What is consciousness? Do you perceive the color red the same way that I do on the inside? What is wrong with the standard textbook version of vision? Why do you have so many feedback loops in the brain? And what does any of this have to do with Ernest Hemingway or Plato's cave or artificial neural networks that.
See dogs everywhere?
Welcome to inner Cosmos with me David Eagleman, I mean neuroscientists and author at Stanford.
And in these episodes we sail.
Deeply into our three pound universe to understand why and how our lives look the way they do. Today's episode is about the sense of being alive, and in a moment, I'm going to bring in my colleague annal Seth, who wrote a great book called Being You, which is all about this neuroscientific problem. Now, by way of setting the table for this, you may say, what is the neuroscientific
problem of consciousness? Well, it's simply this. It feels like something to be you, and that feeling flickers to life when you wake up in the morning, and it's not there when you're in a deep sleep or under anesthesia, and we're not sure how that happens. Our brains are made up of tens of billions of very sophisticated processing units neurons that are all operating together in a giant network.
But just because something has a lot of pieces and parts doesn't tell you anything about why it's conscious, why there's any subjective experience. If you get the right tools and take your cover off your iPhone, you'll find that it has a chip which has nineteen billion transistors. Now just think about the interactions and the almost speed of light signaling in that rich, sweeping electronic landscape.
But we don't have any meaningful reason.
To believe that your phone has consciousness or that it would be like something to be a phone. In other words, when your phone plays a funny video on the screen, do you think it feels amused or is it more likely that it's zero's and ones moving around in a deterministic way through these billions of pathways when it gets an email from your boss, does it feel stressed when it registers the receipt of a text message? Does your
phone have the capacity to feel sad? Probably not? But how do we make a more rigorous assessment of the question. How could we know what is conscious and what is not until we have we have tighter constraints on what consciousness is. This is the problem that neuroscience faces. How is it that all our billions of cells hook up in just such a way that we have consciousness? In other words, it feels like something to be us now.
Not so long ago. In neuroscience, like thirty years ago, this problem of subjective experience was essentially not talked about. People generally felt it was too squishy, and they talked about how the brain worked, but not about why we have subjective experience. But things started to change around the nineteen nineties when some great minds started devoting themselves to taking this problem seriously. And two of those minds happened
to be Nobel laureates in San Diego. One was Francis Crick and one was Gerald Adelman, and they worked in neighboring institutions. And it happened that when I was a young post doc, I got to work with Krick, and just across the way was another young postdoc working with Adelman. His name was Annal Seth, and we both were reared in this environment where it made sense to tackle the
problem of subjective experience. The mission was how can we work towards a scientific understanding of what consciousness is and how brains give rise to it.
Annal Seth is now.
A professor of cognitive and Computational neuroscience at the University of Sussex, where he also directs the Sussex Center for Consciousness Science. In twenty seventeen he gave a very popular Ted talk called Your Brain Hallucinates Your Conscious Reality, and in twenty twenty one he published a book called Being You.
A New Science of Consciousness.
So I called him up to share his views on perception, consciousness and reality.
Here's my interview with annal Seth. What is consciousness?
Well, of course we could yan you and I have just this for many, many hours, and philosophers for centuries, and so you've got to be pragmatic and I define consciousness. So I follow this a philosopher Thomas Nagel, who I think put it very beautifully and very simply, and his idea was that for a conscious organism, there is something it is like to be that organism. It feels like something to be me, and it feels like something to
be you. It's a bit circular, right, There's there's experiencing happening. But I think it's I think there's something useful about that because it doesn't mix up consciousness with other things like intelligence or language or a particular sense of identity. It's just any kind of experience whatsoever. So at least we know what we're talking about. You know, it's also what goes away under something like general anesthesia and then comes back. That for me, is a nice starting point
for what consciousness is. So we know roughly what we're talking about, and then it's the Then the approach is, well, how do we explain it in terms of neuroscience, biology, physics, whatever, How does it happen? Why is it the way it is?
And here my approach has been again quite pragmatic. Instead of trying to find some sort of magic Eureka solution that magic's conscious experience out of neurons or atoms or quantum fields or whatever it might be, let's just take a different approach and accept that consciousness exists, because there'll be some philosophers that try and tell you it doesn't
even really exist, and that it has certain properties. Different experiences feel different ways, and emotion feels different from a visual experience, So let's try to understand how and why these experiences are the way they are. And every experience has various things in common too, like every experience is unified more than more than the sum of its many parts.
