 Hello and welcome, everybody. It is September 19th, 2023. We're here at the Active Inference Institute in guest stream 58.1. And today, the session will be around the experiences of those who have worked with Gerald Edelman. Edelman lived from 1929 to 2014. And as hopefully this conversation can explore and unpack a little bit, worked in various areas related to the brain, body, and mind. So without further ado, I will have our guests introduce themselves, give a little bit of a background on how they came to be working with Professor Edelman. And then we have several prepared questions and several other questions. So thank you all for joining and perhaps Andrew, if you'd like to begin. All right. So I'll just start a little bit with my background. I did my PhD at University of Minnesota. And then I did my postdoc at Hopkins, with Apostles George Oppelis and Vernon Mock Castle. And then I got a job in Phoenix, working in a small neuroscience institute or neuroscience department at a hospital. And I worked there for six or seven years. And my interest was working with nonhuman primates with monkeys and studying how they reached for different objects and drew objects. And then looked at activity in primary motor cortex and we carried out different kinds of analysis based on the directionality of the neurons in motor cortex, built populations. And we're able to actually look at these neural signals and see how they corresponded in a pretty exact way to the way the animals are moved in time and space, in other words trajectories. And after working there six or seven years, I was invited to come and look at this new institute that Gerald Edelman was establishing in San Diego in La Jolla. And met a bunch of super interesting people, like Julio Tononi and Olaf Sparnes. And really their deep intellect and curiosity and creativity has convinced me to move to San Diego. And so I ended up moving there. And so Edelman was able to build this gorgeous research facility on the Torrey Pines Cliffs basically. And it was a magnificent architecture. And he recruited a number of people besides Sparnes and Tononi. And so he divided the group into theorists and experimentalists. And I was an experimentalist. But we would have lunch every day together as a group and discuss different topics. And I was really exposed to a whole new way of thinking about neuroscience in terms of sort of the cognitive aspects of it, which I still have difficulty with to tell you personally, because I don't even know how you define cognition. And I'm not sure that anybody really can. Or as Vernon Mock Castle would say, I don't know the answer to that, nor does anybody else. Maybe Carl would take issue with that. But anyway, the coolest thing about it was being really exposed to a lot of creative thinking and deep intellectual endeavors. And I've really never regretted the seven or eight years I spent there. I think it really helped change the way my career went from being sort of a motor control strict, sort of, you know, very careful scientist to using my imagination a lot more than I would have otherwise. So I'll leave it at that. Awesome. Chengming? Okay. Yeah, I think that the speech about my journey with Dr. Edamon. So I was originally from Taiwan. I graduated with a medical degree in Taiwan University in 78. But I was very interested in doing basic science. So I applied the PhD program and got into Rockefeller University. And that started to search for a laboratory. And certainly Dr. Edamon, you know, he's a very powerful intellectual capacity building on the, in the building, you know, it was on the ninth floor of the Bronx laboratory. I was very impressed. So I joined the laboratory. So since the 78 to 83, I was a PhD student. And I was working on the topic called called Neurocell Adhesion Molecular. So at the time, Edamon already got his Nobel Prize for immunoglobulin. But he would be, you know, usually, you know, in usually elegant way, would say, I solve the molecular recognition. So he said, I don't want to be staying in immunology to collect more awards. He said, I will work out the cell recognition. So in his mind, the cell, how cell recognition work is through a group of adhesion molecular interaction. So that that's how he started to work on the cell adhesion molecule. And the duties house actually work out to the chicken cell adhesion molecule. So when I joined the laboratory, my PhD thing was work out the first mammalian cell adhesion molecule. And in addition to N. Campbell, I supposed to work out on these adhesion molecule, mediating the neural cell recognition. As he said, he would say, you know, I asked him, oh, so after all, what would be my PhD thesis? And he would say mean, you know, when I start to write a poem, I don't know how it's going to end. That's the way he would put his language there. So he just figured out the retinal tectoprojection, you know, so that, you know, I'm hardworking students, so I would work out on that. And as you know, these days, our so-called systems biology approach, right, is these transcriptome single cell RNA sequencing to identify a non-biased way to identify molecules involved. At that time, the so-called systems biology approach was making monoclonal antibodies. So I would be there taking out the brain, you know, and the retina and the tecton and produce, I produce 18 batch of the, of the monoclonal antibody against these, these neuronal cell membranes. So I certainly have identified a lot of adhesion molecules, but none of them really show a very distinct pattern. I mean, these days, I think we, I mean, the field that using the transcription factors was able to identify some patterns. But at the last day, though, it's kind of all together. But I remember that actually, no. So anyway, that's enough. I didn't really figure out the retinal tectoprojection, but that's enough for me to graduate. But at the next time, though, I also still remember, you know, how I actually, I mean, still he has a great impact on my professional career. So I was cutting chicken spinal cord, you know, cross-section to mapping these cell adhesion molecules. So I have some feather, chicken feather hanging outside there. And they stand with this and came with the most beautiful exquisite pattern. You know, I mean, brain, I later work on the feather as my major research model, kind of as a Rosetta song to understand the language of morphogenesis. But there I remember how I started is that you have these feather, they form these branches. So these branches are actually originally formed cells, then they die to become space. But before they die, they actually light up with N cam, light up with N cam with the most exquisite