#903 Luis Favela - The Ecological Brain: Unifying the Sciences of Brain, Body, and Environment

00:00 Ricardo Lopes: Hello everybody. Welcome to a new episode of the Decent. I'm your host as always Ricard Loup. And today I'm joined for a second time by Doctor Luis Favela, associate Professor of Philosophy and Cognitive Sciences at the University of Central Florida. And today we're talking about his book, The Ecological Brain Unifying The Sciences of Brain, body and Environment. And by the way, I'm leaving a link to our first interview in the description box down below which is which to a certain extent is also relevant to the interview today. So Doctor Favela, welcome back to the show. It's always a pleasure to talk to you.

00:35 Luis Favela: Thank you Ricardo. I appreciate the invitation looking forward to it.

00:39 Ricardo Lopes: So I, I mean, the way I would like to go through things here today is that uh first of all, I would like to get into what ecological psychology and neuroscience are because those are the two main disciplines that you explore in the book and also the relationship between them and how they historically sort of came apart theoretically, methodologically and so on and then get into the framework that you bring into the book that you present there that perhaps can bring them back together and perhaps other aspects of our psychology. And so to start off with what is ecological psychology? Really?

01:22 Luis Favela: Yeah. So I think when, um, people hear the term ecological psychology, I think if they think of anything they think of, um, psychology related to the environment. And so commonly when I talk to people, they've said, oh, so you study, uh how productive people are depending on what color their room is. So if their room is painted red, then that means the ecology causes them to be angry and agitated. And I'm like, well, maybe, but that's not what we mean here in this case. So, uh when I say ecological psychology, I'm referring to a tradition and perceptual psychology uh that originates with James Gibson in the mid 20th century around the 19 fifties. Um And also with his uh spouse Eleanor Gibson, also around at the same time. So ecological psychology was a bit of a reaction to um the uh more popular um or increasingly popular approaches to perception uh around the mid 20th century. And so around that time, you had something called the cognitive revolution. And so the cognitive revolution was pushing back against uh behaviorist approaches. And so behaviorism in the late 18 hundreds, early 19 hundreds argued that um if there's anything to, to a mind or to be mental, really, what matters for a scientific study of that is what can be observed in behavior. And so the idea was we can try to explain even the most complex behaviors by things like a, a reflex or stimulus response uh rules um that an organism develops over its lifetime or even over eve evolutionary time scales, the cognitive revolution came along and said, well, that's, you know, kind of interesting and you can explain a lot of stuff that way, but there seems to be a lot of mental things happening that you can't explain just by looking at the environment and then the, the response that the organism has. And so Noam Chomsky has this famous pushback argument against behaviorism uh where he said, um the environment is too impoverished, it's too poor with information for uh example, language learning. So an infant that's starting to learn language, um even if it's exposed much of the day to his parents talking and family talking, that doesn't seem to be enough to account for the richness and the seemingly infinite combination of words that a human being learns how to use. And so Chomsky and others that came along later. So there must be some things that are already built into the mind. And so, yeah, maybe there's stimulus in the environment and then there are responses from the organism, but those responses are gonna be based on innate structures that are already in the brain. And so the launched a whole new paradigm, if you will a whole new way of doing psychology which said, we don't have to treat the inside of the organism like a black box, right? Where you have your input, some magic happens and then you get an output. No, we can start looking at those structures. And around that time also what became popular was uh computers. So the computational devices were becoming more and more popular. And people said, wow, you know, computers, they, they, they have these like internal rules and they can, you know, give them certain kind of inputs and they get really complex outputs and it seems like you can mix that up and almost infinite ways. And so that there was a marriage between these different approaches, um artificial intelligence at the time, linguistics and some other sub fields as well. And they came together and they said, well, then things like perception must also require some internal uh properties as well. And so you can't really explain something like detecting distance just based on the stimulus. Because for example, if you had a little tree that was up close to you or you had a big tree that was far away from you, if all that it requires for vision is the information and the environment. Well, the little tree and the big tree on the same line would cast the same image on your retinal cells. So you wouldn't be able to tell they would look the same spot. Thus, we must have certain rules in our mind that allows us to maybe take cues from the environment. Um uh We see things that maybe, maybe in the angles of shadows or something like that might tell us that something is further away than it is closer. So computers and the idea that you would represent the environment in your mind and then manipulate it computationally. This became the dominant way of doing things in the mid 20th century. Well, here comes ecological psychology, sorry for all the history, but you kind of need to know some of that to, to appreciate what Gibson was doing.

06:15 Ricardo Lopes: A and by the way, just to mention that in our first interview, we talked more extensively about computational representational approaches. So we if people want to go back there and watch that be that bit again because it provides even more con context, I guess to what we're talking about here. So,

06:36 Luis Favela: yeah, exactly. Yeah. Thank you, Ricardo. Um So Gibson said, well, um he was, he was actually he was a, a scientist uh in the army and in, in the US military. And he was um tasked with trying to help develop training better training methods for pilots because he said pilots, they were treating uh the environment like a Cartesian coordinate system where it's just abstract kind of space of three dimensions on an A season. So uh if you want to land your plane and survive, uh you want to think of yourself as one point in that coordinate system and then the landing field and the plane and another part of that coordinate system, and then you try and calculate that. Well, it turns out the pilots were really bad at learning to fly that way. So he said, well, what do pilots actually do when they land successfully? He said they actually pay attention to what the environment is doing in relation to themselves. And so he picked up on the notion of optic flow as something that guides uh the ability of pilots to land. And he said, maybe if we train the pilots to focus on optic flow, so that's when the environment is moving in your your space of vision. If we tell them focus on the optic flow of the runway, and we try and coordinate our sense of our body in relation to that optic flow, maybe people will land better and it turns out that it did, it worked out better for them to think of things in, in that sense instead of the abstract sense. So this is one of the early also approaches um that became known as embodied cognition or embodied mind, the idea that you get your sense of body or your app proprioception and your haptic senses as a way of gaining information about the world. And so what did Gibson then do from this simple lesson? He said, well, maybe, maybe the environment actually is rich with information, maybe um organisms don't represent the world in their minds as much as we think they do if at all, maybe what they do is they leverage things like optic flow or the ambient light in a room or things like that. And so how do we know that the little tree is up close and the big tree is further away? Well, we know that because of information in the environment like parallax, the parallax is what happens when something uh is up close. And if you're moving, it seems like it's moving faster. If something is far away and you're moving at the same speed, it seems like it's moving slower. So if you've been in a car or on a train and you look outside and you look down and you see the road moving really fast, but then you look at the distance and it looks like the mountains are barely moving at all. That's parallax. And that information is in the environment. It's nothing that's represented in the brain or in the mind. So Gibson launched this whole new approach to doing perceptual psychology based on the idea that the environment is not impoverished the way Chomsky and the cognitive revolution uh neuros or scientists said, but that we can actually use the environment to um inform even complex actions. And so from there, here's the last main bit from there, he developed the term uh affordances. And so I think uh this is a common term now outside of ecological psychology, roboticists, people in education, all sorts of different people in art design, they use the term afford it uh loosely what it means is opportunities to do things in the world. So when I see this cup in front of me with little paints of Nietzsche on it, it affords grasping if the features of the object and my body have a nice match, right? If the cup is too tiny for my fingers or if it's gigantic and I can't grab it, then it does not afford grasping. And so Gibson said, it's likely that any organism that is perceiving the world from a little ant to a grasshopper to a dog, to a chimp to a human is likely perceiving opportunities to do things in the world. And those opportunities are constrained by the organisms sense of its body. So it's embodiment and then information in the environment. So that's what ecological psychology in this case boils down to the idea of an organism, environment system that can act intelligently in the world based on embodiment and environmental or ecological information.