So my approach is to try to find ways of bridging between description of the brain in some way collection of neurons or areas or whatever, and descriptions of experience. And this is where this idea of controlled hallucination comes in. And I'm sure we'll dig more into it, but very very simply, the idea is that instead of our experience of the world and the body sort of pouring itself into the brain through the transparent windows of the senses,
in fact perception works the other way around. It's not a new idea, it's it's very old that perception is a process of inference. The brain is locked inside this bony vault of a skull. It's dark and silent in there, and so it has to make sense of sensory signals which don't have colors or shapes or labels, and they're uncertain that they're ambiguous and noisy with respect to whatever's
going on in the world and the body. So the brain's always casting out predictions about the causes of its sensory signals, and using sensory signals to calibrate to update these predictions. And the claim here is that that that's what we experience. The brain doesn't read out the world from the outside in. It's always actively constructing the world
from the top down or the inside out. This is why I think the term controlled hallucination is useful, because we tend to think of hallucinations as things that are internally generated, and I think that that's true for all our experiences. It's just that our normal perceptual experiences are controlled by calibrated, by yoked to, geared to the world and the body in ways that are useful. So perception is a controlled hallucination, and consciousness is a collection of perceptions.
So let's double click on a couple things there. So first let's go back to the history. Let's say Kan't and Helmholtz and think about what were the first clues that people got in thinking about this idea that we're not seeing reality as it is out there, but instead it's something of a construction.
I think you're right.
The history of this is super fascinating and it's I think not given enough credits sometimes and you can go right back to Plato, I think in his allegory of the cave, where you have all these prisoners in a cave. They're chained to the walls, and all they can see are shadows cast on the wall of the cave by the light of a fire, and they take the shadows to be real because that's all they have access to, and they don't really know that there's anything out there,
you know, that is actually responsible for the shadows. So I think that's a great starting point because our brain is in a bit of a similar situation to the prisoners in the cave. You know, they don't The brain doesn't have any direct access to anything really, the body, the world, whatever, so it has to make its best guess of what's going on on the basis of things like shadows, and then can't I think for me is always the reference point. I always keep coming back to
his idea of the newmnen. So there is a reality. I'm often sometimes misunderstood as denying that there's a real world because I've used this word hallucination.
But no, not at all. Now there is a real world.
I think there is objective reality at least to answer that question, you'd better ask a physicist rather than me. But the world that we experience is never identical to that world. It's always an interpretation. In Kant's way of thinking, the newmenon reality as it really is is always hidden behind a sensory veil or a kind of inferential curtain, as I might describe it now. And then, Yeah, there
were many hints I think initially in vision. I think most of the early workin this was done by vision. There's Ibanel Heitm, the Arabian scientist and polymath, did a lot of work hundreds of years ago basically arguing that perception cannot be this direct readoubt of the world because the relation is so in direct and you know, things seen to obey regularities that can't be explained purely in
terms of the sensory data. Like when you take a piece of white paper from insider room to outside room, it still seems white.
You know, how does that happen?
It's because the brain isn't just reading off the light that comes into the eyes. It's trying to figure out what's causing the light.
Just to double click on that.
So if you're under let's say fluorescent lights, and then you walk under the sunlight. What's actually bouncing off the paper and hitting your eyes. There's a different wavelength, and yet we see it as white, and well, this is color constancy.
The brain is always after utility. You know, we perceive the world in a way that evolution has decided is useful for us. The novelist deny as Nin put it beautifully when she said, you know, we do not see things as they are. We see them as we are. That's what the brain is gunning for.
That.
And then there's this trade off between the brains prior expectations or beliefs about what's going on, and how much the brain decides to update its beliefs, expectations, predictions with new sensory data. Sometimes it can update quite quickly, pay a lot of attention to this data. Sometimes it can pay less attention. In fact, attention is exactly that process
in my mind anyway. Attention is exactly the process of balancing how much incoming sensory information is able to update the brain's best guess controlled hallucination of what's actually happening.
Right, So people like Can't and Helmholtz and others all the way back to platos who point out have thought about, hey, maybe we're not seeing reality as it is, but we're seeing something.
That we are having.
To construction the inside because the brain is isolated. So then by the nineteen sixties, the neuroscientist Donald McKay noticed something. I don't know if other people had noticed this before, but he noticed that the the you know, the amount of input to the visual cortex in the back of the brain that's coming from the eyes is actually really small.
I think the estimates now or that it's five percent of the input to the visual cortex comes from the eyeballs and all the rest is this sort of feedback. So let's come back to this issue how you think about this with predictions and what the brain is doing.
That's a great place to start, because that's such a paradox, isn't it. I Mean when I was starting out, and I think you and I started in neuroscience around the same time, and the textbooks I remember reading just describe
perception as this bottom up, inside out process. You know, signals would come into the retina early parts of the visual cortex right at the back of the brain would fish out really simple features like lines and edges, and then you got this picture of information marching deeper and deeper into the brain, sort of more complex things being fished out. And then somehow the brain put all these pieces back together, and that led to this experience.
Of the world.
