Memory Without a Brain: How a Single Cell Uses Slime to Remember the World

1. Tokyo's Railway and a Brainless Engineer

In January 2010, a paper in *Science* left a group of Japanese and British scientists in a kind of philosophical confusion.

They placed a slime mold called *Physarum polycephalum* in a Petri dish, arranged oat flakes according to the geography of Tokyo and surrounding cities — nodes corresponding to Tokyo, Chiba, Yokohama, Kawasaki, Omiya, and Tsukuba. Then they turned off the lights and waited.

After 26 hours, the slime mold had retreated from the empty areas between the oat flakes, leaving behind an interconnected network of tubes. This network connected all the "cities," with a total length close to the shortest possible, fault tolerance close to optimal — and when overlaid on the map of the Tokyo rail network, the two were strikingly similar in topology.

Japanese railway engineers spent decades designing that system. An organism with no brain, no neurons, no eyes — not even a multicellular body — computed the same answer in 26 hours.

This is not a feel-good story about "slime molds being smart." It is a question about what intelligence actually is.

2. One Cell, Two Square Meters, Five Centimeters per Hour

Meet the protagonist.

*Physarum polycephalum* is a slime mold, taxonomically closer to amoebas than to fungi. Its most peculiar trait: its entire body is a single cell. Not "small like a bacterium," but genuinely large — in its plasmodial stage, this single cell can grow to two square meters, containing millions of nuclei sharing one mass of cytoplasm.

It moves at about 5 centimeters per hour, crawling through rotting wood and leaf litter, engulfing bacteria, fungal spores, and decaying plant matter. No mouth, no stomach, no limbs — it is a flowing blob of protoplasm that envelops food, digests it, and keeps crawling.

And yet, over the past two decades, this organism has repeatedly challenged biologists' definition of "cognition."

3. A Single Cell in a Maze

The story begins in 2000, when Toshiyuki Nakagaki of Hokkaido University cut a *Physarum* into pieces and scattered them across a plastic maze. The fragments grew, explored, and reconnected, eventually filling the maze.

Nakagaki then placed nutrient-rich agar blocks at the entrance and exit.

Four hours later, the slime mold had withdrawn from all dead ends, keeping only the tubes along the shortest path between the two food sources.

The result deeply unsettled researchers. Maze-solving is a classic search problem in computer science — you try paths, remember where you've been, backtrack, compare. The slime mold has no concept of "trying" or "backtracking"; it simply grows. But the way it grows is equivalent to running a breadth-first search across all possible paths simultaneously and keeping the shortest one.

Subsequent experiments deepened the puzzle. When oat flakes were placed at nodes of highway networks for Tokyo, Canada, the UK, and Spain, the slime mold reliably reconstructed transport networks highly similar to those designed by human engineers.

It doesn't know where Tokyo is. It doesn't know what a "city" is. It doesn't even know it's in a Petri dish. Yet it solves the same optimization problem.

4. Slime as Memory

In 2012, Chris Reid and his team noticed a detail: *Physarum* leaves a translucent slime trail as it crawls — and while foraging, it avoids its own slime.

This sounds like a simple instinct — "don't retread old ground." But Reid proposed a bolder interpretation: the slime trail is its memory.

Consider how memory is implemented in nervous systems: roughly, synaptic connection strengths between neurons are modified, forming a pattern that can be reactivated later. You need a storage medium (neurons), a write mechanism (learning), and a read mechanism (recall).

The slime mold's trail satisfies all three:

• Storage medium: the slime itself, deposited in the environment
• Write mechanism: automatic secretion during movement
• Read mechanism: behavioral change upon encountering slime (avoidance)

This isn't "like memory" — this is memory, except the storage medium is outside the body.

This "externalized memory" has a strange property: it requires no internal state. The slime mold doesn't need to "remember" where it has been, because the environment remembers for it. It only needs to read the environment to know where it shouldn't go.

5. Memory Can Be Overwritten

In 2013, Reid's team designed a more elegant test.

They placed the slime mold at the entrance of a Y-maze. One arm led to plain food; the other to highly nutritious food (egg yolk). But the path to the nutritious food was covered with the slime mold's own trail.

If "avoid slime" were a fixed reflex, the organism should have refused that path. Instead, it crossed its own slime and took the high-quality food.

This result matters enormously. It shows the slime trail is not a simple "no entry" sign but a memory signal that can be overridden. When the environment provides sufficiently valuable new information (high-quality food), old memory gets rewritten.

This is exactly what distinguishes "memory" from "reflex": memory is integrable. It doesn't mechanically trigger a behavior; it enters a "decision system" alongside other information and produces a combined judgment. The slime mold's decision system has no neurons, but what it does — weighing, comparing, overriding — is not fundamentally different from what neurons do.

6. Habituation: A Single Cell Gets Used to Things

In 2016, a CNRS research team ran another experiment. They had *Physarum* cross a "bridge" soaked in a bitter but harmless substance — quinine or caffeine.

Initially, the slime mold was very reluctant to cross. But after six days of exposure, its crossing speed returned to the level of the control group (no bitter substance). It had "gotten used to it."

After two days without exposure, it reverted to its initial wariness. And slime molds habituated to caffeine remained wary of quinine — and vice versa. The habituation was substance-specific.

In psychology textbooks, "habituation" is defined as the simplest form of learning. When a human infant is curious about a new toy and loses interest after a few days — that's habituation. The slime mold accomplishes the same thing with completely different molecular machinery, in a single cell with no neurons.

7. Another Intelligence Underground

If the slime mold is "a philosopher among single cells," mycorrhizal fungi are "the economists underground."

