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Single-cell organism's memories twists our understanding of intelligent life

Even the simplest of creatures may be able to make memories.

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Slime research may not be the sexiest science, but produces some truly wild results. So wild, in fact, a new study reconfigures our understanding of not only animal intelligence, but also the very idea of memory.

What's new — The study, published Monday in the journal Proceedings of the National Academy of Sciences, investigates how, exactly, giant slime molds (Physarum polycephalum) encode memories in response to food sources.

This study offers clues to how biological signals may generate and alter memories in even the simplest of creatures, according to the researchers.

Karen Alim is a co-author on the study and a professor at Technische Universität München, in Germany. She tells Inverse the study takes what we already knew about these curious life forms, and turns it on its head.

"There is previous work that biological signals within slime molds can store information about previous experiences," Alim says. "Yet, that the network architecture can store memories is [a] novel concept in the context of slime mold and fungi."

Slime mold memory holds clues to animal intelligence, a new study suggests.Philipp Fleig

How they did it — Alim and her team both observed a slime mold in a laboratory setting, and generated a theoretical model to aid their calculations.

Using images generated from their observations and the model, they determined changes in the organisms' tubes (essentially, the tendrils of slime emanating from the organism as it feels its way through an environment) in response to a newly introduced food source.

First, scientists calculated changes in the diameter or size of these tubes in response to the new food source, as well as what the slime mold did over the course of several hours.

It took the slime mold 45 minutes to reorganize its entire network of tubes to face the food source, they found. Around the 90-minute mark, the mold began migrating toward the food source. And after 310 minutes, the slime mold had almost fully engulfed the food source.

Surprisingly, when the scientists trimmed the mold down in size, the organism reorganized even more quickly — the smaller slime mold began to reorganize its tubes within 15 minutes, and began moving toward the food source within 45 minutes, according to the study.

Slime molds are known to "make decisions even within 10 to 20 [minutes]," according to the study. But what drives these decisions was more obscure. These new results offer some clues. As the researchers explain in the study, the slime molds appear to accomplish their remarkable reorganization as a result of encoding the location of the food source via the network of tubes.

Digging into the details — To test this idea, the scientists used their simulated mold to show how a mysterious agent from the food source would likely have entered the slime mold's tubes. In the simulation, the researchers unleashed a softening agent, which caused the tubes closest to the food to expand or dilate.

Tubes farther away from the food source do not expand as much as those closer to the food, essentially establishing a hierarchy of tubes. The engorged tubes then imprint the memory of the nutrient source in its network.

But this isn't just a one-time response. Rather, the slime mold has "irretrievably changed" the flow patterns of its tubes, according to the study — a sign of long-term memory formation.

A figure from the study showing expansion of the slime mold toward a food source.

These findings unlock a "missing piece of the puzzle" to explain how slime molds permanently reorganize themselves in response to nutrients.

In short: Slime molds encode memories of nutrient sources within their tubes. The tubes that survive the longest are those "directly bearing the memory of the nutrient stimulus that led to their growth," according to the study.

"Hence, memories stored in the hierarchy of tube diameters, and particularly in the location of thick tubes, are subsequently layered on top of each other, with every new stimulus differentially reinforcing and weakening existing thick tubes in superposition of existing memories."
An image showing the thickening of a slime mold's tubes. Philipp Fleig

Why it matters — This study hints at memory formation being possible in creatures lacking a nervous system — creatures like fungi or slime molds.

"I believe our study changes our perception on any flow networks in life, may it be our own vasculature or the networks formed by slime molds or fungi," Alim says.

In most animals, memory typically forms as a result of synaptic plasticity, whereby the brain makes connections across specific neuronal and synapse networks that are strengthened over time.

Slime molds lack synapses — or a nervous system at all. But this study shows they effectively mimic synaptic plasticity by encoding memories in their tube networks instead.

Memory formation was previously thought to exist only in higher-level organisms, like us, but now researchers are getting to grips with the idea even the simplest lifeforms have memory.

What's next — The study gives researchers more impetus to explore slime molds in science. Slime molds, for example, are capable of resolving the two-armed (also known as 'multi-armed') bandit problem, which is a problem to do with complex decision-making.

Slime molds are also incredibly good at finding the shortest route between food sources in a maze. These molds, in turn, help mathematicians overcome the traveling salesman problem, which seeks to find the shortest route for delivery drivers between cities.

A scientist holding up a slime mold.Nico Schramma

More immediately, the researchers behind this study want to understand the chemistry at play in the tubes as they change shape in response to food. Scientists speculate the chemical agent which causes the tubes to soften is adenosine triphosphate, an energy-carrying chemical. Future research may delve into the other properties and uses for this strange substance.

The researchers believe their findings may have unimagined implications for biology-inspired design in other fields, too, such as robotics. Much of the current research in artificial intelligence centers on models mimicking the nervous system, but this study provides a new, innovative source of inspiration for A.I. researchers.

"There is a lot of research aiming to design soft robots or built autonomous, intelligent systems. I believe the mechanism of storing information we discovered in Physarum will be very inspirational for this field," Alim says.

Abstract: The concept of memory is traditionally associated with organisms possessing a nervous system. However, even very simple organisms store information about past experiences to thrive in a complex environment—successfully exploiting nutrient sources, avoiding danger, and warding off predators. How can simple organisms encode information about their environment? We here follow how the giant unicellular slime mold Physarum polycephalum responds to a nutrient source. We find that the network-like body plan of the organism itself serves to encode the location of a nutrient source. The organism entirely consists of interlaced tubes of varying diameters. Now, we observe that these tubes grow and shrink in diameter in response to a nutrient source, thereby imprinting the nutrient’s location in the tube diameter hierarchy. Combining theoretical model and experimental data, we reveal how memory is encoded: a nutrient source locally releases a softening agent that gets transported by the cytoplasmic flows within the tubular network. Tubes receiving a lot of softening agent grow in diameter at the expense of other tubes shrinking. Thereby, the tubes’ capacities for flow-based transport get permanently upgraded toward the nutrient location, redirecting future decisions and migration. This demonstrates that nutrient location is stored in and retrieved from the networks’ tube diameter hierarchy. Our findings explain how network-forming organisms like slime molds and fungi thrive in complex environments. We here identify a flow networks’ version of associative memory—very likely of relevance for the plethora of living flow networks as well as for bioinspired design.
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