Plants have neither eyes nor brains, but they can be fooled by “optical illusions.” They aren’t deceived by perceptions of images, though, but by the different intensities of light falling on them from multiple directions.

Researchers at a university in Israel developed a physical and geometric framework that shows how phototropic plants integrate light coming from multiple directions in a way that can sometimes cause them to grow in a slightly different direction from the brightest illumination (Proc. Natl. Acad. Sci. U.S.A., doi: 10.1073/pnas.2614473123). Since plants do not have a central nervous system for guidance, the team proposes that plants operate as a distributed system: gathering light with local sensors (found mostly in the outer layer of the stem), converting it into signals nonlinearly and then adding the signals together. The researchers say their work helps explain the poorly understood phenomenon of coherent response to distributed sensing in biological systems.

Understanding plant tropisms

Without the abilities to react to light and gravitational pull, plants wouldn’t survive on Earth. But even though scientists have extensively studied these tropisms—movements in response to environmental stimuli—they still haven’t figured out exactly how these organisms respond to light coming from different directions. Now, a team of researchers developed an experimentally informed mathematical model to explore just that.

A multidisciplinary team at Tel Aviv University kept sunflower seedlings under first one and then two blue LED panels with a wavelength of 450 nm. The panels, which produced light of varying intensities, were set up facing one another on two sides of a plant holder grid. To quantify movement, the researchers painted two location points on the plant shoots, one at the tip of the plant and another a few millimeters below. Side-view images carefully recorded the plants’ phototropic movements in these unilateral and bilateral experiments and basic image analysis converted the images into data points.

The results showed that the seedlings grew in the direction of the stronger light, but their bending was not directly proportional to the differences in light intensities. This happens, according to the researchers, because a plant’s response to light is nonlinear—a light source with twice the intensity does not stimulate a biological signal that is also twice as strong. When the plants add together the processed biological signals from the light, the resulting direction may be different from what would be expected from the simple physical addition of the light sources. The model was able to correctly predict how strongly and in what direction the shoots would grow in this experimental setup.

Plant delusions

Further experiments exposed the seedlings to three spatially distributed light sources. The researchers added a third, dimmer light panel perpendicular to the first two opposing lights and recorded images from a top view. The painted points were not visible in this configuration, so the researchers tracked the leaves instead with object-detection computer vision trained on segments of the leaf regions.

These tests led to a result not predicted by the mathematical model: The plants grew toward the dimmest of the three sources. The Tel Aviv team attributes this “optical illusion” to the nonlinear response of the seedlings to illumination coming from opposite directions that cancel each other out. In other words, plants combine the directional light signals before growing toward any light.

“What is fascinating is that plants can integrate complex information about their environment without a brain or central processing system,” said Yasmine Meroz in a press release accompanying the work. “The computation emerges from the way light is sensed and processed locally across the stem. Our work shows how the physical organization of a sensory system can determine how an organism perceives and responds to its environment. This principle may extend far beyond plants, to cells, bacteria, and other living systems that rely on distributed sensing.”