Where is Anatomy Encoded in Living Systems? | Michael Levin

Extract from "Cell Intelligence in Physiological & Morphological Spaces", kindly contributed by Michael Levin in SEMF's 2022 Spacious Spatiality.
Full talk: • Michael Levin | Cell I...
MICHAEL LEVIN
Department of Biology, Tufts University: as.tufts.edu/biology
Tufts University profile: ase.tufts.edu/biology/labs/le...
Wyss Institute profile: wyss.harvard.edu/team/associa...
Wikipedia: en.wikipedia.org/wiki/Michael...)
Google Scholar: scholar.google.com/citations?...
Twitter: / drmichaellevin
LinkedIn: / michael-levin-b0983a6
SEMF NETWORKS
Website: semf.org.es
Twitter: / semf_nexus
LinkedIn: / semf-nexus
Instagram: / semf.nexus
Facebook: / semf.nexus

[@FlatEarthMath]

This is such a fascinating subject. I've often pondered this little thought experiment. _"Describe _*_exactly_*_ the shape and size of a human femur. Your instructions can be as long as you like, but you may only use four letters. Go!"_

[@SEMF]

Great thought experiment!

[@Pinstripe6666]

This man has a nobel prize in his bags. It's only a matter of time.

[@SEMF]

Very likely the case!

[@anistissaoui]

I love to picture our cell structure as an orchestra or a choir, pretty much everyone in the orchestra knows what to sing and how to harmonize, they know their melodic role in the piece, and usually you get a group of players/singers play/sing same lines and some times harmonize basic to complex melodies that evoke different emotions in us listeners. If a player/singer falls out of time or skips some notes, the whole orchestra will lift them up and eventually they will know their place again and play their melody the one needs to be heard. So, the encoded anatomy is more like a song that's being sung by the whole community of the cells in our body, and once the song misses some notes the new born cells will jump in to fill their role and sing their life melody. Imagine an old folklore song that you recall but you don't really remember the whole lyric, if you try to sing it with friends that share the memory with you, as a group you will eventually sing the whole of it correctly.

[@SEMF]

That's a beautiful elaboration!

[@richard_d_bird]

I've thought about this before, and based on my complete ignorance, i've generally come to assume that the information for animal morphology is "encoded" in the process of growth itself. that is, the individual cells of an animal are a bit like tiny little iterating math functions, passing their outputs back to themselves, or rather, to their descendants as they divide and reproduce. it's well known that relatively simple little math functions can be iterated, passing their outputs back into their inputs, to create very complicated patterns, the information for the patterns created isn't obviously encoded in the functions themselves, or in the data they pass back to themselves. the patterns emerge as the process is run, they are "encoded" in the process itself. i'm sure this is a lousy analogy, and a pretty picture created by simple math functions isn't really anything much like, say, a frog, but i think there's something similar going on with biological morphology all the same. and i doubt i'm the first one to think of that.

[@SEMF]

Those are very interesting thoughts. Thanks for the detailed comment!

[@solemnwaltz]

That's pretty much what I assume too

[@osaimola]

Interesting thought indeed. How would this play out with mutation? If a mutation occurs in the early stages of growth, will it be able to derail the correct formation of the organism? Or is mutation only restricted to later stages and specific areas of the organism.

[@WisdomThumbs]

@@osaimola I know from my friends who took puberty blockers that “delaying” puberty turned out to be permanent. So after they quit the blockers, they were compelled to move on to HRT, otherwise they were stuck in teenage bodies with the bone and hormone problems of the elderly. And we can also see that a pituitary gland mutation tends to cause stunted growth or exaggerated growth, though it can be hard in those cases to be certain if the pituitary was the first and only cause.

[@christerdehlin8866]

Yes, perhaps, but what makes the process stop at the right moment?

[@ChemEDan]

Wow, this has to be one of the best videos on KZbin.

[@SEMF]

Levin Lab's work really is amazing!

[@VooDooTube...]

Future nobel prize winner.

[@pyropulseIXXI]

for sure

[@SEMF]

Very likely indeed!

[@philanthropicnightmare1206]

110%

[@janemichael5740]

This talk described the threshold of science and magic

[@SEMF]

It really did!

[@brusso456]

Look up, Rupert Sheldrake - Morphic Resonance and Morphic Fields

[@xiaonanw6374]

@@SEMF "inclusion and diversity " wtf man

[@generichuman_]

@@xiaonanw6374 huh?

[@xiaonanw6374]

@@generichuman_ their description in about the channel..

[@pyropulseIXXI]

Pure genius; this is paradigm shifting stuff!

[@SEMF]

Most likely so!

[@commanderthorkilj.amundsen3426]

ML and similar researchers are, of course, building upon previous work, with immense collaboration and sharing occurring on a global basis, leading to the exponential increases in knowledge and astonishing technological development that we’re seeing. Meanwhile, during the quest to eradicate many diseases of humans, improve human lives, nonhuman life is being destroyed, the biosphere is being degraded, fished-out oceans polluted w/ plastic, resources depleted, and 1,000,000 new humans added q 4-5 days. So the exhaustion of the Earth’s resources by too many human parasites, the scary but inevitable military applications of AI, necessitated by an escalation in war and conflict over dwindling resources, and the unintended consequences of bio technological/genetic engineering will make Dr. Levin’s fine work superfluous, as catastrophes loom on the horizon.

[@SEMF]

@@commanderthorkilj.amundsen3426 This is an important notice!

[@laurisafine7932]

@@commanderthorkilj.amundsen3426 Blimey! Doomer, much?

