Complex Systems Science Applied to the Study of Brain and Mind with Michael Mannino
In this episode, Michael Mannino discusses ‘embodied cognition,’ the idea that the mind is not only connected to the body, but that the body influences the mind. His work explores the notion that who you are (your cognitive processes like perception, attention, memory, decision making, reason) has a lot to do with the body and how you move it.
In This Episode We Discussed:
- Why studying the brain is different than studying a computer
- How brain and mind affect each other
- The relationship between movement and cognition
2:24 Intro to complexity science
12:23 What is reductionism?
16:27 brain as complex system
21:30 brain is NOT like a computer
43:28 why reductionism doesn’t work for complex systems
45:00 neurophilosophy - brain & consciousness
46:50 complex systems approach to understanding relationship between mind and brain
50:58 definition of a nonlinear dynamic system
1:02:52 how movement/fitness affects the mind
1:15:05 Zingup.com brain training
1:17:57 Learning and brain development
1:25.00 Types of fitness for brain development
Mentioned in This Episode:
- J.A. Scott Kelso
- The Complementary Nature - Scott Kelso
- Dynamic Patterns - Scott Kelso
- Dynamics of Complex Systems - Yaneer Bar-yam
- Making Things Work - Yaneer Bar-yam
- Santa Fe Institute
- Science and Complexity - Warren Weaver
- More is Different - P.W. Anderson
- De Broglie-Bohm theory
- Sam Harris - Waking Up
- The Embodied Mind - Francisco Varela
- Metaphors We Live By - George Lakoff
- Christof Koch
- Orch OR theory
- Paul Churchland & Patricia Churchland - neurophilosophy
- Center for Complex Systems and Brain Sciences
- The Mathematics of Marriage: Dynamic Nonlinear Models - John M. Gottman
- Self-directed neuroplasticity
- What is Life? - Erwin Schrödinger
- Quantum Questions: Mystical Writings of the World’s Greatest Physicists - Ken Wilber
- Hard Problem of Consciousness
- Ido Portal - movement culture
- Animal Flow - Mike Fitch
- Evolve Move Play - Rafe Kelley
- MoveNat - Erwan Le Corre
- EmbodiedFit - Michael Mannino
Full Episode Transcript:
Daniel Schmachtenberger: Welcome to the Neurohacker Collective Podcast, Collective Insights. My name is Daniel Schmachtenberger. I'm with Research and Development here at Neurohacker Collective. We are really happy to have a good friend of ours, Michael Mannino here with us today. [00:00:30] Michael's area of research are directly related to our approach and philosophy and epistemology here at Neurohacker. He works in Complex Systems Neuroscience.
So he's just weeks away from finishing his dissertation at the Center for Complex Systems in Brain Science, and has been for quite sometime, a professor of philosophy, critical thinking, philosophy of mind, etc. [00:01:00] philosophy of economics. He also happens to be a biohacker personally and teach on the topics of embodied cognition and how working with the body as a whole is related to optimizing the mind. So we're really delighted to meet Michael. We're happy to have him here on the show and share some of his research and insights on complexity in the brain.
Michael Mannino: Thanks for having me, Daniel. It's a pleasure to be here. I'm honored that you would have me in this podcast. I'm looking forward to our [00:01:30] conversation. So thanks once again.
Daniel Schmachtenberger: So let's dive in and some of the listeners here at Neurohacker have heard me talk about why we need a complex system science approach to medicine, and to psychiatry, to psychopharmacology, etc. and why modeling human as a complex system is important as opposed to a reductionist approach to medicine. But we haven't really talked [00:02:00] at much length about what that means for those who aren't familiar. I think most of the audience will be interested because these are very powerful tools for understanding but not familiar. So what is complexity science? How is it different than just saying science? Why is it relevant at all in any system and particularly, in human systems?
Michael Mannino: So I myself haven't heard [00:02:30] of complex systems or complexity science since I started my PhD. So it was actually something new to me. I was looking to get into cognitive neuroscience but I found the complex systems program. So I was introduced to it then. As a field, it's actually quite recent. It's about I'd say 20, 25, 30 years old. So I'm giving some kind of meta, broader definitions or descriptions of complex systems right now. So it's a new [00:03:00] field. There's no unified consensus I would say right now in complex systems itself, you have different people studying different aspects of it. We're still figuring out what it means and how to approach it methodologically and conceptually.
So I mean, you have different people like Scott Kelso who's written the Complementary Nature and Dynamical Patterns which have become classic texts in complexity science. But then you have Yaneer Bar-Yam [00:03:30] of the New England Complex Systems Institute who wrote Dynamics of Complex Systems and Making Things Work which I have the book right here. This is an excellent classic texts I would say here at, which is becoming a classic text for complexity science. More than that, you also have a bunch of institutes and centers now opening in all different kinds of universities and think-tanks which you didn't have even probably [00:04:00] like ten years ago.
I mean, Santa Fe Institute is literally one of the biggest ones and has been for a while. I would think that there are some similarities and differences with science versus complexity science. So one of the similarities is that it's still a scientific viewpoint of the world, I would say. Still using the scientific method, I put that in quotes because I really don't think there's any such thing as a scientific method per say. But it's still using that approach. So there's similarities [00:04:30] there. I think some differences in complexity science lead to ... It's analogous too when I think in the early 20th century, newtonian physics was bumping against what Thomas Kuhn called anomalies, right, black body radiation.
Of course, Max Planck thought about the quanta. Then Einstein came along and thought about how to think of the space and time differently [00:05:00] as well. So that's was a paradigm shift. So I think something is happening like that now. We're bumping up against ... A great article was actually written in 1948 by Warren Weaver. I forget what it's called. I think it's called Science and Complexity. It was early, it was back in 1948 because already, people were bumping up against it. Science itself was bumping up against these problems. He talked about disorganized complexity and organized [00:05:30] complexity.
Disorganized complexity being things like from statistical mechanics, right, describing features, macro-features in terms of the statistics of little kinetic motions of molecules or galactic, like getting cosmology, thinking about galaxies full of hundreds of billions of stars and how they behave gravitationally. Even then, [00:06:00] things like nonlinear dynamics which is the main methodology of complex systems was beginning to come about because of things like the three-bodied problem for example in orbital mechanics. So those kind of things would be classified as disorganized complexity. Organized complexity, how do you describe an ant colony, the behavior of an ant colony? How do you describe the behavior of a whole swarm of birds? How do you describe genetic regulatory networks? [00:06:30] How do you write the mathematical, simple set of equations for these kinds of things?
Whereas you could do them in relativity for cosmological things like ... So physics started bumping up against that when you started doing the physics of life. That was one of the main things, that organized complexity. I mean, maybe it's still actually possible to write down the behavior of economies with a simple equation like the Black-Scholes [00:07:00] Equation, for example, which also has problems, right. We don't know. That's what I think a main difference is, to answer your question, to get back to your original one with that. That's the difference between complexity science and science, right. Yeah. I said a lot there so ...
Daniel Schmachtenberger: So let's recap here.
Michael Mannino: Okay.
Daniel Schmachtenberger: Eddington defines science as, "The earnest endeavor to put into order the facts of experience." So the tools of science have to [00:07:30] extend as we go into new domains of experience. So we didn't know there was such a thing as a placebo effect. Then when we realized there was, we came up with the placebo controlled trial and double blinding of trial. We added to the methodology of science because there was a new phenomena. The same is true when we went from newtonian mechanics, as you were mentioning, to quantum mechanics because at very very little scales, it's just different, right, different kind of stuff. So we extended what we understood. The same is true at the very large cosmological scale of relativity. [00:08:00] The same is true with certain kinds of systems that had usually huge number of interacting dynamics, sometimes as few as three, usually huge numbers of interacting dynamics, so chaotic and complex systems.
Michael Mannino: Right.
Daniel Schmachtenberger: When you were mentioning stable complex systems, life is one of the classic examples that we look at. So when we're trying to study biology, right, if we're trying to study an ecosystem or say a human body or human brain, [00:08:30] what's fundamentally different about studying how a brain works than studying how a computer works? What's different about those kinds of systems?
Michael Mannino: Good question. So as you've rightly said, with complex systems, you're dealing with a system with a large number of components or interacting elements. That is quite true of the systems that you're mentioning, that we've been talking about like economies, [00:09:00] ant colonies and things like that, genetic regulatory networks. That's what I think a definition of a complex system is, right. I mean, Yaneer Bar-Yam would say complexity is defined informationally, that is the minimum amount of information that you could use to describe a system.
Now, that's one definition. I mean, colloquially, we would say a complex system is a system, right, of many many different parts. But those parts are highly coupled. They're highly interacting, may interact in such a way that they produce [00:09:30] novel properties that other simpler systems or complicated systems like a car engine for example or a jet engine don't have. So those properties have been classically talked about right, in the literature as emergence, self-organization, coordination dynamics, pattern formation, symmetry breaking, all of those things. Actually one [00:10:00] of the most famous articles that was written I think in 1972 by PW Anderson, it is the most classic paper. It's a short paper in complex systems or complexity science. It's called More is Different.