11:17 Ricardo Lopes: And so that's about ecological psychology. But then how does neuroscience get into the picture of what you explore in your book? Uh Perhaps, I mean, we have to go through some of the main historical developments here as well uh to then understand why it is that psychology uh or ecological psychology and neuroscience uh theoretically conceptually and methodologically, at least at first sight seem irreconcilable.

11:50 Luis Favela: Yeah. So the uh historical story that I try to tell uh in the book is one in which you've got multiple strands of research happening uh investigating mind in different ways. Um So there are people do perceptual psychology, for example, you know, there are gyps ecological psychology, cognitive psychologists and the like and so, neuroscience. Um uh AND again, this is just painting in broad strokes, right? So there's always gonna be exceptions and things like that. But painting in broad strokes, neuroscience is very much um what I'll call it a anatomical or physiological discipline. I was interested in what are the um the bodily constituents of the nervous system, right? What are, what are nerve cells? What are neurons? What are glial cells? How do they work? How do they act? And so fast forwarding a bit. How do those anatomical units connect to things like intelligent behavior or memory or problem solving? And so, as I try to tell in the book Neuroscience, especially things like Perceptual Neuroscience or cognitive neuroscience, things more concerned with um the type of phenomena that are studied in psychology, for example, um they inherited a lot of the uh theoretical approaches from the cognitive revolution. So the cognitive revolution sparked this approach which uh we call cognitive and cognitive is was the idea that cognition, uh intelligent behavior, perception, memory, um the control of movement, co-ordinated movement. All these things are essentially computational and representational in nature. And So as I mentioned a few minutes ago, the idea is that uh it's not just stimulus from the environment and response uh from whatever is happening in the body. And you don't need to pay attention to what's happening in the brain, right? The black box. But inside here are computations that are manipulating representations. So when I speak a language, I have representations of words and sounds, the computations organize those in certain ways that give me uh language comprehension, for example. So as I argue in the book, Neuroscience inherited this way of thinking about uh organisms as these brains or neurons or nervous systems that are conducting computations and they're manipulating representations of the world. And so when you think about a computer that manipulates bits like ones and zeros, right? So whenever you write a computer program, it's made up of strings of ones and zeros and certain kinds of ones and zeros give you a tiktok video or one gives you music or one gives you a game you're gonna play, it's all still ones and zeros. And so the idea was that neurons which were thought of as simple firing units. So they either fire or they don't. So they set off an action potential. Maybe theoretically speaking, neuroscientists are history club, maybe those spikes can be thought of as like a one. And when it's not spiking, it's like a zero and so taken together, you know, these millions and millions of spiking ones and zeros are like the millions and millions of zeros and ones in a computer. And so the brain must be a kind of computational device. So Neuroscience inherits this way of thinking about thinking uh thinking about nervous systems as essentially a kind of wet computer, right? It's not made out of silicon, like my macbook, but it's made out of, you know, cells and blood and water and proteins and all this kind of stuff. But essentially it's doing the same thing as a computer. Now. Where did the split come in between neuroscience and ecological psychology? Well, right from the beginning, right, from the start, there's a big split and the big split is that neuroscience inherits this view that the environment is too impoverished to provide a kind of information that can guide intelligent action, for example, whereas the ecological psychologist says the environment is rich with information which can guide intelligent behavior and action. And so right there from the start, you have one fundamental break that happens right there. The neuroscience test is put in uh their, their bets on the cognitive this theory and they're saying it's gonna be all about what's happening in the brain or the, or the, you know, cognitive system. The ecological psychologist is gonna say actually what's gonna happen is it's gonna be distributed throughout the body, which includes a brain, but mostly the overt kind of gross body and the environment itself. So they're coming at some of the same targets of investigation, like visual perception, for example, and they are coming from very different uh starting points and theoretical commitments. And so you see that at least since maybe the 19 seventies or so 19 eighties, that this big split between these two approaches and it would seem that they are irreconcilable. They're, they're in some ways, as I say in the book, in some ways, they are different worlds, right? For the ecological psychologist, the world is full of affordances and rich information that's real, right? For the neuroscientists, right? What's really real is what's happening in the mind which equals the brain. And so this is just very radical ways of, of approaching um doing the same kind of work.

17:31 Ricardo Lopes: And by the way related to those theoretical slash conceptual foundations that differ between ecological psychology and neuroscience, one of the things that you also explore in the book, in this case regarding neuroscience is that you talk about two different traditions in neuroscience. And uh I would like you to tell us about them and then perhaps explain why does it matter in the context of your book? So one of them is focused on biological features of neurons that is the Hodgkin Ley tradition. And the other one more on abstract features of neurons, the mccullough pits tradition. So what are those traditions really about in what ways do they differ? And why does it matter for your book specifically?

18:24 Luis Favela: Yeah, great, great um question. I'm glad you, you asked that. So, as I said, the earlier days of neuroscience that I presented in the book and this very broad sketches, it's very focused on anatomy uh and looking at what the anatomy itself is like. And so uh Hodgkin and Huxley did this pioneering work um in the, you know, mid 20th century where they created some of the earlier models of single neuron activity. And so they looked at uh squid neurons. Um uh SQUID was a a great case because their neurons and their axons were so big that they could actually feed them with uh very simple microscopes. They wouldn't need these like high powered electron microscope. So they could test the anatomy in a in a in a in a pretty broad, highly detailed way. And what they focused on was what are the contributions of different kind of molecular activity, calcium, uh things like that. Um And what's happening when the cell is acting in a way to say, make you know, the tentacle move or something like that. What they found was this is a very dynamic kind of activity, right? This is a temporal activity, right? So there's time before the neuron fires and there's build up and there's activity and and say the calcium channels and things like that in there and then it hits a certain point and then boom, you get the spike of activity and then it kind of dissipates and it's prepared for another spike, right? And so this was a very temporal kind of way of thinking about it. So earlier days of Neuroscience, some of the biggest achievements focused on the combination of anatomy and dynamics or time around the same period uh in history, you had some other pioneering work happening by a, a couple of um gentlemen mcculloch and Pitts and what they said was let's try and think about uh abstractly what's happening here. So how do we um reconceive the anatomy in mathematical terms, though not modeling the anatomy, not modeling the activity with mathematical tools, but thinking about what the anatomy is doing as calculating as a kind of mathematical kind of phenomenon. So they developed um some the earliest mathematical models of uh neural activity. So the mcculloch Pitts model um and they treated uh these models as simple on and off switches, right? So the the neural network as we come to talk about them today, neural network models, right? It's a collection of these ones and zeros or that these systems that are weighted, right? And it's all mathematical. And so this mcculloch hits of the quick little aside that work was foundational to um the popular kind of models that we see now known as like large language models. So chat GP T um all these different kinds of systems that are so popular and and and controversial in the news lately, these are all defendants of the mcculloch Pitts model which treated cognition and thinking as essentially kind of like a mathematical phenomenon. It's all about calculations. So you have these two traditions that were being practiced. And I think it's fair to say that the Macao Pits tradition which focused on the mathematics and the computations and the abstraction away from the anatomy. That's definitely the one that has become the most popular. Again. Look at the successes of neural network models like, you know, chat GP T and stuff like that for the purposes of the book. Though I point out that um and this is related to another paper that I wrote called the Dynamical Renaissance in Neuroscience is that while there has been a great popularity in the abstraction away from neurons and into developing these neural networks, there's also been a refocusing as well on the dynamics and the timing of neural systems. And so what we're seeing is more and more focus on uh nonlinear dynamics, things like that um as being essential to nervous systems. And so it's not just about like what calculations they're producing, which don't really matter, like how fast they go or how slow they go. It's just a number of steps and you can do the steps fast, you can do the steps slow, but you get the same output. But there's been a new appreciation for this earlier work which I call the Hot and Huxley tradition that says it's not just about the steps, but it's also about how fast they happen or how slow they happen. And so this renaissance of as I call it and I talk about in the book is that neuroscience is repaying attention to the dynamics of what's happening in cognitive systems, intelligence systems and perception. Um I forget if you had a, a another part of your question. Uh

23:21 Ricardo Lopes: No, no, but I, I actually want to ask you a follow up. So just to see if I understood it correctly, then these emphasis on abstract features of neurons actually something that in more recent times as lether or at least some people in the cognitive sciences, neuroscience and so on to a more uh dynamical systems approach to uh cognition, psychology and so on. Is that correct or?