[@tsbrownie]

Fascinating talk ended before I was ready! As a software engineer I was trying to imagine what kind of program could produce a "self-healing" result from simple inputs that update along the way. Off the top of my head, it looks like a main routine that spawns and passes most functions to subroutines that deal with the finer and finer details (but that stay in touch with other routines above and below). If I were younger....

[@hindenberg25557]

If you want to hear more from him, he had a great interview on Lex Fridman's podcast

[@jonathansmith2323]

this is an extract from the longer kzbin.info/www/bejne/oH3MeX96p7SHjZo

[@canonaler]

Michael is so brilliant, thank you for this !

[@SEMF]

It was a pleasure to host him at SEMF!

[@metacortexvortex2131]

I always wondered how your cells know how to grow and correct errors in 3d space like how do they define a boundary in space so they don't just keep growing. That made me think of cancerous tumors and how they seem to have lost the ability to stay within their spatial domain as they grow out of control.

[@cyberbiosecurity]

they lose growth regulating genes due to dna damage. by 'default' singular cells emerged to just multiply successfully as soon as possible. then regulation of this process evolves to be more adaptive and survive as a colony [see volvex]. these growth-suppression genes get slammed out of the chain and we get faster multiplication. hope your T-killers detect this asap.

[@TristanCleveland]

The book Life Becoming (I think it's called) lays out a bunch of mechanisms. Stuff like: when the density of certain signalling cells get too low, or weird algorithms where the rate by which the cell creates or destroys certain rigid structures equalizes. It's analogous to how hair reaches an equilibrium point based on how quickly it falls out and how quickly it grows. I only vaguely remember, but it's cool.

[@SEMF]

Michael's research is indeed a great advance in this direction!

[@thomashenry4798]

I would suspect that cells constantly monitor their environment. So cells that are on the edge of an embryo, the surface cells, are constantly broadcasting surface signalers. Cells that are next to them broadcast a unique signaler and so on and so forth. By monitoring the average gradient of signaling proteins a cell can get a rough idea of where it is in the embryo as it develops. Then based on their locations cells then attempt to begin to differentiate. My guess is that they start putting out signalers that recruit neighboring cells that recruit neighboring cells until the signal strength reaches a critical threshold at which point an election process begins amongst them to further differentiate, activating some parts of the genome and shutting down others. So say you have an embryonic liver. One cell decides its going to be a liver cell and it tells the surrounding cells to also become liver cells. If those cells are undifferentiated they recruit and turn off their ability to be anything and instead become liver cells, signaling what they are doing all the while. When the signal reaches a strength threshold the cells stop recruiting and start dividing. Cells that are on the boundary layer know this because they dont have liver cells on all sides, only on one side, so signaling proteins would be roughly half of what a cell inside the group might experience. This allows the liver cells to output signaling proteins "Hey I am on the boundary layer!" to other cells. Then once the boundary is established you can link all the boundary cells together with mechanical linkages and monitor those linkages for damage. A loss of a connection could change how the tensile strength of the boundary cells gets interpreted. So if you have mechanical changes, plus damage signals in the water, the cells know to interpret it as damage and so begin the healing process. Whereas if you just have flexing alone, then that triggers nothing. Basically an AND gate if I were to convert it into my field (I work in IT. So feel free to call my meanderings a load of baloney!) I think how the system works is that each cell, having the same genome as every other cell, uses hormones and signals to know which bits to turn on and which bits to turn off. This defines which proteins and signals and chemicals a cell produces vs which ones it doesnt produce, and the presence of these proteins are what chemically and mechanically define how the cells interact with each other. With billions of chemical pathways inside a cell acting almost like very very very tiny logic gates, the cell is able to make decisions based off of its immediate surroundings. Taken in aggregate all these chemical logic circuits combine to produce emergent behavior. The reason that say, Picasso always produces a frog... You have cells that elect to be the front of the organism and cells that elect to be the middle and cells that elect to be the back end. Then you have cells that are eyes and they are basically telling all their neighbors they are eye cells. Except those cells chemically do not respond to eye cell signals. So instead the eye cells look for the signals that indicate front vs back, and begin to migrate to the front. There is probably a mechanism to allow them to migrate around. As the cells migrate they detect 'Face' signals which tells them its going in the right direction. Eventually they find the cells they are supposed to be next to and stop there. They overcorrect because as this is a chemical biological process, they can get too strong a signal and move too enthusiastically, whereupon they encounter boundary cells where they arent supposed to and move away from that boundary layer signal. Because there are TRILLIONS of possible protein combinations, you can theoretically have as many signals as you need to set off as many chemical pathways as you need for these logic circuits that then chemically set off yet more pathways that allow the cell to move around mechanically. Its why you first have a mass of undifferentiated cells in a ball because thats the easiest shape that has a defined inside and outside. At least that is my layperson thinking. No idea how close to the truth I actually got.

[@SEMF]

@@thomashenry4798 Thank you so much for the very detailed comment! I suggest you join our online community to further share your thoughts with SEMF members: semf.org.es/participate/join.html

[@mcferguson81]

Did he really make one of the best science lectures I’ve ever seen … And use Comic Sans font for his slide deck? 😂😂

[@SEMF]

Indeed that was the case! This may give a different status to the font from now on...

[@bradsillasen1972]

Mind blowing! Excellent presentation. Thanks.

[@SEMF]

We thought so too! Thanks for your comment!

