy, media representation, and public perception of psychological scientists' judgments of societal change

At the onset of the COVID-19 pandemic, psychological scientists frequently made on-the-record predictions in public media about how individuals and society would change. Such predictions were often made outside these scientists' areas of expertise, with justifications based on intuition, heuristics, and analogical reasoning (Study 1; N = 719 statements). How accurate are these kinds of judgments regarding societal change? In Study 2, we obtained predictions from scientists (N = 717) and lay Americans (N = 394) in Spring 2020 regarding the direction of change for a range of social and psychological phenomena. We compared them to objective data obtained at 6 months and 1 year. To further probe how experience impacts such judgments, 6 months later (Study 3), we obtained retrospective judgments of societal change for the same domains (Nscientists = 270; Nlaypeople = 411). Bayesian analysis suggested greater credibility of the null hypothesis that scientists' judgments were at chance on average for both prospective and retrospective judgments. Moreover, neither domain-general expertise (i.e., judgmental accuracy of scientists compared to laypeople) nor self-identified domain-specific expertise improved accuracy. In a follow-up study on meta-accuracy (Study 4), we show that the public nevertheless expects psychological scientists to make more accurate predictions about individual and societal change compared to most other scientific disciplines, politicians, and nonscientists, and they prefer to follow their recommendations. These findings raise questions about the role psychological scientists could and should play in helping the public and policymakers plan for future events. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Framing Subjective Emotion Reports as Dynamic Affective Decisions

Self-reports remain affective science's only direct measure of subjective affective experiences. Yet, little research has sought to understand the psychological process that transforms subjective experience into self-reports. Here, we propose that by framing these self-reports as dynamic affective decisions, affective scientists may leverage the computational tools of decision-making research, sequential sampling models specifically, to better disentangle affective experience from the noisy decision processes that constitute self-report. We further outline how such an approach could help affective scientists better probe the specific mechanisms that underlie important moderators of affective experience (e.g., contextual differences, individual differences, and emotion regulation) and discuss how adopting this decision-making framework could generate insight into affective processes more broadly and facilitate reciprocal collaborations between affective and decision scientists towards a more comprehensive and integrative psychological science.

Deliberative control is more than just reactive: Insights from sequential sampling models

Activating relevant responses is a key function of automatic processes in De Neys's model; however, what determines the order or magnitude of such activation is ambiguous. Focusing on recently developed sequential sampling models of choice, we argue that proactive control shapes response generation but does not cleanly fit into De Neys's automatic-deliberative distinction, highlighting the need for further model development.

Insights into the accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data.

Recruitment of dlPFC during dietary self-regulation predicts the transience of regulatory effects

Recent work on the cognitive regulation of dietary decision-making suggests that regulation can alter both the choices that people make in the moment and longer-lasting preferences. However, it is unclear what mechanisms lead to temporary or lingering changes. To address this question, we used fMRI during a task employing the cognitive regulation of food choice and assessed changes in food preference from baseline to post-regulation. We found evidence that regulation may result in a temporary reconfiguration of the neural drivers of choice, de-emphasizing goal-inconsistent value-related computations in the ventromedial prefrontal cortex and resulting in more goal-consistent changes in value-related computations in the dorsolateral prefrontal cortex (dlPFC). Moreover, we find that the extent to which the dlPFC was recruited to represent different regulatory goals during the moment of choice negatively predicted the extent to which those regulatory goals produced lingering changes in preference. Our results suggest that the recruitment of the dlPFC in the service of regulation may have a downside: it is effective at changing behavior in the moment, but its effects on preferences are transient.

Evidence accumulation, not 'self-control', explains dorsolateral prefrontal activation during normative choice

What role do regions like the dorsolateral prefrontal cortex (dlPFC) play in normative behavior (e.g., generosity, healthy eating)? Some models suggest that dlPFC activation during normative choice reflects controlled inhibition or modulation of default hedonistic preferences. Here, we develop an alternative account, showing that evidence accumulation models predict trial-by-trial variation in dlPFC response across three fMRI paradigms and two self-control contexts (altruistic sacrifice and healthy eating). Using these models to simulate a variety of self-control dilemmas generated a novel prediction: although dlPFC activity might typically increase for norm-consistent choices, deliberate self-regulation focused on normative goals should decrease or even reverse this pattern (i.e., greater dlPFC response for hedonistic, self-interested choices). We confirmed these predictions in both altruistic and dietary choice contexts. Our results suggest that dlPFC response during normative choice may depend more on value-based evidence accumulation than inhibition of our baser instincts.

