← Back to Writings
Research Paper

MST Honors English 10 — Camas High School / MST Magnet Program — October 9, 2024

The Intelligence of Brainless Organisms

Abstract

Physarum polycephalum, a brainless unicellular organism, is hypothesized to have the ability to create efficient pathways for our transportation, expand our knowledge on intelligence, and advance our modeling capabilities. Our project expanded on these proposed ideas by performing three distinct experiments to test the abilities of slime molds to make decisions, predict events, and solve problems. The first experiment prepared a culture of slime mold at the center of a Petri dish and placed an oat on the outside edge of the dish. This setup allowed us to observe as the slime mold sensed the oat from afar and progressively grew towards it, showing an ability to decide the direction the slime mold grows in order to achieve a reward. The second experiment tested the reactions of the slime mold to different environments to determine its ability to interact with its surroundings. Nine Petri dishes of slime mold were prepared and subjected to hot (100°F), cold (37°F), and baseline temperatures (70°F) for four hours. The results showed that the slime molds treated with high temperatures died off and didn't recover, cold temperature-treated slime molds were able to recover but grew more slowly, and baseline temperature-treated slime molds were the comparison group. These results show that slime molds are able to be affected by their environment and react based on their surroundings. The third experiment was to test the problem-solving capabilities of slime molds. They were placed at the entrance of a 3D printed maze with an oat at the exit and observed as they attempted to navigate the maze. Two of the three mazes of varying difficulties (easy, medium, and hard) were solved. The process of solving the difficult maze displayed active decision making, suggesting that slime molds have some semblance of intelligence and are able to efficiently map out pathways.

Introduction

Intelligence is something that humanity has always considered rare and a privilege, something that only a select few animals have that enables them to adapt, remember, and learn. As of now, people think of intelligence as something almost exclusively held by humans that has allowed us to spread to every corner of the planet, construct huge civilizations, and invent technology that connects all of it. Compared to all of these achievements, every creature would seem insignificant and incapable of even coming close to the intellect needed to pull this off. Recently, however, scientists may have found a new form of intelligence, an intelligence that doesn't even have a brain but performs the act of learning all the same. This specific type of single-celled organism could have the ability to further the connection between us and our inventions, creating efficient pathways for our transportation, solving mathematical problems, and advancing our modeling capabilities.

Understanding slime mold, or Physarum polycephalum, and how it functions can help us connect our cities and technology through the most efficient pathways while altering our definition of intelligence. Scientists debate what this organism actually is, but either way it's been seen to adapt and problem-solve to a startling degree. Altering its behavior, remembering changes, predicting events, and making decisions are only a few of the things this slime mold can do that can completely change the way we perceive intelligence. Its ability to travel in the most efficient way allows us to use it to model infrastructure, transportation, and even the dark matter of the universe. Past experiments have discovered that slime mold is able to almost completely accurately replicate already existing roads and transportation systems, potentially introducing a new method we could use to model infrastructure. Slime molds are an organism that can help us redefine what intelligence looks like outside of humans, along with potentially aiding us in designing models much more conveniently with their ability to map out the most effective path.

Historical Overview

Slime molds, or Physarum polycephalum, are brainless, single-celled organisms that for a long time were misclassified as fungi. Recently, scientists have realized that slime molds more closely resemble amoeba and have classified them as Myxomycetes in the Protista kingdom (George, 2023). They can be found practically everywhere, including Singapore, the Sonoran Desert, and Antarctica (Johnson, 2021). Many experiments have been performed on slime molds to discover what they're capable of, including a recreation of subways and roads in Tokyo that revealed an impressive ability to model efficient routes. The experiment concluded by noticing that after a few days, the slime mold retracted along the unnecessary paths and left behind interconnected slime branches that connected the pieces of food, closely resembling the man-made roads and subway lines that linked cities in Tokyo, Europe, and Canada (Jabr, 2012). Another experiment took place at Hokkaido University in Japan by Toshiyuki Nakagaki who spread the cut up pieces of a slime mold through a maze. After a few hours, they found that the slime mold thinned itself out until only the shortest path between the two pieces of food in the maze remained (Jabr, 2012). His experiment portrayed remarkable abilities for the slime mold to not only rejoin pieces of itself, but grow along the shortest and most efficient path in a maze, effectively solving it. Another experiment was designed to test the slime mold's behavior when an event is repeatedly performed. The researchers dropped the temperature of the slime mold's environment every 30 minutes to be outside of its ideal range, making it too dry. They found that the slime mold's movement began to slow in an effort to conserve energy. After a few trials of dropping the temperature, they stopped changing its environment, but its pace continued to slow until it eventually returned to normal (Jabr, 2012). These findings displayed not only a change in behavior, meaning that it could properly respond accordingly to its environment, but also a capability to predict these events accurately in order to perform this change in behavior and to later return to its previous state.