23:53 Luis Favela: Well? So sometimes. So um if I understood the question correctly, are people who are focusing on the abstract computations of uh neural systems of cognitive systems? Are they now including dynamics? Um Sometimes they are but not always necessarily and ST as vice versa, people who focus on the dynamics are not focusing on the computational properties per se. So there is some overlap but not necessarily. So. Um Yeah.

24:27 Ricardo Lopes: Mhm No, I was just trying to really understand here and perhaps to some extent I was oversimplifying it, but I was uh since you mentioned the dynamical Renen in cognitive science and neuroscience, uh I was just wondering if really abstracting more from uh neurons for more from their biological features, not focusing too much on them would help moving beyond these. I don't know, perhaps brain centered approach and uh computational representational approach to uh cognition, neuroscience and so on.

25:09 Luis Favela: Well, it's interesting, I think um there's people who have used the same evidence to make different conclusions. So some people have argued that um you know, because nervous systems and take, you know, humans and other mammals um because what really matters to intelligence and perception and memory and all this stuff is the computations in the nervous system. It doesn't really matter. Um If it's in a mammal, it, it could be, you know, in a bird, it could be an insect, it could be in a computer, it could be, you know, I don't know, in a ghost made out of ectoplasm or something like that. I don't know. Whereas other people have said no, no, no, no, no. What the nervous system is doing is a spec you know, special kind of computation that's, you know, specific to, you know, brains and there's something very special about brains. Now where the dynamics come in that just adds another layer, right? Some people say, what's the computations and the dynamics that prove this, what's the computations and dynamics that prove that it's been really tough to, to say uh who's right and who's wrong in those debates? Mhm

26:20 Ricardo Lopes: Yeah. A actually, yeah. Now, now that you're mentioning that uh you're right. So sometimes when there's discussion surrounding uh uh the extent to which uh artificial intelligence, artificial intelligence systems can be or become humanlike, there's that idea that perhaps if it's uh just about computations, I mean, the same computations can be instantiated in silicon based uh cognitive systems as they are in carbon based cognitive systems. Right. Mhm. I guess.

26:56 Luis Favela: Yeah. Absolutely. Yeah. That's right.

27:00 Ricardo Lopes: So, but then, uh, we were talking about uh ecological psychology as well and the relationship or the lack thereof with ecological psychology and neuroscience. But then there's also ecological neuroscience. So what is it? And what's basically the theoretical background behind it?

27:23 Luis Favela: Yeah. So ecological neuroscience um is a term um used loosely, there's no official kind of discipline called ecological neuroscience. Ecological Neuroscience term used to refer to people who are attempting to try and bring together uh these seemingly disparate and irreconcilable approaches to understanding cognition and perception. So what they wanna do, they wanna see if the lessons from Gibson and ecological psychology can be uh integrated with uh what we know about the nervous system. And so you've got work um going back at least to the 19 eighties in which people are paying more attention uh by people. I mean, ecological psychologists are paying more attention to the contributions of the nervous system and brain to things like afford its perception. Now, iii I really need to stress um a couple of things here. So one is that Gibson um James Gibson and his spouse Eleanor Gibson, they were really pushing back against the dominant approach, the dominant approach that you just, you gotta look at the brain, the brain is awesome and computers are awesome. And we've got all this technology, we have put all this stuff together and that's where, you know, we're really gonna be explaining things and I think at least strategically, um you know, the Gibsons especially, you know, James Gibson and his work on perception was like, we're not even gonna really talk about the brain, right? We're not gonna really talk about that. Like, of course, you know, mammals, the chimpanzee has a brain, of course, it has a nervous system, of course, it controls movement with its nervous system and, and, and, and brain. But really what matters is that we need to really appreciate the role of the body and the role of the environment. And so, um by not talking about the brain and not emphasizing the nervous system, this led a uh uh a lot of people to think that uh ecological psychologists uh didn't believe in brains that they ignored brains that they thought maybe that they just didn't exist. Uh So, for example, um Daniel Dennett, the philosopher, cognitive scientist, uh he's get some quotes from some writings he did in the eighties uh where he said, you know, people like Gibson, they treat the brain as if it's a piece of wonder tissue it's, it's like it's magical. We don't even need to explain really how it works or that there's neurons. It doesn't, it's just, it's magical. It's a magical part of the body and it resonates magically with for ins and things like that. Other people like Carl Pribram also in the 19 eighties. Uh He has this other uh great quote and I say great cause it's, you know, it's something special. He says, uh you know, there are some ecological psychologists that acknowledge that there's a brain and nervous system. But for people like James Gibson, uh whether you know, there's really that stuff on the inside or just foam rubber, it makes no difference to their theory, right? And so you've got Dennett who thinks uh the Gibsons ecological psychologists are wowed by the magic of the brain. So they don't even want to touch it or talk about it. And you've got people like prem and other people who are like they, I just think that it doesn't even matter. You could, you could fill, you know, you could just, you know, scoop out all my brain and fill it with rubber and it wouldn't make any difference to my ability to perceive for since, right. So Gibson, an ecological psychologist had a really hard time uh with trying to explain things like perception without doing what everyone else was doing, which was talking about the brain and talking about complications. So, um I think that's really important to, to, to acknowledge that. So, ecological neuroscience was this attempt to say, hey, we have it as ecological psychologists really focused on the brain and specifically what the brain is doing. Um We don't think that it doesn't matter if it's a brain or foam rubber, like no, no brains matter, right? Brains matter. They're important. Are they computing like a computer? Are they representing the environment um in little pictures in the head? And that's how we control things like action and my ability to grab, you know, the avoidance of this cup. Is it really about computing and representing? No, it's not, but the brain is doing something. Let's see what it's doing. So, ecological psychologists were interested in trying to see what is the nervous system activity that is going along with things like hance perception and that was some of the early kind of ecological neuroscience work. Um I can leave it at that for now. Yeah.

32:15 Ricardo Lopes: Sure. So uh I, I think that we've already covered uh lots of theoretical and historical background here. Uh I want to get into the main thesis that you develop in your book. I guess that before that we just need to talk a little bit about complexity science here. We've already talked about ecological psychology and neuroscience, how they relate how they split historically and then also ecology, neuroscience and traditions in neuroscience. So perhaps uh that's enough about it if you have something else to add about it, please go ahead. But uh getting into complexity science, I mean, we've already again, talked a lot about it in our first interview. So I refer to it again. But what role does it play in the context of the thesis you develop in your book? Exactly.