pattern there. So you kind of say, okay, you're going to talk about this region, you light up with N cam, you light up with sonic and then other signal coming to say you die. But before they died, they light up that pattern. So the feather pattern is very exquisite, radio-symmetry, bilateral-symmetry, bilateral-symmetry. So Edelman was very impressed by those, you know, those findings. And so that, you know, that I appreciate that he actually encouraged that. When he sees something, he appreciates, he encouraged, he didn't say, oh, you're supposed to work on the brain or whatever. He actually liked it. And subsequently, he also, you know, developed this idea of topobiology, which he would acknowledge to say it's sort of based on the very exquisite pattern we found in the feather. But of course, he developed it further. But some other time, he would say, if this is not in feather, I'm going to, I am Edelman, I'm going to get another Nobel Prize. So I like it, let him encourage that direction. So later on, when I became independent, I sort of say, okay, you know, a brain is wonderful, but it's all like being curved inside. I don't figure it out. But I'm not that smart, but I might be able to figure out the feather pattern formation. So I have a reasonable, successful career, figure out, you know, the able-devil of the feather. But as I said, not just feather itself, but use feather as a rosetta stone to figure out the morphogenesis. And that sort of, I think I appreciate that he's encouraged on that. And also, you know, as you know, the stem cell biology comes along, and the feather in the bird, you know, baby chicken is one way about chicken, male, female, all looks differently. But they are all from the same group of the stem cell that my lab have demonstrated. So it is the so-called stem cell niche would be modulated by sex hormone, by age, by season, by temperature, and they help you produce different feather forms to adapt to the environment. So I think I enjoy my research career, and it was obviously have his impact. And I think he's intellectually brilliant and always encouraged, going after, after fundamental principles, saying that if you're going to work on a question, ask the most profound questions, and approach it with the most available technology, other than the technology of the day, you know, don't waste your time on small questions. And I think I have to take those in. So I can say up to here and we can discuss more later. Thank you. Awesome. Carl? Hi, so my name's Carl Friston. Like my two colleagues, I found my stay with Jerry Edelman, both foundational and very, very formative. I was quite early in my research career when I joined the Neuroscience Institute. Having trained as a psychiatrist, I got into brain imaging. And at the inception of brain imaging, people were for the first time discovering principles of functional brain organization, such as the principle of functional segregation, and subsequently principles of integration have segregated, specialized parts of the brain, communicate or are coordinated or are integrated together. And one of the key theoreticians and neuroanatomists that authored this particular interpretation deployment of neuroimaging with Semi-Zeki. And Semi-Zeki, for those of you who don't know, he's still reactive, one of the architects of neuroesthetics in his late retirement now. But he was friendly with Jerry Edelman and Semi was famed for understanding the computational anatomy of early visual cortex and visual cortical hierarchies. And I repeat the principles of functional specialization and integration. So after a couple of years at the inception of human brain mapping using positron emission tomography and establishing this, for example, the color center in a particular part of the visual cortex, I was effectively sent to New York. So my period of engagement was a fellowship between about 1990 and 1992, 93s. So this slightly predates on me. And it covered the translocation of the Neurosciences Institute from the Rockefeller University to La Jolla and the auspices of the script. So I spent half my fellowship at the Rockefeller and then subsequently watched the building of the Magnificent Neurosciences Institute on North Torrey Pines Road that Andy referred to with the auditorium, if I remember, designed by imported experts in audition and music and sound engineering from Sweden. It was a really an amazing place. I do remember a couple of lunches before I returned to the UK to pursue my career in imaging neuroscience under the auspices of the Wellcome Trust. But only a couple because we were sort of in rented accommodation from the scripts on the other side of the road. But it was an awe inspiring bit of architecture, both intellectually and practically in terms of the early days of the Neurosciences Institute. So I was sent there basically because some of you thought it would be good for me to go and work with Jerry Edelman. Retrospectively, I now appreciate that I was sent there to replace a general called Reed Montague, who had been tasked with on the pure theories side as opposed to the Scyledesian molecule and the wet lab side of Edelman's research. On the pure theory side, the point of my arrival and to a certain extent at the point of Reed's brief exposure to the Neurosciences Institute, the theory of neural group selection was becoming consolidated. And in particular, what drove the selection of neuronal groups, neural ensemble cell assemblies, however you want to describe them. And given Edelman's polish on for incredibly incisive and straightforward, but very creative biological thinking, he thought, well, it's obviously some kind of natural selection. And therefore, there must be the homologue of adaptive fitness that is underwriting the scaffolding and the dynamic structuring of connectivity or connections that were definitive of in the spirit of functional specialization of segregation, but also the mediator of functional integration of these neural cell neural groups. So this this became known generically as value. So Reed was working on value dependent learning, the pasticity and the principles that underwrite which synaptic connections have the right kind of adaptive fitness in their milieu in that context that enabled them to persist and other connections went away and became more contributed to the sparse coupling of neural networks. And then Reed, and we can talk about the glorious stories about the departure of Reed, Reed actually ended up in a rather circuitous way with Terry Sonoski at the Salk, subsequently then hooked up with people like Peter Diane and Wolfram Schultz, who at that time was in Zurich. And of course, the story that