Gut Instinct, Hard Science: The New Neuroscience of Intuition

People often want to misdiagnose intuition. They want to call things that— that they want to use terms like precognition as into— or they want to describe experiences that we might label precognition as intuition. There's a whole bunch of stuff that way. We are talking literally about a gut instinct, embodied predictive form, as we'll talk about, of pathfinding. We think intuition is a form of pathfinding in the brain, a way of finding the next available best option. It's anchored in two very, very, very important and modern theories of neuroscience.

I'm Ryan Wicks, Chief of Staff at the Flow Research Collective, and today, as always, I'm joined by our Executive Director and bestselling author Stephen Kotler, along with FRC's Chief Science Officer Dr. Michael Mannino. Today, these two are going to break down an upcoming paper that's set to be published in Nature, widely considered the most prestigious science journal on the planet. Today's topic: the neural dynamics of intuition. Or as Stephen put it earlier this week to me, we're going to do intuition and maybe a joke about God walking into a bar. What we're really going to get here is a deep dive in how the brain can know before you know, and what's really happening when high-speed decision-making takes over and why intuition may be a hidden engine beneath flow and peak performance. And then after the breakdown, if we have some time, we will open the floor for a live Q&A. So feel free to drop your questions in the chat as we go. Without further ado, Stephen and Michael, let's just get straight into it.

The paper we're going to be talking about today is literally the culmination of research that started when I wrote West of Jesus on the nature of intuition and its relationship with flow. 10 years ago, I got to know Dr. Daniel Kahneman, the Nobel laureate who just passed, when I was writing Abundance with Peter. And we had a debate back then about cognitive biases blocking intuition and can you trust intuition and all his ideas. And we very disagreed. And he was a very tough, pugnacious guy, so he was hard to disagree with. But that debate went on and on. I actually got to meet him 5 years after that. We picked up the thread, kept arguing about it, and it never got resolved. And I decided to start working really heavily on the neurobiology of intuition. As a way to prove my argument to Danny. And unfortunately, he died before this paper came out. So this paper is actually my rebuttal to Daniel Kahneman in a weird sense. I think I'll share my screen now so you can see what I'm seeing. No, let's go back.

Yep.

So this is the paper. It is, as Ryan mentioned, it's going to run in Nature Communications Biology. It's in press right now. Michael submitted the final drawings that were required, or diagrams, yesterday, and we think it's going to be out in the next 2 weeks. Our co-authors on it are really kind of some of the most amazing neuroscientists working today. Dr. Karl Friston, who's at University College London, he was our partner on our flow and intuition paper that we just published. And it came crazy news because Karl, before we published that paper, was the most cited neuroscientist in history. After we published the paper, he got shortlisted for the Nobel. So that paper has now been viewed like 5,000 times, which just doesn't happen with scientific papers. So he's back. Uri Puzaki is at NYU. He's the world's leading expert on brain rhythms and brain oscillations. Dot Kelso is at Florida Atlantic. This is who Michael studied under, and he's the godfather of social neuroscience. Guillaume Dumas is at the University of Montreal, and he is is the world's leading expert on interpersonal synchrony. And what's really cool about this paper, on top of the fact that it's a 30-year project, is that these are people in very different fields in neuroscience. And the Flow Research Collective was created to try to unite these fields. And this is sort of the best example of, of the work we, we set out to do. So it's very exciting from that perspective as well. So I'm going to jump right into it. The big picture ideas, um, this is a paper about intuition. People often want to misdiagnose intuition. They want to call things that, that they want to use terms like precognition as into, or they want to describe experiences that we might label precognition as intuition. There's a whole bunch of stuff that way. We are talking literally about a gut instinct, a embodied predictive form, as we'll talk about, of pathfinding. We think intuition is a form of pathfinding in the brain, a way of finding the next available best option. It's anchored in two very, very, very important and modern theories of neuroscience that we've talked about before, the free energy principle and metastability. Metastability originated with Scott Kelso. The free energy principle originated with Karl Bristen. And, uh, we'll talk more about these things as we go along. Um, I want to start by defining intuition, how we define it. It's an experience-based process resulting in a spontaneous tendency towards a hunch or hypothesis. This is, in a sense, what we mean by pathfinding. Now, in this definition, you see a number of cognitive processes. First of all, you see non-conscious processing of information. So something going on below our awareness. There's a rapid awareness when intuition comes into the frame. You're aware of the fact that you're having an intuition, and it's a felt certainty. It's often an embodied experience, right? We have a gut instinct. We have a tightening in our chest, and that comes along with the intuition. To distinguish this a little bit from insight, intuition doesn't have language around it. The brain doesn't know, can't exactly frame this hunch in language. Once we put language around it, it becomes an insight. It's a slightly different category. We'll talk about that as we go along. Michael, did I leave anything out?

Can you hear me?

Yes.

Yeah, no, I would like to— no, I don't think so. I think I would just— we define it as a gut feeling that helps us move through life. And I like that phrase because, Stephen, you coined this term pathfinding, and it's literally when we move through life, we guide, we get guided through life, we're you know, it's quickly figuring out what to do next, especially in situations where, you know, stopping to think might slow us down. And so, I like that phrase. Just, it's a mechanism that helps us move through life. If you think about that.