Probably if you open a textbook now, you will probably see something quite similar. I think this has been a very, very pervasive idea despite this long and rich history from Plato to Cant to Helmholt and so on.
In sixty something years since Mackay published his paper.
Is sixty years since Mackay's observation, which is hard to understand in this classical view, Right, if perception is done in this bottom up direction, why do you have so many connections mark going the other way from the brain back out to the census.
It doesn't make any sense.
But from the perspective of perception as this constructive process, it makes much more sense. So digging into it a bit more so far, you know, we've kind of outlined that the brain has to make this inference about what's out there on the basis of noisy and ambiguous sensory signals without labels. Now, in mathematics we call this Bayesian inference. It's a process of reasoning under conditions of uncertainty, or in general, how you should update what you believe when
you get new data. And this is a very very general formulation. The Reverend Thomas Bays and Laplace figured out the maths hundreds of years ago, and it's been used to do all kinds of things like figure out where to look for missing nuclear submarines, or even figure out how likely you are to have a disease if you've got particular symptoms. It's always when things are uncertain that this mathematics is useful. It's the same deal with perception.
The brain is trying to figure out what it should believe now about what's out there, given some new information from the census. Now, the problem is that actually doing Bayesian inference is really really hard. In fact, it's almost impossible to do it exactly. So the brain, any good biological evolutionary hack has figured out an approximation, a very general approximation. And this approximation is in the business we
call it predictive coding or predictive processing. And what this means is that the brain effectively has some kind of model of the world and the body, and it uses that model to generate predictions about the sensory information that should be coming in. And these predictions they cascade in this top down direction and back out to the sensory surfaces through all these connections that Mackay identified, and then the sensory signals instead of being read out by the brain,
they just serve as prediction errors. They report the difference between what the brain expects and what it gets you at every level from the retina to the early parts of the visual cortex all the way up. And if the brain then follows a very very simple rule, which is just either make an action or update its prediction
to try and minimize these prediction errors. So it's just trying to minimize and trying to reduce these prediction era sensory signals, then collectively its predictions will be a very very very good approximation to Baysing inference. So we get a picture in which the brain is constantly casting out predictions into the world, the sensory signals update these predictions, and there's always this simple mechanism which the brain is
just trying to minimize prediction error. And as a result, what happens is the brain is able to make a best guess about what's out there in the world or in the body, and then the claim is, well, that that's what we perceive.
So let me just summarize.
So the idea is the brain can't know exactly what's out there, so it's making its best guesses and then saying, oh, wow, that guess was really off, that guess was a little closer, and so on, and as it matches the incoming data, it gets to refine its model that way until it
has a reasonably good model. And so one of the ideas that's been floating around in neuroscience for a while, but again I don't think this makes it to the textbooks is this idea that all of the data that we see in the century courtices is actually the error. It's the part that you didn't get right. And if you were actually getting everything one hundred percent right, you'd have, you know, golden silence going on in there. But the world is complicated and things are always happening, not in
the way you can predict away. But this is the frame shift that's real required to see this sort of thing. So coming back to why you call this a controlled hallucination, let's do it this way. Which is we don't need our eyes at all to have rich visual experience, right. You have dreams inn when your eyes are closed, right, And so the idea is that maybe you are dreaming, you're producing all the stuff on the inside, but use the word controlled to indicate, Look, you're anchored to what's going.
On in the outside.
You've got this, you know, let's say five percent of data coming in from the central world, and that anchors you somewhat. And that's what you mean, my controlled hallucination control dreaming in a sense.
That's exactly right. In fact, if you describe perception as a kind of controlled hallucination, then you can just flip it around and you can say when you're hallucinating as we would normally use it. You know, when someone sees something that's not there, indeed, when they're dreaming, well you can just call that uncontrolled perception. And I think the point here is that there's a continuity. They're not completely
different categories. So, you know, we used to thinking of dreams and hallucinations as coming more from the inside than the outside. And it's true that in normal perception the outside world plays a bigger role. But fundamentally, I think
it's the same kind of process. It's the same dance, this exchange of prediction and prediction error, but you change exactly how this dance plays out, and you can sort of sweep through all these different ways of experiencing, whether it's normal perception or dreaming or hallucination or something else.
Now use the terms controlled and uncontrolled, but in fact it's more of a spectrum. I'd imagine right where a controlled hallucination is I'm looking for something on my desk, I have to really pay attention, and so in that sense, it's really controlled by what's in the outside world. Here it's more controlled, whereas other times it's less and less controlled when I'm you know, imagining something or just seeing whatever.
And you can imagine in cases like Charles Bonet syndrome, as people are going blind, they have formed visual hallucinations. They think they see somebody walking in or doing a bunch of dancers in the street or something, even though that's not there. So it's sort of like a spectrum of how much control the outside world has.
