Unraveling the complex interplay of sex, endocrinology, and inflammation in post-Injury articular cartilage breakdown through in silico modeling.

The onset of degenerative joint diseases such as post-traumatic osteoarthritis (PTOA) are associated with joint injury, biomechanical changes, and synovial biochemical anomalies. Sex and reproductive endocrinology have been emerging as potential risk factors, with epidemiological evidence revealing that female's exhibit higher PTOA risk and poorer outcomes post-injury compared to males. Sex hormones, including estradiol, progesterone, and testosterone, have been shown to regulate inflammatory signaling in immune and synovial cells, yet their collective impact on injury-induced joint inflammation and catabolism is poorly understood.

How bad becomes good: A neurocomputational model of affect-informed choice.

People often draw on their current affective experience to inform their decisions, yet little is known about the underlying mechanisms of this process. Understanding them has important implications for many big questions in both the affective and decision sciences. Do the same neural circuits that generate affect generate value? What differentiates people who have greater contextual flexibility in their reliance on affect? Do affective choices invoke processes that are distinct from less affective choices? To investigate these questions, we developed a neurocomputational model of affect-informed choice, in which people convert subjective affect into context-sensitive decision value through a process of weighted evidence accumulation.

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.

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.

A neurocomputational account of the link between social perception and social action.

People selectively help others based on perceptions of their merit or need. Here, we develop a neurocomputational account of how these social perceptions translate into social choice. Using a novel fMRI social perception task, we show that both merit and need perceptions recruited the brain's social inference network.

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.

Low-Grade Inflammatory Mediators and Metalloproteinases Yield Synchronous and Delayed Responses to Mechanical Joint Loading.

Objective: Mechanical loading is an essential factor for the maintenance of joint inflammatory homeostasis and the sensitive catabolic-anabolic signaling cascade involved in maintaining cartilage tissue health. However, abnormal mechanical loading of the joint structural tissues can propagate joint metabolic dysfunction in the form of low-grade inflammation. To date, few studies have attempted to delineate the early cascade responsible for the initiation and perpetuation of stress-mediated inflammation and cartilage breakdown in human joints.

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.

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; = 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 ( = 394) in Spring 2020 regarding the direction of change for a range of social and psychological phenomena.

Elucidating medial temporal and frontal lobe contributions to approach-avoidance conflict decision-making using functional MRI and the hierarchical drift diffusion model.

The prefrontal cortex (PFC) has long been associated with arbitrating between approach and avoidance in the face of conflicting and uncertain motivational information, but recent work has also highlighted medial temporal lobe (MTL) involvement. It remains unclear, however, how the contributions of these regions differ in their resolution of conflict information and uncertainty. We designed an fMRI paradigm in which participants approached or avoided object pairs that differed by motivational conflict and outcome uncertainty (complete certainty vs.

Reframing rationality: Exogenous constraints on controlled information search.

Bermúdez argues that framing effects are rational because particular frames provide goal-consistent reasons for choice and that people exert some control over the framing of a decision-problem. We propose instead that these observations raise the question of whether frame selection itself is a rational process and highlight how constraints in the choice environment severely limit the rational selection of frames.

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.

Sexual Dimorphism in the Extracellular and Pericellular Matrix of Articular Cartilage.

Objective: Women have a higher prevalence and burden of joint injuries and pathologies involving articular cartilage than men. Although knee injuries affecting young women are on the rise, most studies related to sexual dimorphism target postmenopausal women. We hypothesize that sexual dimorphism in cartilage structure and mechanics is present before menopause, which can contribute to sex disparities in cartilage pathologies.

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.

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.

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.

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.

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.

Beta oscillations following performance feedback predict subsequent recall of task-relevant information.

Reward delivery in reinforcement learning tasks elicits increased beta power in the human EEG over frontal areas of the scalp but it is unclear whether these 20-30 Hz oscillations directly facilitate reward learning. We previously proposed that frontal beta is not specific to reward processing but rather reflects the role of prefrontal cortex in maintaining and transferring task-related information to other brain areas. To test this proposal, we had subjects perform a reinforcement learning task followed by a memory recall task in which subjects were asked to recall stimuli associated either with reward feedback (Reward Recall condition) or error feedback (Error Recall condition).

Attentional priorities drive effects of time pressure on altruistic choice.

Dual-process models of altruistic choice assume that automatic responses give way to deliberation over time, and are a popular way to conceptualize how people make generous choices and why those choices might change under time pressure. However, these models have led to conflicting interpretations of behaviour and underlying psychological dynamics. Here, we propose that flexible, goal-directed deployment of attention towards information priorities provides a more parsimonious account of altruistic choice dynamics.

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.

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.

Oxytocin and the altruistic 'Goldilocks zone'.

When choosing whether to act altruistically, people may compare the current option to an idiosyncratic ideal. Pro-social individuals seem to represent deviations from that ideal in the amygdala, but selfish individuals do not. Oxytocin administration makes selfish individuals look more like pro-socials, behaviorally and neurally.

Deconstructing Theory-of-Mind Impairment in High-Functioning Adults with Autism.

Inferring the beliefs, desires, and intentions of other people ("theory of mind," ToM) requires specialized psychological processes that represent the minds of others as distinct from our own [1-3]. ToM is engaged ubiquitously in our everyday social behavior and features a specific developmental trajectory [4] that is notably delayed in children with autism spectrum disorder (ASD) [5, 6]. In healthy individuals, model-based analyses of social learning and decision-making have successfully elucidated specific computational components of ToM processing [7-11].

Accounting for Taste: A Multi-Attribute Neurocomputational Model Explains the Neural Dynamics of Choices for Self and Others.

How do we make choices for others with different preferences from our own? Although neuroimaging studies implicate similar circuits in representing preferences for oneself and others, some models propose that additional corrective mechanisms come online when choices for others diverge from one's own preferences. Here we used event-related potentials (ERPs) in humans, in combination with computational modeling, to examine how social information is integrated in the time leading up to choices for oneself and others. Hungry male and female participants with unrestricted diets selected foods for themselves, a similar unrestricted eater, and a dissimilar, self-identified healthy eater.