The Games We Play: Prosocial Choices Under Time Pressure Reflect Context-Sensitive Information Priorities

Time pressure is a powerful experimental manipulation frequently used to arbitrate between competing dual-process models of prosocial decision-making, which typically assume that automatic responses yield to deliberation over time. However, the use of time pressure has led to conflicting conclusions about the psychological dynamics of prosociality. Here, we proposed that flexible, context-sensitive information search, rather than automatic responses, underlies these divergent effects of time pressure on prosociality. We demonstrated in two preregistered studies (N = 304 adults from the United States and Canada; Prolific Academic) that different prosocial contexts (i.e., pure altruism vs. cooperation) have distinct effects on information search, driving people to prioritize information differently, particularly under time pressure. Furthermore, these information priorities subsequently influence prosocial choices, accounting for the different effects of time pressure in altruistic and cooperative contexts. These findings help explain existing inconsistencies in the field by emphasizing the role of dynamic context-sensitive information search during social decision-making, particularly under time pressure.

Temporal dynamics of decision making: A synthesis of computational and neurophysiological approaches

As interest in the temporal dynamics of decision-making has grown, researchers have increasingly turned to computational approaches such as the drift diffusion model (DDM) to identify how cognitive processes unfold during choice. At the same time, technological advances in noninvasive neurophysiological methods such as electroencephalography and magnetoencephalography now allow researchers to map the neural time course of decision making with millisecond precision. Combining these approaches can potentially yield important new insights into how choices emerge over time. Here we review recent research on the computational and neurophysiological correlates of perceptual and value-based decision making, from DDM parameters to scalp potentials and oscillatory neural activity. Starting with motor response preparation, the most well-understood aspect of the decision process, we discuss evidence that urgency signals and shifts in baseline activation, rather than shifts in the physiological value of the choice-triggering response threshold, are responsible for adjusting response times under speeded choice scenarios. Research on the neural correlates of starting point bias suggests that prestimulus activity can predict biases in motor choice behavior. Finally, studies examining the time dynamics of evidence construction and evidence accumulation have identified signals at frontocentral and centroparietal electrodes associated respectively with these processes, emerging 300-500 ms after stimulus onset. These findings can inform psychological theories of decision-making, providing empirical support for attribute weighting in value-based choice while suggesting theoretical alternatives to dual-process accounts. Further research combining computational and neurophysiological approaches holds promise for providing greater insight into the moment-by-moment evolution of the decision process. This article is categorized under: Psychology > Reasoning and Decision Making Neuroscience > Cognition Economics > Individual Decision-Making.

Time to Pay Attention? Information Search Explains Amplified Framing Effects Under Time Pressure

Decades of research have established the ubiquity and importance of choice biases, such as the framing effect, yet why these seemingly irrational behaviors occur remains unknown. A prominent dual-system account maintains that alternate framings bias choices because of the unchecked influence of quick, affective processes, and findings that time pressure increases the framing effect have provided compelling support. Here, we present a novel alternative account of magnified framing biases under time pressure that emphasizes shifts in early visual attention and strategic adaptations in the decision-making process. In a preregistered direct replication (N = 40 adult undergraduates), we found that time constraints produced strong shifts in visual attention toward reward-predictive cues that, when combined with truncated information search, amplified the framing effect. Our results suggest that an attention-guided, strategic information-sampling process may be sufficient to explain prior results and raise challenges for using time pressure to support some dual-system accounts.

Alpha oscillations and event-related potentials reflect distinct dynamics of attribute construction and evidence accumulation in dietary decision making

How does regulatory focus alter attribute value construction (AVC) and evidence accumulation (EA)? We recorded electroencephalogram during food choices while participants responded naturally or regulated their choices by attending to health attributes or decreasing attention to taste attributes. Using a drift diffusion model, we predicted the time course of neural signals associated with AVC and EA. Results suggested that event-related potentials (ERPs) correlated with the time course of model-predicted taste-attribute signals, with no modulation by regulation. By contrast, suppression of frontal and occipital alpha power correlated with the time course of EA, tracked tastiness according to its goal relevance, and predicted individual variation in successful down-regulation of tastiness. Additionally, an earlier rise in frontal and occipital theta power represented food tastiness more strongly during regulation and predicted a weaker influence of food tastiness on behaviour. Our findings illuminate how regulation modifies the representation of attributes during the process of EA.

