How your brain blends mental spaces

0:00You're listening to a podcast right now, driving, working out, walking the dog. If you're into podcasts, chances are you have something to say too. With RSS.com, starting your own is free and easy. Upload an episode, and we distribute it to Apple podcasts, Spotify, Amazon Music, and hundreds more. Track your listeners, see where they're from, and start earning from ads like this. Even with just 10 listeners a month. If you've been thinking about starting a podcast, this is your sign. Start free at RSS.com. Right now, without even realizing it, your brain is actively hallucinating parallel universes just to help you make sense of this sentence. Yeah, it's completely invisible to us. We tend to treat human logic like a calculator, you know? We just add up facts and spit out conclusions. Right, but behind the scenes, your mind is constantly taking entirely unrelated realities, stripping them for parts, and we'll smashing them together.

1:00To create mutant ideas, and you don't even notice you're doing it. No, not at all. I mean, we treat a sudden realization or the understanding of a complex metaphor, like a magic trick. The rabbit just appears out of the hat. Precisely. And we rarely stop to ask how that rabbit was actually engineered in the dark. Well today, we are going into the dark. Welcome to the deep dive. For this one, we are exploring a single, beautifully dense source, a comprehensive Wikipedia article on a cognitive, linguistic theory known as conceptual blending. It's a fascinating topic. Our mission today is to pull back the curtain on that invisible machinery. We're going to map out the hidden architecture of human creativity and reasoning. And hopefully give you a completely new way to look at your own mind. And what's truly fascinating here is that we aren't just examining a neat little psychological quirk. We are looking at the foundational processes of how you think. How human beings communicate. Exactly. And honestly, how we build entire civilizations.

2:00This theory attempts to decode the underlying software of everyday thought. Okay, let's unpack this. Our source refers to this theory as conceptual blending, but also conceptual integration or view application. It was formally developed by Jille Focanié and Mark Turner back in 1993. Yes. Though Focanié and Turner explicitly point back to a 1964 book. Oh, right. By Arthur Kossler. Active creation. Kossler observed a common pattern across art, science, and humor. He called it the bisociation of matrices, which is quite a mouthful. It is. But he essentially argued that the human mind has this unique ability to take two completely unrelated frameworks or matrices and suddenly snap them together to create something entirely novel. I have to admit, bisociation of matrices sounds like an incredibly dry math concept. When I was reading the source, the analogy I kept coming back to was mental genetic engineering. Oh, I like that. Is conceptual blending basically taking the DNA, like the specific traits from completely

3:02different ideas and subconsciously splicing them together in a lab to create a brand new mutant idea? One that somehow survives and makes sense to us. That is a highly accurate way to look at it. And the crucial word you use there is subconsciously because we don't feel it happening. Right. Okay, and Turner argued that this splicing process isn't reserved for brilliant ventures or poets. It is absolutely ubiquitous. You're doing it constantly, effortlessly every single time you speak. Can you mean example? Well, think about a common everyday phrase, like telling someone they are digging their own grave when they make a really bad financial decision. Right. Because I'm not literally picturing my friend holding a shovel in a cemetery. No, of course not. I'm taking the concept of financial ruin and I'm splicing it with the concept of physical death and burial. And my brain just instantly understands the severity of what's happening. Without actually believing your friend is a grave digger. Exactly. You spliced the DNA of those two realities together to understand a complex concept. Foconia and Turner view this theory as an attempt to create a unitary account of how

4:05cultural ideas are transmitted. So it's kind of like mimetics. Very much a kind of mimetics, yeah. How ideas spread, mutate, and evolve across human history. Your sources even mentioned that researchers like George Lakehoff and Raphael Nunez use this exact theory to argue that the splicing is literally where mathematics comes from. Yes, the cognitive science of mathematics. How that understanding math isn't just about recognizing universal truths floating in space. It actually requires the mastery of these extensive metaphorical blends. Precisely. Mathematics isn't just out there in the ether waiting to be discovered. According to this view, it is built by human minds taking basic grounded concepts like physical objects, yeah, physical objects or grouping things together in piles and then blending them over and over again into increasingly abstract mental spaces. I want to take this from the abstract down into a concrete real world application because I want you the listener to actually feel your brain doing this mental genetic splicing

