Mimosa pudica
A series of tests on plants concluded that they are able to “tell” the time and anticipate repeated cycles of light and dark.
For decades, science assumed that functions such as learning, memory and decision-making depended exclusively on the existence of a brain. However, a new published in the journal Cognitive Science challenges this idea by presenting evidence that plants can process information in a complex way, even without neurons.
The research was led by Peter Vishton, a psychology professor at William & Mary, in collaboration with his former student Paige Bartosh. The researchers focused on the plant Mimosa pudicaknown as close the leaves when touchedto explore its responsiveness to environmental standards.
In a set of experiments carried out in a controlled environment, plants were subjected to repeated cycles of light and dark. Initially, they followed a 24-hour pattern, with 12 hours of light and 12 hours of darkness, for two days, followed by a third day with continuous darkness. After a few repetitions, the plants began to anticipate the arrival of lightshowing greater activity before the expected lighting period.
According to Vishton, this behavior suggests that plants can “learn” environmental standards and adjust your response based on experience. The evolution of this response followed a logarithmic curve, similar to that observed in learning processes in animals, where there is an initial phase of rapid adaptation followed by stabilization, explains .
To rule out the hypothesis that plants were simply following an internal clock, the researchers changed the length of cycles. When the daily pattern was reduced to 20 hours, the plants quickly adjusted their behavior. In an additional test, the cycles were made random, varying between 10 and 32 hours.
The results showed that the response pattern remained consistent only in cycles between 12 and 24 hours. Outside this range, the capacity for anticipation disappeared. This led scientists to conclude that plants could be “counting events”, such as the alternation between light and dark, rather than just tracking time.
If confirmed by future studies, these conclusions could have profound implications for understanding biological intelligence. Research suggests that forms of learning can exist without neuronsraising the possibility that other cells, including in human organisms, may also play unexpected roles in information processing.
The results also open the door to innovative applications, such as biological computing systems or plant-based sensors.
