Researchers have become increasingly aware that data-analysis decisions affect results.
Here, we examine this issue systematically for multinomial processing tree (MPT) models, a …

Cognitive models have been instrumental for generating insights into the brain processes
underlying learning and decision making. In reinforcement learning it has recently been …

The relation between religiosity and well-being is one of the most researched topics in the
psychology of religion, yet the directionality and robustness of the effect remains debated …

The drift-diffusion model (DDM) is an important decision-making model in cognitive
neuroscience. However, innovations in model form have been limited by methodological …

Evidence accumulation models (EAMs) have been the dominant models of speeded
decision-making for several decades. These models propose that evidence accumulates for …

In cognitive neuroscience, computational modeling can formally adjudicate between
theories and affords quantitative fits to behavioral/brain data. Pragmatically, however, the …

Older adults typically show slower response times in basic cognitive tasks than younger
adults. A diffusion model analysis allows the clarification of why older adults react more …

People tend to believe that their perceptions are veridical representations of the world, but
also commonly report perceiving what they want to see or hear. It remains unclear whether …

This article presents a theory in which motor execution in perceptual decision-making tasks
is determined by the same evolving decision variable that drives response time. The theory …

Most current sequential sampling models have random between-trial variability in their
parameters. These sources of variability make the models more complex in order to fit …