5:08in real time. It's one thing to talk about it, but experiencing it is different. To do that, we are going to use Arthur Coastler's famous riddle of the Buddhist monk. It's heavily featured in the sources. Oh, it's one of the classic examples used to demonstrate a blend. It perfectly forces your brain to build the machinery we're talking about. Okay, so here is the middle. Picture this. A Buddhist monk begins a dawn one day walking up a mountain path. He reaches the top at sunset. He meditates at the top for several days. Then at dawn on a new day, he begins to walk back down that exact same mountain path, reaching the foot of the mountain at sunset. And here are the constraints for you listening. You can make absolutely no assumptions about his starting or stopping or about his pace during either trip. Right, you could sprint for an hour. He could crawl. He could take a three hour nap on a rock. We don't know. The riddle is this, prove that there is a single place on the path that the monk occupies at the exact same hour of the day on both of those separate journeys. It's a tricky one. When I first read this, my brain immediately tried to draw a graph.

6:10I was trying to calculate velocity in time. And it was incredibly frustrating. I'm sure. The variables of his speed and his brakes make a mathematical approach feel completely impossible. It does feel impossible if you rely strictly on monotonic linear logic. But your brain is a shortcut. How did you find it? Well, the only way to solve it easily is to abandon reality. You have to imagine a completely fictional improbable scenario. Go on. You have to take day one and day two and superimpose them. You just picture two separate monks. One is at the bottom of the mountain walking up. The other is at the top of the mountain walking down. They both start at dawn on the exact same day. And what happens in your mind's eye when you watch that play out? Oh, I see it immediately. If they are on the exact same path, one going up and one going down on the same day, they physically have to collide at some point. They will cross paths. And where they meet, that's the proof. That is the spot on the path they occupy at the exact same hour. It is so elegantly simple once you see it.

7:12It is. But what really strikes me here isn't the math. It's that to solve a completely factual, logical problem, my brain naturally generated a completely fictional world. You built a new reality. We preserve the time of day. We preserve the physical path. But we literally cloned the monk. We hallucinated a parallel universe with two monks just to make the logic work. And you did it instantly. You didn't consciously sit down and instruct your brand, okay, let us now construct a parallel universe. You just blended the scenarios. So now that we've experienced a blend firsthand, we need to dissect how the brain just pulled it off. Yeah. If I picture my working memory like an animation studio, what are the actual layers I'm putting together to make that final scene? The source is called these mental spaces. Yes. Think of mental spaces as transparent layers of animation cells being stacked on top of each other. Okay. Transparent layers. They are small conceptual containers generated right there in your working memory, but

8:12they pull knowledge from your vast long-term memory. In a basic integration network, there are at least four of these interconnected transparent layers stacked up. Four separate mental containers just to solve the monk riddle. Let's reason through them. First you have the generic space. Right. This captures only the common structure shared by your inputs. It's the barest of bones. So no detail. Exactly. In the riddle, the generic space contains a mountain path, the abstract concept of a day passing, and a person moving along that path. Nothing specific, just the rules of the world. Then you need the actual material. That's the two input spaces. So input space one is my first animation cell, day one, the monk walking up the mountain. Yes. This two is my second cell, day two, the monk walking down the mountain. Exactly. And then the integration happens in the fourth container, which is the blended space. The final stack. This is where all the transparent cells stack together. The blended space takes the general structure from the generic space, and through a process called selective projection, it pulls specific elements from input one and input two.