He was using symmetry breaking in quantum physics to illustrate that there's a problem with the reductionistic hypothesis in sciences, right. That psychology is not just applied biology, [00:10:30] there is new laws that were discovered that just don't apply on these different levels. So he ends the article famously by saying, he ends it colloquially and with a fictitious joke in a way. He says, "Marx said it very well when he said quantitative ..." Like when he was talking about wealthy people of the different classes, the bourgeoisie and the proletariat, he said that quantitative differences [00:11:00] become qualitative ones, right.
When you add in more and more parts and those parts get coupled, you get qualitatively new distinct features that are novel and that also have a downward causal effect on the parts that make them up. Then the second way he ended the article was he said, there's a funny conversation I think between Fitzgerald and Ernest Hemingway in the 20s in Paris. Hemingway goes, or Fitzgerald [00:11:30] goes, "The rich are different from us." Hemingway answers, "Yes, they have more money." In other words, so they're different from us in the fact that they have more money but the fact that they had more money makes them qualitatively different people, which is interesting because now in behavioral economics, a lot of studies are coming out and showing there are right economic, and sociological, and psychological character differences between these things because of that. But that's another story. I do not want to get into too much of a tangent. [00:12:00] So those properties-
Daniel Schmachtenberger: I don't want to assume that everybody listening knows the term reductionism or top-down causation, etc. So let's get into those a little bit because these are key concepts. So in this paper, he was refuting reductionism. What is reductionism? Why is it useful? What are its limits?
Michael Mannino: What is reductionism, why is it useful, and what are its limits? Well, let me first [00:12:30] by say, we're all reductionists. I mean, as a scientist, you're a reductionist. That's how sciences, in my view, science progresses that way. It's through reductionism that we actually found out about other things. What is reductionism? It's an analytical strategy, I would say, of breaking down things and explaining them with their parts, if you can figure out what those parts [00:13:00] are, right. It's an analytical strategy that involves trying to explain what the different parts do. Then you add up those parts. You get the whole, okay.
In complex systems, something else happens. It's non-reductionistic in the sense of you add up all those parts and you get something completely different than you would with a thought. It was unexpected. That's the crude phrase, "The whole is more than the sum of the parts." So [00:13:30] that's what I think reductionism is. It's a philosophy. It's a motivation. It's a strategy and it's worked. It's very useful in the sense of it has allowed us to ... Well, I'll give you three examples or more. It's allowed us to cure disease, like cure polio.
The germ theory of disease was a reductionistic strategy I think. It's allowed us to send rockets to the moon by understanding orbital [00:14:00] mechanics and how the planets work, how gravity works. It's allowed us to make decent predictions about hurricanes because meteorology, although meteorology was one of the birth places of complex systems so I really don't want to use this too much. We're going to talk about why meteorology was one of the birth places of nonlinear dynamics and chaos theory and complex systems.
But it's reductionistic [00:14:30] in the sense of there's a methodology. There's a mathematics to explain it. You can explain things with relatively few equations like the Navier–Stokes equations in the geology for example or Bernoulli's equations about flow or something a little bit like that. That's why it's useful. It's allowed us to probe deep into the universe and get an understanding of what's going on. It's allowed us to understand that there's a lot more that we don't understand. Reductionist hypothesis has allowed that. [00:15:00] I forget what Einstein said, the most incomprehensible thing about the universe is that it's comprehensible or actually maybe it was the opposite. But I can't quite remember that. But yeah, so that's why I think it's useful.
Daniel Schmachtenberger: To clarify, reductionism is an approach where we take something that has some complexity and to understand it, we try and break it into parts that might be easier to understand. So we look at human physiology, by looking at gastroenterology, [00:15:30] neurology, oncology, all these different kind of vertical slices. Then we will further slice that and say, "Well, we're not just going to look at the GI track but individual organs, individual tissues, individual cells.
Michael Mannino: In order to explain how the GI track works.
Daniel Schmachtenberger: Right. So typically, in reductionism, we ground things like economics or psychology or human behavior in biology, and biology and chemistry, and chemistry and physics, [00:16:00] and physics and quantum physics. So we're looking for what are those foundational things from which we can construct ...
Michael Mannino: Everything else.
Daniel Schmachtenberger: Everything else.
Michael Mannino: Yeah. I think that's right. That's the general idea. That's been the idea throughout much of history.
Daniel Schmachtenberger: So what's an example where you break something into parts, you understand the parts and by understanding those parts, you miss the properties of the whole completely?
Michael Mannino: The brain. The brain, absolutely, my object [00:16:30] of study. That's where, your third question, "What are some of its limits," right. So I mean, you could talk about this, just to back up for a second from even a more philosophical point of view like you were saying about economics is made up of like markets or made up of people trading or banks trading or organizations trading. Organizations are made up of people. You go down the list. People are made up of brains [00:17:00] and physiology. Those things are made up of neurons and cells. Those things are made up of proteins. Proteins are made up of amino acids and all the way, all the way down.
You can even go down to as far as the smallest thing we know which is maybe strings, right, super string theory. Does that mean you can explain or predict an economic crash in terms of string theory. That seems like it's an appropriate question to ask but it seems like an obvious one. I don't think it's [00:17:30] an obvious one because there's complexity there about what are the limits of explanation. I mean, you go back to Laplace's demon and determinism.
Laplace said if there was a demon who knew all of the laws of the universe perfectly, knew all of the positions and velocities, every single particle in the universe at this instant and knew all the laws, you can make a prediction about anything in the future, anything that would happen like me moving my finger like this, for example. [00:18:00] You could make that prediction at the beginning of time, right. That's things like quantum mechanics and chaos theory and now, complexity science have shown those things to be ... Those doubtful or where they put them in question at least or they show them that they're not so obvious, I guess you would say.
Daniel Schmachtenberger: I think you can actually go further and say that Bell's theorem and pretty much every interpretation of quantum mechanics is a proof of hard random, [00:18:30] proof of non-determinism.
Michael Mannino: Yeah.
Daniel Schmachtenberger: So Bell's theorem extending on Heisenberg more powerfully than anywhere else shows the universe is oncologically unpredictable, future is unpredictable.
Michael Mannino: I totally agree. Although there's one interpretation of quantum mechanics, David Bohm's famous and that's completely deterministic and it has this-
Daniel Schmachtenberger: The De Broglie–Bohm theory is the only one, but it is required that everything you process is infinite, which ends up getting [00:19:00] functional in determinism again.
Michael Mannino: Exactly right, exactly right. Yeah. It's one of the third-eye caveat, exactly right. Yeah, I mean, back to your question, I think the brain is one of the most obvious, well, obvious now but maybe not obvious like 20 or 30 years ago, certainly not obvious in time of like Santiago Ramón y Cajal, one of the fathers of neuroscience, right. Yeah. The brain is one of the most obvious things where [00:19:30] you look at the parts. You examine the parts and all their detail. You put those parts together in such a way. You get something that is unexpected. It's novel. It's a novel property. Well, consciousness of it say, or cognition are novel properties.
It's obvious there. It's not so maybe obvious a lot of people use examples of in chemistry for example, there's plenty of examples in complexity science of chemistry. [00:20:00] One obvious one, a colly one is wetness strength. You find wetness in a single water molecule. You have to define what you mean by wet or wetness and not only in terms of the subjective component but an objective component. How many water molecules do you add up to where you go from an atom or a molecule which we don't think of wet to something that's wet, right? Is it an emergent property? What does that mean to say? I think [00:20:30] one of the obvious one is consciousness. Even that is still being questioned. What does that mean to say in this emergent novel property? But back to defining ... Okay, go on. Yeah.
Daniel Schmachtenberger: Maybe easier for people since consciousness requires that ontologic category shift from subject to object ...
Michael Mannino: Exactly.
Daniel Schmachtenberger: Is just the definition of life, right. That if we look at a cell and there's no respirates, we say, "Well, what parts does respiration occur? If we take the cell apart and we look [00:21:00] at any of the organelles on their own, none of them respirate. If we look at outside of the cell, if we look at any of the molecules that make it up, none of them respirate. Respiration is a submergent property of the cell as a whole system organized in exactly that way.
Michael Mannino: Right.
Daniel Schmachtenberger: It doesn't exist in any of the parts taken separately or the parts rearranged in different ways.
Michael Mannino: Or make the heart pumping blood is another great example that people use.
Daniel Schmachtenberger: So we see in life, we see this everywhere. It's really interesting, [00:21:30] so this is why I was asking the difference between say the brain and the computer is a computer has a lot of parts and has a lot of dynamics. Obviously, the computer being on is doing stuff that the screen on its own, and the motherboard on its own, and the hard drive on its own wouldn't do. They have to be together. But there is still a big difference between the computer and the physiology which is that the computer has a blueprint for how its built that fully specifies how all those parts [00:22:00] are going to work together.
Michael Mannino: Exactly. It's organization by design.
Daniel Schmachtenberger: In a complex system, you don't have a blueprint. What do you have?
Michael Mannino: You have self-organization.
Daniel Schmachtenberger: Right, you have generator functions.
Michael Mannino: Right.
Daniel Schmachtenberger: That's a way to think about it. So the genome isn't actually a blueprint. It's a generator function for how the system will code proteins to create new architecture in different environments, which is why the tree doesn't look like one thing. The human physiology doesn't look like one thing. You lift heavier weights and it starts to change, and the presence of certain [00:22:30] nutrients changes. Whereas the computer doesn't do that, right.
