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Michael Levin is coming close to the positions of both Humberto Maturana (autopoiesis) and of Nick Lane (proton pumping).
Autopoiesis is not an easy set of concepts but one of the ideas is that details of structure are much less important that preservation of relationships that allow an entity to replenish its own constituents. Planarian are damn adaptable, but this is hardly news.
Nick Lane emphasizes that DNA is subsidiary to bioenergetics and “proton pumping” across membranes. His recent book “Transformer” focuses on the Kreb’s cycle and mitochondria as the crux of life (and autopoiesis, although he does not use this term).
Lane is extremely readable. Maturana is almost inscrutable.
I enjoined the target article, but am not comfortable boiling down development to “bioelectrics”. A complementary perspective but I do not think this will get us farther than good old developmental molecular biology.
Lane has spoiled essay for me. I've read all his books and he's in the right place on the readability-complexity spectrum for my case.
I can't find any other author, on any other field, I can learn so much from without being actual work.
I disagree. An electromagnetic paradigm of cell life is critical to understanding predictive molecular dynamics, particularly where cellular neural recruitment is concerned. Moving passed mass and unto the mathematical perfection of electromagnetic radiation - as idealized as realized in the electrical engineering sciences - demonstrates its exaltedness in theoretical application.
I have created a simulation of how a tree can be grown from a programmable cellular automata. Each cell executes some operations, including replication, based on the surrounding conditions and its age/iteration.
More complex organisms can be grown with this technique.
You can play too with it here: https://acionescu.github.io/digitalfire/WebContent/
Very very cool, bookmarked!
Hidden in footnote 5 is a significant fact about the two-headed planaria (flatworms) that produce two-headed offspring: they reproduce not by laying eggs, but by fission. In other words, this physiological trait is not passed through the genes (if it were, that would be a rather astounding Lamarckian fact).
Planaria in general reproduce sexually (with eggs and sperm) and asexually (by splitting).
Isn't that Lamarckian either way?
The language in the article is a bit overhyped. There are multiple examples of gradients being involved in pattern formation. It's just that electrical potentials are a bit of a newer area of study.
There's the chemical gradient based on WNT signaling in fruitfly development, the SHH (sonic hedgehog) chemical gradient in limb pattern formation and body planning asymmetry. There's even auxin signaling in plant development.
Heck, one of Alan Turing's (yes, THAT Turing) most famous papers from the 50s described reaction-diffusion mechanisms for pattern formation.
Basically for evolution to invent some kind of reproducible pattern of something, you need to start with a gradient of something and tie that to gene transcription.
In the fruit fly example it's a chemical trigger that reaches the nucleus via wnt signaling. In the flatworm example, it's a membrane polarization gradient that drives the gradient rather than a chemical one.
I'd imagine the patterns you can create from electrical depolarization are simpler than the ones you can get from chemicals interacting as you lose many of the interesting interactions you get from reaction-diffusion
Yes, I believe that the linked article oversimplifies when talking about a "bioelectric" state, perhaps because this sounds more appealing to those familiar with electrical and electronic technologies.
The actual state that is described is determined by the chemical concentrations of various kinds of ions and molecules along and across the body of an animal.
The distribution of electric potential that appears as a consequence of the chemical concentration variations, due to the fact that the atomic ions and also many of the molecules involved are electrically charged, is just a coupling mechanism between those chemical concentrations, so that when one of them is changed that tends to also change the concentrations of other atomic or molecular ions.
The same "bioelectric" state (i.e. electric potential distribution) could appear as a consequence of distinct distributions of the ions and most certainly those seemingly identical "bioelectric" states would behave quite differently.
This is similar with what happens in semiconductors, whose behavior cannot be simulated based on just the distribution of electric charge, but one must account separately the concentrations of all kinds of charge carriers, e.g. electrons, holes, fixed crystal defects etc.
Ditto. The larger question is how does the linear sequence of DNA (primary sequence) ultimately drive the spatio-temporal development program that leads to mature differentiated cells working together at the organoid / organ / organism scale. How do cells know what to do in time and space as the organism grows? How is that logic encoded in the genome?