emerged from that was the reward prediction error story that actually ironically Reed did not, but a number of Wolfram eventually got the brain prize for some decade or so later. But the inception of that story was actually at the Rockefeller. And it was basically an attempt by I think Reed to formalize the principles that must be in play to make the theory of neural group selection under what was an important dynamic from Edelman's point of view, which is notion of re-entrant dynamics. So very, very early on, he had identified the fundamental importance of recurrent connectivity and re-entry as very formative in the emergence of these structured groups and the associated functional specialization. And I'll just open brackets just to point out that you could claim that certainly his early conversations with the people at that time sort of preempted stuff in computational neuroscience that we now would take as sort of for granted, not really realizing where it came from. But certainly his work with Bernard Mancasse, I'm sure Andy will be able to speak to this later on, the importance of re-entry and dynamics and oscillations in the formation of these groups and sort of cortical columns and the like. That was a sort of, I think, the monographs, not the monographs, but the papers and the articles they wrote at that time, I think were quite visionary. Stephen Grossberg was also hanging around a few years earlier. And I think you could probably claim that between the two of them, they invented computational neuroscience, certainly a la, you know, New York, Boston, sort of, you know, the East Coast kind of style of computational neuroscience, mostly involved with what's called the Neuroscience Research Foundation. So that they, as I understand it, and again Andy may want to correct me here, but this was like the forerunner of the Society for Neuroscience. It was a group of people, people, and perhaps Max Cowan as a name that comes to mind, people who actually invented words like neuroscience, which wasn't a thing, certainly when I was applying to, you know, to do my undergraduate studies, and trying to create institutions, academic institutions that would endorse this notion of neuroscience. And the Neuroscience Research Foundation was like the Old Guard. And then the Young Turks came along and reacted against the Old Guard, the Neuroscience Research Foundation, to form the Society for Neuroscience. And then we all know the story since that time. It's one of the biggest societies in academia. So just making the point that Edelman and, you know, his colleagues and Vicarious colleagues, you know, a lot of people, Oliver Sacks being one, Ernst Mayer being another of his favourite sort of characters to talk to, all of whom would come and visit. And we were privileged just to listen in and conversations in this very formative time where some of the sort of, I think, conceptual pillars of the way that we understand neuroscience in the 21st century were first articulated, probably not using quite the same words that we use nowadays. So no one talks about reentry anymore, it's all about recurrent neural networks or sort of feed forward and feedback and the like. But the same underlying dynamics and maths, I think, is absolutely there. Anyway, I was brought in to replace Reed Montagu. So that was my little contribution whilst we were in the Rockefeller. I made the mistake of thinking that the right way to do this was to actually write down equations and try and sort of naturalise it in terms of mathematics. Edelman was a great biological thinker. He was not a very good mathematical thinker. So there was a bit of a clash there. So I remember one meeting very early on when it was being decided what I was going to be doing. Perhaps it's useful just to say the context in which those early meetings took place. So, Andy, as I already mentioned, Julio Tenone and Olaf Spawns, they were two key people, Edelman's young men, who were already inside you and that I replaced Reed. And they were working really purely on theory. And that theory was tested in the context of what was a forerunner or a supercomputing, a hypercube that was driving, in my day, little robots. So again, Edelman was doing neuro robotics in the 1980s in exactly the same way that people now in developmental neuro robotics are still addressing exactly the same questions. And probably with the same kind of computer infrastructure that obviously upgraded. So we were sitting around and Edelman was called out to take a phone call from Germany. And there was a look of horror on people's faces because I'd suggested a relationship between value dependent learning and the risk or a Wagner rule from behavioral psychology. And as soon as you mentioned an equation or a formula, that set Edelman off. And I didn't know that. I didn't know I pushed the wrong button. So when Edelman came back in, I was effectively rusticated. I was prevented from doing any work for three months. And for every day, afternoon and morning, I had to sit in the Rockefeller Library and read purely biological, great texts. And I ended up having to the last one was the growth of biological thought by Ernst Mayer. I had to read from page to page. And when I did so, I had become sufficiently sanitized to be allowed back into the workplace to actually do some work. So that was our contribution. And then when we moved to the whole parade of 16 wheeler trucks is transicating all the paper work to La Jolla and then relocating out there, settling down. I brought that work to closure. And the interesting that was at the point when Julio, well, Olaf, I remember him saying, you know, what he wants is basically to understand the and simulate the brain in a way that is draws expoundry power from the architecture of the connectivity. Basically, we say he wants to be he wants to establish connectomics as a discipline. And of course, you know, 10 years later, he's Mr. Connectomics. Julio at that point was inventing integrated integrated information theory with a particular focus on information theoretic formulations of complexity and what special, if you like, count intuitive behaviors do you get from these biologically configured connector when you put dynamics on structure and trying to quantify that in a way that ultimately transpired to be measures like phi in IIT. So that was a fun time as the mathematician, closet mathematician, because I wasn't allowed to say anything about the math at the time. I enjoyed that bit and so looking, you know, being in at the, if you like, ground zero at the inception of all these all these aspirations, which eventually led to very fruitful careers. And then I went back to, to the