[@penguinista]

This is such a powerful way to think about biology. And the examples are excellent. The nephron example at 8:45 clearly shows that there is a system with memory of the setpoint structure and access to multiple mechanisms to effect the changes required to become that shape. It also shows that the system is getting feedback from the growing structure. It must know when it is working with cells large enough that only one cell is required to make a tube with sufficient size lumen. They are such big ideas that people brains literally balk when I try and tell them about it. I hope short videos will make it easier for people to be able to digest the new concepts.

[@SEMF]

Thank you very much for the comment! We are also hoping shorter videos will be useful!

[@Quidisi]

Holy crap that was mind-blowing! Especially the "Picasso-Tadpole" 11:37

[@SEMF]

That was a really incredible example!

[@danielvarga_p]

Thank you guys, keep up the good work!

[@SEMF]

Thank you, it is our pleasure!

[@gabrieldaley5881]

This channel and this video in particular are excellent finds. Thanks!

[@SEMF]

Thank you very much for your kind comment. We feel privileged to be able to bring this cutting-edge research to a large audience.

[@philippdeschain2124]

Glad to have stumbled upon this channel, it is of spectacular quality.

[@SEMF]

Thank you so much for your interest! We are glad you are enjoying our content. Please visit our website for more information on the society behind this channel: semf.org.es/

[@Budgiesmudgie]

Thank you for putting this on KZbin

[@longcastle4863]

Fascinating research. What a great project to be part of.

[@SEMF]

It truly is fascinating!

[@nickjunes]

It's so crazy this is the only man talking about this stuff.

[@SEMF]

He is representative of the work at his lab and by his collaborators, perhaps he is the most visible but not the only one?

[@nickjunes]

@@SEMF Yeah I'm sure that in the community there are more people, but in mainstream I think this is getting nearly zero attention.

[@javiermachin1]

“How could we have a navigation system that can have goals in anatomical space?” Living systems are wonderful. Very nice talk. Thanks.

[@SEMF]

Glad to see you enjoyed our content!

[@xiaonanw6374]

@@SEMF how can one claim science but actually be a proponent of the opposite of science ??? Please tell us

[@SEMF]

@@xiaonanw6374 What do you mean?

[@xiaonanw6374]

@@SEMF I appreciate your reply and your content to be clear continue the content... Your content is a meeting place of different ideas , all with the focus of cross pollination ... allowing the absorbing of and discussion of and thus development of deeper understanding for everyone involved ... truly EPIC and heart warming In your about section you boil that down to the "inclusion of diverse viewpoints" which has come to represent of those groups and people who use such language as actually meaning we value all viewpoints but only the "valid ones" and that validity is not created by nor supported by the diverse discussion but rather limits it. As I feel your truly about multi angled and multi disciplinary discussion then I feel you need to be more clear about that in your language... unless you are trying to capitulate to that "jargon" which unfortunately signals fundamental corruption of your stated goals (ideals) In any case. Take it as you will

[@SEMF]

@@xiaonanw6374 Thanks for the kind words!

[@bobaldo2339]

This "goal directed behavior" is so surprising to us because it seems to fly in the face of the unconsciously assumed reductionism that permeates our culture. The whole, in many cases, may not only be "greater than the sum of its parts", but also more fundamental.

[@SEMF]

This is a very interesting observation and one that will be addressed in future SEMF events and discussions.

[@semaifirtes]

This is a much needed video. I want to hear much more about this question. I'd like to understand as a lay person, and not a genetics and development scientist

[@SEMF]

Look forward to future SEMF events, we will be having many opportunities to learn from the basics. semf.org.es/participate/join.html

[@MikeKleinsteuber]

This is a really interesting question extremely well presented

[@SEMF]

We thought so too. Michael is a very clear speaker!

[@LuigiSimoncini]

thank you algo for bringing me this amazing stuff!

[@SEMF]

We are very happy the algorithm is bringing this to the fore!

[@markharris1223]

Splendid. Thank you..

[@SEMF]

Thanks for your comment!

[@lotfibouhedjeur]

This was fascinating.

[@SEMF]

Indeed it was! It was a privilege to host Michael at our conference.

[@dumyjobby]

this is wonderful.

[@SEMF]

We are glad you enjoy our content!

[@user-pq3uz2zb9i]

Amazing!

[@realGBx64]

Wow, based on the channel logo I was not expecting a proper science lecture. Well done!

[@SEMF]

Thanks for the feedback! If we may ask, what about the logo made you think that the content wouldn't be a "proper science lecture".

[@realGBx64]

@@SEMF looks like a spiritual tree of life logo of some cult to me.

[@SEMF]

@@realGBx64 Interesting! Well thanks for the feedback, it is always useful to gather impressions. The tree-like shape is a remnant of our former logo that had the "Tree of Knowledge/Science" as a centrepiece. The current design is intended to evoke dendrites/neurons, particle traces, etc. If you want to learn more about the society behind this channel you can visit our website: semf.org.es/mission/

[@ronmullick253]

Wow.Mind blowing.

[@SEMF]

It really is!

[@JonathanOelkers]

Wow, top notch. It’s cool to see someone talk with specific knowledge about computer science and biology. It seems like the video ended without the question really being answered, or perhaps I just struggled to understand it. Somehow the tissues seem to ‘know’ what morphology they are meant to become, even if they need to take a different approach to getting there. Do you have a mechanism in mind to explain this?

[@sillysad3198]

i think we must ask the question WHAT is encoded before "how" a blueprint encodes a shape and produces identical bolts and nuts. whereas frogs are all different, different IN SHAPE, yet they are all "similar" what IS this "similarity"? let alone Trees -- unique as effing fingerprints! the idea with geometrical space distortion is very misleading, i'd start from the CONNECTIVITY, certanly a connectivity "scheme" of a body must be much more invariant than the shape.

