Summary: Animals do not experience their surroundings passively; they move strategically to harvest high-quality information from the environment. This behavior is known in cognitive science as “active sensing.” A highly specific variant of this is infotaxis, a phenomenon where an animal explicitly optimizes its spatial trajectory to maximize information gain. While rodents are the cornerstone of modern neuroscience research, it has remained an open question whether they possess the capacity for complex visual infotaxis due to their notoriously poor eyesight.
A new study shattered the long-held assumption that mice are purely reactive visual creatures. Researchers demonstrated that mice actively use visual infotaxis to solve complex spatial puzzles. Utilizing an innovative virtual reality (VR) arena coupled with marker-less AI tracking, the researchers proved that mice consciously alter their walking paths, approach angles, and speeds to seek out more informative views of partially hidden objects, adapting continuously to the amount of visual data available.
Key Facts
- The Visual Deficit Baseline: Mice have exceptionally low visual acuity—roughly seven to eight times worse than humans. They also entirely lack a fovea, the specialized retinal region responsible for sharp, detailed central vision and high-definition color perception.
- The Virtual Reality Arena: Because of these ocular limits, researchers previously assumed mice relied almost entirely on smell, whiskers, and hearing. To isolate vision, EPFL built a fully immersive 3D VR arena that rendered a digital landscape in real time based on the mouse’s immediate head and body position.
- The Teardrop Experiment: Mice were trained to distinguish a target object (a white teardrop) from a distractor (a black teardrop). Researchers then introduced virtual walls, occluding up to 90% of the objects and leaving only a narrow central gap for viewing.
- The Infotaxic Inversion: When the objects were heavily hidden, the mice did not guess blindly. Instead, they dynamically adjusted their behavior: they walked significantly closer to the screen to widen their viewing angle, slowed down, adopted winding paths, and even reversed direction mid-trial as new visual evidence emerged.
- Continuous Scaling & Instinct: The mice’s infotaxic behavior scaled continuously across five distinct levels of occlusion. Crucially, they displayed this information-seeking strategy immediately upon their first exposure to the hidden blockades, revealing an intrinsic, internal model of spatial physics rather than a simple conditioned habit.
- Open-Source Behavioral Blueprint: The EPFL team has made the entire VR and tracking platform fully open source. This allows neuroscientists worldwide to combine active visual processing with real-time neural recordings, pulling back the curtain on how the brain coordinates vision and motor control.
Source: EPFL
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.
Key Questions Answered:
A: It is precisely because their vision is so poor that they need infotaxis. Since mice lack a fovea, the retinal sweet spot that allows humans to see sharp details from far away, their world is naturally blurry and low-resolution. When an object is partially blocked by an obstacle, a mouse cannot simply squint or focus its eyes to see it better. It has to physically move its entire body closer, shift its posture, and change its viewing angle to harvest enough visual data to make an accurate decision. Infotaxis is their behavioral compensation for physical sensory limits.
A: The EPFL team used a highly controlled 3D virtual environment where they could manipulate the percentage of an object that was visible, down to just 10%. They discovered that the mice’s movements changed in direct mathematical proportion to how much of the target was hidden. When the teardrop object was fully visible, the mice ran straight toward it. But when it was heavily occluded, they immediately slowed down, took winding paths, and crept close to the screen to open up their field of view. They even executed sharp mid-course corrections the exact second the hidden parts of the object became visually exposed.
A: Historically, studying brain activity required animals to be completely immobilized under a microscope while looking at static images, which fails to capture how brains function during real-world movement. By making this VR arena and the DeepLabCut-Live AI software fully open source, the Mathis lab has given scientists worldwide a standardized, accessible blueprint to study the brain in action. Researchers can now record live neural circuits while an animal is freely running and executing active, information-seeking strategies, unlocking the secrets of how our brains weave seeing and moving together into a cohesive experience.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this visual neuroscience research news
Author: Nik Papageorgiou
Source: EPFL
Contact: Nik Papageorgiou – EPFL
Image: The image is credited to Neuroscience News
Original Research: The findings will appear in Current Biology