Aside from experiments, Physarum polycephalum has already been utilized in a few situations. Slime molds were used in a simulation performed by NASA to model the dark matter of the universe. They first found that there were similarities between the complex structures of Physarum polycephalum and the dark matter that connects galaxies, stating that, "There is an uncanny resemblance between the two networks: one crafted by biological evolution, and the other by the primordial force of gravity" ("Slime Mold Simulations", 2020). Scientists at NASA then designed a computer algorithm based on slime mold behavior which produced a three-dimensional model of the filaments that made up the dark matter and compared the results with a computer simulation. Slime molds can additionally be used to solve problems that are too complicated to otherwise solve. The Traveling Salesman Problem (TSP) is a problem where a salesman must visit n cities and return to the starting point through the shortest route possible. The problem gets exponentially more complicated as n increases which makes it difficult and time-consuming for computers to solve because of the sheer number of possible solutions. However, slime mold was able to solve this problem. The route they mapped was consistently below the average length of a route chosen at random, proving the slime mold's solution effective (Effron, 2018). This study showed that slime molds were able to successfully solve the TSP and therefore displayed an ability to model the most efficient route, which suggests the possibility of other problems similar to this one being solved with slime molds.

Current Trends and Practices

Many abilities and skills have been discovered that slime molds can do, most of which indicate a surprising amount of cognitive ability. Some of these include detecting objects from a distance, transferring information, and communicating chemically. At Harvard Wyss Institute, researchers discovered that slime mold could detect objects without physically contacting them through a process called mechanosensation, made possible by proteins called TRP channels, based on factors like mass and mass distribution. This process works similarly to how a person on a trampoline is able to sense the presence of others on it or how spiders can sense prey that's in their net by relying on vibrations or tension (Walecki, 2021). Based on the discoveries around slime molds' abilities, scientists further understand how exactly these organisms can make decisions and problem solve. By sensing objects from a distance and somehow predicting repetitive events, it's possible for slime molds to be a new kind of intelligence that has the potential to change how we perceive the world around us.

During experiments, researchers have split slime molds into separate pieces and had them grow and live their own lives, learn new things, and later fuse back together. They've found that during this, the individual pieces of slime mold can pass and gain learned information from each other (Johnson, 2021). This displays remarkable behaviors that suggest more potential than a collection of cells was previously believed to be capable of and a capacity for communication that can indicate something more advanced within these slime molds. In addition, slime molds can send chemical signals into the air which they use to attract other slime molds and increase their mass when food is scarce. According to Gillespie, this chemical process is called the plasmodial life state and can prevent competition and assists in communication ("The Intelligence of Slime Mold", 2019).

The process of caring for a slime mold and ensuring its survival depends on its habitat, diet, and maintenance needs. For Physarum polycephalum, it requires only a container with a damp paper towel and regular feeding, which is around every few days. To maintain its health, the bedding or material of its habitat needs to be changed every week by placing a new one near the old one to allow the slime mold to transfer itself over. If the slime mold colony needs to be divided, this can be done by transferring colonized oats to a different container or by separating a piece of paper covered in some polycephalum ("Looking after your slime", 2023).

