Perceptual decision-making: extending a standardized rodent task to humans

Abstract

Mice are widely used to study the neural basis of perceptual decision-making, often with the ultimate goal of extrapolating insights to humans. Yet, whether humans and mice rely on similar computational strategies remains rarely tested, partly because the two species acquire knowledge differently. Animals learn from experience, while humans usually receive verbal task instructions. Here, we explicitly contrast these modes of learning in humans who perform a perceptual decision-making task adapted from a standardized rodent task. Specifically, we present an open behavioral dataset from 80 human participants who performed 600 trials of a visual contrast-discrimination task, matched to the standardized International Brain Laboratory task for mice (International Brain Laboratory et al., 2021, 2025). Participants either received verbal instructions ('Instructed') or were only told to discover the rules of the task by playing ('Uninstructed'). The dataset contains choices, response times, continuous cursor trajectories, eye-tracking and pupil recordings. Descriptive analyses show that Uninstructed participants were less accurate and had higher lapse rates than Instructed participants. They improved over the first 200 trials, approaching the performance of Instructed participants. These data provide a benchmark for testing whether computational strategies identified in mice also describe human behavior.