[@MatthijsvanDuin]

This video is just a small extract from the full talk, see video description

[@aeolianharp1363]

Fascinating new perspectvive

[@SEMF]

It really is!

[@dimomarkov8937]

Your channel, and this video in particular caught my attention due to a completely different reasons - i was planning on making a tool for generating beings for a video game, that have anatomy and can maintain homeostasis of some kind. The things you said gave me a lot of ideas. I doubt it will be useful for advanced academic purposes, but i bet it's going to be a fun little toy, that might or might not give some intuition about further stuff. I reckon feedback loops play a huge role - a homeostasis can be seen as a chaos control mechanism selectively developed by nature, to maintain optimal parameters of a chaotic system throughout its lifetime. Chaos control is currently an emergent tech that has many useful practial AI implementations, and in some sense can reverse-engineer (approximate) some natural mechanisms. So, designing and compiling a living system would inevitably be the designing and compiling a system of feedback mechanisms for chaos control.

[@SEMF]

That sounds fascinating! We invite you to share such projects with our community: semf.org.es/participate/join.html

[@aaronknight7129]

I wish I could participate. This is so fascinating.

[@SEMF]

Thanks for your interest! You can participate in the SEMF community by joining our network (free) following this link: semf.org.es/participate/join.html You will get access to our community forums, mailing lists and early announcements about future events for registration.

[@moderncontemplative]

This is epic! 👏🏾

[@SEMF]

Indeed it is!

[@lavapanther]

Wonderful.

[@SEMF]

Thanks!

[@SirCharles12357]

I've been wondering about this for years this for years. Where is the blueprint? How do cells know where they are at in the tissue/organ/organ system/creature? How do they know when to divide or stop dividing? This is exciting stuff!!

[@SEMF]

This is super exciting indeed!

[@osaimola]

I recall watching a channel abiut single cell organisms and sometimes, and not nearly rarely, you see something that makes you think these things are intelligent & perfectly capable of some sort of reasoning (at least on some level)

[@SEMF]

@@osaimola Interesting!

[@johnk6757]

They don't know, there is no global/top down organization. Local rules evolve into equilibrium

[@SEMF]

@@johnk6757 Local rules evolving into equilibrium is indeed a very important abstraction to model the kind of phenomena Michael Levin studies.

[@wombatmachine2.035]

Please tell us about local growth factors for different facial features pls

[@rb8049]

Wow! My preconceptions are blown.

[@SEMF]

That's a great sign!

[@eaudesolero5631]

So after watching this video I read through a lot of the comments. I then went and watched some more in-depth stuff of his at greater length. My background is computers and physics and I have dabbled in cell and molecular biology and Neuroscience. I cannot help but think about Quantum superposition and entanglement. It has been demonstrated that there are quantum effects going on in the brains of mammals. It must also be true for the way that the protein structures fold. It would answer the question as to how they do it so quickly. Add to that the holographic theory of memory. And how much information is stored in a hologram. And the astronomical number of permutations that are present to encode information in DNA. I would not be surprised at all if the electrical patterns that we are seeing or encoding the shape information in a manner of Quantum superposition

[@SEMF]

There is a real possibility that quantum entanglement is involved in the process. Great comment!

[@Ron-rk6iz]

It is Memory, which is present all over your body, not only in the Brain, the rest is done by food intake. If you eat a piece of bread it becomes you, if another person takes a bite from that bread it becomes his body with all features according to the memory collected.

[@ZapataCarratala]

That's a pretty accurate short account of it!

[@LeeSandis]

I have seen this talk pop up again and again on youtube over a long time. Any news on this?

[@SEMF]

This was an update in the general context of the concept of Spatiality in our conference. Arguably a summary of previous, previously known work, but very relevant to this concept of space and shape.

[@arturwronski8652]

Great insight to understand life! But sill the question “where it is encoded?” is unanswered. I believe that species pass through generations not only physical characters but also experiences. I mean not only instincts, but also complex behaviour patterns (e.g. cuckoo chick ejects eggs out of the nest). The question is relevant not only to morphology, so what is the answer? Kind of The Little Prince’s magic box answer: somewhere within the very first cell AND/OR somewhere outside the cell. The part “outside the cell” cannot be neglected, because “the law of physics,” at least at atom level (and sub-atom) provide infrastructure life is based on. Can we reject the idea of Cloud storage? Or, may be single cell encodes much more than we thought

[@robertpalma7946]

Very interesting concept! Would bone remodeling of a fracture site be an example of this process??

[@SEMF]

It definitely looks like so!

[@p0indexter624]

good question

[@SEMF]

Michael outlines a very enticing answer!

[@GeoffryGifari]

is studying the limit of regeneration useful to figure out where anatomical information is stored? how far can we slice an axolotl until it stops regenerating correctly?

[@edthoreum7625]

5:00 morphOspace

[@prschuster]

There must be some incredible interaction and communication between cells and their molecular signals.

[@SEMF]

That's right!

[@KorenyukOlexander]

Had a lot of thoughts about this topic. For sure, information component persist somewhere in encoded form

[@SEMF]

We are glad our highlight video got you thinking.

[@123100ozzy]

Amazing

[@SEMF]

It really is!