UK, just had fond memories, and non fond memories, but both of a nostalgic source in some time. Awesome. Great tails. Changming or Andrew, anything you want to add or I can go to one of the questions. Well, just to expound a little bit on what Carl was saying, I don't know if you can see this book. Okay. So this was something that came out of the Neuroscience Research Program that was sort of the old boys club that Francis Schmidt started at MIT and later was the basis for the Neurosciences Institute. And what this was was sort of the who's who in neuroscience. So again, if you look at this book, it says edited by Francis O Schmidt. So he was the guy who started that. And so this persisted even to the throughout the 2000s. And so once or twice a year at the Neurosciences Institute, they would organize one of these meetings and it would be a who's who of neuroscience. So all the Nobel laureates in neuroscience, all the big names would come for a four or five day meeting and talk about their research. And as a member of the Neurosciences Institute, I got to sit in and meet these people. And it was phenomenal, especially with my background, because I was sort of not on the the mainstream of neuroscience at that point. And that was really fascinating. So you got to meet people like Will Schulzen and all the the big names that were there, Francis Crick, you know. And what I want to go back to is this original book by Edelman and Montcastle called the Mindful Brain. This is sort of like one of the bibles of early creative thinking about brain function. And it presages the idea that of distributed systems. This was sort of the thing that Verne Montcastle was very much into. And so the to this day, the way most people think about brain function is boxes where each part of the brain is confined to a box. And then there are arrows pointed to other boxes. And so we get this idea that there's a circuitry. So you'll often hear neurosciences talk about circuits. And that kind of comes from the idea that you have these boxes and you have arrows, and you have plus and minus signs with the arrows. And then somehow the pluses and minuses add up and tell you what's going to happen at the next box. And that is nice because you can kind of simplify things and talk about causality in very concrete terms. And it's great if you're an engineer because you can write transfer functions about defining how you can output from an input. But that's not the way the brain works. And, you know, I think Kyle can attest to the early days of NMRR studies where everybody was doing pseudo colored representations of these different areas to see which area would light up in particular tasks as if each area had a specific job and could be assigned to a specific task. And so neuroscience in general is still suffering from that point of view. And it's only become a little bit more clear as computational science has matured in the last five or 10 years, especially with an adaptation of artificial neural networks to the mainstream that, you know, we can start to explore more biological, meaningful ways of brain function. And, you know, Vernon Mock Castle recognized that, you know, as a sort of the, I would say the founder of systems neuroscience, modern systems neuroscience. And Edelman talked about that a little bit, you know, this group theory and some of the things that Olaf has started, you know, with graph theory, still sort of based on strict anatomical connectivity. And, you know, if you read like Olaf's latest review, where the field is starting to progress away from that constraint of anatomical connectivity, we're starting to get more toward the idea of truly distributed systems. And to me, that that's super exciting. But you can look back to this book, you know, from the 70s, and see that the seed was planted way back then, and see how, you know, almost 50 years later now, it's finally starting to evolve into something that's becoming more mainstream. And if you sort of look at the evolution of neuroscience, I think if you project ahead to the next 10 or 20 years, this is going to be really the fundamental change in the way we think about neural function. And I'm super excited about that. And you look and sort of back in history to see how that's evolved. And I don't know, I think there's something very attractive about thinking about things that way. Yeah, okay. Yeah. Okay, I'll add something. I think talking about, you know, Edelman's so the brilliance about, you know, seeing things through. I don't know, in the neural biology field, you people still sort of think the neural Darwinism idea is still there, right? Yeah. So that was the time when I was with him in Rockefeller University. He would talk things like that, you know, Darwinism for evolution species, and he saw that in immunoglobulin coronal selection. So he applied to this neural Darwinism idea. But I have to say, you know, subsequently, actually, my career is mainly in University of Southern California, and working on this morphogenesis tissue pattern formation. And in our field, you know, sort of a more benchwork aspect of Edelman, you know, this direction, not the neural biology direction. But in the field, there were people originally more talking about the same cells are predetermined, and then they go this image, they go this image. But we using the skin as a model, actually, you know, I start to write these things kind of a Darwinism within the skin. I mean, basically, is that there is no preset for ever stem cells. If you wipe out the same cells, other cells are waiting there to take over the space. So there is even during development and during regeneration, to make the tissue patterning process robust, there is a small so called Darwinism competition going on in there. And that is sort of also influencing my our our work in morphogenesis these days. And I think that's kind of the impact of him on this aspect as well. Yeah. All right. I'll read a question. This was from Dave Douglas. Dave wrote, We know that Professor Edelman used deep analogies in exploring new subjects, as in his leveraging his knowledge of immunology and organismal development to probe conceptualization and learning. Did he ever work specifically on metaphor and analogy as such? For example, did he leverage his experience of music and poetry to dig out scientific facts while separating fertile from sterile analogies? In answer or just what that makes you think of? It makes me think of something which Edelman used to call me, which I am an intellectual thug. So I'm sure that there is a great answer to that excellent question. And it does speak to Edelman's skills and interests as a violinist. I do remember