33:12 Luis Favela: Yeah. So um I think historically, part of the problem with bringing together ecological psychology and neuroscience is that they just have very different ways of talking about the world and they have different methods and different tools that they use. So my thinking was what if we start bringing them together by applying a similar kind of investigative approach. Uh AAA similar set of concepts, a similar set of methods that both ecological psychologists and neuroscientists can both agree on and use and maybe that can be a way to bring them together. So to that end, um I thought that complexity science offered those concepts and those tools that are applicable to the very little. So the neurons in the brain, to the very big, just an organism acting in the world. And so um this is not anything especially unique to me because the fact is that if you look at the ecological psychology literature and you look at the neuroscience literature, there are people who have been trying to pull little bits from complexity science because it's such a broadly applicable set of tools. So complexity science is um made up of a lot of sub disciplines. But in short, it tends to include things like systems theory. Um So the idea from like cybernetics and things like that of the importance of feedback loops in systems. Uh It takes a lot from nonlinear dynamical systems theory. So these tools that have been developed to capture very complicated um types of temporal uh behaviors and systems, right? And so all these different kinds of of tools have come together into complexity science to allow you to say I'm gonna study what the neuron is doing while an organism is perceiving and afford it. And I can talk about the neuron and the body and the environment in very similar ways. I can use very similar tools. And that's the what the role of complexity science plays um in my approach.

35:33 Ricardo Lopes: And so tell us then about what you call in the book, the next framework that is the neuro ecological nexus theory framework. So what is it about? Exactly?

35:48 Luis Favela: Yeah. So the uh neuro ecological nexus theory is, you know, my attempt at synthesizing really the best of ecological psychology, the best of neuroscience and the tools and concepts from complexity science into a way in which we can understand the contributions, the nervous system to the body, to the environment and back all under one framework. So the uh the neuro part refers to the importance um of the nervous system in the brain. The ecological part refers to the importance of environmental or ecological information. The nexus part refers to the idea that we have to find some way to systematically connect, right, there's kind of a flow from brains into bodies into the environment. And back, we have to understand our task of understanding intelligent behavior and mind is to understand that nexus that flow between those different uh spatial and temporal scales. And coming up with a system that makes sense um that is, is, you know, have scientific virtues like simplicity and prediction and things like that. And so um this is a, a theory um or philosophy if you will about minds, but it's also supposed to be a scientific research program. And so, while it has these strong theoretical and philosophical approaches, you know, stuff from ecological psychology, complexity theory and things like that, it also offers testable hypotheses. And so the theory um uh is, do you want me to get into, can I explain uh briefly the the different hypotheses? Y yes, of course. Yes. OK, great. So um as a testable kind of science of mind, science of intelligent behavior, um next offers stick hypotheses which I'll go over briefly. And so the first hypothesis um is that the organism environment system is the privileged spatial temporal scale of description to understand mind. So we wanna understand what mind is. And I use mine loosely like refer to intelligent behavior which could include things like perception and action, but also you know, memory and problem solving if we wanna understand that really, we have to pay attention to the real time interactions going on in the body and the environment. So the environment will always be constraining the body, the body will always be kind of constraining the environment. So that's the first hypothesis. The second hypothesis is that when it comes to the contributions of the nervous system, the most significant contributions come from the neuralation dynamic. But when it comes to understanding coordinative behavior or problem solving really the action, so to say is coming from neuro populations. So it's not in single neurons, it's not in broad regions of the brain, but it's in the connection of populations of neurons. And so that's the significant target of population. The third hypothesis is that those neuro dynamics, uh what is really significant about them is their low dimensional activity. But there's always gonna be a lot of activity going on, we'll call that high dimensional activity. But when we sift through that high dimensional activity, we will zero in on actually a much more sim simple structure of dynamics that are driving the behavior. So the third hypothesis is to discover to reveal those low dimensional dynamics in the nervous system. The fourth hypothesis is that uh just like the brain of the nervous system um is most significantly about the low dimensional dynamics. So too is the body. So the body, uh this is again, hypothesis for the body is organized into low-dimensional synergy and so synergies are particular organizations of the body for purposes of intelligent behavior, for purposes of, you know, swinging a bat and hitting a ball or dribbling a football, right? The body organizes into certain synergies in order to perform those actions. And those synergies are essentially those low dimensional um kinds of coordinative aspects of the body. The fifth hypothesis is that mind again used very broadly, is it fundamentally emerges at low dimensional scale of these organism environment activities. So, although there's a lot of uh neural activity happening all over the place, although the body is constantly moving, although there's a lot going on in the environment, really intelligent behavior, mind perception problem. So all these things happen when all of that collapses into low-dimensional uh structures. And there's a coordinations between the low-dimensional structures of the brain, the low dimensional structure of the body and the low dimensional structure of the environment. And that's how we are best poised to understand the brain body and environment contribution to those activities. And so the final uh hypothesis is that the neuro ecological nexus theory explains those low dimensional structures in terms of a finite set of organizational principles. So there's not gonna be an infinite set of um rules that guide the organization of my body, but there will be a finite set of rules that guide the organization of my body, for example. So things like um critical states, criticality is one kind of rule or principle that guides a lot of different kinds of organization in the brain body and environment, essentially to kind of flesh it out a little bit. A critical state is when you have uh a lot of high dimensional activity that gets to a point where uh it is balanced between disorder and order. So it's organized enough to maintain a structure, but it's loose enough that it can adapt. And so we call that that comes from physics. And this is another key term in complexity science, a critical state. And so I think it's likely that neural activity, the body and the environment, they reach these critical states in order to achieve uh mind behavior activity and things like that. And so as hypotheses, I think these are all empirically testable, I think they all have to be theoretically reasonable. Um But they can also all be wrong. Uh If they were, if it wasn't possible for them to be wrong, it wouldn't be a science, it would just be a dogma and that's, that's not fun. Mhm

43:02 Ricardo Lopes: Yeah, that, that's all great. And by the way, I have a question saved for later on in our conversation about the main challenges to your proposal here. And we can come back to that. But I wanted to ask you at this point specifically when it comes to those hypothesis that you mentioned there and looking at the evidence across the different cognitive disciplines and so on at this point in time, at least, and I hope this is not uh too unfair of a question to ask at this point because you're just suggesting this theory in your book. But at this point in time, uh how much do you think uh uh how much support do you think they have scientifically, not only empirically but also uh how the uh how accepted they would be theoretically taking into account our current state of the art in the cognitive sciences and how much work and what sources of evidence would we need to draw from? To uh really demonstrate that it's potentially uh true or correct?

44:18 Luis Favela: Yeah. So um it is a fair question and I think in one way, um I think things are going in my favor and they're going in my favor because uh I can interpret a lot of research that has been done in ecological psychology in neuroscience through the lens of a neuro ecological nexus theory. So I can point out at research on network neuroscience that looks at critical states, I can look at affordances perception that's been modeled uh as synergies connected to, you know, self-organization and things like that, right. So I can, I can pull out these examples, right? And I can say, oh, so this is support for hypothesis one, this is support for this. The hard part though is um supporting the theory as a whole, right? So the tough part is gonna be running maybe an experiment that's gonna hit on all those different levels, all those different scales and that's gonna be really hard. So, how would I uh test the neuro ecological nexus theory? Uh AS a whole? Well, I would, I would have to have a subject come in. I would have to record from their brain. I would have to record from their body. I would have to record the environmental information. Oh, this is just gonna be a huge amount of data, right? It's gonna be enormous. I mean, look at, look at the brain, all this, you know, brain research that's been happening the last 10 years. Uh THE brain initiative, the human brain project, they received billions of dollars uh on the promise that in 10 years they would simulate a whole brain. Well, it didn't happen, right? It didn't happen because they started finding things like, well, there's actually not just a few kinds of neurons in the brain or a few kinds of cells. It's actually probably a couple of 1000 different kinds of cells just in the brain alone. So we might be kind of worse off than we thought we were. It might be much more complex than we thought it was. So what we ended up seeing was a lot of these approaches, they change their goal from, we're gonna simulate a whole brain to we're gonna develop ways to record data and share it with each other. So that's just the first step, right? So a way to, to handle all this data and, and, and making sense of it is gonna be a very big challenging part and that's just the brain alone and I wanna come along and say I wanna do that and the body and the environment, right? It can be really hard to do, at least in one kind of um straightforward, simple setup that's gonna hit on all of those hypotheses. What I'm gonna end up having to do is do each one individually and then build up a case and hopefully motivate that case. But again, each of the hypotheses are hypotheses and they can be proven wrong and it would require revising or undermining the whole project. Um But I think there's a reasonable shot that the hypotheses will turn out to be supported because there is other work as I point out in the book that supports each of the hypotheses on their own. Does that address the, the question? Uh Y