Michael Mannino: Yeah.
Daniel Schmachtenberger: Computer, it has very fixed structural dynamics. That's the real interesting thing in complex systems is the self-organization and self-interacting dynamics. So I would say there probably is no place where this is more relevant than human physiology and brain specifically because of the degree of complexity.
Michael Mannino: Well, yeah. To your point, many people have said, I mean, 80 billion neurons [00:23:00] massively massively connected, not only locally connected like in a computer. I want to go back to that actually cue for a second. The computer metaphor but I mean, many people have said it's the most complex system of which we know. You get 80 billion neurons. It's even more glial cells, astrocytes and things like that, way more. But back to I think for your listeners, one thing that is written about quite a bit right now in the literature [00:23:30] and in different magazines and periodicals and things like that is the computer metaphor for the brain, right, thinking about the brain as a computer, thinking about the mind is the software running on the hardware which are the neurons in the brain, and throughout history, there has been tons of metaphors for the brain, right, like systems of pulleys, all kinds of hydraulic systems.
Actually Sam Hash has a great waking up podcast. [00:24:00] He has a great episode where he talks about this with David Krakauer who is the head of Santa Fe Institute for Complex Systems. Those should understand that that only goes, that metaphor goes so far. There's more disanalogies than there are analogies and similarities. I mean, the computer, like you say, as an information processor, the information is not integrated in a way that the brain is. So you have connections of course in the computer but those connections are [00:24:30] very local. Whereas you have those connections in the brain but you also have a mixture of global connections and local connections, right.
The brain has been talked about as a small world network. If you listen, as I've heard about small world networks and what that means, like you can jump to a node in the system, a far away in the network or in the system, a far away node but with not that many hubs, right. So the average distance between hubs is not that great even though you have a massively [00:25:00] connected network. That difference, there's the integrated, as I say, the information is integrated. There is also the neuroplasticity, right. If you break the computer or destroy the CPU or a part of it, it's no longer, not going to work. If you do the same thing to the brain, that's not necessarily true. The brain is anti-fragile in that way I think. You can split ends.
Daniel Schmachtenberger: These are a couple really critical differences, right which is anti-fragility, self-repair, which are properties of [00:25:30] self-organization.
Michael Mannino: Yes. That's part of it.
Daniel Schmachtenberger: The other key thing is that as you were mentioning, in computers, the distinction between hardware and software is pretty clear.
Michael Mannino: Yeah.
Daniel Schmachtenberger: Which is that every time you run new software, the computer doesn't structurally rearrange itself in a significant way.
Michael Mannino: Right.
Daniel Schmachtenberger: That's actually not true in the human nervous system, which is that you have this complete coupling between hardware and software where any changes in the physiology affect nature of mind [00:26:00] and any processes in mind actually change the structure of brain.
Michael Mannino: Yeah. Perfect, well said, well said. D, to go even further up, the computer is ... I mean, as a Von Neumann machine, right, or touring machine, the computer processes information that way and so does the brain. But one thing I think further is that the body, we'll talk about this later of course, but the notion of embodied mind and embodied cognition and embodied consciousness, software [00:26:30] might require a hardware of a certain way. Not only that, but the movement of that hardware affects the way the software is running, if we're continuing with this computer metaphor. Although like I said, I think it breaks down very easily.
Daniel Schmachtenberger: So embodied cognition is a great example of limits in reductionism where we started by recognizing that there was information processing happening in the brain and the nervous system. Then we assumed it was all happening there.
Michael Mannino: Right.
Daniel Schmachtenberger: Then have started to recognize [00:27:00] maybe the rest of the body is not exclusively just carrying the brain around and processing nutrients for it but is actually doing something else interesting as well.
Michael Mannino: Yes, right.
Daniel Schmachtenberger: Talk to us about that, talk to us about why people's psyche changes with legal transplants and organ transplants, and movement patterns and ...
Michael Mannino: Yeah, that's a great, another new field within complex systems and philosophy of mind, right. [00:27:30] I think it originally began, well, began with several philosophers like Maurice Merleau-Ponty and Heidegger, and some other philosophers talked about this way back when. One of the most recent I guess scientists, neuro scientists and philosophers wrote a book called the Embodied Mind, Francisco Varela. He really talked about, along with some others, [00:28:00] like Alva Noë is another philosopher has written about this within activism, George Lackoff wrote Metaphors We Live By, all those people are different versions of embodied mind.
That's another thing. Embodied mind is really not a whole unified philosophy. There's different aspects of that as well, different things to focus on. So yeah, embodied cognition is the fact or the observation I guess you would say that having a body directly affects and shapes [00:28:30] cognitive processes. That the mind, having a mind and having cognitive processes might require having a body that moves around in an external world, and an environment and interacts in a dynamical relationship with that environment. In fact, in neuroscience and philosophy of mind have been looking for consciousness in the brain, all the views in philosophy of mind like reductive [00:29:00] materialism, unlimited materialism, all these different views.
If they say, well, let's look for consciousness in the seed of the soul in the mind, which is reducing the brain. Now, people are thinking that maybe that's the wrong, like Alva Noë would say, "The wrong place to look," that's the wrong way to go. We should probably look for consciousness in the fact that the brain exists in a body that moves and exists in a relationship with the world.
Daniel Schmachtenberger: Why?
Michael Mannino: Because traditional views have [00:29:30] bumped up against some limits. There's a lot of theories, there's a lot of different physical theories of consciousness. They've all hit dead ends, so far. Right? So the neural correlate theories of consciousness, NCCs which was started by Christof Koch, looking for the qualia, right, of love and experience of ray and then the C-sharp in terms of neurons. So [00:30:00] looking for mental states in physical states, right, looking for the mental states and the mental experiences, looking for those, explain them in terms of the physical processes that go on in the brain.
There's that. There's also Stuart Hameroff, right, explaining consciousness by looking at the microtubles with Roger Penrose' Quantum Theories of Consciousness have run up against dead ends, [00:30:30] global workspace hypothesis. So all these different theories of consciousness and mind, and looking for them in terms of what happens in the brain have run up against dead ends. People were saying, "Well, wait. Maybe we're neglecting the body here. Maybe we're neglecting a major component of this." I mean, if you look at the brain, let me get my model. So I mean, if you just look at the brain, right. Essentially, this first half of the brain [00:31:00] is largely devoted to, I mean, if we could, this is a crude description but essentially what you could do is the frontal part of the brain is largely devoted to motor acts and motor coordination to action.
The back half of the brain is largely devoted to perception and sensation. So you have what's been called the action perception cycle. So I mean, even just half of the brain is devoted to moving, right, and to doing motor acts with the body. [00:31:30] From the simplest example of talking with your hands or body language or facial recognition and things like this, all of these different parts of the body affect our consciousness and people started thinking, "Well, wait. Maybe we should not try and explain mental states in terms of just brain states," or what neurons are doing but what neurons are doing inside the body and how it moves.
Daniel Schmachtenberger: So I [00:32:00] think-
Michael Mannino: You were going to say something, no, go ahead.
Daniel Schmachtenberger: I think something that all of the people listening will relate to is that changes in many parts of your physiology obviously are going to affect your mind and psyche. You stubbed your toe and your psyche is in a very specific state. You have hormones that are out of balance that are not primarily neuro hormones, right, that are happening in the adrenal glands or in the thyroid or in the gonads. Your system feels radically different. You have food poisoning or something going on in the GI track, right.
Michael Mannino: [00:32:30] Yeah.
Daniel Schmachtenberger: We know that most of our neurotransmitters are actually produced by a microbiome in the gut. The gut is not traditionally thought of as the nervous systems. We have to have this gut, brain access. We start realizing that there are these axis everywhere with the anatomy and physiology, the dynamics of all of the body relate to the nature of our mind, our brain, mind, psyche. Then we can extend it a little further, right and say, "Well, [00:33:00] if we just had our brain without the rest of our body, we would not have conscious experience in the same way."
Michael Mannino: Yeah. Right. That's right. Yeah.
Daniel Schmachtenberger: Then we can say, "Well, if we just have the entire body without an environment, then that wouldn't work either," right.
Michael Mannino: Yeah.
Daniel Schmachtenberger: So we get this nested complexity topic.
Michael Mannino: Can I cut you off with just one thing ...
Daniel Schmachtenberger: Yeah.
Michael Mannino: Before I forget? The latter, what you just said, a great example of that is a famous experiment by Hein and Held, I think that's cat experiments. [00:33:30] In psychology, it was well-recognized. The cats, they put two cats in a carousel. The carousel has the screen on it, so black and white stripes so that they can see movement, right. One cat was in a little gondola so it couldn't move. The other cat was moving the carousel itself. But both cats were seeing this go by. They did this for like three weeks. This is a crude explanation of the experiment but they did this for three weeks with the little kittens. [00:34:00] Then they put them out in the world.