[@andrewsheehy2441]

Just want to say how wonderful it is to have credentialed scientist asking such a question. If we assume that information is encoded at the level of base pairs then the total amount of information that can be represented by a single molecule of human DNA is about 1.5GB - so not very much at all. If you were to model the human body down to the level of the individual cells (so not down to protein level) and tried to do that in a 3D modelling software like Blender then you'd need literally TB of data. So Mr. Levin right to ask how the 'missing' information is encoded. I think answering this question will open a door to a new panaroma for biology, and probably physics as well. Bravo!

[@SEMF]

That's a very relevant observation!

[@Ikbeneengeit]

How then??! Tell us please!

[@Solar_Max]

He ends with the question. I am no further ahead than at the beginning.

[@SEMF]

This is the beginning of a scientific research field, it is natural to still be humble and stay sceptical.

[@GeoffryGifari]

what is it about amphibians that makes them regenerate more easily?

[@eloycolombo7125]

We need to learn how to talk to cells, proteins to convince them to do what we want.

[@SEMF]

That's the idea!

[@melblock1882]

form, FIT, and function

[@Gamemake]

Did you check if the wave function collapse algorithm is a good approximation for this? It seems like it can solve very similar problems by only looking at local state like cells can.

[@SEMF]

This really was an amazing contribution. We are having a Levin-focused event in our community. You can join the live discussions on our community here: semf.org.es/participate/join.html

[@MNC2k]

so one starts out as a point in morphospace (I like that term) and gradually expands, stretches and shifts to occupy different regions. sort of like mthematical functions in a vector space? can we then work out the orthonormal equivalent in cell mrphology?

[@MNC2k]

how many dimesnions can morphospace have as well?

[@rogerjohnson2562]

Shape and function is information; where is the information stored? The question perhaps is how can proteins (made from the nucleus) effect the electromagnetic signals that direct shape and function? Also, what feedback mechanism informs the nucleus to shift protein generation.

[@SEMF]

Great question!

[@glenliesegang233]

What makes living systems different from nonliving is simple: Order. The degree order imposed on matter and the flow of energy through it is specified by digitally encoded symbolic data, AND an operating system of immense complexity which regulates the production of each nanomachine and the regulation of each metabolic and structural component in patterns where groups of machine and processes unfold to produce a generative whole. A blueprint may be used to build a factory. But in living systems, instead, there is a written instruction manual made of words, interpreted by a cooperative robotic system which interacts with software which "understands" how to translate those words into structures and further instructions,, with regulations in timing. If the first group of builders builds the first room specified, copies his textts but highlights what the next builder should do and shouldn't do, and this process continues. What should make this extraordinary, actually a miracle, is these processes have built in error correcting systems which can accommodate changing environments. The individual words which are written for the builder to read may be "door" but the where and when of installation cannot be found in a simple sentence.

[@SEMF]

Great summary!

[@jamespercy8506]

the power of exaptation/re-purposing/comporting to novel contexts.

[@SEMF]

indeed!

[@javiercamposgomez1287]

Awesome!!! I always wondered about how shape and symmetry were “encoded”. Since I was younger I noticed that people who have extra fingers usually are not symmetrical and if symmetry was encoded in the DNA a mutation causing an extra finger should produce it on both hands, at least there were two sets of genes to control ontogenesis of each body side the body, which does not make much sense.

[@SEMF]

Precisely!

[@aj-uo3uh]

This is explained at 12:30 in the following kzbin.info/www/bejne/iWScZqSOa6xpfq8

[@SEMF]

@@aj-uo3uh Thanks for the link!

[@anthonyrepetto3474]

14:56 - "GOALS in anatomical space" I hear echoes of teleology... and I'm going there :)

[@SEMF]

Some causally justified teleology is probably the way to go!

[@anthonyrepetto3474]

@@SEMF :) hehe - I wrote an essay, googleable, "Biological Teleology" as to my guess how cells can "choose what *will* be good for them."

[@SEMF]

@@anthonyrepetto3474 Interesting!

[@scenFor109]

The Cellular Positioning System is probably set by holographic interference transmission and reception by cell wall antennae.

[@roger_isaksson]

Well, if the geometry isn’t in the proteins, clearly it’s “downloaded” from the mother by some means of information transfer. It could be a simple hormonal sequencing information transfer.

[@SEMF]

The most likely mechanism, as Michael pointed out, is DNA and well-known genetic inheritance. But any other mechanisms, such as the ones you point out, are reasonable possibilities.

[@Will-kt5jk]

I liked the talk, but rather than suggesting routes of future research, it was describing why the question is a question to begin with & that it is yet to be explained. To be fair it does end by suggesting it’s unlikely purely emergent, but (based on the title) I was expecting some potential explanations of how it is encoded & more about ongoing research into those explanations.

[@SEMF]

That's a fair description. Michaels work is amazing and very promising but still early stages. We look forward to inviting him and his collaborators again!

[@aj-uo3uh]

I recently wondered about this so thanks youtube. Being a c++ coder I was wondering where the memory of the huge design of our body is situated. I googled a bit and I found that we know at least some genes that code for some structure. Good to know that overall its still a mystery. Being in addition a mathematician I know that a fractal can be defined by a simple formula. Together with this feedback idea we can at least get some intuition.

[@SEMF]

We are glad to provide the content to support such thoughts!

[@kokopelli314]

Or some kind of recursive tensor with tightly distributed means.

[@SEMF]

@@kokopelli314 Could you expand what you mean by this? Sounds intriguing!