Interesting.

Literally motion. It's literally movement, pathfinding.

The point Michael just made, why did intuition evolve? You have to start with exactly what Michael said. Brains evolved to move our bodies to uncertain environments. And predicting what happens next is absolutely fundamental to movement and by extension cognition. Intuition extends on this. It's a fast predictive mechanism for agency. Agency is a very precise term. It is proto-consciousness. Stuart Kauffman, sort of the godfather of complexity biology, wrote a brilliant book called Reinventing the Sacred that is almost unreadable, but it's really brilliant. Um, and he's talked about agency as requiring 3 things. Once you have a decision-making— once you have decision-making ability, sensing, environmental sensing, um, and memory, you have agency. By this definition, every conscious being on the planet has agency. All animals, all insects, our cells have agency. They will swim up and down gradients. They will make choices. So agency is a very, very early form of cognition. Intuition, we are saying, was a pathfinding mechanism that co-evolved around the same time as agency. It was our first internal directional signal. Which way should I go? What decision should I make? This is how that signal showed up in consciousness. And this is a great, uh, Rodolphe Nina's quote, and who is a neuroscientist that both Michael and I love. Michael, why did I just blank his book?

Eye of the Vortex.

Eye of the Vortex. Thank you. One of the coolest books in neuroscience. Really a neat book. And this is his quote. The brain's control of organized movement gave birth to the generation and nature of mind. This is again the idea that our brains evolved to organize movement and gave birth to the nature of mind, meaning including intuition. So as Michael also mentioned, I borrowed a term from the field of robotics, pathfinding, to describe how intuition functions in the brain. In robotics, pathfinding is an efficient search through high-dimensional space. So lots of options, lots of variables. How do you figure out where to go next, right? In Brains, we make the argument that intuitive navigation evolved to generate coherent action, and it evolved combining a couple of, like, previously evolved processes. The first is memory. We talk about that with agency affordances. Is the technical term for our ability, when we look at objects, we rarely see objects. This is J.J. Gibson's big insight. He's a vision researcher. We don't see objects, we see opportunities for action. So if you see a, if a frog and a fish see a lily pad, the frog sees a place to sit on and the fish sees a place to feed beneath, to hide from birds of prey, right? We see what the objects afford us. That's where the term comes from. And finally, goal sensing. What do I want to do next? The ability to have goals. You combine these things and you get intuitive pathfinding. So this is a very early evolutionary development, is our argument. Not just humans, though it goes places in humans that it hasn't gone in other species. And there's essentially— Michael, please, over to you. What did I screw up?

No, you didn't screw up anything. I just want to add something. Go back one slide.

Yes, sir.

I just wanted to flesh this out. Maybe we talk about this later, but so when we think about the normal paradigm or the traditional paradigm in neuroscience of we get sensory input and then we get processing and then we do motor output, right?

Mm-hmm.

And stimulus response. What we now know, and thanks to the work of like Steve was talking about J.J. Gibson and now more theoretical frameworks like Karl Friston, is that you shouldn't think about it as first we get sensory input, second we process information, third we do motor output. You could actually invert that and first we think about motor output. Our brain looks out there and then changes the world or itself to then affect the way sensory input gets— comes into the brain. And so it's not really stimulus-response, but you want to think about it as response first and then stimulus second. It's a counterintuitive notion, but that's what modern neuroscience is showing us how the brain works. That's it.

Excellent.

Thank you.

That was good. Awesome. So there are 3 forms of pathfinding that evolve, right? Like, first came intuition. This is fast, embodied, and it's really— and this is really interesting about intuition. It's a go/no-go signal. Don't walk down that alley. Go into that room. Like, it's that level of information. It doesn't contain much more than that. And often we don't know the origins of the signal. We just get the signal. We're not even quite sure where it originated from because it came up, it bubbled up in the unconscious. Insight, that's sudden coherence. Suddenly you're like, aha, I know, I know what this, this is. I know why this is. I know what it means. You have context around it. The other way, the slow way, the top-down way is analysis, step-by-step logical navigation. These are all forms of pathfinding. How do we make our way through the world? Michael?

Yeah. Onward.

Onward.

I think that's a great thing.

So when we started looking at this puzzle of What the hell is intuition? How do we explain it? How do we think about it? We had a bunch of ideas that came from a bunch of different researches we sort of brought together into this puzzle. The first kind of— there was a huge body of research done on what are known as spontaneous judgments of coherence. This is a really— this is sort of like linguistic pathfinding. And you'll be given 3 words that seem randomly associated, and then you'll have to pick a third word that coheres, that links them all together. And when we do studies of coherence judgments, these kind of intuitive coherence judgments, you find the orbital frontal cortex lights up. Now, this says that this is the portion of the prefrontal cortex that sort of evolved with us around intuition. Now, the orbital prefrontal cortex, as you would imagine, it's the oldest structure in the prefrontal cortex. Prefrontal cortex is the newest structure in the brain. This is the oldest structure there. It's the first one to evolve, which also maps onto intuition being this proto system. You also see the anterior insula get involved. This is involved in interoception and gut feeling. So this is what's generating the signal. Now, other research, some of the coming out of this research, some coming out of other studies, have linked both the hippocampus and the entorhinal cortex to intuition. Now, this normally has been thought of in terms of memory, and that's true. One of my big insights is the hippocampus and the entorhinal cortex are memory storage, but they're also pathfinding. When we're trying to find our ways through ideas or find our ways to the world, they evolved originally these structures to help us navigate the world. We had to remember where was the ripe fruit tree at, where's the cave I could hide in. All these are things we needed to remember along the way. That's what the hippocampus and entorhinal cortex evolved to do. And finally, the basal ganglia was involved, and that's goal direction, right? And implicit learning. So unconscious learning, finding without conscious involvement in the conscious mind. Michael, I'm sure I left something out here.