47:39 Ricardo Lopes: yes, but, but then uh a follow up to that since you mentioned the human brain project and all of that, uh when it comes to having a better understanding or ideally a complete understanding of how our human cognition works, our, how, how our psychology works. And of course, the human brain project is or is or was not just simply about cognition or anything like that, it was about the entirety of the human brain. And so I'm not sure what kinds of claims exactly people were making about how much of our psychology we could understand through it. But let's say that your theory is correct in comparison to something like the human brain project. If people were to apply it, to have a full understanding of our cognition, how much better of a prospect do you think your theory would be in comparison to just having a complete mapping of the human brain when it comes to understanding how cognition works?

48:51 Luis Favela: Yeah. So um I think uh here's my uh as, as they say, my hot take, um we will not be able to explain most things. We find interesting about cognition in mind by just looking at what the brain is doing. The brain is in some ways. It, it's the most, you know, people describe it, you know, in a cliche, it's the most complicated thing in the universe that we know about. Um But in, in other ways, it's not that interesting. It's just made up of cells that are the same as the cells, you know, in my stomach or on my arm or that used to be in my hair. Um It, you know, it's just the same kind of structure of those cells they communicate um in interesting ways. Uh THE communication, we see that kind of level of communication and things like like beehives and ant colonies uh in cities and the internet and stuff like that. So, there's nothing really Irle about it. That's particularly interesting. Um One of my um colleagues, uh Maor Mangala, he's a neuroscientist uh uh who's highly influenced by ecological psychology. And, and he often refers to one of his colleagues, Damien Kelty Steven, who describes the brain as a milkshake. And he says that uh the brain is more like a milkshake than it is like a computer. Uh MILKSHAKES are made up of fats and proteins and sugars. Brains are made up of fats and proteins and sugars. Uh COMPUTERS are nothing like that, right? And the swishing and swirling of, you know, the activity in the blood and the oxygen and all that stuff, it's more like a milkshake, right? And so my hot take is when it comes to understanding um you know, intelligence and memory and creativity and coordinations. Um IT'S gonna have to include an understanding of the body, it's gonna have to include an understanding of body's en environment. Um And I think that's something that um you know, Gibson was really focused on. He wasn't necessarily like anti neuroscience, right? But he was anti uh privileging the brain that the brain is just, it's like, you know, kind of like magic. Oh we worship the brain, right? And, and, and it's like we've got the little, you know, your little soul or your little homunculus sitting, you know, controlling everything and it's like, no, no, no, that's not happening, right? The brain is just an organ in the body that plays a role as the heart plays a role. Um YOU know, different things like that. Um I was very privileged to have um the eminent neuroscientist, uh Gary Bussi, um who's one of my heroes in neuroscience. He's um really emphasized, you know, dynamics and time and, and that feature of the brain. But he endorsed my book and, you know, one thing he said was, um we really need to understand the fact that the brain is just an organ, it's just an organ in the skull. Um And it, you know, you have to understand how it's situated in the body. And there's a, a, you know, a, a mutual kind of pathway between what the body does and the, you know, the brain does and it's not just about a top down kind of control. And so I think it's not my approach, you know, the neuro ecological nexus theory, I think something along those lines is gonna have to be true uh to explain even the most simple of cognitive or mental phenomenon. Um And one last little bit on, on my tirade, um a response to your question is we already kind of know that that project is gonna fail, not just um practically, right? So it's not like, OK, uh give us $10 billion over 10 years, we'll simulate a brain. OK? That didn't happen. Uh So it failed. No, no, even if it worked, I don't think it would have provided the kind of uh explanations or understanding we want because we've already done it with simpler organism. So we've basically already done the human brain project with uh little little tiny organism of the ce again worm, which only has about, I think it's like 307 neurons. And I mean, compare that to humans that have about, you know, I don't know what it is. 80 billion,

53:25 Ricardo Lopes: 80 86 billion, I think,

53:28 Luis Favela: yeah, 86 billion. That's just the neurons, right? So uh not mentioning the connections and the supporting cells like glia and stuff like that astrocytes, but we already know the full mapping and all the connections of a seal again and yet we can't predict its movements. We still don't have an ex full explanation about how it moves and coordinates its body. That's only 300 neurons. All right. And we can't do it with that. My thought is we can't do it with that because it's not just about the neurons, right? A full explanation of ac elegance, intelligent behavior is gonna require yes, the neurons, but also the body and the features of the environment and that's gonna be just as important.

54:17 Ricardo Lopes: Well, uh I I guess that things are not looking good for people who have brain centered approaches, but also not for uh those sort of transhumanists who would want to upload their brains to machines.

54:36 Luis Favela: Yeah, I mean, we can talk about that if you want. But I mean, my take is that that's not a real possibility. Um THE uploading of, of the mind um if there is any uploading, it won't be completely you. Um IT may be a feature of you but, but that's a whole other interview. I'll have to come back in a few months and then we can talk about transhumanism.

54:57 Ricardo Lopes: Yeah, I it was just me because II I have this sort of beef with some

55:02 Luis Favela: friends. You

55:04 Ricardo Lopes: don't take it too seriously. So, uh OK, so uh let me just think here. So we were talking about the ne next uh theory that you presented there and you also explained how it integrates ecological psychology, neuroscience and so on. So what is the ecological brain then? Really?

55:31 Luis Favela: Yeah. Um And it's like, as I was writing the book, I realized I was like already finishing the book and I said, I don't think I've explained what I even mean by the title and I think that happens too often. People have really cool title and then they, they don't explain it. I'm not saying mine's a cool title, but I didn't explain it. Um So in the end, um you know, II I mentioned it um in the concluding chapter, what is the ecological brain? Well, the ecological brain in short is the idea that a brain is always a part of an ecology, right? It's not this system, it's not this machine that you can understand it in isolation. It's not like I can explain, you know, I have my, you know, my phone, it's not like I have my phone and whether I'm sitting here in a nice temperature controlled room or I sit outside and it's warm or I go into a, um, a freezer that's storing meat and, and other kinds of foods, but it's still operating the same way. Right. The ecology doesn't matter really to my iphone to a certain degree, right? It gets too hot that it stops working. But, but the brain is always a part of ecology, the temperature of the body gravity, all these things are acting on the brain and the brain is also contributing to directing what ecology the body will be in. So if I am feeling really cold, right? And, and I'm sending information, you know, across my body into my brain and then my brain is now, you know, getting oh that I'm not feeling too good. You know, my brain might send out signals that says we need to change the ecology, right? We need to be in a different environment and those different environments are gonna affect what it does, right? And I think this is kind of the, you know, the point that uh Bussi was saying when he, you know, you know, endorsed, you know, my book is that the brain is always a part of these ecologies. The brain is not this isolated kind of system. And so to understand what the brain is doing, we have to understand that it is part of that interactive kind of system and, and to that and not to beat up on the uh transhumanists again. But um and to beat up on the human brain project, but that's what's kind of missing, right? Is this lack of appreciation of what actually should just be a really simple fact, right? Um So in short, what is the ecological brain? The ecological brain is the claim that like every other aspect of organisms, the brain too is situated and embedded in a certain kind of ecology and that's gonna affect its functioning and what it does. Mhm

58:07 Ricardo Lopes: By the way, I hope this is not a silly question. But since we're talking about ecology here, there's also an approach coming mostly from biology, but also nowadays, many anthropologists apply it or use it as a framework. There is behavioral ecology and then in the context of anthropology, human behavioral ecology that is people look at different aspects, different factors that differ across different ecologies and then try to understand uh in terms of our behavioral outputs our behavior. Uh IF there's regularities in terms of, if people are exposed to this or that technological factors, uh if there are some tendencies to uh develop societies with certain characteristics or they themselves as individuals behaving in certain ways, so does uh it connect or has any relationship to that in any way because I was trying to understand if, um, that aspect of biology could also play a role here or not.