Eric Davidson did a bunch of pioneering work meticulously "debugging" this spatiotemporal genomic logic in the sea urchin. Pretty amazing. Eukaryotes like us have control elements directly upstream of our genes (trans-acting aka close acting) and also 100,000's of base pairs distant (cis-acting). The region of DNA directly preceding the beginning of an open reading frame at the start of a gene usually has a sequence of DNA motifs that bind proteins that can increase or decrease expression of the gene. Davidson and others showed that the transcription factor proteins that bind to these control motifs actually have additional other proteins that bind to them, in literally a layer on top, and that the sequences of proteins in this second layer recruit a tertiary layer of proteins that conditionally cause more or less gene expression, depending on their identities. You could say the secondary and tertiary layers are a form of "abstraction" in a literal sense, since they encode a hierarchy of logical operations.
Here's an open-access overview of Davidson's work which incidentally illuminates a lot of these concepts in more detail for a lay audience: "ERIC DAVIDSON: STEPS TO A GENE REGULATORY NETWORK FOR DEVELOPMENT" by Ellen Rothenberg, 2016; doi: 10.1016/j.ydbio.2016.01.020 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4828313/
to see the decoded logic in pseudocode and with a diagram, see "cis-Regulatory control circuits in development", Howard and Davidson, 2004, Developmental Biology, vol 271, https://doi.org/10.1016/j.ydbio.2004.03.031 (open access)
Your response has fascinated me. Listening to podcasts, I have always so dearly wanted to know what Michael or others meant specifically by "Voltage gradient". These have given me great topics to further conduct research into, with my currently fundamental neuroscience knowledge rooted in understanding of memory, learning and Action Potentials.
I have tried to further this understanding with LLMs but am ofcourse not sure if what they are saying is correct (given the understudied and sparse nature of this research).
If you had a moment to help me understand what exactly these voltage gradients are, how they differ from action potentials, and to tie these to the processes at the cellular level to the larger system, I would be so grateful (for example, is SSH used in limb regeneratio nas well as pattern formation? How? Is it dormant in normal limbs? Which cells, in the limb or in the brain? Which research articles found this? I am fascinated!).
In the meantime, here is what Claude told me. I am not sure if it is accurate, I get a sense of "sweeping under the rug":
"Specific ion channels and gradients:
During limb regeneration in amphibians like salamanders, one of the key ion channels involved is the V-gated proton channel (Hv1). The wound epidermis cells at the amputation site become depolarized due to the influx of protons (H+) through the Hv1 channels, creating a localized region of elevated intracellular pH. This pH gradient, or proton gradient, is believed to be a crucial signal that initiates and guides the regenerative process. Other ion gradients, such as calcium (Ca2+) and sodium (Na+), have also been implicated in regulating various stages of limb regeneration, but the proton gradient is particularly well-studied.
Reaching and influencing cells:
The voltage gradients or ion gradients can propagate through tissues and reach distant cells due to a phenomenon called bioelectric signal propagation. Cells are electrically coupled through gap junctions, which allow for the passive spread of ions and small molecules between cells. This electrical coupling enables the voltage or ion gradients to be transmitted from the source cells (e.g., wound epidermis) to the target cells (e.g., blastema) over long distances. The gradients can influence gene expression, cell proliferation, and cell migration in the target cells, guiding the regenerative process.
Pattern effects and limb regeneration processes:
The specific patterns of voltage or ion gradients are crucial for determining the outcomes of regeneration, such as the completeness and proper patterning of the regenerated limb. For example, manipulating the proton gradient can lead to the formation of supernumerary (extra) limbs or alteration of the limb pattern. The voltage gradients are involved in various stages of limb regeneration, including wound healing, blastema formation, patterning, and differentiation of cells into specific tissue types (e.g., bone, muscle, nerves).
Gradient vs. specific voltage measurement:
The term "voltage gradient" or "bioelectric field" refers to a spatial pattern of voltage differences, rather than a singular voltage measurement at a specific point. It's similar to a topographic map, where the voltage (or ion concentration) varies across different regions, creating a gradient or slope. In contrast, an action potential or membrane potential refers to a specific voltage difference across the cell membrane at a given point in time. The voltage gradient is a long-range signal that provides positional information and guides cellular behaviors during regeneration, while action potentials are localized electrical signals involved in neuronal communication and muscle contraction.
The voltage gradient, or bioelectric field, is a spatially distributed pattern of voltage differences that serves as a long-range instructive signal for coordinating cellular activities during regeneration. It is distinct from a singular voltage measurement or an action potential, as it represents a gradient or slope of voltage across different regions, providing positional cues and guiding the regenerative process."