9:17Wait, selective projection. That means I'm not just mashing everything together thoughtlessly. Right. Notice the word selective. We keep the mountain path as one single element. We keep the time of day as one single element. Yeah. We don't have two mountains or a 48 hour day. Oh, I see. But we project the monk twice. Because the motion's direction is different in each input, your brain selectively decides to create two separate monks in the blended space to represent those two directions. But how does the new reality actually start moving? I've got my animation cell stacked up. Two monks, one path, one day. How do the monks suddenly know they're supposed to walk toward each other and meet? That's where the three operations of blending come in. This results in what the theory calls an emergent structure. An emergent structure? Yes. This is a structure or a realization that did not exist in either of the original inputs. So the meaning of the monks is the emergent structure? Exactly. The first operation to get there is composition. This is simply the act of bringing the elements together onto the same cell.

10:18You compose the scene by putting both monks on the same path on the same day. Setting the stage. Got it. What's next? Second, is completion. This is where your brain reaches into its long-term memory and passes on additional background meaning to the blend. Like the laws of physics. Exactly. Your brain already knows how physical space works. It knows that two solid objects moving toward each other on a single path will eventually collide. You don't have to relearn physics every time you think. Your brain automatically completes the logic of the scene. And the third operation. A elaboration. This is the dynamic running of the blend. You press play on the animation. Ah, okay. You watch the two monks walk in your mind's eye and you watch the meat. The meeting only exists in the blend, but it solves your real world problem. It's incredible when you break it down into mechanics like that. But the sources are quick to point out that this monk riddle is just one specific type of blend. The theory categorizes the vast chaos of human thought into four main types of integration

11:18network. Oh, yes. And moving through these four networks really shows how scalable this theory is. The Buddhist monk riddle we just did is an example of a mirror network. Because the two inputs mirror each other. Because there is a shared organizing frame present in all the mental spaces. In all the spaces you have a man making a journey on a mountain path. The core activity mirrors itself. But you know, not all blends are that symmetrical. Right. The sources list three others. Let's try to ground these. The most basic one is the Simplex network. A Simplex network is essentially just dropping values into a predefined frame. Like filling in a blank. Basically. If I say Paul is the father of Sally, you have a frame for family roles of a father and a daughter. That's one input. The other input is just the specific people, Paul and Sally. And you blend them together. And you instantly understand their relationship. No parallel universes required. Okay. Then there's the single scope network. The sources say this is where you have two totally different frames. But only one gets projected into the blend to organize it.

12:20A perfect example of a single scope blend is how you understand a computer desktop. Oh, interesting. You have an input space for a physical office, environment desks, folders, trash cans. You have another input space for digital computer code and file directories. Oh, wow. I see it. We don't organize our screens by reading raw code. We project the organizing frame of the physical office onto the digital space. Yes. We literally drag a digital file into a digital trash can. It's two completely different realities, but the physical office frame organizes the blended space. Precisely. And I bring this to the most complex one. The double scope network. This is where you pull parts of the organizing frames from both inputs to create something really wild, often resulting in frame clashes. This would be like a computer virus, right? Yes. You have the biological frame of a virus, an organism that infects, replicates and destroys a host. And you have the computer frame of software code.

13:23You pull the replication and infection from biology and you pull the digital environment from the computer and you create a mutant idea, malicious code that acts like a biological pathogen. Exactly. And all the networks are the engine of high level human creativity and navigating all these different networks, whether it's a computer virus or the month riddle, requires us to manipulate what the theory calls vital relations. Okay. I really want to push back on this idea of vital relations because it seems like the cheat code that makes the whole theory work. In the month riddle, time was completely manipulated. We compressed two separate days into a single day so the month could walk up and down simultaneously. But if we are constantly blending realities, we must be manipulating other things besides just time, right? What other rules of reality are we subconsciously bending to our will? Well, time compression is the most obvious, but the sources list several vital relations we manipulate constantly. We manipulate cause effect. We manipulate change, how an entity transforms over time.