No, no, I just wanted to add again. So the, when we think about the hippocampus, go, you know, Stephen, go.

I'm sorry. Yeah, I'm sorry.

The hippocampus being, it's been called the GPS for the brain, right? It helps you remember where you parked and things like that. And there are specific cells within the hippocampus that actually map out where you are. And so there's a spatiotemporal space and time component that the hippocampus actually does. And it's not just The point here is it's not just a GPS physically throughout the world. This is back to this whole idea of it's a GPS for how we move through life, the decisions that we make. And a very interesting study came out last year showing something like this, actually, that it found that we have social networks there's one degree of separation, two degrees of separation within our social networks. And actually the brain thinks about those social networks with motor parts of the brain and with the hippocampus. So it's actually mapping.

Yes.

Space. So that's why that's a brilliant insight of the, which you'll, we'll come to, Stephen, of yours, the hippocampus.

Yeah. One other thing that there's a division of labor. Hippocampus, as Michael pointed out, is place cells, locations. The entorhinal cortex does pathfinding, the map between the locations and predicting where should we go next. It's the part of the brain that's always sort of solving the traveling salesman problem, or it's the part of your brain that goes, okay, if I stop by Walgreens on the way to the grocery store before I get the kids, I can drop off the map. That's the part of the brain that's doing that.

And now the interesting thing here is that this traveling salesman problem is not just a spatial problem of mapping, it's actually a problem of making decisions and how the brain makes decisions just in general.

So that's— all right, so one of the really big clues on our way to this paper, when I was thinking about intuition, um, after my argument with Daniel Kahneman, sort of before Michael and I started working on this formally together, I had read a paper, I think it's in the Cambridge Handbook of Imagination, which is phenomenally interesting, by a woman named Colleen Seifert, who's at the University of Michigan. She's a psychologist, and she was working on intuition as well. And through a bunch of research, sort of discovered that the brain— she predicted basically that the brain solves unsolved problems. So things that we think about really hard, but we can't find the next step. And it's a pathfinding problem, right? We've got this whole construction, we're trying to solve it. What's the next step? What's the answer? What's the solution? And her argument was that these were— that these kinds of problems, because they, they can come up with a lot of emotional strife, right? If you can't solve something, you get frustrated. We know this from flow's struggle phase, that those problems get stored in a special area of the brain. Now, When you translate that into computational neuroscience and modern neuroscience, we talk about those special areas, maybe not in terms of anatomy. We talk about them as attractors and basins of attraction. And so these unsolved problems form networks in the brain that will attract other inputs so that in a later time, if we walk into an environment that might contain the clue that solves our problem, problem, we're going to notice it. The brain stores unsolved problems in a network that is readily accessible so that if we walk into situations, for example, high in novelty, the brain goes, oh wow, there's a lot of new stuff in here. Maybe something in here can solve some of those open loops, those unsolved problems, those things I've been thinking about for a while. This is not a very unusual idea. It's very much related to how long-term priming works, and that's research going back to the '70s, and incubation effects. If you've ever heard me talk about, for example, the MacGyver method, where you can sort of program your subconscious to solve problems for you, this is a methodology based on incubation effects. And Colleen did a lot of research on it and coined the term opportunistic assimilation for the process. So you walk into a room that's potentially high novelty, they could solve these unsolved problems, and you have opportunistic simulation. Basically, like, those attractors start functioning, they bring in other ideas, suddenly you have a solution. How'd I do?

Perfect.

Perfect. Good. All right, next. Here was the second really big insight, and this is how Yuri Buzaki got involved. I was reading Yuri Buzaki's second book. His first book is called Rhythms of the Brain, and it's sort of the masterwork on brain oscillations. He followed it up with a book called Your Brain from the Inside Out. And it's a really— it's, again, one of my favorite neuroscience books. It's a very complicated book. Michael and I, I think, didn't we?

Yeah, we read that together.