Controversies and Debates

However, even though there is some evidence to suggest that slime molds are more intelligent than they appear, humans and slime molds are completely different organisms, and the single-celled slime doesn't possess anything resembling a brain or even a neuron. Behavior that resembles existing behaviors in humans doesn't necessarily mean that slime molds actively exercise it or that it implies higher intelligence. An example called habituation is when you acclimate to a cold temperature after a few minutes or tone out a buzzing background noise. Physarum polycephalum seems to do this by habituating to environments or chemicals that aren't ideal for them, including "acidic, dusty, dry, salty, or chemicals like caffeine or quinine," as long as they receive some sort of reward, like oats, for it (Shields, n.d.). But the mere fact that slime molds are willing to adapt to an environment if they receive a reward doesn't provide absolute evidence that they have the capacity to make decisions based on personal preferences or a higher level of thinking. The "habituation" that researchers have seen them perform could easily just be a survival mechanism instead of a choice to adapt to an environment.

Slime mold is furthermore composed of many cells that cooperate together and behave as one, more closely resembling a colony than an organism. This system of cells is "decentralized and myopic with no ability to plan over time and no 'over-the-horizon' vision of potential gains from new lines of exploration" (Little, 2020). This simply means that Physarum polycephalum lacks intellectual insight and behaves solely on short-term trial and error, which aren't signs of a more sophisticated capacity for intelligence. It's entirely possible that slime molds' pathway decisions are based not on a broader understanding of its surroundings, but random decisions that look like intelligence. From a slime mold's perspective, they're not solving elaborate mazes or mapping complex pathways, they're simply selecting a direction and later thinning itself into a simpler path that happens to be what we consider achievable and effective. Daniel Little further states that slime molds don't have beliefs, they don't have a central cognitive or executive function, and they lack a proper memory. These are all indications that some would say provide substantial evidence of an absence of intelligence and that the slime mold is only an adaptive system instead of a decision-making, self-aware creature.

Conclusion

Evidently, Physarum polycephalum holds great potential for assisting in the modeling of transportation systems and other forms of mapping to increase how efficient our interactions with the world are. Additionally, slime molds give us a further understanding of the cognitive functions in nature, furthering our understanding of how nature can behave. Precious technology and time can be spared from engineering routes of subways or metros by utilizing the mapping capabilities of slime molds, allowing this technology to be redirected towards other uses, such as exploration and discovery. Maximizing the efficiency of how human civilizations connect and interact with each other enables us to increase our connection with the more complex and unknown natural world. However, the key to achieving this connection is by first understanding the lengths to which unique organisms, like slime molds, can aid us in improving our technology and communication. By further researching the extent to which slime molds' potential can reach, we simultaneously expand our knowledge on how nature functions around us and create more efficient transportation systems, allowing us to ultimately improve the quality of life for our communities.

Materials and Methods

Physarum polycephalum is suspected to possess a greater degree of intelligence than its appearance may lead many to think. Its intelligence and pathway-mapping abilities can be tested through a variety of experiments, but our project focused on three specific tests to observe its decision-making abilities, reactions to environmental conditions, and capacity for problem-solving.

The first experiment, to test the decision-making capabilities of slime mold, utilized an environment where the slime mold was given an option to essentially grow immediately towards an award or slowly grow on its own until it reached a reward. We tested whether or not the slime molds would be able to sense a target from afar and then grow in the target's direction. We prepared eight Petri dishes with a cut out piece of plasmodium from a culture of growing slime mold. We prepared agar by heating 2% premade transparent lab agar gel to about 105°C to melt it and then pouring it in the Petri dishes to be about 3–5 mm deep. The agar was left to solidify for 30 minutes. We placed an oat next to each plasmodium in the center of the dish and on the edge. We then observed the direction that the slime mold grew in. Photos of the slime mold's growth were planned to be taken roughly every 2 hours or whenever was convenient. The distance grown between each photo was recorded in millimeters, as well as the direction in degrees from the center. (Figure 1: Setup of 8 Petri dishes prepared with plasmodium and oats.)

The second experiment tested the slime mold's responses to different environmental conditions over a period of time to determine the extent to which it can interact with its environment. This experiment used temperature as the independent variable, which consisted of hot temperatures at around 100°F, cold temperatures at 37°F, and a baseline temperature of around 73°F. The hot temperature was generated by heating a large sealable container in a heating grill and then placing the slime molds in it for 4 hours. The cold temperatures were simulated by placing the Petri dishes in a refrigerator for 4 hours. Nine Petri dishes were prepared with a 2% agar powder mixture. Each Petri dish was prepared with a dehydrated sclerotium and given three oats. Pictures were recorded every hour for four hours during the test and after the test, and more pictures were taken two days after the test to monitor the health of the slime molds. (Figure 2: Setup of the Petri dishes in the environmental conditions experiment.)

