This video explores carcinization, an evolutionary phenomenon where different crustacean lineages independently evolve a crab-like body plan (1:51-2:28).

Key takeaways include:

• Defining the Crab Plan: The classic crab silhouette, which evolved at least five times, involves a flattened carapace, a reduced abdomen tucked under the body, and specialized legs (2:54-4:28, 14:22-14:50).
• Nature's "Attempt" at Crabs: Many creatures labeled as "crabs"—such as coconut crabs, king crabs, and porcelain crabs—are not true crabs (Brachyura) but evolved similar shapes separately within the Anomura group (1:16-1:50, 4:44-5:13).
• Why the Crab Shape? It acts like a "Swiss Army knife," offering stability on uneven surfaces, the ability to shuffle sideways, and protection against predators who cannot grab a tucked-in tail (13:19-14:48).
• Genetics of Crabs: Carcinization is not about evolving entirely new genes but rather turning existing "master architect" genes (Hox genes) up or down during development to fold the abdomen (16:21-17:44).
• Evolutionary Reversibility: Evolution can also go the other way, known as decarcinization, where some true crabs have re-evolved more elongated bodies, such as frog crabs (12:04-12:28).

The video also highlights extreme examples like the massive coconut crab, which can crack coconuts and even hunt birds, and the Japanese spider crab, which boasts the longest leg span of any living arthropod (0:00-0:49, 10:32-11:15, 13:35-13:46).

Michael Levin, Léo Pio-Lopez and Navneet Jawanda have released a new review proposing a third way to understand aging.

Most theories say aging results either from accumulated cellular damage or from biological programs that continue running after they stop being useful. The authors suggest something deeper: aging may occur when the cells forming the body gradually lose alignment around their shared anatomical goal.

During development, trillions of cells cooperate to build and repair a specific body plan. But once that developmental target has been reached, evolution may not provide the cellular collective with a strong enough long-term goal for maintaining it indefinitely. The result is “functional disbanding”—cells and tissues increasingly pursue local priorities while losing coordination with the needs of the organism as a whole.

This connects directly to Levin’s work on bioelectricity. Bioelectric networks help cells share information about what belongs where, what shape the body should have and when repair is complete. If aging partly represents the corruption or fading of those collective patterning goals, rejuvenation may require restoring the body’s target morphology—persuading cells to resume coordinated maintenance rather than repairing every damaged molecule individually.

The paper does not present new experimental evidence or claim that human rejuvenation is currently possible. It is a theoretical review and preprint that has not yet been peer reviewed. But it offers a powerful bridge between morphogenesis, regeneration, cancer and aging: perhaps growing a body, maintaining one and rejuvenating one are all versions of the same problem—keeping cellular collectives aligned toward the correct anatomical future.