We went chapter by chapter and sort of did one chapter a weekend, would meet and discuss. We book clubbed the book, basically. And along the way, that's fun. Buzsaki is talking about this really interesting phenomenon that happens in the hippocampus, which is known as sharp wave ripples. So these are a known feature. They show up. They were first found in rats. They'd show up in humans. And it's basically that we see a sharp wave ripple is, if you look at it on an EEG, it's a big spike. That's the sharp wave followed by ripples that spread out across the brain to sort of activate attractor basins in a sense. And what they are is a compressed replay of past experiences and possible futures. So the brain is basically taking stuff that happened in the past and using it to make predictions about the future, where to go next kinds of predictions. Associated with memory and creativity and problem solving and pathfinding. And it occurs during sleep and wakefulness. And as I'm reading this, I went, holy crap, I'll bet it happens with intuition. I'll bet that's opportunistic assimilation. That's the mechanism of action. You walk into a room high in novelty and the brain goes, oh, look, it's delusions. Maybe it sends out a sharp wave ripple into all the attractor basins to see if it can close a loop. If for no other reason, open loops, problems you can't solve, they gnaw at you. They burn energy. The brain is super efficient. It always wants to save energy. So this is a fast way to solve problems and maybe save some energy when there are possible solutions around. And it's a pathfinding mechanism. And I thought, wow, this could be intuition. So we came together, to write this paper. And that's sort of— this is what I brought to Michael and said, okay, what do you think? What should we add? How else do we need to think about it? And over to you, doctor.

Okay. That was great. Great work, Stephen. So let me just define the— you could take questions whenever, but I'm happy to answer. Stephen, you want to take them now? You want to take them, wait for the end?

I think we should go to the app because God knows when we're going to shut up.

Okay, good point. Okay. Okay. So let me just also define attractors for folks actually.

Oh yeah.

It has a lot to do with the free energy principle and the other framework that we invoke, metastability. So it's actually a term from physics, from nonlinear dynamical systems. And what it just means is it's a stable state. It's a stable state that the brain returns to, or parts of the brain return to. Analogously, or not even analogously, you could think about like if I have this cup of coffee, if you could see it, the coffee is hot, right? I put it down and then it will return to a stable state in equilibrium with the rest of the room, right? So it will cool down versus if it's a cold cup of water with ice, it will warm up. So it's that equilibrium the room temperature, and getting that is an attractor. So it's a stable state, and the brain finds these stable states, and it likes them, and it wants to return to them. So if it gets pulled out of them, it wants to return to them. So that's what this whole idea of hippocampal sharp wave ripples do. And so all of this is great. This is mechanisms, neural correlates, different brain rhythms. So very empirical. What we wanted to do is ground all of this work and intuition in some theory, because then we could make testable hypotheses and predictions. So grounding this in some theoretical frameworks is very, very helpful. And that was the, that was the point of bringing in the free energy principle and Karl Friston and Scott's work on metastability. And these two principles, these two theoretical frameworks are are very complementary. They're not opposed. And this is really, there's an overwhelming scientific consensus in modern neuroscience that this is how the brain works. So the free energy principle, it's a relatively simple idea. And we've talked about this before. And Stephen, feel free to piggyback, that the brain is a prediction mechanism. It's a prediction engine. It makes predictions about the world. It makes its best guess, and what the brain tries to do is minimize uncertainty. It doesn't like surprise. It wants that, and that's getting pulled out of that attractor, and the brain wants to get back into that attractor. Very helpful for survival from an evolutionary perspective. And so you think about the brain as a prediction mechanism, and if it makes predictions again about sensory input, right, about sensory input. If the predictions match and they're right, okay, we're calm, everything's fine, don't need to do anything. But if they don't match, that is, if there's an error or a discrepancy or a difference, literally a mathematical difference between the brain's prediction and the sensory input, then what it can do, two things to resolve that. It can change its internal self or it can change the world. Okay, so when it changes its internal self, that means it changes the beliefs, the prior assumptions, the internal mental models that we have either about ourself or about the world. Or it can take action, and that's something called active inference. The brain can produce motor outputs to change the world and to change its environment and to change the sensory input. So that's the idea of the free energy principle, and that's how the brain works. So we're grounding intuition in this free energy principle framework. It's a rapid subconscious uncertainty minimization. So it's trying to minimize that error, that uncertainty. Intuition is a predictive thing. It's a predictive mechanism. It's a predictive emotion or a cognitive process, and that's representing the expected outcome of That is that surprise of a particular action that we're taking. That's path. That's the path. Okay, Stephen, next. Is that— do you want to—

yeah, the only reason the summary signal, folks, is, uh, you— when you get the— you get one emotion, right? You get a gut sense, don't walk down that alley. But there's a bunch of different analysis. There's a risk assessment, there's a future prediction, there's a whole bunch of different things coming together. We don't get individual conclusions. All that information gets summarized into a single signal very, very rapidly.

Right. Yeah. So it's trying to minimize that error, right? And so metastability is another framework coming from Scott Kelso. And these two, Theoretical frameworks for how the brain works are very complementary. Scott and Friston have given many talks together and published papers as well. And just a larger high-level point here is that the reason why this is important is because we want a theory of how the brain works. We want a very grounded theory. Think about like the theory of evolution or the theory of gravity. Those theories make predictions. They describe how things work and they explain things. And so we want that of the brain as well. As well. So that's what these two things represent. Metastability is the— we have it on this slide too, the rapid switching. So metastability is a— what it basically says is that different parts of the brain can talk to one another, and they can connect and talk to one another, and at the same time they can do their own thing. Now this is really good because it allows for what's called cognitive flexibility. Being able to transition between different, making rapid decisions, like which what we're talking about intuition in the world, right? When that prediction error is high, we need to rapidly figure out what to do. And so what Scott came up with this theory, now it's very well tested, very rigorous, very mathematical, is that the brain can do that at the same time. It can integrate and it can segregate and it can really switch very quickly. The analogy that's normally given is if you think about a tennis player, a receiver receiving a serve, you know, it's, it's, it's poised. The tennis player's poised to go left or go right or go high or go low very, very quickly. So it's on that, what we call edge of criticality, able to do something really rapidly and switch really quickly. So that's this idea of metastability.