The third experiment tested slime mold's problem solving capabilities. We designed and printed a 3D maze with varying levels of difficulty; easy, medium, and hard. The easy maze was 8cm × 8cm and the medium and hard level mazes were both 10cm × 10cm. Once the mazes were printed, a culture of slime mold was grown to harvest from. Agar was prepared for the mazes and poured into each of the mazes and given 45 minutes to settle and solidify. A culture of slime mold was added to the mazes by cutting a centimeter by centimeter block of agar from the Petri dish and placing it at the entrance of the maze with 2 oats. Another oat was added to the end of the maze to give it an incentive and goal to reach. The mazes were covered with aluminum foil to limit contaminants and provide a dark environment. Pictures and data of the mazes were recorded twice a day, in the morning and at night. (Figures 3–4: 3D models designed in TinkerCAD and maze setup.)

Results

In the decision making experiment, the slime mold initially grew outwards in all directions for a few centimeters before narrowing in the general direction of the oat. In all of the trials, the slime mold successfully grew in the direction of the oat. At 48 hours, five of the eight slime molds began growing in the general direction of the oat and began growing significantly at 60 hours. After 75 hours, seven of the eight slime molds had successfully reached the target oat.

The environmental conditions experiment showed that the heated slime molds died off and weren't able to recover, while the cold ones were able to recover and grow again. However, their growth was slowed compared to the growth rates of baseline-temperature slime molds, showing that there was an effect on their health.

The slime mold successfully solved the easy maze on May 7 at 9:48 PM, four days after it was placed in the maze on May 3 at 11:03 AM. As it grew throughout the maze, it mostly grew in one straight path to the exit without any detours. The difficult maze was successfully completed on May 9th at 5:20 PM. The slime mold explored more of the dead ends and spread throughout more of the maze. On May 8th it was about two centimeters away from solving the maze, then reversed direction — most likely due to a gap in the agar — before completing it after an additional oat was added at the exit. The medium maze was not solved; the slime mold spent more time exploring dead ends, likely due to imperfect preparation of the starting culture.

Discussion

The decision-making experiment successfully displayed slime mold choosing to grow towards a reward. As time progressed, the variation between distance from the oat decreased until all except one slime mold had reached the oat. This shows that by almost 72 hours of growth, 7/8 of the slime molds had successfully grown towards the oat, displaying an ability to make decisions on where to grow based on the direction of a reward. Instead of aimless growth, the slime mold showed active decision making and an ability to grow in a directed and motivated manner.

The slime mold's responses to different environmental conditions show that they can actively interact with and be affected by their environment. High temperatures are detrimental to the wellbeing of slime molds and kill them, while colder temperatures only slowed the growth while the lower temperature was applied. Once the temperature was restored to normal levels, its growth rate returned to normal. The slime mold's responsiveness to environmental stimuli opens up possibilities for guiding its behavior and using it for modeling by controlling its surroundings.

The solving of the easy maze shows that slime mold has problem-solving capabilities and is able to solve problems quickly and efficiently. The difficult maze showed active decision making — after reversing direction near the exit and then completing the maze once rewarded more strongly, the results suggest that slime mold is capable of weighing the effort of a task against its reward. Future experiments should use a larger maze to allow the agar to stick to the walls better and more agar powder should be used in the mixture to make it more concentrated.

Conclusion

The experiments performed on the slime mold display decision making capabilities, problem solving, and adaptation that contribute to the idea that slime molds are capable of learning. The form of intelligence they could possess is supported by the findings from these experiments and suggests that slime molds and their many abilities could potentially be used in furthering scientists' definition of intelligence in the natural world and the way infrastructure and transportation are mapped. Together, these findings highlight the potential of slime molds not only as a tool for modeling complex systems like infrastructure and transportation networks, but also as an example of other forms of intelligence and decision making in the natural world.

References