59:19 Luis Favela: Yeah. Absolutely. I think it's definitely friendly at a minimum. It's friendly to those kinds of approaches. Um, WHAT you're talking about as well. I think, um, there might be some overlap with what I'm talking about, what you're talking about and then with something called developmental systems theory. And so developmental systems theory is its approach to biology and psychology and it's come to influence um even things like such as understand the criminal justice system um and things like that. But the idea is always that it's these whole systems that undergo change and adaptation. So it's uh I'm not what you're specifically referring to. I don't wanna say what I'm about to say, applies to that, but this applies to what I'm saying and what the developmental systems theorists say they are uh anti reductionist in the sense that um it's not just genes, for example, as maybe the most reductionist approach to biology, it's not just the gene that is uh driving um you know, um in organisms, uh th the, and it's not just the gene that is being acted on by selective pressures, but actually, it's the gene part of the organism, part of the environment, that whole system is what's being selected for. So, for example, um you know, when beavers, um you know, they have a certain kind of body. They exist in certain kind of environments. They build certain kinds of dams, their teeth work on both kinds of trees and wood in that area. If those beaver families survive, it's because it's the whole system that survived. It's the, the fur, the tail, the teeth, the wood, the water, all of that is a developing system over time. And so it wouldn't make sense to just focus on what is, what are the genes doing, right? Put those same genes, you know, in a different body or put those beavers in a different environment and they might not be selected for or they might be selected for. The point is, is that it takes this whole entire kind of system to be selected for. Is that what you're, does this fit with what this behavioral kind of and the anthropological stuff you're talking about?

1:01:39 Ricardo Lopes: Yes. And I guess that perhaps one of the things you were alluding to there, I'm not sure if directly or not when you mentioned the example of the beaver disease, uh niche construction as well or

1:01:53 Luis Favela: not. Yeah, absolutely. Um I think even people who were the most, uh and I use, you know, scare quotes again, the most reductionist about biology, I think even they, um, you know, you push them enough and they'll say it can't possibly be just the genes. So even so Richard Dawkins was one of the big proponents of the gene centric approach. He also had a book called The Extended Phenotype, right? And he talks about how, you know, these behavioral things that happen in the world, the use of wood and the environment and stuff like that. He'd like to frame it in terms of extensions of the genes. I would just, I actually, I, you know, I'm reading the same thing that he's saying and I come to different conclusions. It makes me think that gene is less important. But, you know, that's uh the biologist. Uh

1:02:41 Ricardo Lopes: Sure. So um I, I mentioned this question earlier, but what would you say are perhaps some of the main challenges to your ees to your next uh framework?

1:02:58 Luis Favela: Yeah. So there's uh there's challenges across the board, right? So, um you know, conceptually, right, um when I say mind, what do I mean by mind? Um DO I also mean consciousness, do I just mean problem solving? Do I mean perception action, right? And these things are all debatable, right? So um some people argue that perception of action is not mind, right? It's not cognition, it's something quite distinct, it's something that's more like me. You know, again, I like using these quotes. It's more like mere reflex, right? Whereas cognition is it allows you to make decisions and intervene on mere reflexes. So, so I've, I've already got challenges conceptually, right? Method of logically, how do I put these things in practice? I talked about that a few minutes ago, right? If the human brain project with billions of dollars in time and thousands of scientists couldn't come up with a full simulation of just the brain. How am I gonna basically try and do uh an afforded simulation from brain body and environment? That's methodologically, that's gonna be very challenging and then theoretically right do and this overlaps with, you know, concepts as well, but are affordances something that need to take the nervous system into account? Um Am I missing the, the whole point of what Gibson was saying? Uh THIS is, you know, kind of push back. I've gotten from some ecological psychologist, right. Affordances only exist in the environment and the organism and where they meet and if you go too low into the brain, then you're missing it. If you go too high, then you're out of the system, right? That's a theoretical issue. So I, I think I am open to being, you know, attacked and criticized in those three ways. But in particular, I think um I face criticisms both from people who I think would be friendly um to ecological psychology. But I also faced criticisms from people who are against ecological psychology. So people who are friendly might be an activist. So an active cognition or an activism is um a kind of popular approach to understanding what it is to be an intelligent living organism. And sometimes there's some overlap with what ecological psychologists say, but not always. And so there's that approach. Why not do um why not call my book, The Inactivate Brain, right? They might wanna say that and that they'd say that's better than the ecological brain. Maybe I'd have to argue with them about that. Right? Then I also need to argue against people who are against ecological psychology and people who are proponents of computational representational approaches, proponents of mechanistic approaches, proponents of reductionism, right? My book uh as I say towards the end, uh I say something along the lines of you might have noticed that I didn't explain anything. I didn't describe anything about my approach with computing, representing, I didn't describe any mechanisms and I didn't reduce anything. And for some people, if you miss, if you're missing out on some of these and you're just not doing science, right? If you're not providing a mechanistic account, whatever that is, we could talk about that also. But if you're not giving a mechanistic account, then you're not giving an explanation. So I'm pushing back, it's just, it's a different way of doing science also that is pushing back against, you know, more reductionist approaches. Um PUSHING back against mechanistic approaches and then pushing back against, you know, the apparent richness of the computer metaphor and a representational approaches. So I, I've got, I've got, I've got a line of people, they, they, they're taking their number and they're, they're ready to come in and get me.

1:06:55 Ricardo Lopes: So I have two questions. One about one specific thing that you mentioned there and a follow up to the challenges here. So you mentioned uh mechanistic explanations there and you that many people would be dismissive of your framework if it doesn't provide, provide them with the mechanistic explanation for whatever aspect of human cognition we're studying here. I guess. So um I mean, what is a mechanistic explanation exactly, particularly for the people who might not be familiar with this kind of terminology? And what would be, let's say in this case, a non mechanistic explanation?