The cat that could move the carousel and was actually walking and seeing things go by at the same time was able to walk normally. Whereas the cat in the gondola that was just seeing things go by in its ocular, its visual field, its optic field as JJ Gibson would say, the theory is built on that, could not walk, could not see the depth of things much similar to the hunters that were [00:34:30] in the forested, thick forest and all they see was distances like this their whole lives. Then they were taken out in the field. They could not perceive a buffalo correctly that was way out on the field because ... All right. So that hypothesis there was exactly as you just said. If we don't have the correct environment, that also will affect our cognitive processes. It's not just having a body. It's having an environment and the relationship between that environment and the body that needs to be addressed.
Daniel Schmachtenberger: So to tie and [00:35:00] explain together.
Michael Mannino: I don't know if why ...
Daniel Schmachtenberger: Hey, no, very clear. So tie the thread together, we're talking about reductionism and finding the properties of holes and the parts and that there are times where the nature of the interaction of the parts, the networks of dynamics that the parts have together end up being critical to the behavior of the whole system, right. Synergy defined as the behavior of whole systems unpredicted by the behavior of the parts taken separately. So systems are particularly synergistic systems.
Michael Mannino: Yes.
Daniel Schmachtenberger: [00:35:30] So then we jump without saying it to the topic of consciousness and looking for consciousness in association with the brain and in saying well, we see that when people are in different states of subjective experience and we haven't hooked up to EEGs, to different brain monitoring devices, we'll see correlates between certain neural states and certain conscious states.
But the fact that we see correlates doesn't mean that we don't see correlates anywhere else and doesn't mean that you have one directional [00:36:00] causation meaning that the brain is causing the mind exclusively and also doesn't mean that you have perfect correlation. These are all the assumptions that when we started to see the correlation we figured would may be happen in the reductive models of mind is the result of brain.
Michael Mannino: Right.
Daniel Schmachtenberger: Now, we're extending it to say, "Well, maybe it's not just brain but brain and nervous system and body."
Michael Mannino: That's right.
Daniel Schmachtenberger: Then it's brain, nervous system, body taking in the environment. So then we start to think about mind not as an emergent [00:36:30] property of brain but as an emergent property of the relationship of self with universe.
Michael Mannino: Exactly. Right. I mean, well, yes, exactly right. In the paper that we just got, we just wrote then and also in my talk, I boil it down to that. The brain is a dynamical system. The mind is an emergent self-organizing process that exists, that it's an embodied process [00:37:00] that exists in relationship with the external world, with the universe as you say. So that's how I would define the mind and cognition and cognitive processes and probably even consciousness as well. I would say that consciousness and not to jump a gun or anything right, but consciousness requires embodiment. Subjectivity requires dynamics meaning a relationship through time [00:37:30] that evolves, a dynamical relationship between the environment and the body itself.
Daniel Schmachtenberger: Both sensory and motor processes, as you were mentioning.
Michael Mannino: Yeah. We have this diagram in the paper where it's like you have the box of the brain. Then the brain exists in a body. The body exists in the environment. Inside the brain, you have what you've just alluded to now, sensory systems, [00:38:00] the motor systems and the interactions between sensory and the motor systems back and forth. It's actually exists in a hierarchical level in this what's called action-perception cycle, some people called it reception-action cycle. Yeah. The limbic system is highly involved and creates an integration let's say of space and time and it goes on and on from there.
Daniel Schmachtenberger: Just this is actually fun [00:38:30] because we actually defined the mission statement of Neurohacker in relationship to complex systems at one point which was at-
Michael Mannino: That's what led me to you.
Daniel Schmachtenberger: Yeah. So we defined it as that all complex systems have a triplicate of these three properties that defined their adaptiveness that are what has them evolve which is sensory input of information from the environment, information processing, modeling of that and then actuate or output in a closed loop. [00:39:00] So it's not just input and output, there's processing in between which takes the input, makes sense of it, right, sense-making to then be able to inform a decision, be able to act on it. Then again, if we have to be able to incur in sense the effective reaction on the world, so the cat pushes a little bit the carousel and it moves a little bit. It pushes a lot, moves a lot. Its sensing and its action are both informing its sense-making, its ability to understand, right. They're all co-informing, co-evolving.
Michael Mannino: Right. No, that's [00:39:30] exactly right. Yeah. Not to interrupt you again, just don't want to forget this point. That was the heart of our paper that we wrote is the idea that ... So my adviser's adviser is Walter Freeman, as I was mentioning to you before. He just died last year. He was a pioneer in applying complex systems to brain sciences. He was the guy, the pioneer to applying nonlinear dynamics. He has actually what's called his own Freeman's nonlinear neurodynamics [00:40:00] to understanding the brain, like chaos theory to understanding the brain. What he said, what his work shows I believe is that exactly what you're saying, it's not just the brain. The body's not just a stimulus response.
It's not a computer in that way, right, garbage in, garbage out. There's a whole bunch of ... This is the idea of perception being active or constructive, perception is constructive. It's not like a camera that just records a one to one isomorphism between [00:40:30] reality, just doesn't record. So you get sensory information that gets transduced and then processed. But what Freeman showed, was one of the first to show is that actually a lot of what you perceive is driven by endogenous input, by the brain's own internal activity, the milieu of what's going on in the neurons and the brain is actually producing what you see almost sometimes more than what the external environment is producing what you see.
Daniel Schmachtenberger: Okay. That's another [00:41:00] way of saying that learning is possible.
Michael Mannino: Yes. It moves-
Daniel Schmachtenberger: It could be the endogenous input is based on previous experience so that we're actually making meaning of ...
Michael Mannino: I can't believe you just said that. That's exactly right. So Freeman thought that the brains are dynamical systems that are in the business of creating meanings not responding to stimuli. That's what organisms do. That's perfect that you said that. That's what the whole paper is about, yeah.
Daniel Schmachtenberger: When Victor Frankl [00:41:30] said that between action, between stimulus and response is the last human freedom.
Michael Mannino: Yes.
Daniel Schmachtenberger: Paraphrasing that, it's actually key insight here. But just the mission statement, how we had it.
Michael Mannino: [crosstalk 00:41:44]
Daniel Schmachtenberger: I'll actually link this in the show notes is in their most abstracted cases, sensory input we're relating to sentience, the ability to actually take in and have some experience of anything. [00:42:00] The information processing, we're relating to intelligence, the ability to make sense of and make meaning of that sentience and the actuator output to agency, the capacity to make choices and navigate in the world.
Michael Mannino: Right.
Daniel Schmachtenberger: And that those three are actually XYZ axis. They're in orthonormal basis for defining what adaptiveness means, what sovereignty means. So that our goal here is how do we actually optimize people's sentience [00:42:30] intelligence agency and then triplicate between them.
Michael Mannino: So that creates a coordinate system. It creates a space of possibility, right. So I love this idea of thinking about not only spatial extension about space, but also like different spaces like a state space. So in complex systems, we think about a phase space or a relationship space or a connectivity space, this is what I actually study. It's my research particularly. So this triplicate orthonormal basis forms [00:43:00] of space and that space describes all of this possibility of optimization that you're talking about.
There's parts in that space where things are non-optimal. There's part in that space where things are optimal, where it's possible like where human optimization is going to review the most ... Which is going to come to fruition I guess or manifest itself the most I should say. So that's an interesting thing you're saying.
Daniel Schmachtenberger: So let's jump from the [00:43:30] philosophy to the practical there regarding optimization and say reductionism did a good job with polio because polio really did have an acute cause, right, there's pretty much one cause that if you address it, you do a pretty good job with it. Medicine has not done a great job with cancer or Alzheimer's or neurodegenerative disease in general or auto-immune disease because they don't have one cause, right.
Michael Mannino: Right.
Daniel Schmachtenberger: So when you're dealing with multi-factorial dynamics, reductionism doesn't work as well because you're looking for one thing that is off. It's [00:44:00] some weighted set of many things with delayed time causation.
Michael Mannino: Right.
Daniel Schmachtenberger: Which is why a complex systems approach to not only medicine but also medicine has not done a good job with mental illness or psychiatry.
Michael Mannino: I know.
Daniel Schmachtenberger: We don't have cures for anxiety or for depression. We have symptomatic treatments that all have side effects and are just treatments. So that doesn't mean these things are curable. It just means we need an approach that can look at the complexity [00:44:30] of the dynamics that are leading to these altered homeo dynamics and can actually address them which is our whole goal here. So talk to us about that a little bit, talk to us about as someone studying complexity applied to neuroscience, as you're thinking about the future of psychiatry, psychology, neuroscience, medicine, some of your thoughts.
Michael Mannino: Yeah. So I think that again, [00:45:00] just from a personal viewpoint, a personal standpoint, I was looking to study ... I was inspired by ... I'll get to your point in a second. I just want to say this. I was inspired by Paul and Patricia Churchlin who started this field of neurophilosophy. They basically said, "Where does philosophy go from here into the brain?" So I was interested in trying to solve these problems, these complex problems by looking into the brain and [00:45:30] explain consciousness by looking into the brain, like we've already talked about.
So I didn't know anything about complex systems. I have found out complex systems when I entered this degree and started studying at the Center for Complex Systems and Brain Sciences and realize that the methodology of looking at the brain from a complex systems or complexity science viewpoint actually is wide applicability and leads to a whole bunch of other things. I went to the New England Complex Systems Institute at MIT for two weeks, a couple of suns ago. We studied ethnic conflict, [00:46:00] ethnic violence.
