By balancing effort with the possibility of risks and rewards, honey bees make extremely rapid and accurate assessments of which flowers are most likely to provide them high-quality food – an amazing capacity that emerged after millions of years of evolution, according to a new study led by the University of Sheffield.
The researchers created a model of decision-making in bees and outlined the neural pathways that enable this capacity. As a result, the experts hope to enhance our understanding of both insect brains and how our own brains have evolved, while opening new pathways toward designing better robots.
“Decision-making is at the core of cognition,” said study senior author Andrew Barron, a professor of Biological Sciences at the Macquarie University in Australia. “It’s the result of an evaluation of possible outcomes, and animal lives are full of decisions. A honey bee has a brain smaller than a sesame seed. And yet she can make decisions faster and more accurately than we can. A robot programmed to do a bee’s job would need the back up of a supercomputer.”
“Today’s autonomous robots largely work with the support of remote computing. Drones are relatively brainless, they have to be in wireless communication with a data center. This technology path will never allow a drone to truly explore Mars solo – NASA’s amazing rovers on Mars have travelled about 75 kilometers in years of exploration.”
In their daily lives, bees are forced to work quickly and efficiently, finding nectar and returning it to their hives, while avoiding a variety of predators. To accomplish this, they need to make fast decisions regarding which flowers have nectar and what are the possible risks of predation while landing on these flowers.
“We trained 20 bees to recognize five different-colored ‘flower disks.’ Blue flowers always had sugar syrup. Green flowers always had quinine [tonic water] with a bitter taste for bees. Other colors sometimes had glucose,” explained lead author HaDi MaBouDi, a research fellow in Complex Systems at Sheffield.
“Then we introduced each bee to a ‘garden’ where the ‘flowers’ just had distilled water. We filmed each bee then watched more than 40 hours of video, tracking the path of the bees and timing how long it took them to make a decision.”
The investigation revealed that, if the bees were confident that a flower would have food, they would quickly decide to land on it, taking an average of 0.6 seconds. Similarly, if they were confident that a flower would not have food, they would just as quickly decide not to land on it. However, if they were unsure, they would take much more time – approximately 1.4 seconds – to reach a decision.
Afterwards, the scientists built a computer model aiming to replicate the bees’ decision-making processes, and discovered that the structure of this model turned out to be very similar to the physical layout of a bee’s brain.
“Our study has demonstrated complex autonomous decision-making with minimal neural circuitry. Now that we know how bees make such smart decisions, we are studying how they are so fast at gathering and sampling information. We think bees are using their flight movements to enhance their visual system to make them better at detecting the best flowers,” Marshall explained.
Since millions of years of evolution have led to highly efficient brains with very low power requirements, AI researchers have much to learn in devising robots from insects and other “simple” animals. Thus, the future of AI is likely to be inspired by biology, according to Marshall, who is also the co-founder of Opteran, a company devising algorithms inspired by insect brains to make autonomous machines as robust and efficient as nature.
The study is published in the journal eLife.
Despite having relatively small brains, bees have remarkable cognitive abilities. A bee’s brain is capable of complex tasks like navigation, memory, and learning. Here are some notable aspects about the bee brain:
A bee’s brain is divided into different sections, each of which has a specific role. The mushroom bodies are responsible for sensory integration and learning, the antennal lobes are involved in olfaction (the sense of smell), and the optic lobes are responsible for visual processing.
Bees are capable of associative learning, meaning they can associate certain smells or visual cues with rewards such as nectar. This ability is useful for remembering the locations of flowers. Bees have both short-term (a few seconds to minutes) and long-term memory (days to weeks), allowing them to remember the locations of food sources.
Bees use a combination of path integration, landmark recognition, and even the sun’s position in the sky to navigate. They can remember the direction and distance of their hive from a food source and communicate this information to other bees using a “waggle dance”.
Bees are also capable of sophisticated forms of communication. The most famous example is the waggle dance, which they use to tell other bees the direction and distance to a food source. The angle of the dance relative to the vertical indicates the direction relative to the sun, and the duration of the waggle phase indicates the distance.
Recent studies suggest that bees even have a basic understanding of numerical concepts. They can be trained to recognize colors representing specific quantities, and to choose between different numbers of shapes or symbols.
Bees have shown the ability to solve complex problems. For example, some studies have shown that bees can learn to pull a string or push a ball to receive a reward, demonstrating an understanding of cause and effect.
It’s important to note that while bees show these remarkable abilities, their brains are fundamentally different from human brains. They have evolved to be incredibly efficient at performing specific tasks necessary for their survival and reproduction, but they don’t have the same general intelligence that humans do. The study of bee brains and behavior can provide fascinating insights into how complex cognitive processes can emerge from relatively simple neural structures.