1:07:44 Luis Favela: Yeah, good, good. So this is a very big issue and um the philosophy of science. Um And uh I actually, I think it's a big issue in science, the life science for practicing scientists, they should think about this. Um So the mechanistic approach um historically goes back to Newton and Descartes where they um were thinking about say the solar system as a kind of machine, right? Uh PLANETS that are kind of, you know, moving around in a certain way, right? Almost like pivoting on a kind of central piece which is the sun. Uh And then the body of des Cartes who's famous for his dualism, his mind, body, dualism. He still was a great anatomist and he spent a lot of his time studying the structures of the body and he thought the body was very much like a like a mechanical system. So for example, uh if I had my hand, if I were to open up my forearm, you'd see all these like tendons. And if I were to pull one, my finger would move, right? He said this is like it's a machine, right? We are living machines, fast forward a few 100 years. And um the mechanistic approach in the late nineties, early two thousands in the philosophy of science, there was a group of philosophers who said, what do scientists do when they try to explain something in the life sciences, when they're trying to explain a cell or an organism or an environment or something like that, how do they explain digestion or memory or whatever? And these, and these people said, well, what they do is they, they try to isolate as much as possible, their target, they try to break it apart, they try to understand the contributions of the parts and then they try to understand what they do together. And so you have a mechanism when you can say this is the phenomenon, be it, you know, memory like long term potentiation or digestion or whatever. And here's the starting point, here's what each of the parts do. And here's the ending point. Now you got a memory. Now you have digested food. Now you have a new baby, right? Um And so this was, this is a very general sense in which you have a mechanism. The problem that the mechanist quickly um realized was you can't always break things apart and give an understanding of them outside of their context, right? If you have say, um, you know, uh a toilet and the toilet has, you know, a handle and the handle lifts, the little thing on the inside which lets the water run. And if you wanna unders, if you want to describe the mechanism of how a toilet flushes that handle is always just a handle, that flapper is always just a flapper. The seat is always just a seat and you just add them together. But pretty much most things actually in nature are not like that, pretty much things always require a context and their capacities require the situation, understanding the situation that they're in. And so this mechanistic approach um had some problems and required some modification. So people started including descriptions of things as being decomposable. So coming apart uh non decomposable. So systems that um only work when they are a complete whole and then you also have descriptions of nearly decomposable systems. So systems where you could kind of maybe get an idea of what the parts are contributing. Uh YOU know, things like that. This has been of the most popular um way of understanding explanation in the life sciences and philosophy of science. And it, it I think it tracks well with what scientists, especially like neuroscientists and biologists are doing. So what would be a non mechanistic approach? Well, a non mes mechanistic approach to explanation could be something like a mathematical description. Um Einstein's equation uh Newton's um differential equations of the solar system, these types of things are not mechanistic, they have variables in the equations that refer to real things in the world. But when you are trying to understand how those things interact, you're paying more attention to the relationship of variables than you are as opposed to the specifics. Uh So you kind of, you're abstracting away a bit. Uh So that's one example of a non mechanistic um approach. Um Yeah. Do,

1:12:25 Ricardo Lopes: do you think that in this particular case, if we would have a mathematical explanation, perhaps one of the reasons why maybe I don't know, psychologists and neuroscience, neuroscientists, uh I mean, at least a big number of them wouldn't be too fond of uh an approach based also on complexity theory because I don't know, perhaps the mathematics there is a little bit too complicated for most people. I mean, I, I'm not trying to claim that pe people from those disciplines can't learn it. It's just that perhaps they are not used to that level of mathematics. I don't know,

1:13:12 Luis Favela: I think it's an excellent point. Um And, and I think, you know, now we're, now we're psychologizing our scientists, right? We're trying to, and this might require um its own kind of study, right? The nature of, of, of scientists and what they, they prefer, you know, we could say again, broadly speaking, um people go into physics because they want to understand the general principles of how things are organized, right? They wanna understand um you know, entropy, you know, of, of, of the particles in a container. But they don't really care about the specific particle. But someone might be interested in doing chemistry because they care about the specific chemical structure, but they care about biology because they care about identifying the specific cells and the organs and how those things come together. And so there might be a tension here where someone who's more, you know, quote unquote physics minded might say, oh, you biologist, you care about all those methods, details. But what are you really telling us? That's interesting. Similarly, the biologists you know, might be looking at the physicist and saying all you're giving me is all this crazy math and you haven't really told me how anything actually worked, right? It's like taking a car, right? Do we wanna understand how combustion works or do we want to understand how the parts fit together? Well, I think these are different kinds of temperament, but my bet is that when it comes to understanding mind, cognition, perception, memory, all this kind of stuff, right? That these emerge, these these properties, these abilities emerge from highly complex systems, highly complicated systems with many degrees of freedom, right? And keeping track of all those is gonna be really difficult. And in that sense, I think going the more kind of physics route where you don't care about the location of every particle inside the container, but you care about general kind of patterns of behavior. I think that's gonna give us more scientific virtue like uh manipulation, prediction, things like that with that sound is the physics approach gonna develop any medication. Is the physics approach gonna help, you know, cure cancer? II, I think it could contribute to it. But I think in, in that way, the kind of, you know, medical approach, the anatomical approach, I think that's gonna benefit uh from having someone who's more uh biological mechanistic minded, who wants to focus on the the wet sticky detail, right? But as we're seeing, I think there's, you know, a co evolution of the two to help us understand mine, it's gonna take both approaches, but I lean towards my intuition is that it leans more towards the physics kinds of stuff.

1:16:07 Ricardo Lopes: So let me ask you one last question then still related to the challenges to your proposal. Because I mean, I guess that one of the main things that you pointed to here is the fact that you would have to convince many different kinds of people from the different disciplines, different theoretical frameworks and so on. So do you think that perhaps one of the challenges here and it, it's not only to your framework or to convincing other people that potentially your framework is correct, but also perhaps a broader question that applies to the to your book in general also to perhaps understanding why it is that different disciplines, even though they might be focusing on similar objects of study might diverge so much historically. Do you think that has anything to do with how difficult it is to have interdisciplinary in academia and the university context? Because people are trained in specific areas, specific domains with specific theoretical approaches, methodologies and so on. And of course, then they have their careers and it's based on the kinds of things they have been working with the frameworks they have been applying. And of course, it's also uh many times extremely difficult for people to acquire enough knowledge, enough competence about other disciplines and methodologies and frameworks. So do you think that perhaps uh in the context of your book in general? Um THIS is uh something that we need, we need to take into account and perhaps presents a big obstacle here.

1:18:03 Luis Favela: I think it's an excellent point. Um I wish I had asked you to ask me this question because it, it's it, it is such an excellent point. Um You know, the, the way that yeah, the way that knowledge acquisition happens, um you know, in, in our systems and our culture is to have this kind of, you know, siloed, you know, discipline, you have a, you know, you have your Department of Physics, your Department of Chemistry, you know, et cetera, et cetera, et cetera. Um And for good reason, right. Because you can only do so much. So, I'm, I'm kind of repeating a little bit what you're saying in agreement, right? You can only get, you know, you get your ph getting one phd is hard enough, right? And then getting good at it is a whole other level, right? And making contributions and pushing the field forward, whatever the field it is, it's literature, history, economics, physics, right. Getting good enough because there's so we know so much, we have so much information that we have to deal with just within one discipline alone. Um How are we supposed to engage with these really complicated difficult topics like mine, cognition, intelligence. Well, one thing is to say um the discipline that I do, that's the right discipline and right. So I'm a neuroscientist and I care about biochemistry and that's how you're gonna do it, right? That's one way to approach it. And you say everyone else is wrong, another way to approach it is to say I'm a neuroscientist. I care about the biochemistry, but I know I need to talk to other people who do other things and I need to make connections and you know, to see how we connect in that way to give a more complete account, more complete explanation. But when is that supposed to happen? When does that conversation happen? Not in the journals? Right? In the journals, they just publish very specific kind of issues, right? Very very limited, right? You look at a neuroscience journal and they, they say, well, we are now looking at molecule X that's an AX on receptor 32. And this, and I spend my whole career, you know, doing that. Well, what does that have to do with cognition? If anything? Right? I, I don't know, but someone needs to be talking about this. Uh AND, and, and trying to bring these things together, the establishment um doesn't reward that kind of work, right? Whenever you publish in the top journals, you're usually very focused. When you get grant money, it's to, to look at very specific kinds of issues where you already kind of know how the problem is gonna be solved. You kind of, you end up especially in the US institutions with, with grant funding, you kind of have to already have succeeded in your project in order to get the money. Um AND, and, and so where's the risk and where's the interdisciplinary when it's other people who are very specific and focused, who are making the the decisions about whether your grant gets funded or your paper gets published. So the system itself makes it very difficult to um embrace these multi scale kinds of approaches. Um As I think my approach is, I think sometimes this is the luxury of being a philosopher is um I get to kind of, you know, I get, I get to dabble in these different areas, right? Um But I also thought at least personally, if I want to explain or at least engage with the sciences of the things I'm interested in like cognition or intelligence, I think I should have had some training to see what these scientists do. And so I have, I have training in experimental psychology and neuroscience because I wanted to see kind of what the philosophers are saying. And if it makes any sense, I wanted to see what the neuroscientists are doing that the philosophers are right or wrong about, but it's been really hard to do. Um And not everyone wants to do that. Um NOR should they uh you end up getting more successful if you focus on a limited range of things and get really good at that. So, yeah, I think interdisciplinary, I think um the way the system is set up of reward in academia and things like that, I think that's definitely poses a challenge to providing a multidisciplinary multis scale account of very complicated phenomenon. Mhm