And the other thing that's really important about the edge of criticality is you have— on the edge of criticality is right at the edge of chaos. There's maximum complication in the system, so the greatest possibility for discovery.

Yeah, great point. And in fact, the brain is very, very chaotic, and it exists at that edge of chaos where different rhythms of the brain, back to Uribuzaki, are sort of simultaneously existing at any one point. And in fact, when you get large swaths of the brain to synchronize together, that's actually bad. That's epilepsy. And that's associated with all kinds of neurodegeneration like dementia and Alzheimer's. Large parts of the brain are really like synchronous. So you need this balance between synchrony and not being in synchrony and existing right at that edge. For optimal brain efficiency.

And metastability actually gets its name because if you look at it, what it looks like on an EEG is two brainwaves that almost come into synchrony, right? They almost start moving at the same time, but right at the last minute, they pull apart and they break apart. So, it's like almost synchrony, break apart, almost synchrony, break apart, that sort of rhythm in the brain that is the signature of metastability.

Yep. And then, you call it metastability because back to attractors, stable states. But the meta, we want to almost get to that stable state but be able to pull back and switch really quickly. So both free energy principle and metastability are very, very grounded in this idea of embodiment and embodied cognition. And Stephen, you already talked about interoception, I think, but the idea of embodied cognition, um, or embodied mind, which we've talked about quite a bit before, is the idea that the body and how it moves plays a huge role in cognition and consciousness and how all cognitive processes like learning, working memory, perception, and so on. So all of those things are really informed by the body and how it interacts with its environment and moves around. And so cognitive navigation is based on this idea of embodiment agency, and Stephen already talked about affordances. So again, think about sensory input, information processing, then motor output. And body cognition again flips that on its head and says motor output is first, and then— or can be very first— and then changing the sensory input. And so interoception is this idea of paying attention to what's going on inside the body. That idea of that gut feeling. So being able to sense your own heartbeat, being able to sense the temperatures in your body and things like that, that's interoception, as opposed to paying attention to your external world, it's exteroception. And so we argue that because the free energy principle, free energy principle and metastability are grounded in this idea of embodied cognition, and interoception, that intuition is also this non-conscious embodied mechanism. Now we combined this with this idea of corollary discharges. So there's a lot of terminology here and in neuroscience, but really it's corollary discharges. You think about it this way: when the brain sends a signal from one area to the other, it simultaneously sends a backup signal. In another way. And that backup signal is called a corollary discharge. And that, Stephen argued, uh, and I— we think rightly so from this paper— is the summary signal. So Stephen, I don't know if you want to pick it up.

Yeah, the only— so the, the, the, the only bit that Michael left out that was great, uh, is the corollary discharge is another one of these things that evolved out of motricity, out of the fact that the brains were designed for movement. So It turns out that if you're going to reach for a tree branch, your brain, before you make that movement, predicts that you're going to make that movement. So it predicts what's going to happen after you make that movement. Otherwise, it won't know. And so it basically sends a signal that says, hey, I'm making this movement now as you move to back the signal up so it can interrogate it later to see did it work or did it not work? And I realized that that was the same thing that was happening with intuition.

And another very simple sort of analogy that's sort of well known in neuroscience now is that's actually why we can be tickled because you can't— your expectations are messed up because you can't predict when someone is going to touch you and that corollary discharge gets cut off. And so that's actually one of the reasons why tickling happens. And it also happens in different disorders. Neurobiological disorders as well. Sometimes that gets messed up and the corollary discharge gets cut off, and that can create problems. Next slide. Okay, so summing up, pathfinding as active inference. This idea of the brain being able to take action can change the world and find its way through the world through intuitive, rapid, non-conscious decision-making. We define, we literally define in this paper this idea of pathfinding as this active inference, which is again a core, core, core tenet of the free energy principle. So the sharp wave ripples are the neural correlate, the neural mechanism, the neurobiological mechanism to rehearse future plans, to make those predictions. Free energy, the brain works by trying to minimize that and make the correct prediction. And then planning as inference under constraints. So you want to think about this. There's actually another term which we introduced, which we talk about in the paper, called the action-perception cycle. So the brain cycles through taking actions and changing perception, and then that then has an effect on new actions. And so the brain goes through this action-perception cycle by continuously moving through the world as active inference.

One thing to note here that helps make this make sense. So this is how we work all the time. Yes. But when we say action, right? When he says the action perception cycle, usually that action is nothing more than a saccade. So the brain is going to predict something that's going to happen in the world and then it's going to move its eyes to try to match that prediction. You're going to move your eyes to try to match that prediction. That's why your eyes move around all the time. And if it doesn't move physically in the world, it can also move cognitively by having a thought that can also serve as an action. So in the context of the action prediction cycle, thoughts are actions.