[@kokopelli314]

@@SEMF so fractals exist in state space where consecutive points have indeterminate or chaotic vectors. That is the N+1 point is indeterminate given variation of initial conditions, but the attractor, or pattern remains fairly consistent within a set of mean values. These values could be represented by tensor, or sets of n vectors with probabilistic values affected by a recursive function. Like you indicated in the video. It might look like magic, but a recursive function, acting through state space would be like the complex plane.

[@SEMF]

@@kokopelli314 Thanks very much for the clarification!

[@notlessgrossman163]

DNA might describe a cell but may also convey rules to each cell like cellular automata does for each pixel. Maybe there's biochemical markers and cellular sense making of its environment.

[@SEMF]

That's a very real possibility, thanks for the insightful comment!

[@billmcdonald180]

You say something that is 'goal' oriented rather than simply 'emergent' is uncomfortable for biologists, but I would argue it is indeed the opposite because as you've described, the reality is that these things ARE in fact goal oriented. So biologists should be very interested in this because it reflects what IS happening, rather than someone's preconceived ideology about how they think the world 'should' work.

[@SEMF]

How are goals defined in nature?

[@roger_isaksson]

14:58 The “smell” perhaps? A sensitive enough instrument likely could pick up how a certain “shape” “smells” from the metabolism of growing tissue which would correspond to the actual value in feedback control. After all, we’re a collection of cooperating cells and not cells that are programmed to grow into a certain shape. The macro shape of this collection of cells merely happens to be evolutionary advantageous as a configuration.

[@SEMF]

That's a very interesting suggestion!

[@fbkintanar]

Oh wow, this is very insightful. I am wondering how this take on closed loop pattern homeostasis, with a certain notion of "agency" and "intelligence", might be applicable to the patterns of (gross and fine) neuroanatomy and morphobehavioral outcomes in cognition. One system I have been thinking about for some time is the phonological component of linguistic competence. I am intrigued that all normal children will develop some kind of "morphospace" of phonemic distinctions (a system of "cognizable types"), incorporating the particular phonetic acoustic signals they happen to be exposed to in their household and community. What is surprising, and indicates that there are multiple paths to "the same" kind of outcome space is what happens to deaf children (or even hearing kids), especially those that are raised in a household or community where a lexically rich and fully grammatical sign language is used. (These are known as Deaf of Deaf kids, or in the case of hearing kids, Children of Deaf Adults or CODAs, and they grow up as highly fluent native signers.) They acquire an "emic system" that classifies "etic" gestures (distinguishing the phonemic-like level of cognizable types from the phonetic level of percept-level or subcognitive sensory signaling). My working hypothesis is that the similarity of behavioral outcomes (and potentially some of the encoding in brain morphology) can be understood in terms of the topological invariants on the geometric space of what seems to correspond to your notion of morphospace. Specifically, it seems like the etic space (of acoustic or gestural signals) undergoes some kind of (strong) deformation retract to a subspace of isomorphisms (identity functions or identifiability "functions" or perhaps homotopy types). There is a dramatic reduction in the degrees of freedom, and the phonemic (or gestural emic) types of the household-community are the outcome, different for each speech community or signing community but remarkably similar in structure when viewed as mathematical invariants. These ideas about phonology are about a relatively small subsystem of linguistic cognition, sort of higher percepts, that are closely tied to more elaborate linguistic systems like lexis and grammar constructions and semantics and pragmatics (and other areas of cognition like concept formation and recognition of intentional mental states in others). I have some ideas how a more general framework of cognizable types can accommodate some of the other subsystems of language, but phonology seems a practical place to start. This fits in with a broader framework of "information flow" influenced by the work of Barwise and Seligman (a 1997 book with that title), which may have a general enough mathematical model of information to accommodate the notions of biological information you are developing. I need to start looking into some of the papers you cite.

[@SEMF]

Thank you for such a well-written and informative comment!

[@fbkintanar]

@@SEMF You are welcome. I am trying to schedule binge-watching some of your content, hopefully I will have something more to say in the near future. Cheers!

[@SEMF]

@@fbkintanar That's great to hear! If you want to contribute to the community, you are very welcome to join our mailing list and Discord server: semf.org.es/participate/join.html

[@AwnSight]

One thought i havent heard u touch on is how much can cells copy. Why do most embrios grow inside the mother. The cells might be using input from mother to know how to build

[@SEMF]

That seems to be one of the most characteristic functions of cells indeed.

[@vesuvandoppelganger]

Since very little of genomes is understood, how can someone claim that the information for body development is not contained in the genome?

[@anonimperson7778]

Low IQ.same genome different anatomy he explains how.

[@aaronrodriguez4449]

First time I’ve ever wanted to hear the words “like for part 2”

[@SEMF]

We will invite Michael to future SEMF events! For now, you can watch the full talk here: kzbin.info/www/bejne/oH3MeX96p7SHjZo

[@Embassy_of_Jupiter]

So cells are like complex state machines, every cell senses it's own state and that of surrounding states and it tries to move to the end state (maybe along multiple states?) via some sort of minimization function, by signaling to itself and to the cells around them? I imagine it kind of how gradient descent moves along some manifold in high dimensional space and you minimize the distance to a point in state space. So is it in reality just a very complex fixed state machine or does it follow some minimization algorithm? I guess they both are the same in the end, but I hope you get my point. I imagine it a lot how machine learning works, mashing together vectors in some sense that doesn't seem to make sense initially, but it all works because the network has learned to interpret it. Like cells probably can't separate the signals from their neighboring cells and their second order, third order etc. neighbors, but because the states are so high dimensional, the mashed together states still encode that information. And I guess separating those signals isn't really necessary in the first place? But I think I'm simplifying this too much, there probably isn't one grand minimizer, but many different ones operating independently, that are again orchestrated through one or multiple state machines. Kind of like some parallel gradient descent working on different parts of the vector independently. And it's all happing using all kinds of different mechanisms from DNA, RNA, Proteins, hormones, methylation etc. working together in complicated and non-standard ways. But all the smallest scale components don't know their ought state, but it's encoded in their state machine. So the gradient descent analogy probably doesn't make sense. Or maybe there is a grand scale minimizer algorithm actually watching the states and orchestrating all the smaller state machines. Or is this again just some really complex "dumb" fixed state machine?