We studied healthcare, sworn behavior, even dermatology. There was a dermatologist in my group studying why people get a rash here and not here or something like that or why this person has this physiological response in their skin and this person doesn't from a complex systems viewpoint. So I think that you're absolutely right. We have talked about these limits of reductionism [00:46:30] and this new complexity science that's emerging to try and explain and describe and also make predictions. So am I getting to your question now? I don't want to get too off topic [crosstalk 00:46:43] but ...
Daniel Schmachtenberger: You're saying that complexity is being applied to things.
Michael Mannino: Right.
Daniel Schmachtenberger: Can you say more about ... Whether you want to go into complexity or to embodied cognition, how [00:47:00] a more complete approach to understanding the relationship between the mind and brain affects how we would go about affecting the mind.
Michael Mannino: Yeah. Right. I mean, even in my particular research, so I study causality actually. I study brain networks. So we're using network science applied to the brain. Now, people are using all kinds of network science to apply to everything including things like healthcare, economies and markets, and all kinds of thing. [00:47:30] Even terrorist networks, counter terrorism is using complex systems to apply graph theoretic approaches to how different cells communicate and different hubs and things like that.
So that's the sort of approach that I'm using in my own research to study large scale brain networks. My general viewpoint is that cognition and cognitive processes do originate in the brain but it's a necessary [00:48:00] but not a sufficient condition for cognitive processes or things like attention and perception and memory and language. They also require the body. They also require movement. They require embodiment, movement, and a dynamical relationship with the external world as we've already said.
For example, working memory network between different aspects of the brain and how information flows from one area to the brain to another area of the brain. What I'm doing in my research actually, just [00:48:30] to briefly tell you, is we're using nonlinear dynamical systems which imitate or simulate brain data, neuro-imaging data. Then we set up the connectivity between those regions. Then we try and recover that connectivity using different methodologies that are now becoming wildly popular in complex systems in general. So there was just a conference in Cancun I think in April. Now, there's a lot of conferences by the way in complex systems. They're huge. They're big.
[00:49:00] One was in Cancun where they were talking about all these different topics. One of the biggest topics was using causal analysis to try and locate the information flow in these networks, whether it be a terrorist network or a brain network or a social network or something like that. So just to sum up, that's my area of research. We used to think, right, that from phrenology, right that this part of the brain does this. This part of the brain does that. [00:49:30] Over here, this part of the brain does this. We now know that that's not what happens. We now know that cognitive processes are largely subserved by the interaction, the dynamical interaction of all these different brain areas.
So the idea is to examine that connectivity. There's different kinds of connectivity, functional connectivity, causal connectivity, structural connectivity. So we've actually found, to go back to embodiment, to take this, is there's this concept of meta-stability which exists and coordinate [00:50:00] in the field of coordination dynamics which was largely started by Scott Kelso and my adviser, Steven Bressler in Center for Complex Systems. Brain science is where different parts of the brain have a tendency to coordinate but they also have a tendency to compete.
So they have a tendency, a simultaneous tendency to integrate but then also to want to do their own thing and be autonomous and segregate. It's this perfect balance of integration and segregation that allows for cognitive processes to take [00:50:30] place. So that's the concept of meta stability. Now, this concept of metastability in the brain is also being explored in other areas as well. We started out this conversation, economies, social coordination, markets, worn behavior, all kinds of different things.
Daniel Schmachtenberger: Again, I don't want to assume that the terms are familiar.
Michael Mannino: Okay, yeah, sorry.
Daniel Schmachtenberger: Would you define a nonlinear system?
Michael Mannino: Right. [00:51:00] There's different ways to define it mathematically or just conceptually. Math, let's start off with mathematically. You have a mathematical function, right. I don't want to get too complicated or complex, no pun intended. It's necessary. That's actually one of the things that I do is what's called computational neuroscience or mathematical neuroscience. One of the things we're learning [00:51:30] is how to appropriate mathematics and writing things down to describe them. So you see that in all complex systems, in all complex system trying to describe this complex behavior through mathematics, through the language of mathematics.
Actually a great book, let me just get another book on my desk here. This is a phenomenal, phenomenal book by John Gottman, one of the top psychologists. This is called the Mathematics of Marriage, Dynamic and Nonlinear Models. So this is a phenomenal book about [00:52:00] modeling different properties of marriages and relationships and seeing if you could model that and then make predictions from that mathematical model, it's fascinating, his results. He's actually affiliated with the center. So dynamic and nonlinear models, so a linear model, right, is a model where you, like we said before, conceptually, you take the parts and you add them up. You just get the addition of those parts, right.
Daniel Schmachtenberger: We say for simplicity, where the outputs are proportional [00:52:30] to the inputs.
Michael Mannino: Exactly right, right. The linear models where the outputs are directly proportional to the inputs. A nonlinear model is just not that. The outputs are unexpected and not directly proportional to the inputs. You put a little input into something. In a linear system, you would get a little output. You put a little input probably so probably to a nonlinear system, you get a large or an unexpected output. Mathematically, as I was saying, F of X [00:53:00] plus F of Y equals F of X plus Y.
So the function of X, the function of Y, you add those two functions together. You just get one function that is the superposition of both of those individual functions. So that's one mathematical definition of linearity. So a nonlinear system is a system such that you cannot add up the individual functions to a system, that would just be the superposition of those functions.
Daniel Schmachtenberger: So we can see a bunch of dynamics [00:53:30] happening in the brain but you can't add up those dynamics to explain what's happening in the brain in a really clear way?
Michael Mannino: Yeah, exactly right. I mean, the brain is a nonlinear dynamical feedback system in the sense of you ... I mean, a single neuron itself is a dynamical system. It goes through things called bifurcations or symmetry breaking, like I mentioned earlier on the podcast here where a neuron is doing something or it's silent. It's quiescence, right. [00:54:00] You just give it a little tiny input and boom, it bursts like ... Like this. It starts doing this bursting behavior. The reason for that is you look at the mechanics of the neuron, the input of sodium and the output of potassium and so on and so forth. Even one neuron is a nonlinear dynamical system, the whole brain itself ...
Daniel Schmachtenberger: And when we think of an input that doesn't have proportional output or a tiny [00:54:30] input might be a huge output or a huge input might produce a tiny output or an unexpected one, seems like all right, well that's just chaos. But we're actually not talking about chaos here. We're talking about complexity and metastability meaning that you have feedback between these different nonlinear systems that create different stable states and the system can move between these different stable states.
Michael Mannino: Right, or unstable states, right. Right. I mean, you have these equilibria, these [00:55:00] fixed points in the system and a stable equilibria is one where the system is here. Take a neuron for example, if a neuron is doing something and it might be in a stable state where if you perturb it, it will do something else but then it will return back to what it was doing. Whereas an unstable state is the neuron is like, let's say quiescent or just relaxing, in a relaxed, in a resting state, right, and you just perturb it a little bit. All of a sudden, [00:55:30] it explodes and gets far away from what it's doing and never returns back to what it's doing.
Nonlinear dynamical systems is a mathematical apparatus that actually describes what neurons do and then what the whole brain does. So that's the idea of nonlinear dynamical systems and metastability. You brought in chaos. So neurons are chaotic. Some people, like my adviser's adviser, Freeman thought the brain was chaotic in a sense. [00:56:00] So that's debatable whether the brain is actually a chaotic system. So the neuronal populations, I've studied neuronal populations, so a population of 10,000 neurons here and a population of 10,000 neurons here and their connectivity.
This whole population of neurons here is actually chaotic meaning that it's very sensitively dependent on initial conditions. Meaning that if you, for your listeners right, they probably heard of the butterfly [00:56:30] effect just to not to get into chaos too much, but a butterfly flaps its wings in Texas and creates a hurricane in the Caribbean. That's back to the meteorology and Edward Lorenz, that's more metaphorical. The idea is that you'd put a small little input. You would think if you have a system, and if you put one tiny little input here but then you let the system run, and then you put another tiny input very very close to the first tiny [00:57:00] input, you would think that the system would run in the very same manner that it did in the first one, in the first case. A chaotic system is very very sensitive to those initial inputs.
So those initial input can be really really infinitely so close from the order of many magnitudes. But then you would get widely widely different behaviors in the system. So a chaotic neuronal population or a chaotic brain allows for neural [00:57:30] flexibility. The brain is very very flexible. It's able to ignore large amounts of information which is necessary for survival. It's enabled to adapt. It's enabled, its neural populations of the brain itself is a very very flexible system. That's what that chaotics of these do.
Daniel Schmachtenberger: I'm hoping that people listening are just starting to think about the brain. The sheer volume of stuff that's happening, [00:58:00] right, when we're talking about tens of billions of neurons and we're talking about trillions of synaptic connections between them, this level of sensitivity to initial conditions and what single neurons are doing, what small networks, what large networks are, all of that interacting with the environment, all of that interacting with the body, storing information and then taking in new information and factoring the stored information simultaneously. The fact that we're [00:58:30] not just goo, right, that it doesn't just entropically dissolve into goo instantly, that there is able to be homeo dynamics at all.
Michael Mannino: Right.