Related. Others?
Computational Boundary of a Self: Bioelectricity and Scale-Free Cognition (2019) - https://news.ycombinator.com/item?id=39244333 - Feb 2024 (1 comment)
Brains are not required to think or solve problems – simple cells can do it - https://news.ycombinator.com/item?id=39127028 - Jan 2024 (396 comments)
Bioelectricity, Biobots, and the Future of Biology [video] - https://news.ycombinator.com/item?id=38423588 - Nov 2023 (1 comment)
How bioelectricity could regrow limbs and organs - https://news.ycombinator.com/item?id=38027587 - Oct 2023 (100 comments)
M. Levin – Bioelectrical signals reveal, induce, and normalize cancer [video] - https://news.ycombinator.com/item?id=37140965 - Aug 2023 (1 comment)
https://news.ycombinator.com/item?id=36912245 (July 2023)
Aging as a morphostasis defect: a developmental bioelectricity perspective - https://news.ycombinator.com/item?id=36264719 - June 2023 (1 comment)
Bioelectric networks: cognitive evolutionary scaling from physiology to mind - https://news.ycombinator.com/item?id=36009513 - May 2023 (1 comment)
Bioelectric networks: from body intelligence to regenerative medicine - https://news.ycombinator.com/item?id=35763121 - April 2023 (1 comment)
Non-neural, developmental bioelectricity as a precursor for cognition - https://news.ycombinator.com/item?id=33902641 - Dec 2022 (1 comment)
Michael Levin: Intelligence Beyond the Brain (networked daptive morphogenesis~) - https://news.ycombinator.com/item?id=33217070 - Oct 2022 (1 comment)
Plasticity without genetic change – Michael Levin [video] - https://news.ycombinator.com/item?id=32119375 - July 2022 (1 comment)
Mike Levin on using bioelectricity to study how cells form (2019) - https://news.ycombinator.com/item?id=27819791 - July 2021 (21 comments)
Persuading the Body to Regenerate Its Limbs - https://news.ycombinator.com/item?id=27062477 - May 2021 (69 comments)
The Link Between Bioelectricity and Consciousness - https://news.ycombinator.com/item?id=26435281 - March 2021 (1 comment)
Growing Neural Cellular Automata: A Differentiable Model of Morphogenesis - https://news.ycombinator.com/item?id=22300376 - Feb 2020 (46 comments)
What Bodies Think About: Bioelectric Computation Outside the Nervous System - https://news.ycombinator.com/item?id=18736698 - Dec 2018 (16 comments)
Brainless Embryos Suggest Bioelectricity Guides Growth - https://news.ycombinator.com/item?id=16589702 - March 2018 (35 comments)
Memory in the Flesh: Can memories survive outside the brain? - https://news.ycombinator.com/item?id=9226391 - March 2015 (12 comments)
Holy ... he's been features on HN since that long ago ?? I only heard of him from a random partial misclick on a funny youtube thumbnail less than two years ago.
thanks for the background
Growing Neural Cellular Automata https://news.ycombinator.com/item?id=22300376, February 2020
It's incredible that the information necessary to create a human is just about 750 MB uncompressed. For example the very specific shape of the scapula bone or fear of spiders...
It's really not. If nothing else, conditions in the uterus, especially in the first few months, are extremely crucial. Take 10 identical fertilized eggs and put them in 10 different people and you'll get 10 different humans, not 10 clones as people generally assume. And this is not just genetics of the mother, differences in diet and lifestyle will also significantly (not to mention history) impact the development of the fetus, especially in the early months.
In compression contests you count the size of both the compressed data (DNA) and the decompressor binary (egg cell).
We don't know how much data is required to fully describe a living cell, but it's not just the DNA since you can't turn that into a cell without using an existing cell
To be fair that’s just the size of the installer
DNA is just a "program", and a living cell is basically an advanced programmable nanorobot. When cells divide or reproduce, the whole nanorobot is cloned with some modifications. The DNA tells how to modify the cloned nanorobot, and it is also possible to reprogram any cell back to the original state. Nobody knows how to make a cell i.e the nanorobot from stratch. The information is not in the DNA, like a computer program doesn't contain the instructions to build a computer.
Well until they succeed in creating artificial wombs it's technically a much larger amount of information (e.g. the cellular composition of the womb, how many and what kinds of nutrients that flow through, etc). We are still scratching the surface of epigenetics too.