[@SEMF]

Many interesting ideas in this comment! Perhaps you would like to bring them to the SEMF internal community: semf.org.es/participate/join.html

[@willowFFMPEG]

I wonder if an individual cell can detect how many cells away is the nearest cell of a different tissue. like if a skin cell can detect how many skin cells are between it and the nearest subcutaneous fat cell, or if a liver cell can detect how many liver cells are between it and the nearest blood vessel cell, etc. Because if a cell *can* tell these things, then it seems to me like it would be a lot easier to figure out how anatomy emerges; each cell could roughly "triangulate" its position relative to other tissues in the body, and reproduce or die as needed to maintain an appropriate range of distances from the appropriate surrounding tissues. This is just a hunch but I'd be interested to hear what you think of it @SEMF

[@BrainConduit123]

Perhaps DNA contains the blueprint and specs for making whatever needs to made by simply storing pointers. The pointers point to a specific blueprint stored in some huge universal database from which the cells somehow retrieve the required information. For example, Pointer 6582240352982549 references the geometry of my big toe. Questions remain: Where exactly is the database, and how is the data retrieved? If you can answer either of these, I will gladly share my Nobel Prize with you.

[@SEMF]

That's essentially what Michael's research seems to point towards.

[@jamesjones2212]

The answer to this question can be found by deeply understanding the mechanism of self-similar structure transformation (Fractals). Just as the lungs were mapped by Mandelbrot himself so too can anatomical structures (Mandelbrot BB. The Fractal Geometry of Nature. W. H. Freeman & Co. Ltd; 1982.). Just as the Mandelbrot set forms 3d acorns, so to do organs and anatomy form finite shapes and they dont "stop" they continue but they iterate on themselves until no more energy is left in the system in which they are derived from. The key would be to use cross sections view (such as from fMRI etc) of development and with OpenCV to devise the baseline "fractal" that creates said shape. As to "where" this information is actually encoded, that answer becomes more clear when you start deconstructing all biology in terms of its baseline fractal. The encoding of this information is not present in the system directly, just as if we were to look at ChatGPT and view one of the transformations it wouldn't make sense as to how that singular transformation is able to perfectly structure sentences and the things it does. The information is encoded more in a gestalt way. (Fractals of Brain, Fractals of Mind: In Search of a Symmetry Bond (Advances in Consciousness Research, No 7)

[@SEMF]

Thanks for the insightful comment!

[@Quidisi]

Would love to know what Rupert Sheldrake would say to this. He has some pretty interesting theories about similar.

[@dradvice9349]

I ve been in medicine field since many years ago, and I can call it after more than 33 years of practice , that God is real. !!! Congratulations for your incredible videos!!!!❤❤❤

[@guidopahlberg9413]

The key is the distribution of regulatory substances in the body and their interaction with information/rules in the cell: if there is too much or too little of the substance, less or more will be produced. If you have rules for multiple substances, you get a stabile pattern (standing wave), like the stripes of a zebra, that define areas of the body. Think how this works on a scale with hundreds of regulators that create a complex pattern to define aspects of the morphology. If this system is perturbed, if will strive to get back into balance. If a new cell migrates into a tissue, its role is defined by the mix of regulators in its surroundings. The informational model for this would be a 3D pattern of Turing engines, interacting with each other locally, writing and reading streams of 'tape'. Each engine has hard-wired ROM data (DNA) as well as local RAM storage (RNA, methylizations). With the right kind of wiring and initial settings, the machines will interact to create an organism. If the settings are wrong, the organism will not converge and die off. Nature selects the working settings.

[@SEMF]

Very interesting thoughts! You may want to share them with our internal SEMF community: semf.org.es/participate/join.html

[@guidopahlberg9413]

@@SEMF Thanks for the invitation, I feel honored and will grasp the opportunity.

[@guidopahlberg9413]

@@SEMF Thanks, I feel honored by your invitation.

[@wcoenen]

See also "Growing Neural Cellular Automata". (I would provide an actual link, but youtube doesn't seem to like comments with links.)

[@SEMF]

Thanks very much for the suggestion!

[@jmarz2600]

This is Faraday and Maxwell level science. Their explorations in electromagnetism led to electric motors, telegraphs, phones, computers, etc. What will Levin's explorations into the bioelectric role in morphogenesis bring?

[@SEMF]

We hope to be there to attest future results!

[@binra3788]

History reveals the weaponisation and marketisation of science by invested insiders seek prior advantage of insider knowledge, kept secret or surrounded by obfuscations. The Field approach is NOT a control model but a mindset of control seeks according to its own conditioned thinking, under the mask of serving humanity, for possession and control. Hence The Biotech revolution of augmented or captive human to such systems is close at hand. Living waters are structured by nanoscale quantum charge domains as a medium of translation of information unfolding from a whole. The pathological model rises from a sense of lack, exclusion, conflict, denial, set to defences that boost and reinforce the model as the basis for interpretation. Wholeness is a balancing alignment of a life as contextual expression. But All the king’s horses and all the king’s men cant see it as that predicates on a broken life that must be fixed.