Daniel Schmachtenberger: That level of complexity is just like it should be awe-inspiring and humility-inspiring, and fascination-inspiring, and maybe make you want to go do a PhD in complexity neuroscience.
Michael Mannino: Correct. That's a pretty apt description there.
Daniel Schmachtenberger: Whenever we think about psychiatry or bio-hacking [00:59:00] for cognitive enhancement or anxiety or whatever, we're talking about ways we can affect the body that are going to affect the mind or the psyche.
Michael Mannino: Yeah.
Daniel Schmachtenberger: So we're looking at the fact that mind, body are linked, and that the body to the mind direction has some causal dynamics that we can work with.
Michael Mannino: Right.
Daniel Schmachtenberger: Now, we don't have to have any deep philosophy of mind to say is the mind emergent property of the body, of the brain is mind fundamental. [00:59:30] It actually doesn't matter. So just say there is some coupling. There is at least some causal dynamics in the direction of body to mind. You might also say there's causal dynamics in the direction of mind to body.
Michael Mannino: Right, right.
Daniel Schmachtenberger: Self-induced neuroplasticity direction.
Michael Mannino: Well, I mean, not to cut you off. I want you to go on and say it. But you're right. You don't need a philosophy of mind to talk about those things. I think you're absolutely [01:00:00] right. But the essential question is if the mind is an emergent property, if consciousness is an emergent property of the brain, the question becomes, "Are emergent properties real? What does that mean to say?" Then you get into a whole philosophy of whether it's just in terms of predictability, whether it really exists and blah, blah, blah. I totally agree with what you're saying and the thread of what you're saying. It's spot on.
Daniel Schmachtenberger: Yeah. I wouldn't say that saying that mind is a an emergent property [01:00:30] of the brain is something that is solid agreement across philosophy of mind, right. We've got consciousness as fundamental interpretations. We have dualist interpretations. We have all different kinds of things.
Michael Mannino: Right.
Daniel Schmachtenberger: We could have a whole deep conversation on philosophy mind which should be fun. For those who aren't even very familiar with it but are just curious like, "What is physics? What is matter, and energy, [01:01:00] and charge, and weight and that stuff? What is consciousness which is filled with feeling and emotion and impulse and thought and totally different kind of stuff, what are those two universes of stuff and how do they relate?" That's the hard problem.
Michael Mannino: Well, let me quote Erwin Schrödinger who wrote a very very famous book, "What is life," which started molecular biology. In the chapter called the Arithmetic Paradox, he starts off the chapter by saying, "The reason [01:01:30] that the sentient percipient ego can be found nowhere in the objective universe can be easily answered in seven words: because it is itself that world."
Daniel Schmachtenberger: Yeah.
Michael Mannino: "Because it is itself that world." Yeah. So those seven words, right, so absolutely, yeah, we're on the same.
Daniel Schmachtenberger: There is actually a really fun book Ken Wilber put together when he was young called Quantum Questions ...
Michael Mannino: Yes, yes.
Daniel Schmachtenberger: Which was basically just the quantum physicist who really developed [01:02:00] modern physics. It was their philosophic musings on what is the nature of reality as indicated by what they're seeing in quantum mechanics. What was so fun was this is Einstein, and Schrödinger, and Heisenberg who all came from classic philosophy science and then solved just the most phenomenally weird things in quantum mechanics. Their philosophy all sounded quite a bit more like Vedanta or Taoism.
Michael Mannino: The Upanishads, the ...
Daniel Schmachtenberger: Yeah. Actually [01:02:30] that's a great book if people want to check it out. If anyone wants to check out whether they agree with him or not, David Chalmers framing of what he calls, The Hard Problem to even understand the problem of what consciousness is, what brain is, and why there is a very deep philosophic topic. It's a good place to go start.
Michael Mannino: Absolutely, David Chalmers is a leader in the philosophy of mind.
Daniel Schmachtenberger: The question I have for you is ...
Michael Mannino: Yeah, go ahead.
Daniel Schmachtenberger: When we come back to however they're coupled, body affects mind, and not [01:03:00] just brain affects mind but body and movement and dynamics affect mind.
Michael Mannino: Right.
Daniel Schmachtenberger: If someone is wanting to understand that in a way that they can apply, you focus on specific types of exercise and lifestyle specifically not just for health and longevity, but for mind dynamics. Will you talk about that?
Michael Mannino: Yeah. Absolutely. I'm just trying to connect these ideas [01:03:30] like you did so well, just a moment ago about the essential notion of embodied mind which is like we talked about, a big field in the philosophy of mind. Now, neuroscientists are starting to look at that too, not just philosophers. Neuroscientists are starting to look for explanation of cognitive processes in terms of how the body moves. So I thought it to myself, [01:04:00] the idea of coordination dynamics which was started by like I said, Scott Kelso and my adviser, and their application of coordination dynamics to limb movement, right. Then not only that, but different areas of the brain coordinating in different ways like in metastability and different people coordinating in different economies and markets and things like that.
I was thinking, "Well, if that's the case, how can we connect coordination dynamics and this notion [01:04:30] of embodiment to my other area of interest which is fitness?" Fitness is movement. Movement affects cognition. Movement is a requirement for the mind. So I thought that maybe there are some studies now that are showing, that can actually give in some empirical evidence of this. I looked and turns out there are. There are plenty of studies now showing how different patterns of movement affect the brain and therefore, cognition. You see [01:05:00] a lot of articles are coming out. A lot of studies are coming out every year and increases at a rate, at a certain rate about what running does for functional connectivity of the prefrontal cortex or something.
I even just read a study that I put on my talk which came out last year I think showing that expert practitioners of tai chi which is a contemplative interoceptive pattern of movement with the body affects [01:05:30] their proprioception of their body and those people who are expert practitioners of tai chi are less susceptible to what has been called the rubber hand illusion. So we're given this body schema. Our brain has this body schema. Sometimes that goes wrong. Sometimes we think that sometimes people have alien syndrome, alien hand syndrome rather like where they don't think their hand belongs to them or something like that. So this sense of belongingness to our body and how we move it, [01:06:00] gestures, those things or even fine handwriting skills like this, fine motor skills of playing the guitar or an instrument or even cursive writing.
There's all kinds of evidence showing that that expects cognitive processes and learning, and being better at logic or mathematical reasoning or spacial reasoning or something like this. I wanted to tie those areas together, movement, fitness and embodied cognition. So what I do is [01:06:30] I used to be very interested in weight lifting and different cardio like running and things like that. I lifted all my life on and off of course. Those days of those kinds of fitness are kind of like old. The days of Arnold Schwarzenegger and Jack LaLanne and those people, those body builders are antiquated now.
People are more into body weight movement [01:07:00] and you hear about what's called floor surfing, for example. I just learned about that term recently. So you have all these different movement camps out there like Ido Portal and Mike Fitch who has this animal flow, just started here in Miami. There's Erwan Le Corre's evolve, move, play. There's Move Mat. There's all these different primal movements out there that are focusing on just getting on the floor and doing things in a different way, much like the experiment [01:07:30] that I was talking about in the beginning, early in the podcast, the cat experiment. Hein and Held's cat experiment, seeing how optical field flows in the ground versus up higher.
So people are getting back to that now. Getting back to that, what I mean and say like getting back to crawling and just moving on the floor and things that we used to do as maybe way back in our ancestral days or even as children or something like that. So different levels of play. I think there's a direct connection between those different kinds of movement and cognitive processes. [01:08:00] That's really the bottom line. So I try to incorporate different patterns of movement on myself and not ... N equals 1 to see how those are affecting my cognitive processes but there's evidence that they do.
Daniel Schmachtenberger: So we have some very general insight which is that movement at all is going to affect cognitive process in a very generalized systemic way through let's say endocrine effect or generic transcription effects that ...
Michael Mannino: Okay, right.
Daniel Schmachtenberger: Exercise [01:08:30] is going to increase BDMF. So you're going to get more neurogenesis. It's going to increase androgen production, growth hormone production. So nitric oxide production, right.
Michael Mannino: Right.
Daniel Schmachtenberger: Those basic things and it doesn't matter what type of exercise. Some will do that more than others, but they're all going to do that a little bit. That's going to affect neurological health at large which will affect cognitive process. Then we can go a bit deeper and recognize that certain body regions and certain types of movement and certain types of physiologic [01:09:00] engagement actually affect cognition in different ways.
Michael Mannino: Yes. Well, let me take a step back. I mean, there are different patterns. They're finding different patterns and movement affect different kinds of cognitive processes, right. Like I said, you're right. Brain-derived neurotrophic factors will increase which will lead to more neuroplasticity or neurogenesis and certain areas of the brain involved with learning and memory like the hippocampus. Running will increase functional connectivity in the prefrontal cortex, [01:09:30] maybe high intensity interval training, they're theoretically, well, empirically I should say finding that affects cerebral vascular function or something like that in certain areas of the brain rather than others.
So there are different patterns. I think there are probably a category of different patterns of movement that will affect different areas of the brain which will then affect different cognitive processes in general. It's still [01:10:00] unclear, right. It's still a very large work in progress. We still don't know.
Daniel Schmachtenberger: Right. I don't remember where the study was published from but I saw a study not long ago, a neuroscientist who was looking at regions of the body that mapped to regions of the brain.