> It's incredible that the information necessary to create a human is just about 750 MB uncompressed
Hold up, isn't the point of this article that genes do not have all the information?
The, er, bootup environment of a freshly-fertilized human egg normally provides a lot more than merely protection and raw materials for nine months. Likely a lot of required parameters, and definitely a lot of important tuning optimizations.
> For example the very specific shape of the scapula bone or fear of spiders...
There were some studies a decade back about mice inheriting fears of certain smells from the father, I wonder if anyone discovered the mechanism (or disproved the effect) by now.
> It's incredible that the information necessary to create a human is just about 750 MB
Have you not been playing with LLM's in the last year or so ?
They seem to compress a sizable chunk of human knowledge in about 7 Gig
And, when they find a gap, they lie through their teeth to provide a reasonable answer.
I wonder if there's some sort of similar process (hallucination) going on when the final human is rebuilt from the 750MB.
I guess that's without considering epigenetics which have some heritable marks. We are very far from knowing how much epigenetics contribute to the making of an organism and as a whole it is controversial. But one of the great lessons of the human genome project is that DNA coding does not account for all of the biologic information and that epigenetics may have a bigger part to play than what was previously thought. If we were somehow able to model every epigenetic marker the uncompressed information would be quite heavier
It's the initial state for a self-replicating hardware procedural generator.
> create a human *body*
As an aside
> His work has been featured everywhere from Scientific American to the Lex Fridman podcast and The New Yorker.
This is a weird way to posit someone's scientific achievements. Had they said eg Lancet, Nature and Science -- ok, clearly someone publishing in those venues is a scientific heavyweight. But being featured in pop-science, a famous podcast and a general audience magazine only tells me how well someone can explain/sell their research, but doesn't actually say anything about the strength of that research.
Maybe because the target is the general audience.
> They’ve done things like getting frogs to develop extra limbs, and getting them to develop an eye in their gut, or an eye in their tail that they can actually see out of.
I have two contradictory reactions to this. 1. "Isn't science amazing!" 2. "Poor froggy, how horrible."
Eye tails sound pretty awesome if you’re a frog tho.
Really bad title. Here is a better one:
Bioelectric Signals Guide Body Development and Regeneration
He used human tracheal cells, not lung cells.
"Because they are one of the few tissues in the body that have motile cilia."[0]
So they can move around.
[0] https://twitter.com/drmichaellevin/status/173042805284737055...
This “Fractal Intelligence” stuff feels super Wolfram-like. Just as Wolfram argues that simple rules in cellular automata can create complex, intelligent patterns, Levin’s bioelectric networks show how cells and organs have their own built-in smarts and adaptability. Both are about how simple, foundational principles lead to sophisticated behaviour, challenging the old deterministic ways of thinking. It’s basically a fresh take on how complexity and intelligence arise, and could really shake up how we understand biology and systems in general.
That doesn't inspire confidence in Levin's research, if it were true. Wolfram's quixotic quest for a theory of everything is something basically only he believes in, with very little shot at doing anything worthwhile, at least for physics. I hope that Levin's notions are more likely to bear some fruit.
> studying cancer as a “dissociative identity disorder” of cell groups,
> finding that ant colonies succumb to “visual illusions”
> had created biobots from frog skin cells
> and then created human biobots from lung tissue that can heal damaged neurons.
Oh man, the entire article is a train wreck. Theranos level. I don't even know how to start.
I wouldn't advise to put your money on this. Not without a lot of safety measures.
With such apparent speed and quality of research thought we will never have anatomical compiler, let alone electroceutocals and anthrobots, on a routine basis at least in the next couple of hundreds of years.
It's surprising that the main thrust of this is surprising. Do biologists not tend to think about electromagnetic force and it's implications?
They do but that doesn't lend to a hype topic for writing poorly about
When in 18xx FDA or its precursor was being formed, its goal was to confine various "bioelectrical woo" present in medicine and biology at that time. And back then there was Rife's microscope, for example, which was able to accurately image living cells.
Yet no-one tried to account for the cumulative damage/adverse effects done by FDA approved treatments in comparison with a potential or actual damage done by such "woo".