In February 2025, a 28-person team from Princeton University and VU Amsterdam published a paper in *Nature*, using purpose-built robotic microscope systems to observe fungal network behavior continuously for three years. These fungi weave vast mycelial networks between plant roots and soil — each hypha one-tenth the diameter of a human hair, but with total lengths spanning the underground of entire forests.

They found three things that force a rethink of "intelligence."

First, fungi favor future opportunity over short-term gain. Growing tips extend outward like pathfinders, investing in network expansion even where no immediately tradable resources exist. This "delayed gratification" is, in animal behavior, a complex decision requiring neural support.

Second, nutrients flow bidirectionally. Within the same tube, sugars flow from plant to fungus while phosphorus and nitrogen flow from fungus to plant — simultaneously. The team tracked roughly 100,000 flow trajectories and found the fungi adjust flow based on local demand — widening tubes and increasing flow near plant roots, like a city traffic system opening more lanes at rush hour.

Third, decision-making is decentralized. No "central processor" decides how the network grows. Each growing tip makes decisions based on local conditions — grow toward food, fuse with its own hyphae, detour around obstacles. But these local decisions aggregate into an efficient, fault-tolerant, adaptive global network.

This system has been running for about 500 million years. It stores 13 billion tons of CO2 per year — more than a third of global annual fossil fuel emissions. It supports the roots of nearly all land plants. And it does all of this without a single neuron.

8. Where Does Memory Actually Live?

Now back to the sleep-depriving question.

Traditional cognitive science carries an implicit assumption: memory resides in the brain; learning is done by neurons. The assumption is so deeply rooted that when we say "memory," we almost default to "something inside the brain."

The stories of slime molds and fungi break that assumption.

If memory can be stored in slime trails, then "memory" is not a specific biological structure but a functional pattern — any system that can record past states and influence future behavior can be memory. Neurons are merely one way of implementing this function, not the only way.

Philosophers have a concept called "Extended Cognition": cognitive processes are not confined within the skull but extend into the body and environment. When you do multiplication with pen and paper, part of the computation happens in your neurons and part on the paper. The paper and pen are part of the cognitive system, not external tools.

The slime mold pushes this idea to the extreme. Its "cognitive system" is almost entirely externalized — its body is merely an actuator, the real "memory" is in the slime it has crawled through, the real "sensors" are on the cell membrane touching its environment. It is an almost completely externalized cognitive system.

This sounds abstract, but it has a very concrete corollary: our definition of "intelligence" may be too narrow.

9. Implications for AI

Today's AI is built almost entirely on the "neural network" paradigm — inspired by the brain: artificial neurons, weighted connections, backpropagation. The field's success seems to prove that "neuron-style architecture is the correct implementation of intelligence."

But slime molds and fungi suggest another possibility.

*Physarum* solves mazes and reconstructs transport networks not through weight updates but through physical growth. It expands in all directions simultaneously, then contracts along nutrient gradients — a continuous, parallel, physically embedded optimization process. There is no separation between "training" and "inference"; it is always learning and always acting.

Mycorrhizal fungi solve resource-allocation problems not through backpropagation but through decentralized local decisions. Each hyphal tip knows only its own vicinity, yet the whole network exhibits globally optimal transport strategies. It resembles ant colony optimization or particle swarm algorithms — but running in an organism that has been "optimizing" this algorithm for 500 million years.

This doesn't mean neural networks are wrong. But it reminds us: intelligence may have many implementations, and we have seriously explored only one.

Imagine an AI whose "memory" is not stored in weight matrices but etched into the environment it operates in — an agent leaving traces in a file system, where its "experience" is the pattern of paths it has left. Imagine an AI whose decisions emerge not from a central model but from many simple local agents — each seeing only its neighborhood, yet collectively exhibiting complex behavior.

These are not science fiction. Slime molds and fungi have proven them feasible over 500 million years of evolution. We just haven't been listening carefully.

10. A Quiet Conclusion

*Physarum polycephalum* has no consciousness. It doesn't wonder who it is, doesn't feel pride in the elegance of the Tokyo rail solution, and experiences no inner struggle when crossing its own slime to reach an egg yolk. It is a single-celled organism doing what single-celled organisms do — crawl, engulf, flow, retreat.

Yet its behavior satisfies every functional criterion we use to define "memory" and "learning." It records the past, modifies the future, weighs information, and adapts to its environment.

This leaves an uncomfortable question: if "memory" doesn't require neurons, "learning" doesn't require a brain, and "decision-making" doesn't require consciousness — what are these words actually describing?

Perhaps they describe not a specific biological structure but a relational pattern — an ongoing conversation between a system and its environment, through some medium (slime, synapses, hyphae, silicon), about "what happened" and "what to do next."

Neurons are one carrier of this conversation. Slime is another. Hyphae are a third. Perhaps there are fourth and fifth kinds we haven't yet learned to see.

Next time you step past something yellow and slimy on a rotting log in the forest, pause for a moment. That is not a simple organism crawling aimlessly. That is a memory system without a brain, remembering the forest in its own way.

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References:

• Nakagaki et al. (2000). Maze-solving by an amoeboid organism. *Nature*.
• Reid et al. (2012). Slime mold uses an externalized spatial memory to navigate in complex environments. *PNAS*.
• Reid et al. (2013). The mechanism of flow-based optimization in *Physarum*. *Journal of Physics D*.
• CNRS (2016). A single-celled organism capable of learning. *ScienceDaily*.
• Tero et al. (2010). Rules for biologically inspired adaptive network design. *Science*.
• Oyarte Gálvez et al. (2025). A travelling-wave strategy for plant-fungal trade. *Nature*.
• Sims, M. (2025). Memories without brains. *Aeon*.