that BBC Horizon came to do a profile on him and his ideas. And it was prefaced with, I think shots of him playing the violin, to concert standard. But I have absolutely no idea whether he used that sort of part of his life to take things beyond metaphor. So as an intellectual thug, I'm going to hand over to my two colleagues to see if they can give a more elegant answer. Or anything in that area of the arts, and you brought up poetry, anything in the arts and sciences? Well, actually, I'm not a great biologist. I've just said that from my side of the interaction, he really tried to merge science and art. He would think a real science would be beautiful. And that's the way I think when I learned, as I mentioned, when I say, oh, I was expecting a more clear-cut CC's idea. But he would say, Ming, it's like writing a poetry. He said, when I start, I don't know where it's going to end. It's like some artists, when you ask them, how do you create this painting? I try to ask this question to some of my friends who are artists. And they say, they do not have a clear blueprint of how that painting would look like. They have an idea. It's kind of floating in the sky, and they try to grab it down. So they paint on the way, and try to make it into a painting. Or I have a friend who I poet. I ask them this. They say, they grab the word to make them come in town. And I kind of feel, Adam, I sort of treat the scientific idea like that. This is my superficial interaction. Yeah, just some experience. Well, I don't have a correct reply to that. But in general, I think there's the idea of creativity that he brought to the forefront. And then also, with that creativity, you have to have a certain amount of courage to move out of the mainstream. So if you have an idea, and you have to have a certain amount of courage to put that forward, if that idea is creative and out of the ordinary. And I think artists and sort of really great scientists have that in common. Maybe to that nexus of creativity and career development and courage, for you or just in the environment, how did his mentoring help bring out these threads in people for better and for worse? I think Carl could attest to that. I have a hard time viewing Edelman as a feel-good mentor. I think he would throw ideas out there. He could be pretty aggressive and I would say frightening to young people. So I wouldn't cast Edelman's behavior as sort of the typical mentor. But again, I think the environment that he created was someplace that was really special and reflected that kind of courageous creativity. And I really appreciate that now. Yeah, just to endorse that notion of courageous creativity. I think it's a really nice observation. I've often reflected on whether, let's take for example, Julio and Olaf. And I think you could probably apply it to me and Andy and a number of other people as well. But if we just take Julio and Olaf, who've both become world leaders, thought leaders in their own particular field, having brought something new to the table. And in some instances in more than one area, so Julio to know in terms of sleep research and synaptic homeostasis in terms of his work in consciousness studies, integrated information theory, Olaf in terms of structural function and connectomics. I mean, is it that Edelman had a good eye for bright young men? Or is it that bright young men learned how to do this, that this was the way to be courageous and to send us an adversarial in that courage to be creative and to pursue what you have created in a slightly adversarial or at least sort of defensive way. I'm not, I don't know, but what I do know is there was certainly a culture that was established that would allow those kinds of skills to be developed and is referred to them slightly obliquely. It was a dark culture. It was, and it has to be said, it was a very homophilic culture. There were no women allowed in this culture. So in my time, the culture was really one man and adoring young men and you had to repeatedly affirm that adoration and part of that was really useful and really enjoyable and as already mentioned, the lunches, the exactly the same regime characterised my stay. There was a rigorous routine where all the young men would go off to the New York cafe, would have onion rings and burgers and alem over to wax lyrical and perhaps this is not art and creativity, but he was artistic in his joke telling. So it would always have a new joke every lunchtime in a New York diner and that was a routine and it was just pure theatre day after day after day, incredible energy, but it was theatre. The young men were the audience and we basically, I think, were dancing to his orchestration. He was the conductor and he was the director. If that culture, if it's possible that that culture did actually instill in all of us and particularly Olaf and Julio the notion that to make it, to make a difference and to be true to one's convictions, you really have to fight for and be autonomously pursue what you want to do and it is interesting that the style in which both Julio and Olaf have pursued their scientific ideology and ideas and creativity is very much, it's slightly lonesome with the exception of Julio's work in the molecular biology of sleep. The theoretical contributions are very associated with them personally to a certain extent with me and what one could argue is the mathematical version of value-dependent learning which would be the free energy principle. All of these things have the same flavour as Neural Darwinism or as some people used to call it Neural Adelmanism. So I often ask that question, was this the skill of Adelman in choosing people who are going to make a difference or did he basically provide a culture in which it gave people the tools or the motivation or the confidence that you can make a difference because you saw him make a difference? I don't know. I think both of you actually said something, I share the experience. Definitely he set up a right environment but just like when we do same-cell, same-cell and it's niche. You need the interaction, you need the conversation between Epicephalia and mesenchymal cells or in the brain I heard it's more like interaction between Neural and Guriya cells. So a successful interaction would lead whatever the process to move forward but not every process would be successful. So as I said, I also like the way Kyle mentioned about Adelman is the conductor. He actually said that in our last meeting at the time, he said, I am the conductor, you guys are my symphony players and you play together, you can make a good music. But it's also true, not every interaction works because I was with him for almost eight years or