New research challenges the long-held assumption that brains are required for learning, suggesting plants may process information in unexpected ways.
For decades, scientists have assumed that learning, memory, and decision-making require a brain. However, growing evidence, including a recent study published in Cognitive Science, challenges that idea and suggests that complex information processing may not depend on neurons.
The study, led by William & Mary psychology professor Peter Vishton and his former student Paige Bartosh, suggests that plants may be able to count. Not in the human sense, but Mimosa pudica appear to be able to “keep track of the number of events in their environment,” said Vishton.
According to the researchers, this is the first evidence that plants can enumerate, meaning they can distinguish and track separate events.
Mimosa pudica, often called the shy plant or touch-me-not, has delicate, frond-like leaves that fold inward when touched or shaken. The leaves also close at night and reopen with daylight, a movement known as nyctinasty.
Experimental Setup and Plant Behavior Observations
In a humid tent inside a windowless room at William & Mary’s Integrated Science Center, the researchers exposed the plants to repeating cycles of light and darkness and monitored their responses.
“In the first phase of our experiment, we used a 24-hour cycle. On days one and two, the plants were exposed to 12 hours of darkness and 12 hours of light. On day three, the lights remained off,” Vishton explained.
After about five repetitions, the plants began showing increased movement during the “pre-dawn” period on days when light was expected, but not on the third day when darkness continued.
Evidence of Learning and Pattern Recognition
“This seems to suggest that the plants were able to ‘learn,’ for lack of a better word, this three-day cycle and shift their movement in response,” said Vishton.
Modeling this shift yielded a logarithmic curve, meaning the plants’ movement changed rapidly at first before gradually stabilizing into a consistent pattern.
“This is the same pattern we see all the time in animal learning,” said Vishton. “For example, if you are teaching a rat to perform a series of actions in a certain order, you would expect to see a period of time when they’re figuring out the sequence and then a gradual increase in their ability to predict the pattern.”
Time Tracking vs Event Counting Hypothesis
To rule out another explanation, the team tested whether the plants were tracking time instead of counting events.
“It’s well established that many plants move in alignment with a 24-hour circadian rhythm, opening up in anticipation of the sun,” said Vishton. “While no evidence suggests plants can track a 72-hour cycle — the duration of the three-day pattern in our study — we wanted to test that possibility.”
When the researchers shortened the daily cycle from 24 hours to 20 hours, the plants quickly adjusted their movement to match the new pattern. To further test their hypothesis, they ran a final experiment in which each three-day cycle varied randomly, ranging from 10 hours (five hours of light and five of dark) to 32 hours.
Testing Limits of Plant Memory and Patterns
They found that the pattern broke down when the cycles were shorter than 12 hours or longer than 24 hours. This suggests there may be both a minimum time needed for plants to process light and dark signals and a limit to how long they can retain that information.
Within the 12-24 hour range, however, the plants consistently showed more movement on days when light was expected compared to days of continued darkness.
“The simplest explanation for this result is that these plants are tracking the number of events that take place,” said Vishton. “Not simply responding to time.”
Implications for Non-Neuronal Intelligence
If confirmed by future studies, these findings point to a form of information processing that does not rely on neurons.
“Every theory I’ve ever read on memory and decision making always involves neurons,” said Vishton. “Big surprise, plants don’t have those. And yet it looks like they can perform cognitive-like functions. Just not cognitively, per se.”
The results raise the possibility that other non-neuronal cells may also be capable of learning.
“There are lots of cells in animals and humans that aren’t neurons. And we just assume they’re not involved in learning,” said Vishton. “But maybe they could be. Maybe learning is present in every cell. We’ve just never really studied it before.”
Future Research and Broader Impact
How this type of intelligence works at a biological level remains unclear and will require further research.
“As a developmental psychologist, I’m interested in characterizing behavior,” said Vishton. “I’m hoping the chemists and biologists of this world can ask more mechanistic questions to understand how this is actually happening. With more research on both fronts, I’m very excited to see where this field of study is headed.”
Potential applications could include biological computing systems, plant-based sensors, and even approaches to help people “unlearn” addictive behaviors at the cellular level.
Blurring the Line Between Plant and Animal Intelligence
By pointing to a new kind of intelligence, the findings add to growing evidence that the boundary between plants and animals may not be as clear as once believed.
“Typically, we don’t conceptualize plants as thinking, behaving creatures, right? We think of them as reflexive objects that are responding to stimuli in a simple way,” said Vishton. “But, at least to me, our results suggest that there might not be this boundary between the animal and the plant kingdom — or it might be a lot more porous than we think.”
Reference: “Can Mimosa pudica Plants Enumerate Light Exposure Events?” by Peter M. Vishton and Paige J. Bartosh, 28 December 2025, Cognitive Science.
DOI: 10.1111/cogs.70161
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