UCLA

Understanding how subjects perceive sensory stimuli in their environment and use this information to guide appropriate actions is a major challenge in neuroscience. To study perceptual decision-making in animals, researchers use tasks that either probe spontaneous responses to stimuli (often described as "naturalistic") or train animals to associate stimuli with experimenter-defined responses. Spontaneous decisions rely on animals' pre-existing knowledge, while trained tasks offer greater versatility, albeit often at the cost of extensive training. Here, we review emerging approaches to investigate perceptual decision-making using both spontaneous and trained behaviors, highlighting their strengths and limitations. Additionally, we propose how trained decision-making tasks could be improved to achieve faster learning and a more generalizable understanding of task rules.