A map of decoy influence in human multialternative choice.

Human decisions can be biased by irrelevant information. For example, choices between two preferred alternatives can be swayed by a third option that is inferior or unavailable. Previous work has identified three classic biases, known as the attraction, similarity, and compromise effects, which arise during choices between economic alternatives defined by two attributes.

Perceptual suboptimality: Bug or feature?

Rahnev & Denison (R&D) argue that whether people are "optimal" or "suboptimal" is not a well-posed question. We agree. However, we argue that the critical question is why humans make suboptimal perceptual decisions in the first place.

Gain control explains the effect of distraction in human perceptual, cognitive, and economic decision making.

When making decisions, humans are often distracted by irrelevant information. Distraction has a different impact on perceptual, cognitive, and value-guided choices, giving rise to well-described behavioral phenomena such as the tilt illusion, conflict adaptation, or economic decoy effects. However, a single, unified model that can account for all these phenomena has yet to emerge.

Robust averaging protects decisions from noise in neural computations.

An ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant ('robust averaging'). Why humans adopt an integration policy that discards important decision information remains unknown.

Robust sampling of decision information during perceptual choice.

Humans move their eyes to gather information about the visual world. However, saccadic sampling has largely been explored in paradigms that involve searching for a lone target in a cluttered array or natural scene. Here, we investigated the policy that humans use to overtly sample information in a perceptual decision task that required information from across multiple spatial locations to be combined.