1:22:32 Ricardo Lopes: You know, one of the reasons why I asked you that question is that, I mean, perhaps uh I have a privileged position because I'm able to do this full time. And I talk, I get to talk with people from many, many different disciplines, mostly the psychological, behavioral evolutionary sciences, but also from other areas. And I mean, I understand it's perfectly understandable that people of course cannot learn all of these and neither can I, I mean, I only know tiny bits of uh everything, let's say. But, um, I mean, it's perfectly understandable. But on the other hand, sometimes I see a lot of people from this different disciplines dealing with the same subjects talking past each other just because they are not versed on what the other people, what the other person is working on. The kinds of theoretical approaches. They have the kinds of methodologies, they apply uh concepts and so on and, and, and sometimes it's really, it, it can become really frustrating to see that perhaps people are clinging so much to their own. I don't know, pet theories or pet methodologies or their own uh preferred frameworks. And just very, and perhaps this is the part that frustrates me the most just easily dismiss uh some other things that or, or other approaches that other people have and many times it's because they don't even have a good enough understanding of what the, the other people are coming from because again, they don't have enough knowledge about it. I mean, ii, I don't know if you agree with what I'm saying here or if you, we and the criticisms of it.

1:24:33 Luis Favela: No, I agree. And I'll take you one step further and here's another hot take. I think a lot of scientists um don't even really understand the commitments of their own discipline. And I say that as a matter of fact, not as a value judgment because there is no need to question uh the commitments, right? Um So Thomas Coon, uh historian, philosopher of science, he talks about normal science. Normal Science is when you have a community of people who speak the same language, right? So maybe we'll take a biologist, they kind of understand what a gene is, what a cell is. Uh They have shared methods like, you know, basic statistical analysis. They all understand that they all, you know, read the same journals, they all um teach the same textbooks, right? They all have an idea of what experiments should look like and what an answer should look like. And this is just normal everyday kind of science. They don't have to question whether a gene really is exist or whether, you know, what is a spell or what, you know, are these statistical methods found? They don't have to uh and they probably as a discipline would be worse off if they paid attention to that, they can make a lot of progress by just accepting the paradigm, right? The problem though is when you start hitting, you know, at least what Thomas Coon said, you start hitting anomalies like, right? Too many things that you can't explain or when things get too messy, that's when scientists are questioning their paradigm. And so I totally understand and I totally respect uh the, the day to day scientist who doesn't have to question the foundation and they don't have to pay attention to anybody else. Um But if you have that, that tendency, if you have that personality, that questions things, um it's very easy to find what people don't know about even their own discipline.

1:26:35 Ricardo Lopes: OK, great. So perhaps this is a good point to wrap up the interview. And the book is again the ecological brain unifying the sciences of brain, body and environment. I'm leaving a link to it in the description box of the interview. And Doctor Favela, apart from the book, would you like to tell people again, where can, where they can find you and your work on the internet?

1:26:59 Luis Favela: Yeah, so you can um you can find me. Um My website is a little bit um The link is a little bit long. Um But I'll ask Ricardo to post it, but it's uh Luis H Favela one word dot Wix site, Wix si te.com/luis H Favela. Um If you go there, you, you can get links to my papers and see what's, what's going on. What I'm up to. Um You can feel free to email me um at Luis dot fella at ucf.edu that's also um on the website as well. Um But yeah, and you can pick up the book at any, any seller, books, Barnes and Nobles Amazon. Um Yeah, glad to be here. We're uh happy uh to talk about this stuff.

1:27:49 Ricardo Lopes: No, it's always a pleasure to have everyone. Doctor Fave and I really love the book. So I really hope that uh people from the audience also buy it and read it. It's a very interesting read. And thank you so much again for coming on the show. And I really hope to have another chance of talking with you somewhere in the future. So that'd

1:28:10 Luis Favela: be great. Thank you, Ricardo.

1:28:12 Ricardo Lopes: Hi guys. Thank you for watching this interview. Until the end. If you liked it, please share it. Leave a like and hit the subscription button. The show is brought to you by N Lights learning and development. Then differently check the website at N lights.com and also please consider supporting the show on Patreon or paypal. I would also like to give a huge thank you to my main patrons and paypal supporters, Perera Larson, Jerry Muller and Frederick Suno Bernard Seche O of Alex Adam Castle Matthew Whitting B no wolf, Tim Ho Erica LJ Connors Philip Forrest Connelly. Then the Met Robert Wine in NAI Z Mark Nevs calling in Holbrook Field, Governor Mikel Stormer Samuel Andre Francis for Agns Ferger, Ken Herz and Lain Jung Y and the K Hes Mark Smith Jungle. Tom Hummel s friends, David W and the desario Roman Roach Diego and Jan Punter Romani Charlotte Bli Nicole Barba, Adam Hunt, Pavlo Stassi, Nale Me, Gary G Alman, Samo Zal Ari and Ye Polton John Barboza, Julian Price Edward Hall, Eden Broner Douglas Fry Franca Gilon Cortez or Solis, Scott Zachary FW Daniel Friedman, William Buckner, Paul Giorgino Luke Loki, Georgio, Theophano Chris. Williams and Peter Wo David Williams Di Costa Anton Erickson Charles Murray, Alex Chao, Marie Martinez, Coralie Chevalier, Bangalore Fist Larry Dey junior, Old Einon Starry Michael Bailey. Then Spur by Robert Grassy Zorn, Jeff mcmahon, Jake Zul Barnabas Radis Mark Temple, Thomas Dvor Luke Neeson Chris to Kimberley Johnson, Benjamin Gilbert Jessica. No, Linda Brendan Nicholas Carlson Ismael Bensley Man George Katis Valentine Steinman, Perlis Kate Van Goler, Alexander Abert Liam Dan Biar Masoud Ali Mohammadi Perpendicular J Ner Urla. Good enough, Gregory Hastings David Pins of Sean Nelson, Mike Levin and Jos Net. A special thanks to my producers is our web, Jim Frank Luca Stina, Tom Vig and Bernard N Cortes Dixon Benedikt Muller Thomas Trumble, Catherine and Patrick Tobin, John Carl, Negro, Nick Ortiz and Nick Golden. And to my executive producers, Matthew Lavender, Si Adrian Bogdan Knits and Rosie. Thank you for all.