Decision-Making and Behavioral Economics

This study investigates how choice overload affects neural mechanisms in multiattribute decision making, finding inverse U-shaped DLPFC activity and linear ACC activity with choice set size.

The paper shows that humans generate sequences to evade prediction, but these sequences remain predictable due to biases in how people estimate others' predictions.

This paper introduces a state-dependent framework for drift diffusion models to better capture sequential decision-making in natural environments.

This paper shows acute stress reduces risk-aversion by altering magnitude perception, as evidenced by behavioral and neural changes in payoff valuation.

The paper tests whether people use explicit memory of past outcomes in experience-based decisions, finding that ignoring specific outcomes changes preferences, suggesting reliance on episodic memory rather than incremental reinforcement.

This study investigates whether ghrelin modulates risky decision-making through homeostatic state changes but finds no credible effects on behavior or neural activity.

The paper shows humans use a two-stage strategy for epistemic information seeking, combining streaking and uncertainty-guided exploration to improve inference accuracy.

The paper shows probability weighting arises from cognitive noise repelled by probability boundaries, confirmed through experiments on risky choice and perception.

The paper develops a quantitative model of transactions between buyers and suppliers for drugs and other commodities, showing how transaction rates vary with deprivation and satiation effects.

This study compares metacognitive ability across perception and valuation tasks using a computational model of confidence, finding it reliably estimable and well-conserved within domains.

The paper examines how control preferences differ between neurotypical individuals and those with OCD in contexts where decisions benefit self or charity, finding reduced control preference in neurotypicals and preserved preference in OCD individuals.

This paper introduces a foraging-theory-based model that better captures human behavioral diversity in sequential decision-making compared to traditional value-comparison models.

The paper examines how free choice preference changes in neurotypical and obsessive-compulsive individuals when decisions benefit charities, finding reduced preference for free choice in neurotypicals but not in those with OCD.

The paper shows that human exploration behavior follows a U-shaped pattern with the ratio of volatility to stochasticity in uncertain environments, with optimal performance at intermediate uncertainty ratios.

This study shows primate amygdala neurons encode subjective values consistent with economic choice theory, integrating reward probability and magnitude into decision-making.

The paper identifies a dominant nonlinear axis of individual variability in decision-making tasks, showing that exploration tendency, rather than personality or learning parameters, drives differences in performance.

The paper introduces a framework using neural networks to predict human decision-making across different task conditions by encoding individual behavior into a latent representation.

This study shows that rats adjust their risk preferences based on environmental richness, spending more time on low-variance options with short travel delays.

The paper shows that biased neural replay of aversive and uncertain outcomes underlies irrational decision making in humans.

This study shows that parietal magnitude representations causally influence risk preferences by increasing noise in small-magnitude encoding, leading to more risk-seeking behavior.

The paper investigates how people infer the elasticity of control in environments and shows that misestimations lead to maladaptive behavior and psychopathology.

This study shows that humans, rats, and mice invest time based on statistical confidence, approaching optimal time allocation strategies under uncertainty.

This paper demonstrates myside confirmation bias-like behavior in mice during rule revision tasks, showing it emerges through deliberative processes rather than heuristic responses.

This paper derives an optimal patch foraging policy incorporating temporal discounting and shows how it differs from the Marginal Value Theorem under varying conditions.

This study investigates how humans prioritize decisions during planning by analyzing gaze and choice behavior in a multi-category task involving subjective value assessments.

This study identifies context-dependent repetition as a driver of decision biases and demonstrates a computational model based on reward learning and decision repetition that outperforms existing models.

The paper shows that imprecise counting of observations in averaging tasks leads to primacy and recency effects, modeled by a Bayesian central tendency mechanism.

The paper compares the long-term dynamics of idiosyncratic choice bias and feedback-induced bias, finding that feedback-induced bias is transient while idiosyncratic bias remains stable.

This study shows humans use divisive normalization in two different choice environments, suggesting it is a fixed cognitive mechanism.

The paper investigates whether gains are prioritized over losses in perception and finds greater limbic activity for gains in fMRI studies.