[@SEMF]

@@binra3788 Interesting considerations!

[@lake5044]

Do we have some clear experimental example of when the cells fail to form the typical structure they usually form, after some disturbance? If yes, then I think researchers should focus on that because it would allow us to pinpoint a necessary mechanism that didn't work. It's like how solving mazes is easier if you start from the end. Just observing that cells know how to rearrange themselves (on multiple levels and following multiple paths) simply looks like "magic" and doesn't really tell us how. Also, perhaps the complexity of how DNA translates to such diverse mechanisms can be better explored by automation. Imagine if we could automate making genetic (and epigenetic) changes and observing the effect on millions of test cell groups, it would become feasible then to launch a massive brute force search to pinpoint the genes necessary for this regeneration and be able to observe a huge number of variations and understand the effect of each change...

[@SEMF]

Levin's work shows some direct experimental evidence. You can check other videos in our channel for it!

[@HyperFocusMarshmallow]

Ok. Simple model problem. Suppose we want to generate a ball of cells with a certain number of cells as its radius or a certain distance as radius. What would be a simple way to achieve that. What would each cell have to measure, and what would be a mechanism to compare that to a number stored in for example the genome? A ball seemed like the simplest Morpheus space I could imagine, maybe there are simpler once.

[@SEMF]

Simpler problems like these are probably important to investigate. Perhaps you would like to share your thoughts within our community: semf.org.es/participate/join.html

[@yw1971]

4:50 - Missing the words 'as efficiently'. Or in other words - by better predicting the future

[@SEMF]

Interesting observation!

[@user-nd7rg5er5g]

Perhaps the nephrons forming the lumen are paying attention to the surface tension across their cytoskeletons. If multiple cells could bend together and achieve their desired surface tension amount together, then great. If only one giant polyploid cell is available, then that's fine too.

[@SEMF]

A very real possibility!

[@123TeeMee]

There’s a game called cell lab where you make little multicellular organisms by defining a set of cell types, for each saying the angles of the descendants upon splitting, and what cell types the two descendants are. Combine this with the physics based precession of cells pushing and deforming each other and you arrive at some morphology. I’d say that encoding is not a great word for organisms that we know in real life, as code suggests it’s all layed out in readable form, when really it’s just a lot of evolutionary biases and constraints from physics, that is with the exception of the more organised aspects of dna, which aren’t the full picture.

[@SEMF]

That sounds super interesting! Why don't you share some links or info about that game with our community? You can join at no cost other than filling a quick form here: semf.org.es/participate/join.html

[@GeoffryGifari]

how can the axolotl tell when the set point is reached? amazing

[@SEMF]

That is indeed part of the mystery!

[@anywallsocket]

I thought we already knew this. It’s not just life, but physics as well. Universal darwinism applies to all self-stabilizing systems ie any dissipative structure whatsoever - including physics itself. Clearly complexity and order supervenes on self-interaction at various levels of scale - it is not built into the initial conditions like your reversible, idealized, linear, physics would have you believe. Most phenomena are non-linear open dynamical systems, so if they are not autopoietic or at least self-stabilizing, they will dissipate due to the stochastic nature of reality, and therefore will not perpetuate long enough to converge onto self-replication and eventually become an ideal Quine.

[@gabbyappo1511]

So if a salamander was born with a deformed leg, that gets cut off, does it grow back a deformed leg or does it fix itself given another chance to grow the leg.

[@SEMF]

From what we learnt from Michael, it would depend on what caused the leg to be "deformed" in the first place.

[@drphosferrous]

Til there are comicsans powerpoint presentations that i would pay to see.

[@SEMF]

Our thoughts exactly!

[@drphosferrous]

@@SEMF is it assumed that the undiscovered genetic data for morphology works in amphibian maturation just like it does for regular growth in other creatures?

[@SEMF]

@@drphosferrous It seems to be the case, yes.

[@generichuman_]

That lumen example is so good, that if I were a creationist, I would use it as one of my arguments. Luckily, I know better.

[@SEMF]

It is an amazing example indeed! Michael did say it was his favourite example to date.

[@liqo12]

So anatomy growth is a confluent rewrite system

[@SEMF]

Indeed! That's a very interesting angle! Many SEMF community members would love to discuss these ideas further. We invite you to join by following this link: semf.org.es/participate/join.html

[@nishanthmurugan8084]

Not only cells have intelligence but i think DNA also has intelligence because it has goal directed behavior.some components of the cell like ribosome,mitochondria also have goal directed behavior.Is it possible that cellular components also have intelligence?

[@SEMF]

Intelligence in the sense described here, absolutely! That's a very real possibility.

[@xxpandaluv9126xx]

Subhanallah. The more we try to understand the less and less we know

[@SEMF]

How come?

[@xxpandaluv9126xx]

The dunning Kruger effect shows us that you initially learn about a topic you have this false confidence about knowing it well. It’s when you really dive into i]the subject that you realize how little you really know and how there is sooooo much yet to be learned. So same with research the more we find out the more we realize we have yet to learn.

[@SEMF]

@@xxpandaluv9126xx Indeed a relevant effect in this context!

[@BenjaminHare]

The Platonic form strikes back.

[@SEMF]

The return of the Platonist when? ;)

[@TropicalCoder]

Wow - that is a fundamental mystery there. It's as if - the tadpole _wants_ to be a frog. He puts his mind to the task. and wills his limbs into being.