Related Experiment Video
Updated: Jan 8, 2026
04:43
Visualizing Visual Adaptation
Published on: April 24, 2017
9.5K
What if eye...? Computationally recreating vision evolution
Kushagra Tiwary1, Aaron Young1, Zaid Tasneem2
1Camera Culture, MIT Media Laboratory, Cambridge, USA.
Science Advances
|December 17, 2025
Summary
Computational evolution simulates eye and behavior development, revealing task-specific selection drives eye diversity and optical innovations. It uncovers scaling laws between visual acuity and neural processing for vision science discovery.
Area of Science:
- Evolutionary Biology
- Computational Neuroscience
- Artificial Intelligence
Background:
- Natural selection has shaped diverse vision systems.
- Computational evolution provides a method to test hypotheses in vision.
- Understanding the evolutionary pressures on vision is crucial.
Purpose of the Study:
- To computationally recreate and analyze the evolution of vision.
- To investigate the principles shaping vision across different levels of Marr's hierarchy.
- To use embodied artificial intelligence (AI) as a tool for hypothesis testing in vision science.
Main Methods:
- Co-evolving eyes and behaviors in embodied agents.
- Utilizing computational evolution to simulate evolutionary outcomes.
- Analyzing the emergence of optical innovations and their trade-offs.
Main Results:
- Task-specific selection drives the bifurcation of eye evolution.
- Optical innovations emerge to balance light collection and spatial precision.
- Identified scaling laws between visual acuity and neural processing.
Conclusions:
- Computational evolution offers a powerful paradigm for understanding vision.
- Embodied AI can accelerate scientific discovery in vision science.
- The study provides insights into the evolution of eye and brain size.
Related Concept Videos
01:15Depth Perception and Spatial Vision
1.7K
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
1.7K
01:26Visual System
1.6K
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Once through the pupil, the light passes through the lens, a...
1.6K
01:24Vision
59.2K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
59.2K
01:22Photoreceptors and Visual Pathways
8.6K
At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
8.6K