so, not every person worked. Let's put that way, that's the fact. So some work, some don't. So I think people are given that opportunity and as Andrew said, it's a good outstanding environment. So you pick up the idea from Adelman, you develop yourself and some of them, you know, or what you can call it, Adelman, then we success in a certain way or not. But I think it's an exciting environment. I would put it that way. It's both, you know, he inspires you, he gives you a sort of exciting environment to evolve but not everyone he can choose everyone to be successful. No, it's not like that. But he did give you that opportunity to be successful and to pick up something. And he also gave you that courage to do it. As I mentioned, you know, people would normally think that, you know, using the feather as a model is kind of very, very high risk. But he has that encouragement that I do that. And I feel I really using feather as a Rosetta song, I have learned something for the morphogenesis, pattern formation field. Yeah. So I appreciate him on that. Yeah. And true. Or I can ask another question. I really don't have anything to add right now. Thank you, though. It's really amazing. It's such a different world. And the environment of learning and of carrying out science is so different. So personally, I really appreciate just even a window into settings that are elsewhere and in a different time. So thank you for all of this. All right. I'll ask another question from Dave. Professor Edelman was reputed to be skeptical about the risk of abusing mathematical or computer models in creating theories of neural functioning cognition and consciousness. Some reviewers went so far as to mock him in print for using computers as research tools. But he worked with Tanini on the foundations of integrated information theory, an extremely math heavy theory that sometimes explained using computing imagery. Did Edelman change his attitude towards the role of math or of computing paradigms and thinking about the mind? Or did he simply start trusting his colleagues to think computationally without falling into rabbit holes dug by Von Neumann and Turing? Or how did you see the role of math and computers in Edelman's thinking and research develop over a period where they were also undergoing such rapid developments more broadly? So I'm pretty sure that Edelman respected mathematics and computational approaches to neuroscience. There certainly were a lot of theory fellows that were computationally savvy while I was at the Institute. And so for instance, Carl mentioned these robots that were used to sort of explore and learn and sort of the beginning, I guess, of embodied cognition, Carl, you would say, where they explore the environment and learn. And then from that learning, they build internal models. So that is, I would say, and that was Olaf Spallywig. I would say that that was highly computational and certainly a major thrust in Edelman's emphasis and what he wanted to do at the Institute. And there were a number of other things. I think the integrated part that Julio did, I think that was almost all Julio's work along with some of the other computational fellows. So I think Edelman wanted to be part of that, but that really, I think, was mostly Julio's. And I think as part of the culture, Edelman managed to get his name on Julio's paper. We used to laugh about that quite a bit. But again, I would say that was 99% Julio's work. Yeah, I can come care because I was there when the work was actually done. There was a sort of period, I can't remember, there was some hypothesis that pertained to a core, a dynamical core as sort of oppressions are necessary for some kind of consciousness. And I think Edelman was comfortable with this sort of intuitive notion of a dynamic core. But when it became articulated in terms of information theory, he started, I think, even if he didn't say so out loud, he would have responded as he responded to me with, oh, you've got Mathematosis. So this is another of his ways of dealing with people who had a tendency to over-mathematicalize and oversimplify as a physicist toward reducing a horse to a point and then writing down differential equations. He was very allergic to that. He didn't like that and would call that an instance of Mathematosis. I think that's very distinct there from what Andy was just talking about, which is the commitment to physically realized, embodied computation. And I think it's a really well-abserved point that this was embodied cognition circa 1918, 1990. So he was quite visionary in, I think, sort of testing out ideas in physical and realized systems. You couldn't just hand away with maths. You had to show it worked. This idea worked in a real setting. And at that time they were at the Darwin series. To the extent that I, for example, had to spend six months learning to paralyze C in order to program the robot. So it wasn't he who was frightened of new technology or computer science. I think he didn't like trivializing things, you know, allophysicists with mathematics. But you would certainly be fully committed to the notion that computation is at the heart of the kind of dynamics that he wanted to understand and underwrote theory. And indeed, I think the theory of neural group selection speaks that he wanted to see it realized in a robot. But I think Andy's absolutely right at the point when Julia sort of just basically went straight from the axioms to consciousness and phi with equations. I think that was the time that Julia had to leave the family basically. And Julia did so. But extrapolated that a little bit more. I think, you know, when I read Edelman's books and some of his papers, I don't understand his words. Okay. And, you know, his phrases and his descriptions, you know, a lot of things don't make sense. If he had written those out or someone had written those out as equations, okay, you know, that's the nice thing about equations. Once you see the equation, you don't have to worry about the word so much. You know, things become pretty clear. And I think, you know, looking back, if he'd been able to do that, I think his ideas, first of all, would have been crystallized in his own mind better. And second of all, would have been able to be others would have understood them more clearly. And I think that's really important. If you have, for me, okay, maybe with an engineering background or something, you know, if you have a model or if you have an idea, if you can write that out explicitly with an equation, it really clarifies things, it crystallizes things. And that was the thing that I liked about Julia's work. Because again, this word of consciousness, you know, it's