Locating what comes to mind in empirically derived representational spaces.

Area of Science:

• Cognitive Psychology
• Decision Science

Background:

• Real-world decisions involve open-ended options, making exhaustive consideration impossible.
• People tend to consider options with specific features, like high historical value.

Purpose of the Study:

• Investigate if option generation reflects a general mechanism for recalling information.
• Evaluate how feature spaces and relevance guide what comes to mind during decision-making.

Main Methods:

• Developed an empirical approach to derive feature spaces for categories.
• Mapped category members' likelihood of recall to their location within these feature spaces.
• Introduced a novel measure for general feature relevance.

Main Results:

• Category members' positions in feature spaces predict their recall likelihood.
• Recalled items originate from default locations, showing limited conscious control.
• Feature relevance correlates with a dimension's predictive power for recall.

Conclusions:

• Option generation is driven by recall based on representational space location.
• This mechanism prioritizes considering options with features predicted to be useful.
• Understanding this guides decision-making strategies in complex choice scenarios.