Reinforcement learning theories postulate that actions are chosen to maximize a long-term
sum of positive outcomes based on value functions, which are subjective estimates of future …

In reinforcement learning (RL) experiments, participants learn to make rewarding choices in
response to different stimuli; RL models use outcomes to estimate stimulus–response values …

Here we report persistent choice variability in the presence of a simple decision rule. Two
analogous choice problems are presented, both of which involve making decisions about …

The strategies found by animals facing a new task are determined both by individual
experience and by structural priors evolved to leverage the statistics of natural …

Reinforcement learning causes an action that yields a positive outcome more likely to be
taken in the future. Here, we investigate how the time elapsed from an action affects …

Temporal limits on perceptual decisions set strict boundaries on the possible underlying
neural computations. How odor information is encoded in the olfactory system is still poorly …

Concentration invariance—the capacity to recognize a given odorant (analyte) across a
range of concentrations—is an unusually difficult problem in the olfactory modality …

Rodents can learn from exposure to rewarding odors to make better and quicker decisions.
The piriform cortex is thought to be important for learning complex odor associations; …

In reinforcement learning (RL) experiments, participants learn to associate stimuli with
rewarding responses. RL models capture such learning by estimating stimulus-response …

Choice history effects describe how future choices depend on the history of past choices. In
experimental tasks this is typically framed as a bias because it often diminishes the …