like, nobody knows what that really means. But at least Julia had a form of equations, right, where he was talking about information theory and the way, you know, you could have a cluster where information was internal versus the external information and say that, okay, if you have to have consciousness, here it is. And you could describe that with a concrete equation. I mean, that's a step forward. And again, I always say as someone that records neurons in the brain all the time, if I wanted to find consciousness, how would I know it if I found it? Right? I mean, if I had an equation, maybe I could do it. But, you know, just the way is defined right now. I mean, who knows, I could have already discovered it, I wouldn't know. So I think that's an interesting point anyway. I can't resist his follow up on that because especially evident for me in the remembered present, this notion that his words don't actually make any sense. I think that's pure poetry and pure brilliance. Because what I tend to find myself doing is reading the meaning into his ambiguous sentences and finding all sorts of meanings which wouldn't have occurred to me otherwise. I think that's part of his art. I suspect that he would have been terrified if somebody had actually come along and tried to time down to a clear, formal, naturalized, mathematical formalism. Because you wouldn't have had that sort of biotic expressiveness and ambiguity that of course is at the heart of his evolutionary thinking. But I think it's great and you're able to say you don't understand what he wrote. Because I look at some of his sentences that, what on earth is he trying to say here? And of course, but the exercise of trying to make sense of Adelman itself brings to the table some really interesting sort of associations and ideas. I'm wondering whether that was part of the secret of his success is that he resisted the temptation to be crystal clear and just left that mystical magical ambiguity hanging in the air for people like you and me to worry about and try to resolve. I suppose he's given that privilege after winning a Nobel Prize. I think some of us mere mortals wouldn't be afforded that luxury. All right, I'll read a few more questions. We can have a few more things. So small questions. In the book, Topo biology, Cheng Ming, did you draw the feathers or is that your work? The feather is my work. Yeah, it's based on my work. Yeah. Awesome. Well, how do we take things forward in science and in our work here in this level of the fractal with this amazing story and history with Edelman, but how do we take our historical and our mentoring context? Like how do you carry that forward? Is it something you think about? I personally do and I congratulate myself every day on not being like Edelman when it comes to mentoring. How so? I'm not going to answer the how so question, but you could read between the lines. Whether that's the right thing to do or not, I don't know. I don't think you could be Edelman now. In the 21st century, we'd be too close to all the culture wars, I think, to even entertain that style anymore. And I suspect that's quite a good thing. Although, you know, pressure makes diamonds. And as Andy says, it was an exciting, both my colleagues have said, it's an exciting informative time. It was a pressured time. It was a dark time for me in terms of the dynamics, the systemic, the personal interactions. But because it was pressured, it made diamonds. And so we may be throwing away the opportunity to make academic diamonds and be truly creative in terms of making things that endure like diamonds by not having that style of mentorship. But I don't think it will be even legal nowadays to be quite honest, to run a lab like Edelman. So again, I mean, I think that over the years, neuroscience, I don't know about the rest of science, but it's almost become sort of industrialized. So there's a method, you know, you as a young person, when you finally get your own job, you have to set out and if you're at a university environment, there's certain boxes you have to check off, you have to get a grant, you know, you have to get a certain number of papers, you have to get something in science or nature in order to get promoted. You know, there's these steps. And I think young people are so focused on moving through those steps at the point in their career where they're going to be the most creative and their minds are the most flexible and they can be the most productive. And, you know, I see that as a shame, actually, that they're not given this opportunity to be a little freer in the way they accomplish things. And then, you know, when they do accomplish a modicum of success, they rely on their past behavior. So instead of saying, okay, I had to go through that in order to get tenure. Now that I have tenure, I'm free and I can do something that I really want to do. That really doesn't happen because people get stuck in a rut. And I see that as really holding back progress in neuroscience. And that was kind of the cool thing about the Neuroscience Institute. For better or worse, we weren't allowed to go out and get our own grants. We had to rely on internal funds. But as a result, the only person we had to convince was Edelman in order to get funded. And to a certain extent, that allowed us to do things that were really creative. In hindsight, I think that was a mistake because financially, that was a doom for the Institute. There could have been a hybrid approach that would have been more productive. But then again, as Carl was saying, the investigators would have had to have more freedom to do that. And that was not exactly in the culture. Although I think I was an outlier because I maintained a separate lab. So I was somewhat inoculated from that. And that made it a lot more pleasant for me. But again, I see that in current neuroscience, it would be nice if people were willing to take more chances and be a little more creative instead of hoeing to the status quo. That would be, I think, what we need in order to move forward. Yeah. No, I think that in terms of the mentorship that Carl was talking about, I mean, certainly I have seen people do very well. But I also have the opportunity, sort of when I moved to Southern California, University of Southern California, to have some interaction with Dr. Seymour Benzer. And some of you probably know him. I mean, you would see actually, he is also very successful. But when he came out, he would always have his students surrounding him very kindly. I think that Edmund is brilliant, but it's kind of the sun. It's too bright. Sometimes people have to be distilled into the, as you say, academic diamond. That's interesting. So