Michael Mannino: Okay.
Daniel Schmachtenberger: Who was hypothesizing that exercising in specific regions might have specific kinds of psycho cognitive effects, and specifically ended up finding that working abs had more effect on decreasing anxiety than working in [01:10:30] the other muscle group and body.
Michael Mannino: Okay. That I never heard of, that's very interesting though.
Daniel Schmachtenberger: It wasn't being postulated that it was because it was affecting the viscera and the gut brain. It was because of actual-
Michael Mannino: I was going to say the vagus nerve.
Daniel Schmachtenberger: It was the innervation to the abs specifically affecting brain regions that were involved in anxiety. That was the hypothesis.
Michael Mannino: Okay. That seems-
Daniel Schmachtenberger: Now, that seems to be kind of at the cutting edge of a new level of insight where you could actually have therapeutic exercise programs.
Michael Mannino: That would be very very interesting. I mean, that's ... There are probably all these [01:11:00] kinds of things that are happening that we don't even know. That's why I'm saying it's a large work in progress. But what I'm really fascinated about is so take yoga for example. We now know that well, I don't want to say that definitively, "We now know," but I will say that some studies are suggesting that yoga has different impacts on brain waves like alpha waves, decreasing gray matter in the amygdala which is involved in fear and anxiety, right, an increasing neuronal generation or neuronal connectivity in other [01:11:30] areas of the brain that are involved with compassion.
So it is very interesting. Or empathy, for example, let's take away for a second the connection of yoga to a philosophy, like Hindu philosophy or something like that. Just look at it as a pattern of movement that is simultaneously timed with the breath, okay. So just that, I think it's fascinating that even ... So western yogis, there's this big [01:12:00] movement on Instagram, right, with yogis putting their poses in and having these deep insights or something like that. I just think that it's fascinating to me that this pattern of movement can affect those kinds of cognition or those kinds of cognitive processes like compassion or empathy. You find a lot of yogis who might be vegetarian or vegan or something like that. I don't know what the exact numbers [01:12:30] are.
It's just phenomenal to me that you have this direct connection between a system of movement and a cognitive process, right. Not even a cognitive process or a mental state like empathy or something like that. There are to me, that direct link exists, the direct correlation exists. I don't know if it's actually causation. It could be. I guess in my whole thing, I'm actually assuming there is causality. You do this pattern of movement, you're going to change.
Daniel Schmachtenberger: I mean, it's obviously hard when people [01:13:00] are studying yoga and there really is a cultural context that is implicit. There's a whole sent of aesthetics that are implicit. So there is selection bias. I think it is fair to say when we just look at the pattern of movements of yoga compared to most of other exercise systems, it's kind of fascinating because you've got stretching of the whole body and strengthening of the whole body, and balance and inversion, and cerebral blood flow dynamics, and increased conscious [01:13:30] proprioception, and breath. There's really a pretty complete system, complex system in terms of all the different things you'd want to engage in a movement system.
Michael Mannino: Yeah. It's fascinating and it's widely applicable, like people of all ages, all different kinds of geographical and demographics can do yoga which even makes it more complete. Well, there are optigenery and marathon runners, don't get me wrong, but yeah. [01:14:00] No, I think that's fascinating. One of the causal links could be like we actually mentioned, the vagus nerve. So the effect of yoga on something like heart rate variability which cannot be measured. There's different algorithms to measure it. It seems to be quite difficult to get at reliably.
That could be a link between this system of movement and this different kind of mental state, [01:14:30] right, or mental awareness or cognitive process. Like perception, maybe you can go back to I mentioned is like posture. Posture has been linked to psychology and psychological aspects. But we're now linking posture to neurobiological aspects, right. So there can actually be effects of posture on the brain and the way the brain perceives the external world. That's not a system of movement like yoga but it's another empirical example of the effective movement [01:15:00] and the body on different kinds of cognitive processes. So we're talking about fitness still.
Daniel Schmachtenberger: There's a program. I'm not sure if you've seen but I just want to let the people listening know, if you go to the website ZingUp.com, Z-I-N-G-U-P.com it's Wynford Dore, CEO of that company is a friend. We did quite a lot of dialogue. His daughter had autism, wealthy guy and after selling some businesses and just [01:15:30] decided to bring all the neuroscientists that were having some good insights in autism together and try and create a program. The current program is not advertised. It's something you need to do with autism, this performance enhancement.
Michael Mannino: Okay.
Daniel Schmachtenberger: The study is on someone juggling and IQ, going up three points when they get juggling down or learning how to drum and then learning to drum with the opposite, non-dominant hand stuff. So what they have is an entire program of just really heart coordination exercises based on tests. The [01:16:00] moment you start to get it, it moves to a new one because the insight that they found was that in the beginning of doing some motor, sensory motor coordination type activity that you can't do it all, you're starting to ride a bike and you're going to fall over, there's a threat signal that actually drives radical neurogenesis to figure out because in evolutionary environment, it would have been like, "Whoa, fuck. It's not safe to not be able to do this thing."
Michael Mannino: Right.
Daniel Schmachtenberger: You have this very fast uptake of new neural network formation. [01:16:30] Then you start to get decreasing returns as you go into skill perfection of just in terms of neural network dynamics. So the moment, and of course, that doesn't mean you're getting good at the scale. It just means if you're trying to drive neurogenesis, right, then you do it. As soon as you start to get the hang of it, you switch into something else.
Michael Mannino: Right.
Daniel Schmachtenberger: You start to get the hang, you're switching to something else. They found that they've got this ten minutes a day program that within six months, they had 18% increased volume in the cerebellum, [01:17:00] which was phenomenal. They saw 11 points increase in IQ in a teenager study and decrease in violence and criminal populations with no psychology involved at all.
Michael Mannino: Amazing.
Daniel Schmachtenberger: They were basically looking at the limbic brain and the basal structures of the brain having increased capacity to process information, increasing our cognitive capability, our athletic capability but also our psychological capability because people could actually process the input without going into reaction.
Michael Mannino: Yeah. That's amazing.
Daniel Schmachtenberger: The whole [01:17:30] thing, and why it increased rate of learning specifically, that aspect of intelligence, their hypothesis was our ability to automate new learning, right, so you're trying to drive the stick shift and it takes all of our attention or trying to ride the bike, it takes all of your attention. Eventually, you can do it without even thinking about it. It was evolutionarily critical for us to take some new skill that required our conscious attention. If we're going to do it regularly, learn to automate it so the conscious attention would be free to scan the environment.
Michael Mannino: Exactly, yeah.
Daniel Schmachtenberger: So whatever we're doing regularly, our brain automates. [01:18:00] But their idea was that the things that we were doing the most for the automation of learning or sensory or motor dynamics, so you actually get the most neurogenesis there. Then it's actually that same neurological infrastructure that cognitive knowledge, interpersonal knowledge also runs over. So that was the hypothesis. If we do this sensory motor stuff, can we affect the brain a lot in ways that will then affect learning, math or language or [01:18:30] anything else. It has shown up that way. So I think that's pretty exciting and fascinating.
Michael Mannino: That is amazing. Four things to say about that, I'm just kidding.
Daniel Schmachtenberger: Okay.
Michael Mannino: Okay, let me see if I remembered all of them. Yeah, that's amazing. I heard about that. But in my own, so a shameless plug, in my own fitness paradigm that I have which I'm calling Embodied Fitness, [01:19:00] so that's the shameless plug there. So I'm trying to build a website, which I'll launch pretty soon. It's actually called EmbodiedFit.com although it's not launched for your listeners, but Embodied Fitness. In my own paradigm, I actually do what you're talking about. Yeah. I go to the park right here. I just recently, two months ago, took up the bow staff. So I have my bow staff right here. [01:19:30] I'll put videos up of me doing it on my website.
You're just doing, spinning motions like this, spinning behind or something like this. Just learning the coordination or learning a sense of space around you. I mean, it's mighty elite to say that's going to change certain cognitive processes in my brain. It might change my personality. That's not what I'm saying. But that's exactly what you were talking about with what you were just talking about, like juggling for example. I do juggling. I juggle [01:20:00] three balls. Now, I'm learning to juggle four.
These things take time obviously, like riding a bike or learning to drive a stick shift, right. So it depends how much time people have, but just in the shower brushing your teeth. You hear this all the time, brushing your teeth with your opposite hand. Those things have effects down the road on I think cognitive processes. So that's one thing to say. But yeah, you're absolutely right [01:20:30] that learning new things, there's this threshold in neural networks. The artificial neural networks are learned, right. Unsupervised or supervised learning, for example, they call it machine learning. Neural networks, natural neural networks, they do learn. There is this threshold of adaptation. That's called neural adaption that happens with sensory adaptation as well. So we don't realize that we're wearing a shirt now.
When we put the shirt on, we first feel it, but then the neurons adapt and we don't feel it. So the same sort of things [01:21:00] neurons do adapt, and you'd need to constantly change them. The other thing I was going to say related to that is this idea of neurogenesis, right. Different kinds of exercise do promote neurogenesis. Neurogenesis meaning the creation of new neurons, not only the creation of connections between already existing neurons. The thing though is well at least one thing that we're finding out now is that neurogenesis only happens at certain areas of the brain. Neuroplasticity is global in that sense. Neurogenesis [01:21:30] is rather local. For example, there's a couple of places in the brain where neurogenesis happened. The hippocampus, which is the space for learning and memory, at least where that initially happens, then it's consolidated in all these kinds of networks in the brain in the neo cortex.