Affect and Decision Making: Insights and Predictions from Computational Models

In recent years interest in integrating the affective and decision sciences has skyrocketed. Immense progress has been made, but the complexities of each field, which can multiply when combined, present a significant obstacle. A carefully defined framework for integration is needed. The shift towards computational modeling in decision science provides a powerful basis and a path forward, but one whose synergistic potential will only be fully realized by drawing on the theoretical richness of the affective sciences. Reviewing research using a popular computational model of choice (the drift diffusion model), we discuss how mapping concepts to parameters reduces conceptual ambiguity and reveals novel hypotheses.

Empathy is hard work: People choose to avoid empathy because of its cognitive costs

Empathy is considered a virtue, yet it fails in many situations, leading to a basic question: When given a choice, do people avoid empathy? And if so, why? Whereas past work has focused on material and emotional costs of empathy, here, we examined whether people experience empathy as cognitively taxing and costly, leading them to avoid it. We developed the empathy selection task, which uses free choices to assess the desire to empathize. Participants make a series of binary choices, selecting situations that lead them to engage in empathy or an alternative course of action. In each of 11 studies (N = 1,204) and a meta-analysis, we found a robust preference to avoid empathy, which was associated with perceptions of empathy as more effortful and aversive and less efficacious. Experimentally increasing empathy efficacy eliminated empathy avoidance, suggesting that cognitive costs directly cause empathy choice. When given the choice to share others' feelings, people act as if it is not worth the effort. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Cognitive regulation alters social and dietary choice by changing attribute representations in domain-general and domain-specific brain circuits

Are some people generally more successful using cognitive regulation or does it depend on the choice domain? Why? We combined behavioral computational modeling and multivariate decoding of fMRI responses to identify neural loci of regulation-related shifts in value representations across goals and domains (dietary or altruistic choice). Surprisingly, regulatory goals did not alter integrative value representations in the ventromedial prefrontal cortex, which represented all choice-relevant attributes across goals and domains. Instead, the dorsolateral prefrontal cortex (DLPFC) flexibly encoded goal-consistent values and predicted regulatory success for the majority of choice-relevant attributes, using attribute-specific neural codes. We also identified domain-specific exceptions: goal-dependent encoding of prosocial attributes localized to precuneus and temporo-parietal junction (not DLPFC). Our results suggest that cognitive regulation operated by changing specific attribute representations (not integrated values). Evidence of domain-general and domain-specific neural loci reveals important divisions of labor, explaining when and why regulatory success generalizes (or doesn’t) across contexts and domains.

Self-Control as Value-Based Choice

Self-control is often conceived as a battle between "hot" impulsive processes and "cold" deliberative ones. Heeding the angel on one shoulder leads to success; following the demon on the other leads to failure. Self-control feels like a duality. What if that sensation is misleading, and, despite how they feel, self-control decisions are just like any other choice? We argue that self-control is a form of value-based choice wherein options are assigned a subjective value and a decision is made through a dynamic integration process. We articulate how a value-based choice model of self-control can capture its phenomenology and account for relevant behavioral and neuroscientific data. This conceptualization of self-control links divergent scientific approaches, allows for more robust and precise hypothesis testing, and suggests novel pathways to improve self-control.

Cognitive regulation during decision making shifts behavioral control between ventromedial and dorsolateral prefrontal value systems

Cognitive regulation is often used to influence behavioral outcomes. However, the computational and neurobiological mechanisms by which it affects behavior remain unknown. We studied this issue using an fMRI task in which human participants used cognitive regulation to upregulate and downregulate their cravings for foods at the time of choice. We found that activity in both ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) correlated with value. We also found evidence that two distinct regulatory mechanisms were at work: value modulation, which operates by changing the values assigned to foods in vmPFC and dlPFC at the time of choice, and behavioral control modulation, which operates by changing the relative influence of the vmPFC and dlPFC value signals on the action selection process used to make choices. In particular, during downregulation, activation decreased in the value-sensitive region of dlPFC (indicating value modulation) but not in vmPFC, and the relative contribution of the two value signals to behavior shifted toward the dlPFC (indicating behavioral control modulation). The opposite pattern was observed during upregulation: activation increased in vmPFC but not dlPFC, and the relative contribution to behavior shifted toward the vmPFC. Finally, ventrolateral PFC and posterior parietal cortex were more active during both upregulation and downregulation, and were functionally connected with vmPFC and dlPFC during cognitive regulation, which suggests that they help to implement the changes to the decision-making circuitry generated by cognitive regulation.