So, so, Stephen, can I just show the figures that we've produced in this paper?

Hold on, let's go to our last slide and then yes.

Okay, good. So again, this allows us to come up with testable hypotheses. So moving from theory to actual experimentation, which is very good to confirm or disconfirm those, those, those theoretical elements. And so a couple of the testable hypotheses that this paper produces are: do ripples— these sharp wave ripples— precede intuitive decisions? That's a very testable measurable thing that we can go into the lab and look at. Measuring the hippocampal sharp wave ripples and then giving folks different protocols. There's plenty of different protocols out there like the Iowa Gambling Task or the Wisconsin Card Sorting Task. Pretty standard experimental frameworks and protocols that you can actually test. Another one is, do attractor landscapes store unresolved problems? So we can come up with experimental protocols of giving folks a lot of information, they can't solve the problem, they get new information, they solve the problem, and then does that actually change the attractor landscape in the brain? Which can be measured. That's the whole point. All of these things can actually be measured, quantified. And Stephen, I'll let you handle the can intuitive prepared minds be measured? Because the prepared mind hypothesis is basically what you were talking about with the opportunistic assimilation.

Yeah, it's the— if these things are true, we should maybe through corollary discharges be able to measure the prepared mind hypothesis and offer this opportunistic assimilation. And what's cool about sort of all of this stuff and where this leads us is this has some pretty practical applications. One, it gives us a much better way to understand intuition and uncertainty. In fact, one of the things that comes out of some of this work is that we know that if you have an instinct, what's the difference between instinct and intuition is a really thorny, they're sort of it's language from two different periods in science. They don't really work together. But one of the ways they think about it is instinct tends to be a lot around very basic needs. And one of the things that we know is if you have a strong intuition that is about kind of one of your basic needs—sex, hunger, money, safety and security, that sort of stuff— you're probably going to make errors. This is why we always say never trust the dopamine. It's sort of the same. It's the same thing. Like, think about how often that, you know, the guy in the bar is sure that the woman across the room is hot for him and then walks over and introduces himself to her and she's like, just get lost. What are you doing here? Right? That signal is wrong. And it's because sort of basic primal needs and the dopamine that you get around them can block Intuition a little bit. So there's really interesting kind of ramifications for trusting intuition and for how to amplify intuition. Right. We know if this theory is right and Colin Seifert's work is right, it means that spending extra time struggling in the struggle phase can actually prime the brain for future learning. And things along those lines in really interesting ways, which has ramifications in creativity and innovation discovery. What else did I leave out, Michael?

Yeah, no, we do address some limitations in the paper as well about intuitions can be wrong. And Colleen Seifert gives some great examples in her paper, Stephen, I remember about like Feynman figuring out the problem of the Challenger, the guy who discovered the benzene molecule. And there's a bunch of different models out there, like the prepared mind hypothesis, the creative cycle, the— Stephen, your work on the flow cycle, and so on. So all of this, all of it really highlights around those, those different roadmaps, those different cycles, creativity, innovation, discovery, that kind of thing.

Yeah, that's all I was going to say. Michael, Deborah had a— somebody had an interesting question. Yeah, it was Deborah. Are attractors major neural pathways? And the answer is no, but interesting. Yeah, they're probably networks.

Yeah, no, so that's what I was going to say. So let me— this would be a good time to share the figure. So let me share my screen actually.

So I'm done.

Okay. So here is one of our figures in the paper, and we're just sort of highlighting those different neuroanatomy that's involved in intuition, the insula here on the left side, and then this is the orbitofrontal cortex. This is the anterior cingulate cortex. This is the hippocampus and the amygdala. This is the basal ganglia in the center brain, and this area over here is the precuneus, which is also involved in non-consciousness and non-conscious reasoning. And so we think about these— are attractors neuropathic? They can, yeah. So like They're— we want to think about these brain areas as working together. So in something, as in neuroscience, it's called functional connectivity. They're functionally connected even though they're not anatomically connected. And there's a connect— there's an ideal connection, and that ideal connection is an attractor that we— that it returns— that it tries to return to. And now the other figure in our paper is this one. And so this one just tries to tell you about this whole neurodynamical framework for intuition. It's just trying to visualize that the primary motor— we talk about hierarchies in neuroscience and the brain. So there's a hierarchy in the primary motor cortex going out, sensory motor and sensory information coming in. The brain creates this internal model based on the free energy principle. This is— this centerpiece here represents the attractor landscape. So you think about these trajectories through this high-dimensional space, and it tries to return to these states. And the states are like, you know, you think about it like as a valley, and a ball drops it down a valley, and it just rolls back and forth, back and forth, and it just stabilizes to that position. And that's that those brain areas connecting. And those are those attractor states. And this here represents the opportunistic assimilation. So you're the neuroscientist that, Stephen, I think this was your—

Yeah, it was his story is the neuroscientist is walking down a street after failing to solve a problem and looks up and sees an oak tree and the branches remind them of dendrites, which solves the problem.