>the impact of Levin’s work is a shift away from genes as the only determinant of structure
Nobody was making the claim that genes are the only determinant of structure though. A trivial example is the mother's hormones affecting her child's development in utero. To cause a shift away from genes would require showing that the bioelectric network is not itself caused by genetic factors. Otherwise while it may be useful as a tool to develop treatments for developmental diseases it does not change that genes are the ultimate cause of the bioelectric network itself (except as when directly manipulated by scientists).
Quoting Levin himself:
>Evolution was using bioelectric signaling long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies.[0]
It sounds like to me from this quote that bioelectric networks are not something outside of genetics but just another important biological system.
It's hard to pin down what the author is really getting at in the first place. For example these two lines:
>genes are great, and they do contain much of the necessary information for building our bodies. But they don’t contain all of it >[...] >Levin’s point is that genes are like machine code, and modern-day programmers never think about machine code—they think about higher-level software constructs like objects, modules, and applications.
Yet machine code really is what is being executed by the computer. Nobody would say that the computer is really running c++, for example, or that c++ is a new "determinant of structure" of the program. It is completely subsumed by machine code.
The author is the entire time equating a set of instructions (the genome) to a biological system (the "bioelectric network"). However it does not make sense to equate these things in the way the author has done it (at least not without a lot more elaboration). The genes do not really do anything except get copied and transcribed into mRNA while the bioelectric network clearly is doing something. So it really seems more like the author should be comparing proteins with the bioelectric network. But I think here the problem becomes much more obvious – there is no other way besides proteins for biological organisms to do work. So it is obvious that the bioelectric network is somehow formed by the work of proteins, and the proteins are themselves caused by genes. The human body has within it many systems: the circulatory system, the respiratory system, the endocrine system, the nervous system, the muscular system etc. These all exist at "higher levels of abstraction" than genes and some of them, like the endocrine system, play a role in development. But it wouldn't make sense to say that these system are "in competition" with the genome. Even though we can use the circulatory system to transport a drug to the body that changes the structure of the body.
Another major difference is that genetics are continually showing their influence because the body is continually creating proteins from the genome. It sounds from the article that this bioelectric network is really only relevant at the developmental stage (if I am wrong here then I feel the article should have made that more explicit).
Ultimately I feel the article is arguing a bit against a strawman of "genes as the only determinant of structure" and is also making too vague of a claim about genes having a new competitor, so to speak.
[0] https://link.springer.com/article/10.1007/s10071-023-01780-3
levins work is great, except that afaik it hasnt been reproduced outside of his lab
Way out of my wheelhouse but after reading this it leads me to believe "heal machines" like in elysium and other scifi movies may not be that much scifi after all.... block an ion channel here, send a signal there... poof, your arm is back!
website blocked in my country :(
wearing a tail?
I'm about 55 now, and if I was high school or college age again, this is what I'd study. There is huge potential in future biological developments.
As a biologist, how do you account for the existence of life?
The most interesting for me is the offspring, reproducing a different structure with the same genes. I think mathematically this could be the missing link in evolution, where random gene modifications are just not probable enough to drive evolution. 3 billion DNA pairs cannot evolve randomly, there is not enough time and matter in the universe to randomly try successful generations of life forms. However, bioelectric might be a much much more straightforward and fast way of driving evolution instead of randomly mutating DNA.
The first observation is that DNA, on its own, is useless. It has no causal power. It doesn't generate or explain life or cells. You need an existing cell, an existing organism, to make use of the DNA, as it were. Of course, without DNA, the cell cannot proceed. So this mutual dependence tells you that they're a package deal, and neither can be reduced to the other.
The second is that you really cannot get away from telos. The ostensible banishment of telos is not a scientific conclusion, but a metaphysical choice, and one that is incoherent. Telos isn't will or desire or planning or intent per se, though these are examples. Telos is what explains why an effect follows from a cause, and does so with regularity. That striking a match (efficient cause) results in fire (effect) is a question of telos, of the match being ordered toward the effect of fire, effected and actualized by striking. The match obviously is not planning to produce fire, it doesn't will it or want it. But it is causally ordered toward that end or effect. Otherwise, you could not explain why striking it actualizes this potential for fire. You could not make sense of any phenomena, why striking a match results in fire instead of, say, nothing or the appearance of an elephant or whatever.
Biology is no different, but here we can speak of higher order telos. And as biology progresses, the more difficult it is to maintain the crude mechanistic view of life reaching back to the 17th century, that is, one modeled on the machine metaphor. Living things, strictly speaking, are not machines. They're integral wholes, not accidental arrangements.