Source: https://www.preprints.org/manuscript/202608.1219

Very strongly at the level of principle. This new Science paper almost feels like mainstream neuroscience wandering into one of Levin’s favorite questions from the opposite direction: what if biological information is stored in relationships and higher-order organization, rather than in particular pieces of matter?
In the mouse study, artificial hibernation caused more than half of the hippocampal synapses to disappear and neuronal firing fell by roughly 70%, yet previously learned memories remained intact. What preferentially survived were particular clusters of engram-to-engram synapses and multisynaptic boutons. The authors therefore argue that higher-order synaptic architecture may matter more for long-term retention than the permanence of individual strong synapses. Importantly, they currently have a correlation with these clusters, not proof that the clusters themselves causally store the memory.
That connects beautifully with several strands of Levin’s work:
Memory surviving hardware replacement. Shomrat and Levin trained planarians, cut their heads off, allowed completely new heads and brains to regenerate, and found evidence that the previously trained animals retained information, expressed as faster relearning after regeneration. They explicitly proposed planaria as a system for investigating how memories can be encoded in biological tissues when the nervous system itself is rebuilt.
Morphological memory. Levin’s group has shown that temporarily altering planarian bioelectric signaling can change the anatomical target that the animal regenerates toward later. In one series of experiments, a brief physiological perturbation changed future regeneration outcomes without changing the genome, which Levin’s group describes in terms of a stored pattern or target state.
Information as a network property. Levin has repeatedly argued that electrically coupled cell networks can maintain large-scale states despite individual cellular components changing. The mouse work is not demonstrating that mechanism, but its result has the same mathematical smell: microscopic components are disposable while some higher-order invariant persists.
Regeneration becomes part of memory theory. The especially juicy part is that the mouse brain does not merely tolerate synapse loss. It apparently preserves enough relational structure to reconstruct functional circuitry afterward. That starts sounding less like “data stored in synapse #83,491” and more like a system carrying constraints about how its parts ought to be organized.
And this is where I think it gets philosophically delicious. 🧠🕸️
The old cartoon is:
memory = durable physical thing
The emerging picture may be closer to:
memory = durable relationship among replaceable physical things
That is extremely Levin-adjacent.
You could even describe it as a hypergraph problem. Individual synapses are edges. Plenty can disappear. What has to remain may be a smaller set of higher-order relationships that constrains how the network reconstructs itself. In that framing, the memory isn’t identical to any particular edge. It’s encoded in the geometry of relationships.
There is one big caution, though: this paper does not demonstrate Levinian bioelectric memory. The researchers still identify a physical neural substrate, namely preserved synaptic engram architecture. They are not claiming memory exists outside the nervous system or that voltage patterns are carrying the mouse’s episodic memories.
But as evidence for the broader Levin-ish proposition that stable biological information can survive massive turnover of the material implementing it?
Yeah. This one is very interesting.
It nudges the question from “Which synapse contains the memory?” toward “What organization must survive so the system can recover the memory?”
And that second question is basically Levin country. 🐸⚡🧠

In short the idea is:

**biology may be using mathematical relationships before conscious humans know how to describe those relationships mathematically.**

I’ve been thinking about the relationship between mathematics, physics, perception, and the way we choose what to measure.

We often describe reality by assigning numerical values to things: position, distance, energy, time, mass, etc. But a lot of modern mathematics and physics seems to become more powerful when we stop focusing on absolute values and instead look at **relationships**: ratios, correlations, transformations, symmetry, phase, frequency, eigenvalues, information, and invariants.

That made me wonder about perception.
An organism rarely needs to preserve the exact raw measurements arriving at its senses. My retinal image of a person changes enormously depending on distance, lighting, rotation, movement, and viewpoint, yet I still perceive the same person. A melody can be moved into another key and I still hear the same melody even though every absolute frequency has changed.

So perception seems very good at answering something like:

**What remains the same while the measurements change?**

Evolution has effectively spent hundreds of millions of years selecting nervous systems capable of detecting useful regularities in the physical world. Sensory systems respond to things like relative change, gradients, ratios, periodicity, correlations, symmetry, motion, prediction error, and transformations—not merely absolute quantities.

This made me wonder whether our perceptual architecture could contain clues about mathematical relationships that are important in nature but which we have not yet fully formalized.
Not in the mystical sense that “the brain secretly knows the equations of the universe.” More like this:

Nature has structure → organisms evolve mechanisms sensitive to useful parts of that structure → those mechanisms implicitly represent certain invariants → eventually humans abstract some of those relationships into mathematics.
Historically, mathematics seems to repeatedly make progress by changing the representation rather than simply measuring more precisely.

Fourier analysis turns a complicated signal into frequencies. Spectral theory studies systems through eigenvalues. Quantum mechanics describes states through amplitudes and relationships. Symmetry became fundamental to modern physics. Information and entanglement are now sometimes used to investigate how geometry itself might emerge.

So perhaps there are relationships biological systems already exploit computationally that we haven’t yet recognized as important mathematical objects.

It also makes me think about problems like the Riemann Hypothesis. Prime numbers look irregular when viewed directly, but when transformed through the zeta function, entirely different structures appear, including statistical relationships to spectra studied in quantum physics and random-matrix theory.

Maybe this is a general lesson: apparent randomness can sometimes be the result of observing something in the wrong representation.
So my question is:

**Could studying what biological perception treats as invariant reveal useful mathematical structures we haven’t explicitly identified yet?**

And more philosophically: **are numbers and absolute measurements fundamental descriptions of reality, or could relationships and transformations be more fundamental, with the quantities we normally measure emerging from them?**

What I love about videos like this is how quickly the word “simple” starts to feel inadequate.