14:24We manipulate space, compressing vast geographic distances so we can compare things side-by-side in our minds. Like saying New York is brooding down London's neck in a financial context, we compress an ocean of space to create a physical race. Yes. Perfect example. We also manipulate identity and role. Think about what someone says, if I were you, I would quit that job. Right. You are blending your identity with their role. You maintain your own decision-making logic, but you project it into their life circumstances. Well, I do that all the time. We all do. These vital relations are the threads that allow us to stitch different mental spaces together without our brains glitching out. And speaking of glitching out, if we've managed to map out human thought so systematically, literally breaking it down into four interconnected mental containers, three operations and specific vital relations, it raises a massive, obvious question. I think I know where you're going with this. Here's where it gets really interesting. If we have the blueprint, why can't we just code this into a computer?

15:24The artificial intelligence question. If conceptual blending is truly the architecture of thought, can we build an artificial brain with the same architecture? Our source is actually dive deep into this. The attempt to model this mathematically isn't new at all. Even before conceptual blending was fully formalized by Fakaniye and Turner, an early computational model of a closely related process called view application was implemented in the 1980s. Yes, by a researcher named Jeff Schrager. Right. At Carnegie Mellon University, he applied it to causal reasoning about complex devices. But modern AI has struggled profoundly with this. They are trying to build with sources called non-monotonic reasoning into AI systems to handle complex human-like concept combinations. Okay, let's pause there because non-monotonic reasoning sounds incredibly dense. From my understanding, normal machine logic is monotonic. It builds up in a straight irreversible line. If A is true and B is true, they just add together. But human logic is non-monotonic, meaning we can learn a new fact that completely contradicts

16:29an erase is an old conclusion. We can rewrite the rules on the fly. That is a brilliant way to explain it. In monotonic logic, adding new facts only builds up a conclusion. In non-monotonic logic, a new piece of information might force you to completely withdraw a previous assumption. And the classic example cited in our sources for this computational hurdle in AI is the famous petfish problem. I love the petfish problem because it perfectly illustrates the gap between human blending and machine logic. It really does. If you tell an AI about a pet, it activates a frame. Pets are furry, they live in houses, they are affectionate, they seek attention like a dog or a cat. Right. And if you tell that same AI about a fish, it activates a completely different frame. Fish live in the ocean, they are scaly, they are cold-blooded, they are often caught for food like a salmon or a shark. But if you say the words petfish together, a human being instantly creates a blended space. We don't picture a furry affectionate salmon living on our living room couch and we don't picture a cuddly, great white shark.

17:30No we don't. We instantly generate an emergent structure, a small goldfish living in a glass bowl. And we effortlessly discard the irrelevant parts of the pet frame, the fur, the cuddling, and we discard the irrelevant parts of the fish frame, the ocean, the food aspect. We selectively project only what works. But an AI naturally wants to strictly add the two frames together, it wants monotonic logic. A pet is furry, plus a fish is a fish equals a furry fish. Exactly. Teaching a machine to selectively project and create an emergent structure that is completely different from its original inputs is computationally agonizing. It requires immense creativity frameworks. And honestly the fact that a supercomputer crashes trying to imagine a goldfish in a bowl brings up a glaring issue with this whole theory. It acts as a perfect transition into the philosophical pushbacks. Yes, the critiques. If conceptual blending is so hard to program, is it actually a rigid predictive science? Or is it merely a descriptive framework? Let's bring in the critics because they have a lot to say.

18:32They certainly do. The main skepticism comes from Raymond W. Gibbs Jr., who publish a heavy critique in 2000. Gibbs essentially points out a major flaw that you, the listener, might already be sensing. The theory lacks testable hypotheses. Which is a big problem. If a psychological theory is going to be treated as hard science, it needs to be able to predict behavior. Gibbs argued that blending theory is really just a framework. It's a way of describing things after the fact, not a single testable theory that predicts what someone will think next. The analogy that came to mind when I read Gibbs's critique was baking a cake. How so? Gibbs is essentially arguing that inferring how a mental process works just by looking at the final product is deeply flawed. It's like looking at a fully baked chocolate cake and claiming you know exactly with 100% certainty, the exact order the baker added, the eggs, the flour, and the sugar. That's a great way to put it. We can look at the final blend in your head, the goldfish or the monk, but we can't actually