The moral emotions: a social-functionalist account of anger, disgust, and contempt

Recent research has highlighted the important role of emotion in moral judgment and decision making (Greene, Sommerville, Nystrom, Darley, & Cohen, 2001; Haidt, 2001). What is less clear is whether distinctions should be drawn among specific moral emotions. Although some have argued for differences among anger, disgust, and contempt (Rozin, Lowery, Imada, & Haidt, 1999), others have suggested that these terms may describe a single undifferentiated emotional response to morally offensive behavior (Nabi, 2002). In this article, we take a social-functionalist perspective, which makes the prediction that these emotions should be differentiable both in antecedent appraisals and in consequent actions and judgments. Studies 1-3 tested and found support for our predictions concerning distinctions among antecedent appraisals, including (a) a more general role for disgust than has been previously been described, (b) an effect of self-relevance on anger but not other emotions, and (c) a role for contempt in judging incompetent actions. Studies 4 and 5 tested and found support for our specific predictions concerning functional outcomes, providing evidence that these emotions are associated with different consequences. Taken together, these studies support a social-functionalist account of anger, disgust, and contempt and lay the foundation for future research on the negative interpersonal emotions.

Loving-kindness meditation increases social connectedness

The need for social connection is a fundamental human motive, and it is increasingly clear that feeling socially connected confers mental and physical health benefits. However, in many cultures, societal changes are leading to growing social distrust and alienation. Can feelings of social connection and positivity toward others be increased? Is it possible to self-generate these feelings? In this study, the authors used a brief loving-kindness meditation exercise to examine whether social connection could be created toward strangers in a controlled laboratory context. Compared with a closely matched control task, even just a few minutes of loving-kindness meditation increased feelings of social connection and positivity toward novel individuals on both explicit and implicit levels. These results suggest that this easily implemented technique may help to increase positive social emotions and decrease social isolation.

Failure to find executive function deficits following one night's total sleep deprivation in university students under naturalistic conditions

Young adult male students participated in a naturalistic, group-design experiment to ascertain the effects of one night's total sleep deprivation (TSD) on performance of diverse executive function tasks presented as an extended, multitask battery. On the majority of component tasks in this battery, performance has been reported to be impaired following one night's TSD when tasks are administered in isolation. However, participants sleep deprived 35 to 39 hr showed few performance deficits among tests in this battery when compared with non-sleep-deprived controls. Sleep-deprived participants showed only poorer recognition memory and overconfidence in incorrect temporal judgments. Behavioral and physiological adaptation to chronically sleep-restricting lifestyles may confer resistance to the cognitive effects of sleep deprivation in high-functioning young adults.

Attention and emotion influence the relationship between extraversion and neural response

Extraversion has been shown to positively correlate with activation within the ventral striatum, amygdala and other dopaminergically innervated, reward-sensitive regions. These regions are implicated in emotional responding, in a manner sensitive to attentional focus. However, no study has investigated the interaction among extraversion, emotion and attention. We used fMRI and dynamic, evocative film clips to elicit amusement and sadness in a sample of 28 women. Participants were instructed either to respond naturally (n = 14) or to attend to and continuously rate their emotions (n = 14) while watching the films. Contrary to expectations, striatal response was negatively associated with extraversion during amusement, regardless of attention. A negative association was also observed during sad films, but only when attending to emotion. These findings suggest that attentional focus does not influence the relationship between extraversion and neural response to positive (amusing) stimuli but does impact the response to negative (sad) stimuli.

Attention and emotion: does rating emotion alter neural responses to amusing and sad films?

Functional neuroimaging of affective systems often includes subjective self-report of the affective response. Although self-report provides valuable information regarding participants' affective responses, prior studies have raised the concern that the attentional demands of reporting on affective experience may obscure neural activations reflecting more natural affective responses. In the present study, we used potent emotion-eliciting amusing and sad films, employed a novel method of continuous self-reported rating of emotion experience, and compared the impact of rating with passive viewing of amusing and sad films. Subjective rating of ongoing emotional responses did not decrease either self-reported experience of emotion or neural activations relative to passive viewing in any brain regions. Rating, relative to passive viewing, produced increased activity in anterior cingulate, insula, and several other areas associated with introspection of emotion. These results support the use of continuous emotion measures and emotionally engaging films to study the dynamics of emotional responding and suggest that there may be some contexts in which the attention to emotion induced by reporting emotion experience does not disrupt emotional responding either behaviorally or neurally.