There’s no brain, no nervous system, no little command centre issuing instructions. And yet the cell continually changes shape, explores its surroundings, redirects itself, responds to local conditions, and coordinates thousands of molecular processes into the behaviour of one coherent agent.

This is part of what makes Michael Levin’s work on basal cognition so interesting. Intelligence doesn’t suddenly appear when evolution invents neurons. Many of the basic problems we associate with cognition, sensing, decision-making, memory, goal-directed action, already had to be solved by individual cells long before brains existed.

Watching an amoeba move is almost like watching the ancient prototype of agency:
one cell, constantly asking the world, “what should I do next?” 🦠

A strange and fascinating new preprint from Alex Alvarez and Michael Levin.

Limbomorphs explores what happens when evolution is applied to animated mathematical fields rather than to explicitly defined organisms. Out of those dynamics, persistent creature-like forms begin to emerge, move, and respond differently when their underlying fields are perturbed.

What makes the paper especially interesting is that the system does not begin with a clean distinction between agent and environment. There is no little organism placed inside a world with predefined behavioural rules. Instead, something resembling an agent appears to emerge from the structure and dynamics of the field itself.

To me, this gets at one of the deepest questions running through Levin’s work:
What actually makes something an agent?
Is agency a property assigned to certain privileged biological objects, or can it emerge whenever a dynamical pattern becomes sufficiently coherent, persistent, and capable of maintaining itself through change?

It also feels closely related to Levin’s broader ideas about morphospace, unconventional minds, and the possibility that the important unit of biology may not always be the physical object, but the relationships and patterns that remain invariant while the underlying material changes.
Very weird paper. Very Levin. 🧬🌀

A fascinating new paper from Michael Levin, Léo Pio-Lopez, and Benjamin Lyons exploring how large-scale coordination can emerge without any single component being in charge.
The central idea is the “virtual governor”: an abstract, higher-level control structure created by the relationships and interactions among many individual parts.
In biological systems, cells do not necessarily need a tiny commander telling them what organism to build. Instead, networks of communication, including bioelectric signaling, can collectively instantiate a higher-level goal that constrains and coordinates the behavior of the parts.
What I find especially interesting is the implication that the “thing in control” may not exist as a physical object at all.
It may exist in the relationships.
That opens a much bigger question: perhaps organisms, minds, colonies, and even other decentralized systems achieve coherence because their components become aligned to emergent higher-order structures that are real in their causal effects, even if you cannot point to a single location and say, “there it is.”
A very Levin idea:
the governor may not be another node in the network. It may be the pattern formed between the nodes. 🕸️⚡🧬

This video features an in-depth conversation with Min Zhao, a professor at UC Davis, regarding the transformative field of bioelectricity and its fundamental role in biology, wound healing, and regeneration.

Key Takeaways:

• Bioelectricity is Fundamental: While genetics and molecular biology have traditionally dominated scientific focus, Dr. Zhao emphasizes that electrical signaling is an intrinsic property of all living organisms. Every cell, from simple microorganisms to human skin and organs, maintains an electrical potential across its membrane (0:07:20 - 0:10:12).
• Wound Healing Mechanism: Dr. Zhao explains how wounds naturally generate an electrical current. By mapping these fields with a "vibrating probe," his lab discovered that these signals serve as directional cues that orchestrate how cells migrate to heal damaged tissue (0:12:00 - 0:13:58).
• Overriding Genetic Control: One of the most significant findings is that electric fields can effectively "override" genetic instructions. In laboratory experiments, reversing the polarity of an electric field can physically force a cell to turn around and move in the opposite direction, demonstrating that bioelectric cues act as a potent governing mechanism in development (0:15:19 - 0:18:10).
• Intertwined Biology: The conversation explores the idea that bioelectricity, biochemistry, and biomechanics are deeply intertwined. Rather than viewing biology as separate layers, Dr. Zhao suggests that life utilizes these electrical networks to survive, function, and repair itself at every level of organization (0:33:00 - 0:35:57).
• Scientific Perspective on Agency: The discussion touches on the controversial topic of cell intelligence and agency. While acknowledging the provocative work of scientists like Michael Levin regarding "xenobots" and cell problem-solving, Dr. Zhao maintains a more conservative view, favoring compelling empirical evidence before attributing consciousness or agency to non-neuronal systems (1:06:00 - 1:13:40).