19:33prove your brain used for separate distinct mental containers to get there. It's a devastating critique. We can guess the recipe, but we don't really know what happened in the bowl. Gibbs even suggested that other linguistic theories might be equally effective at explaining these cognitive phenomena without requiring this incredibly specific architecture of mental spaces. And I want to jump on another criticism here from David Ritchie in 2004 who argued against the unnecessary complexity of the theory. Right. The Occam's razor approach. Exactly. Ritchie brings Occam's razor to the table. He asks, does every single metaphor we use really require this massive invisible machinery? Think back to our earlier example of digging your own grave or just basic trash talk. Yeah. Are we really generating a generic space, two input spaces and a blended space, running three distinct operations and manipulating vital relations just to understand a simple insult? Ritchie argues that it is highly possible we are over complicating what might be a much simpler, faster cognitive process.

20:35Even with the Buddhist monk riddle, Ritchie argues there are alternative, simpler interpretations for how human beings solve it without needing the complex mere network model. But what I find most telling in all of our sources is the philosophical boundary drawn by Mark Turner himself, one of the literal creators of the theory. Yes. In his book, The Literary Mind, Turner makes a really fascinating admission that seems to agree with the critics on some level. He does. Turner's stage that conceptual blending is undoubtedly a fundamental instrument of the everyday mind. But he clarifies that the insights obtained from it, the metaphors, the solutions, are the products of creative thinking. The products. Yes. And this is the key limitation. He admits that conceptual blending theory is not in itself a complete theory of creativity. Because it can't explain inspiration, Turner admits that blending provides the terminology for describing how we combine realities, but it has absolutely nothing to say about where the inputs to a blend originate in the first place. It explains the mechanics of the mashup, explains how the DNA is spliced, but it does

21:40not explain where the DNA came from. So what does this all mean for us? We've journeyed from the spark of an idea through the dissociation of matrices. We have. We've walked up and down the mountain with our cloned Buddhist monk. We've watched artificial intelligence struggle to understand a goldfish, and we've waited into the philosophical critiques of whether this is hard science or just a really good metaphor for thought. It means that whether it actually takes four distinct mental animation cells, or whether it's a much simpler process, as Occam's razor suggests, the undeniable truth is that your brain is constantly performing high-level conceptual gymnastics. Every single day. You are continuously pulling frames from your memory, selectively projecting elements and running dynamic simulations, just to make sense of a simple conversation, or solve a daily problem at work. You are, quite literally, a walking, talking engine of conceptual integration. But I would like to leave you with a final thought to mull over. Lay it on us. Conceptual blending only provides the terminology for how we mix and match existing inputs.

22:40If it only explains the recipe, but not the ingredients, then where does the very first spark of a truly original idea actually come from before it has ever blended? What generates the input before the input? Wow. That is a deeply haunting question to end on. Where does the original thought come from? Well, thank you so much for joining us on this deep dive. As you go about your day-to-day, pay attention to your own thoughts. Notice the hidden blends in your conversations, the metaphors you use without thinking, and the fictional realities you construct just to navigate the factual world. Keep questioning the invisible machinery we'll catch you next time. You're listening to a podcast right now. Driving, working out, walking the dog. If you're into podcasts, chances are you have something to say too. With RSS.com, starting your own is free and easy. Start an episode and we distribute it to Apple podcasts, Spotify, Amazon music, and hundreds more. Track your listeners, see where they're from, and start earning from ads like this.

23:40Even with just 10 listeners a month. If you've been thinking about starting a podcast, this is your sign. Start free at RSS.com. The sun shining birds are singing and all feels right in the world. All the season changes and suddenly you lose your motivation to get out of bed. In fact, one in five people experience some form of depression no matter the season or time of year. At the American Psychiatric Association Foundation, our vision is to build a mentally healthy nation for all because we want you to live your best life and be your best you all year round. Please visit mentallyhealthynation.org to learn more.