Perfect. That's so great.

And then the action perception cycle, and then the, the, the short sharp wave ripple that exists in the hippocampus as the neural mechanism for opportunity.

In other words, when our neuroscientist looks up at the tree and goes, wow, that branching structure, before the word familiar gets— comes out, we get a sharp wave ripple. Yeah, perfect. Yeah, right. Like, that's, that's sort of what that diagram is. All right, so, uh, We will open it up. Spare. Great.

Yeah, we'll open it up for Q&A.

Thanks for your patience, folks. Yeah, sorry.

But before I kick it over, uh, to all of our guests here, when you were talking about, um, sharp wave ripples, it made me— is there any influence or relationship between the P300 waves, that surprise, uh, that's associated with flow?

Between Hippocampal Sharp Wave Ripples and the P300? Yeah. So, the answer— so interesting. If the sharp wave ripples find a solution, right? They come up with a solution. If you have opportunistic civilization, the next thing that's going to happen, or among the next things that are going to happen, is you're going to get a P300B, which is what shows up before flow. That's surprise, better than expected results. Right? Right. So it's, oh, wow, that worked. Right? So suddenly you were like, oh, wow, I solved that problem, right? That, that really good feeling you get with the aha moment, that sort of, that sort of thing. And as we know, a couple of those in a row, and you're in flow. Right.

And that, that I saw a relationship between them.

That's right. You know, if we're dealing with like reading-based flow states, Ryan, right? The mechanism in is is usually this sort of thing. You're reading, you have an opportunity, you have an insight, right? Something in the book triggers something in your mind. It leads to an incident, and that can day trip you into flow very quickly. Yeah.

Cool. Cool. Last one. Edge of criticality. And, you know, we often talk about challenge skills sweet spot. Do you two see any relationship there?

Yeah. Same. Yes. Cool. Yes. Cool. That, that's, yeah, very much so. Sort of the neurodynamical version of that in a weird way.

Yeah. All right. Right on.

But it's the, it's the sweet spot for high performance. Right. Mm-hmm. Yeah. In both cases. Yeah. Okay.

The plot thickens. All right. Now it's time to kick it over to you guys. If you wanna raise your hand, please do. I'm looking at the chat here. We've got some really good questions. Stephen and Michael, if you see anything that you immediately want to tackle. You could pull up your chat windows. Please do. But I will open the floor.

Mercedes, I think I answered your question along the way. And yeah, the— can intuition be trained or enhanced through accessing flow? Yes. That's sort of— we wrote a second paper with sort of a smaller group of the same team, a couple different people on flow and intuition. That came out in the Neuroscience of Consciousness 3 months ago. It's a sister paper to this one, and that's the work we did there.

I will drop that paper in the chat, folks. Claire, you had some really good questions. Deborah, you did as well. Oh, we've got Julian. Yeah, please take yourself off mute and And the floor is yours. Hi, how are you today?

I have— I'm curious about, as you talk, the relationship between intuition and analytic thinking. I remember reading some— you, Stephen, about reading you about the concept of minimum viable feedback loop. Loop, okay, in relation to FlowState. And I'm curious about, can we maybe— Oh yeah, that's an awesome idea.

And you're totally right.

When we train Flow, like expand like the intuition space and having in place like a minimal viable feedback loop, like using analytical thought, but we expand the intuition space or something of those lines. What are your thoughts about this concept?

Yeah, it's a great idea. So you're totally correct. I think when you're— when I talk about the minimal feedback for flow, right, we all require different kinds of feedback and it's really just sort of like what is the minimum amount of steer you need? And in a sense, what you just did is really cool. You just took it one step further, which is what the next step in the equation was. The minimum amount of steer you need for pathfinding to get to intuitive insights. So yes, I think there's a correlation there between, you know, or it could be, you know, what's the minimum amount of feedback you need to get to analysis? I think both of those things come up in feedback. When I'm getting feedback, I have insights. And when I'm getting feedback, I'm like, oh yeah, I see your point. If let's be so, I think both happen.

Right. Yeah, Julian, we actually, that's a, I agree. That's, that's an amazing insight. We indirectly tackle that in our flow and intuition paper. Then Ryan, you just put the link there. We indirectly tackle that. We don't talk about feedback per se, but we talk about flow and as a trigger for flow. But you can extrapolate, I think, Julian, that, that exact point. For analytical reasoning, but also for intuitive judgments while you're in flow, which we tackle in our previous paper.

So we can try. Like a second question, can we like trust ourselves? Like it's a good way to train ourselves to expand those like feedback loops, like maybe at the beginning you need more short-term period feedback and then you can trust your gut feelings or your senses to don't need so much feedback.

Less feedback because the feedback is coming from—

Yeah, I think that's right.

You trust your intuition.

More? Well, I mean, Julia, so I'll give you an example. I've worked with the same editor, Michael Warden, now for 25 years. Right. We read— and it's really an intuitive decision-making process, especially if you're like writing nonfiction or fiction or something like that. And what's interesting is at this point he doesn't even have to give me feedback. I get all the feedback I need by what his— by his tone. Like, I know my writing is bad if he stumbles over words. Like, literally, I can literally just— I just have to listen to him read my stuff. I don't— like, I'm gonna know 80% of what he's gonna say afterwards. Um, so yes, that, that, that compresses it over time. Yeah, it does for sure.