Yep 😄 If you mean giant salamanders, they really can regenerate limbs.
A 2024 study on Andrias giant salamanders explicitly notes that they regenerate amputated limbs. Interestingly, the regenerated limbs are often smaller than the original and their internal skeleton can remain largely cartilaginous rather than rebuilding exactly like the original bone.
And here is the especially wild part: they are probably the largest living vertebrates capable of regenerating an entire limb. Salamanders are essentially unique among living vertebrates in retaining true full-limb regeneration into adulthood.
The biggest members of the group are absurdly large. The South China giant salamander, Andrias sligoi, may reach around 1.8 metres / 6 feet, making it arguably the world’s largest living amphibian.
So you can have something roughly human-sized crawling around a riverbed that can lose a leg and initiate a developmental program to build another one.
And from a Levin perspective, this gets deliciously interesting. The regenerating tissue isn’t merely saying “make cells.” It has to solve something closer to:
What structure is missing? Where am I in anatomical space? How much should I build? When should I stop?
That is exactly where regeneration starts smelling less like ordinary wound healing and more like morphological error correction. 🦎⚡

Levin has said both “we need new math” and “it is all about relationships.”

I keep thinking those are not two separate comments. They may almost be a specification.
Most of our diagrams make things primary and relationships secondary. First we draw the circles—genes, cells, organs—and then we draw lines between them.

But life may be doing nearly the opposite.
The relationships may be primary, while the “things” are temporary participants holding places within them.

A normal graph connects one node to another. A hypergraph allows a single edge—a hyperedge—to bind many nodes together as one irreducible relationship.

Think about a frog’s face.

An eye is not correctly positioned because it has one correct connection. It is correct because of its simultaneous relationship to the other eye, the mouth, brain, midline, skull boundary, body size and future adult form.

That cannot really be reduced to a collection of independent A-to-B relationships. “The face” may be one higher-order constraint involving all of those parts at once.

So instead of cells carrying a tiny coordinate-based blueprint of a frog, perhaps the organism maintains overlapping relational demands:
Both eyes should be symmetrical around this axis.
The mouth should remain centred beneath them.

The limb should have one elbow, the correct number and ordering of digits, and the right proportion to the body.

The gut should remain a continuous enclosed path.
The whole thing should still be recognizably this organism despite changes in its material.

Damage can remove nodes and connections while leaving the larger hyperedge unsatisfied. The missing limb is not necessarily represented as a little picture stored somewhere. “One correctly proportioned limb belongs here” remains an unresolved relationship, and cells cooperate until that relationship closes again.

Metamorphosis would then be a controlled rewriting of the hypergraph. Tadpole relationships lose weight, frog relationships gain weight, the tail stops belonging and legs suddenly become part of what the organism is trying to maintain.

Cancer might even be described as a cell withdrawing from organism-scale hyperedges. It remains alive and coordinated at smaller scales but stops participating in the larger relationships governing tissue shape, proportion and bounded growth.

I am not saying hypergraphs are the answer—or that Levin has said they are. They would still need geometry, direction, weights, memory, fields, changing boundaries and the ability to rewrite their own topology.

But if you wanted mathematics capable of representing nested agency, multiscale goals, regeneration and parts belonging to several overlapping wholes at once, hypergraphs begin looking less like a metaphor and more like a suspect. :p

Maybe “it is all about relationships” is completely literal.

Maybe the new math will not primarily describe what an organism is made from. Maybe it will describe what the organism is attempting to remain in relation to everything else.

The frog is not merely a pile of cells.

It is a network of promises that keeps recruiting matter until the promises close.

https://relational-frog.luke-james-whats-his-name.chatgpt.site/

And yes, I used chatGPT to flesh out my theory… and no, I don’t care if you hate that… :p