But in the limbic system, the center of the brain, the hippocampus, there's another area, the subventricular zone which the ventricles, the outer [01:22:00] edges of the ventricles is neurogenesis happens. Then it makes sense that neurogenesis happens. You can get new neural growth actually, new neurons to grow late in life in the place where your learning for something new, which happens to do with survival. So from an evolutionary perspective, it makes sense that neurogenesis would happen in the hippocampus.
So learning new, so it's not only learning skills like a new language which you hear it can prevent or slow down Alzheimer's or something like that, but [01:22:30] there might be evidence that learning new motor acts can actually have effects down the road on cognitive processes and in maybe the prevention of pathological conditions like Huntington's or Parkinson's disease which are problems within the basal ganglia, right, deep inside the brain where dopamine is created.
Daniel Schmachtenberger: Right.
Michael Mannino: Or one of the places where dopamine is created and then sent off to the rest of the brain. So learning new motor acts is just generally a very very good thing. There's so much evidence that it [01:23:00] might be a requirement for consciousness, a requirement for having a mind, changes the mind. My whole central tenet of Embodied Fit is that the how you move changes who you are. That's maybe a crude way to put it, right, or maybe I'm taking ... I don't know, I'm making a leap there, a hasty generalization or something that there's no evidence for. But it sounds cool and there might be some evidence for that at the level [01:23:30] of science, at the state of science now, in the state of science we're seeing.
Daniel Schmachtenberger: I'm going to bite my tongue because we've got to close.
Michael Mannino: Okay.
Daniel Schmachtenberger: I will just say we have a paper that we wrote and we'll publish soon. But I'll send it to you which is on literature review of adult neural restructuring. So it is synaptic caving and synaptogenesis, neurotophogy and neurogenesis.
Michael Mannino: Okay.
Daniel Schmachtenberger: The breakdown of old structures, development of new ones, all of the mechanisms that we know about in literature. One of the things that's profound [01:24:00] is that there is more neural restructuring capacity into late age from the scientific literature that almost anyone would think about. One of the reasons that we don't have that much brain changes because we just get stuck in behavioral patterns where we don't do things at all about different, behavioral central patterns. Then if you could actually get deep enough behavioral changes that the brain's biological plasticity is actually still pretty profound.
Michael Mannino: Yeah, even later [01:24:30] age. I was just going to say something and I forgot. I lost my train of thought because I was listening. So-
Daniel Schmachtenberger: It's okay because I had a question for you.
Michael Mannino: Okay.
Daniel Schmachtenberger: My question was-
Michael Mannino: See I'll remember it.
Daniel Schmachtenberger: Embodied Fit is not up yet, when it is up, we'll share it with people.
Michael Mannino: Thank you.
Daniel Schmachtenberger: I'm happy you're doing that, so changed the way you move and changed the way that you think or are. If there some basic things that they were the highest leverage physical movement dynamics for people to engage in, [01:25:00] what might you share?
Michael Mannino: Okay. Let me think about that. That's a good question. But before I say that, I remembered what I was going to say. In the context of what you are all about at Neurohacker Collective, human optimization and individual optimization, right, and that leading to societal optimization. I know you have a clear definition of what you mean by optimization. I think learning new motor acts and practicing different movement patterns is [01:25:30] a great way, is sort of a biohacking way, right. It's a DIY, a do-it-yourself way to change yourself. I think my personal experience and what there's evidence for, objective evidence for is change who you are for the better.
So a way to optimize yourself is to learn different movement patterns. Back to your question about which kinds of movement patterns would do that, again, there's no general evidence. There's only evidence about very very particular [01:26:00] things because that's all we can really do right now in science and trials, clinical trials is to look at well, how does this thing change this thing. Let's get rid of all this other confounding effects. I mean, a study that I talk about in the talk is about strength training and lifting weights.
Strength training can actually have effects and decrease white matter track legions in elderly women. So that's [01:26:30] a very very specific thing like wow, lifting weights can actually do that. Why? What is the causal mechanism and why is it doing it? But why is it so specific? That's a scientific question, an empirical one that I think could be answered. But my point is that I don't know. I would say yoga is probably one of the ... We already talked about this. I would definitely say yoga is something very very problematic.
Daniel Schmachtenberger: One of the things with yoga is that [01:27:00] yoga is a fairly complex set of dynamics.
Michael Mannino: Right.
Daniel Schmachtenberger: As you go through the levels, it keeps changing and you keep doing different things. I'm also hearing high intensity interval training has certain effects. Weight training has other effects and running has other effects. Juggling has other effects. One of the things I'm hearing you say is that people should be moving and that if there's a movement thing that they've already got really well down, doing something else will provide additional benefit.
Michael Mannino: Right. [01:27:30] So there's this ...
Daniel Schmachtenberger: As far as learning and stimulation goes.
Michael Mannino: Right. So I consider myself not only in fitness but probably in other things too. I mean, I have three different wildly different degrees and in fitness as well, a jack of all trades, master of none kind of thing. In fitness, that might be better to have rather than to ... Or at least in terms of cognitive processes, right, in terms of those kinds of things in that context. Now, don't get me wrong, I don't want to say this [01:28:00] or dumb this situation for simplicity's sake but not all athletes, right, are smart or ...
I read an article on Big Think a while ago saying, "This is the exercise for smart people, running," because it increases the functional connectivity like I said in the prefrontal cortex which is involved in decision-making, orienting your goals, thinking about the future, things like that, and also emotional regulations highly involved in emotional regulation. So there's that bit of evidence but [01:28:30] yes, learning different new things, taking the time even if you're not going to get good at them. Like me personally, I can talk just talk from personal experience, I do all kinds of different things. I love to run. I love to do body weight exercise with the gymnastics rings.
I love to trying to master to flexibility, mobility, strength and control just with my body, right, just with my body, and also coordination, right. So I do all kinds of different things. Like I said, I just took up the bow, something [01:29:00] completely new. I go to a park and I bring my bow. I juggle. I'm trying to learn. I do hand stands and all kinds of different things like that. But I'm not a master at any of them, but I'm trying to like dabble and become good at each of them.
Daniel Schmachtenberger: I think for people to learn more about what you're saying-
Michael Mannino: And there is an endless resource about that, yeah.
Daniel Schmachtenberger: What's that?
Michael Mannino: There's an endless of resource of sets of movement to learn.
Daniel Schmachtenberger: I think Ido Portal is a good place for people to go, learn more-
Michael Mannino: Yeah.
Daniel Schmachtenberger: Since various movement patterns [01:29:30] are what he specializes in. Specifically, he does talk about the evolutionary biology of movement patterns driving neurological growth and cognitive effects so.
Michael Mannino: So let me just say one more thing. If Ido Portal, I've been studying him for a while. I actually prefer Mike Fitch, just to give another plug, and animal flow. I think that's fascinating. I think it encaptures this idea of Embodied Fitness very very well. However, I will say this about Ido Portal, it's funny because the connection [01:30:00] was so perfect and I learned this after I did my talk. But Ido Portal trained Connor McGregor, for mixed martial arts or whatever it was. I wasn't too sure.
I was reading Connor McGregor's Wikipedia page. On the right hand side, it has all of Connor McGregor's trainers for different things, right. This one's for nutrition, diet, etc. For Ido Portal, it was movement. You could click on the link of movement on that page. So I clicked on the link of movement. It takes [01:30:30] you to the Wikipedia page of motor coordination. If you go down that page or read the section, there's a whole section of coordination dynamics that it mentions Scott Kelso from the Center for Complex Systems and Brain Sciences, where I am and that whole field. So it was just that that connection was very ...
Daniel Schmachtenberger: Cool.
Michael Mannino: Very synchronistic from a Carl Young sense. It was really cool.
Daniel Schmachtenberger: Cool.
Michael Mannino: Yeah.
Daniel Schmachtenberger: Well, Michael, this has been fun. I appreciate you being here with us today.
Michael Mannino: Thanks, Dan.
Daniel Schmachtenberger: I'm excited that you are sharing [01:31:00] the applied neuroscience fitness work with people soon. We'll share that when it comes.
Michael Mannino: Thanks.
Daniel Schmachtenberger: We'll share a few link ...
Michael Mannino: Soon.
Daniel Schmachtenberger: To your TED Talk and to some other resources that we have in the show notes. It'll be useful.
Michael Mannino: Okay, thank you.
Daniel Schmachtenberger: If anyone did get inspired to study complexity science or complexity neuroscience, awesome.
Michael Mannino: Yeah, for sure.
Daniel Schmachtenberger: Yeah. Just a bunch.
Michael Mannino: I think it's the future. It's the future. It's the future of human optimization, understanding the brain from [01:31:30] a complex systems perspective.
Daniel Schmachtenberger: Thanks for being here with us.
Michael Mannino: Thanks, Daniel. I appreciate it.
Daniel Schmachtenberger: It's good, my friend.
Michael Mannino: Take care. Bye bye, you too.