Right on.

We have time for one more. Yeah.

Uh, Claire, you have had your hand up for a while now and, and dropped many great questions in the Mike is yours. Thank you.

Um, two things occurred to me. The, this— my second question was the one that I kind of came into this, um, this with, which was a question about what impact or correlation do delta waves have with intuition, or is there a sequencing? Because some of the work that I've read, which is quite old now, correlates delta waves with what you might call intuition or sensing or reaching out and connection. I'm just curious about that. Um, I don't know if you've got any thoughts or findings on that. Um, and my other question was about the opportunistic assimilation, and I'm thinking here about epiphany, realization, and growth, because to me assimilation is in a sense, when you fit a new piece of information to new— into existing bucket or existing model, you get that, oh yes, I'm— I understand, versus accommodation, which is when you need to create a new container for all your existing buckets, which is more, um, I'm struggling to find the words, um, more of an aha, kind of an outward embodied feeling, if that makes sense. And does that— is there a correlation between different types of intuition and those two processes, or am I just— am I reading more into that word assimilation than there is? Does that— do those two questions make sense?

I can't remember the first one. Correlation of delta. Um, so delta is binding. Right? When the brain puts together ideas in a new way. And I don't actually know if it would have to be associated with intuition, but I don't know if I've ever seen that work, Michael.

Well, Anna Wise's work on the back of Max Cade's work. Okay. The Mind Mirror. So I can send the link if it's helpful. Yeah, that'd be good.

Well, I mean, that's also, I mean, all of Richie Davidson's work on the Tibetan monks, right? They're high in gamma. Gamma as well.

High in gamma, right? So the theta waves are largely what is going on, theta rhythms in the hippocampus. And the sharp wave ripple is actually riding on top of these theta waves. It's the most synchronous signal in the brain. And that happens very, very— it's the most synchronous brainwave. That is when neurons, a bunch of neurons are firing together. You get this sharp sharp. That's why it's called sharp, because it's riding on these theta waves. Theta waves, uh, we know alpha, theta, right?

Um, but they're grounded in alpha for the realization. But also gamma.

Gamma is coupled to theta. You can't have a gamma spike in the brain if the brain's not in theta, right? Um, which is why that was, uh, so this— and, and this is the answer to your second question, Claire, which is Intuition can— so you are probably reading a little too much into assimilation as an opposite of in that terminology. But conceptually, you're right there because this is sort of— and I didn't really spend a lot of time on this. This is our colleague John Kuenos's work with Mark Beeman. But they've done tremendous amount of work separating instinct— not instinct, separating insight from intuition. And sometimes they arise together, sometimes they're distinct. They happen in sort of distinct areas of the brain, but both are primed for by opportunistic assimilation. So it primes the brain to have either experience.

Yeah. Okay, that's really helpful. Thank you. I'll ask Ryan for the references and I'll send the stuff that I was talking about if it's of interest, please.

Awesome. Yeah. Thank you, Brian.

Can you do it in a minute? Well, I don't have the references, but I can write the name.

Sorry. Really quick about metastabilities. When a running back breaks free, a really good one, you'll see them look up at the Jumbotron and then they'll keep running. So they're already running in there. And I used to think of that as multitasking. But with metastability, what's really happening is that they're switching back and forth really quick. I'm switching from the meta view of the Jumbotron and I'm running and I'm going back and forth really quickly. Is that what metastability means?

Essentially, yes. Yeah, there's, there's, and there's no such thing as multitasking in the brain. It's just switching back and forth very rapidly. I think metastability nicely explains the reason why that, you know, you can't multitask neurobiologically.

Well, but, but you can run and look at the Jumbotron at the same time, though. They're not mutually exclusive processes, right? It's the rearview mirror.

That, that, that's correct.

Is that part of— that's part of how the flow— when you're in flow, I bet you can do both at the same time. Well, I will—

Ryan, who speaks as the resident quarterback in the room, Ryan's point is you're looking up at it because it's feedback. You want to see if somebody's chasing you, right? Like, who's behind you? That's why they're looking up at the Jumbotron.

Yeah, yeah, right. Very cool.

Cool, cool question, Brian. Yeah, I know it ties directly into the family too. Stephen and Michael, thank you so much for today, folks. We will get you— I'll get you a list of resources that Stephen and Michael cited today because I know that I was only able to drop one in the chat. But beyond that, please send me any questions that you have. That's actually something we really want to encourage for the few remaining Expert Live calls that we have. If you have topics if you have questions that you'd like Stephen and Michael to tackle, because I know sometimes when we jump into a Q&A, you know, we've got a fixed amount of time, please send them to us and I can pass it up the chain and perhaps get a session formed around it. Thank you, everyone. Stephen and Michael, so cool. This really, I think it's, it's amazing to see you two just continue to unpack what's going on. In the brain and body when we're performing our best. So appreciate your hard work.

Thanks, folks.

Thank you. Thanks, folks. See you next month. See you.