Animals don't experience the world passively. A hawk tilts its head to track prey. A person leans forward to read a sign. Scientists call this "active sensing": moving the body to gather better information.
A specific version of active sensing is infotaxis, which describes how animals move strategically to maximize the information they gain from their surroundings. Whether mice use this strategy has remained an open question, despite their central role in neuroscience research.
Mice have low visual acuity, roughly seven to eight times worse than humans. They also lack foveas, the small, specialized areas in the eye's retina that allow us sharp, clear central vision, color perception, and fine detail.
Because of these apparent deficiencies, researchers have assumed that mice rely on smell, their whiskers, and hearing far more than sight. At the same time, we know that mice use vision for a range of tasks, from detecting predators and capturing prey to navigating spaces.
A team of scientists led by Mackenzie Weygandt Mathis, professor at the Bertarelli Foundation Chair of Integrative Neuroscience at EPFL, has now shown that mice do perform visual infotaxis. Using a custom-built virtual reality (VR) system, they show that mice move strategically to seek out more informative views of partially hidden objects, and that this behavior adjusts precisely to how much visual information is available.
The work is published in Current Biology.
Black and white teardrops
The researchers built a freely moving VR "arena" where a screen displayed a 3D scene rendered in real time from the mouse's point of view. They tracked the animals' positions and movements a 100 Hz overhead camera and DeepLabCut-Live , a marker-less tracking platform that Mathis's group developed in 2020.
Mice were trained to identify the location of a target object, a white teardrop, from a distractor, a black teardrop, and indicated their choice by walking to the corresponding side of the arena.
Then came the key manipulation: the screen would place virtual walls in front of both the target and distractor objects, leaving only a narrow central gap. In the most restricted condition of the first experiment, only 10% of each object was visible from the starting area. But as the mice walked closer to the screen, the viewing angle widened and more of the hidden objects came into view.
When the teardrops were mostly hidden, mice walked significantly closer to the screen before committing to a choice, slowed down during the approach, and took more winding paths. They sometimes reversed direction mid-trial when new visual evidence came in.
A fully open-source platform
The team tested five levels of occlusion and found that the mice's infotaxic behavior scaled continuously. The less the target was visible, the closer the mice moved before making a choice. Mice that moved closer also tended to make more correct choices under the most difficult conditions, suggesting that the strategy helped them solve the task.
The mice showed this behavior immediately when they first encountered occluded objects, after they had already learned the task. This suggests that they drew on an internal understanding of the environment to meet a new visual challenge.
The work shows that even mice, despite their relatively poor vision, actively move to gather better visual information rather than simply react to what they see. The team has made the platform fully open source and proposes that it is well suited for future studies combining brain recordings with active visual behavior, helping researchers understand how seeing and moving are coordinated in the brain.
This experiment, conducted under conditions governed by Swiss animal welfare legislation , was approved by the relevant veterinary authorities.
Other contributors
- Baylor College of Medicine
- Stanford University
- University of Oregon
- Carnegie Mellon University
- Rice University
- Columbia Engineering School
- Tübingen University
Reference
Célia Benquet, Thomas Sainsbury, Léo Bruneau, Yang Lin, Chenchen Cai, Mariia Popova, Kayla Ponder, Lydia Ntanavara, Rachel Froebe, Zheng Tan, Paul Fahey, Katrin Franke, Luis M. Franco, Keaton Jones, Yizhou Chen, Reece Keller, Xaq Pitkow, Cristopher M. Niell, Andreas S. Tolias, Mackenzie Weygandt Mathis. Visual uncertainty and task demands shape active sensing strategies in mice. Current Biology 20 July 2026. DOI: 10.1016/j.cub.2026.06.011
