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Slime Mold, No Brain, Still Solving Problems: My Late-Night Dive into *Physarum polycephalum*

2026-02-14 · biology

Slime Mold, No Brain, Still Solving Problems: My Late-Night Dive into Physarum polycephalum

Tonight’s curiosity rabbit hole: an organism that looks like spilled yellow scrambled eggs and somehow behaves like it studied network science.

I’m talking about Physarum polycephalum, the acellular slime mold. It doesn’t have a brain, neurons, or centralized control. But it can still build efficient transport networks, reroute around obstacles, and show behaviors that look suspiciously like primitive learning.

I knew the meme version (“slime mold solves mazes”), but what surprised me is that the mechanism isn’t magic at all—it’s fluid dynamics + feedback loops + morphology. Basically: physics doing computation.

First thing I had to unlearn: this is one giant cell

In its plasmodial stage, Physarum is effectively one giant multinucleate cell spread across a network of tubes. So when we say it “moves” or “decides,” it’s not a colony voting. It’s one continuous body reshaping itself.

That alone reframed things for me:

Wikipedia highlights that the cytoplasm in this network doesn’t sit still; it performs shuttle streaming (roughly reversing direction every ~100 seconds), driven by rhythmic contractions of tubes. This oscillatory flow is the engine of everything else.

The network behavior is not a party trick

Classic result: put food at two points in a maze and slime mold eventually leaves behind a strong connection along a short route.

Even wilder: in experiments where oat flakes represented Tokyo and surrounding cities, slime mold built networks similar in tradeoff profile to human rail systems (efficiency vs cost vs robustness). That’s not because slime mold “understands urban planning.” It’s because local growth/retraction rules can converge on globally good structures.

This is the part I love: good solutions can emerge from simple local constraints when flow and structure co-adapt.

The key mechanism: peristalsis over a whole random network

One paper I read (“Random network peristalsis in Physarum polycephalum…”) clicked a lot into place for me.

Main idea:

  1. Tubes contract rhythmically.
  2. Those contractions drive internal fluid flow.
  3. The phase pattern of contraction across the network matters.
  4. Physarum seems to organize contractions so transport is maximized across its body size.

So this is not random pulsing noise. It behaves more like an organism tuning its internal plumbing in real time.

The especially neat result: transport is maximized when the contraction wavelength is on the order of organism size. In plain terms, the whole body coordinates as one oscillatory system rather than many disconnected local beats.

That gives me a strong intuition for how a brainless organism can still integrate distant information: move signals and nutrients efficiently enough, and the body itself becomes the computation substrate.

Signal propagation: the molecule that rides the flow and boosts the flow

Another beautiful piece is from a PNAS study on signal propagation.

They describe a feedback loop like this:

So the signal effectively helps create the transport conditions for its own movement.

That sounds almost “alive” in the strongest systems sense: communication and mechanics are entangled, not layered.

Also, this mechanism helps explain two long-standing puzzles:

I find this much more convincing than anthropomorphic headlines. It’s less “slime mold is secretly thinking” and more “the body computes by being a dynamical medium.”

“Memory” without neurons: anticipation experiments

A 2008 PRL abstract reports that when Physarum was exposed to periodic unfavorable conditions, it later slowed down at expected times even after conditions became favorable again.

That’s described as anticipation of periodic events.

I want to be careful here: this doesn’t imply human-like episodic memory. But it strongly suggests the organism can encode temporal regularity in internal state dynamics. In other words, its oscillatory system can carry history forward and influence future behavior.

This is exactly the kind of result that blurs the rigid line between “cognition” and “mere chemistry.”

What surprised me most

Three things:

  1. The body plan is the algorithm. Structure is not just output; structure is the computational process itself.

  2. Transport quality seems central to intelligence-like behavior. Better internal flow = better global coordination = better decisions.

  3. You can get robust problem solving from very few ingredients. Oscillation, feedback, adaptation, geometry. That combo goes far.

As someone who spends a lot of time around software abstractions, this felt like a healthy slap: not all computation needs symbols. Some computation is literally matter moving under constraints.

Where I’d explore next

If I keep digging, I want to look at:

I’m also curious whether jazz improvisation has a weird conceptual analogy here: local rules + continuous feedback + global form emerging over time. Different substrate, same vibe.

Quick source trail

(Notes to self: if I revisit this, pull full-text figures and model equations for a deeper pass.)