we also have seen some people, you know, didn't get along with him well. But still, I think there are many, many impacts here. He certainly has encouraged many people go different directions. And in terms of the academic, the academic future, right? I mean, I think you too are more talking about the neurobiology side. But on the morphogenesis side, I would also say he always emphasized the patterns. Thinking that the pattern is kind of the way nature, either biology, non-biology, they leave some some clue for us to figure out. And when I was there, I remember every time he talked about the visual columns. And we saw they have worked out. He got very excited. And in fact, I have one of my peers at that time was working on the visual columns of the class. But I think that paper, that work never really go out to be published. But anyway, on the more practical things, I work on the tissue patterns. And I feel that, you know, go, you mentioned about the topobiology. And I again, I think he coined the term and I think the term, I mean, I think it means a lot because I kind of, you know, eventually my career was trying to figure out these signaling molecules. Because at that time, people only talk about the signaling molecule are very, very important. But the idea of topobiology is that you even position these simply by positioning these signaling centers in a different topology, you can actually have a lot of consequence. So from there, and the signaling center can also have a different lifetime, the strength and the duration and the range they can influence. So by modulating, you know, he liked these terms too, modulating these signaling center, you can create a lot of regional differences. And up to now, as I say, from my own take, you know, but you look at it, right feather here, downy feather here, you know, the beautiful crown feather here, tail feather, but these are all from the same genome. So it actually is through the positioning of these different signaling center in a different way. And you basically have the same same ingredient, but you can play with them by topologically temporal space temporal and especially arrange them and to create a quite complex pattern. So, so I feel that in the tissue patterning morphogenesis side, I feel that, you know, his vision is great. And I, I think we still try to work out more about how these patterns are positioned. But I think that's sort of the direction in a more visualized topobiology aspect that we can appreciate. Awesome. Well, perhaps if each of you would like to give any closing thoughts. Yes, I'll just start, I'll just do it to echo your those last sentiments. I think everything that Adelman said or tried to say, depending whether you could understand him, I think he's absolutely right. And we're slowly discovering the truths we just heard about topobiology and the importance of patterns. And of course, if you speak to somebody like Mike Levin, he'd be talking about exactly the same thing. He'd use words like basal cognition and, you know, pattern formation. But I think that we're talking about the same, the same principles of biological self organization. You know, and Adelman, I didn't know about topobiology. But I do know, you know, there are other fundamental ideas that he just, you know, incidental to him, I am absolutely sure. I think notions of degeneracy in the neurosciences and psychology, you know, the notion of many to one structure function mappings, for example, these are fundamental ideas, which now are taken almost for granted in my world. But you sort of forget how much he actually contributed, or at least laid the seeds for and sometimes very explicitly. So it should be acknowledged, although he was as Mark Raeckel put it in his typically gentlemanly fashion, Adelman was a very complicated man. He was also very brilliant and is responsible, I think, for a lot of the direction of trouble and the intellectual growth, certainly my intellectual growth, but I would say also many aspects of our academic communities. Thank you, Carl. Perhaps Andrew. Oh, and then please continue. So I would say, you know, if there's anyone listening out there, there's something to be said about maybe looking back in ancient literature that goes back quite a bit and maybe seeing how some of these things came about and trying to put it together and see that, you know, there's this iteration that constantly takes place. People rediscover the same thing that's been discovered multiple times. And, you know, try to see how there is a status quo and the way science works. And then there is these outliers where there's sort of creative bubbles that come to fore. And I think it's interesting to think of Adelman and the things he did and the people that were associated with him in terms of sort of these disruptive, right, they call it disruptions. And how those disruptions may have consequences many years later. It's kind of interesting to take the long view. So I think it's maybe worthwhile thinking about this once in a while. And for young people out there to be encouraged to think off, to think out of the normal way of doing things once in a while. Try to foster your creativity and have the courage to go after some of those ideas. I think that's a take home message for me anyway. Yeah, I would say I always like, you know, all sort of, you know, influenced by his idea, saying that we should study the important question that have a general meaning. So I think that kind of idea, he said, look at the big picture. I remember when I was there, you talk like that, the big pictures. So that is where when he thinking about Darwinism, he would say, it's not only for the species evolution for the immunoglobulin chrono selection, he would push it to the brain theory. And for me, I work on the morphogenesis, I actually would come to realize that is also what happened at the tissue level. These cells are competing with each other to form that pattern. And then pattern is selected when there is a functional advantage, it will be stabilized. So I think the idea of saying, if we're going to do science, we ask big questions, ask for the generalization, I appreciate that. And certainly he is like how you want to call it, a huge elephant. So we all touch him through different side and have a different take on that. And in terms of the young scientist, I also remember he likes the Chinese proverb, I cited to him, let's say, if you want to get a tiger's son, you must get into tiger's cave. So we treat it. Thank you all. That's a great note. Really appreciate this conversation. And again, thanks until next time. Okay. Thank you. Bye. Nice meeting you all. And thank you for that. Thank you.