That's exactly right, And in fact, one of the powers of this approach is that you can use it to better understand what's going on in conditions like Charles Bonne, where people have hallucinations. One of the things we did in my research group last year was we built computational models of this process of prediction and prediction error and so on, and we tweak the model in different ways
to try and simulate different kinds of hallucination. So Charles bona syndrome where indeed people often see patterns, but also people wandering around. Then there's in Parkinson's disease, people often have quite rich and complex hallucinations. And then in psychedelics you get all kinds of different hallucinations too that seem sometimes seem to emerge out of things that are already there in the environment. That clouds can become animals or people,
things like that. So we've been able to use this approach to really drill down and understand not only how these hallucinations happen, but how they and why they differ from each other. And what we did was we actually went to people who have these kinds of hallucinations in real life and we asked them to judge the output of the model so that we could test whether our you know, our computational model of these hallucinations was right.
You know, would somebody with Parkinson's disease pick the output that we generated when we were trying to simulate Parkinson's hallucinations and more or less that that works well. So we're beginning to be able to really characterize and at the level of what the brain is doing these different kinds of hallucinations.
You know, one of the things that I talked about in my book Incognito was this possibility that all of us might be having hallucinations all the time, but we don't know it. So for example, you know, it's something on my desk here, or you know, I think my dog's over there when he's not, and so on, and we only notice it when there's a clear indication that it's not true, either because someone else tells us, or I go look for my dog and realize that was a bag on the floor, not my dog, or so on.
But probably this is happening all the time. I want to drill in on what you said about how you go out to different people with psychedelics or with Parkinson's disease and ask them and find out the degree to which this match is. What you're doing is taking things like, for example, in your Ted talk a while ago.
You used Google deep.
Dream to take footage, and Google deep dream sort of has these psychedelical aist nations where it sees dogs, faces and everything, So tell us about that.
That's exactly right.
So this is I think it's a nice story because we basically did their own to start with, just because it was a lot of fun. You know, we had
this virtual reality lab. One of my post docs is very good at coding these things up, and we just thought, why can't we try and make a situation where you know, at the time, people had been just taking photos of bowls of pasta and then putting them through Google deep Dream, and they'd all become you know, they'd grow, loads of puppy heads would be there in the in the bowl of pasta. And we just thought, should we just try
and do this in virtual reality just because? And so we took a panoramic movie, so three hundred and sixty degree movie, and we put every frame through an adaptation of this deep dream algorithm so that you would get framed frame continuity. So it was it was not an easy to do.
Can I for just one second just over on sclear The reason Google deep dreams sees puppy faces everywhere is because that's its expectation. It's busy and prior is that it's looking for puppy faces, and so that's why that's why it sees it everywhere.
If you even vaguely have like two dots.
In the line or something, it says, oh, there's a puppy face.
Okay, keep doing that.
That's exactly right. And of course it doesn't have to be puppies. You could you could give the network another expectation and basically fix another node or part of the network, and then it's expecting something else. And that's actually the key.
So once we'd done this with Sussex campus, and we did it with the dog expectations, so suddenly people would have all these strange experiences of Sussex University campus, all these dogs coming out of the walls and the windows and the sky and and we tried it and it was fun, and it just struck us when we were thinking about this, what would there be any actual scientific utility in it? And what we realized was that in a lot of psychology experiments, people focus, for good reasons,
on very constrained situations. You know, they ask people was the dot moving to the left or the right, or was the patch of light there or not there, or something very very simple, so that you can make very precise measurements. But these things are very far from the richness of everyday conscious experience. In the end, that's what we want to understand. So what we realized was what we built was not a model of any kind of cognition of what people think or any kind of behavior
what they do. What we built was a model of experience. We built a model of particular way of encountering the world, and not many people have really been doing that. In fact, it was probably one of the first examples of doing something like this, and it was really just for fun. So from that starting point, then you're point is exactly right. So that initial network was set up to project expectations
of dogs into everything. But so what we then did was we moved on from the Google Deep Dream algorithm to some more complicated neural network architecture that we could tweak in different ways so that we could begin to simulate different kinds of hallucinations. So some hallucinations are very rich and very complex, others are very simple and very geometric. Some hallucinations appear out of nowhere, you know, they just spontaneous.
Theorize other hallucinations are transformations of things that are already there. So we were able to kind of create this space we could move around in to generate these different kinds of experience.
So tell us what you learned from that.
So what we were able to do this is with my colleagues David Schwartzman and ks Ksuzuki.
They did all this work. By the way, I want to make that very clear.
We went to people who have these hallucination in real life, people with Parkinson's disease, people with another condition you mentioned, Charles Bonne syndrome, people who've had psychedelic experiences, not that we're having them then and.
There, but have had them.
And we ask them to pick examples from our models that were most similar to the experiences that they had, and that way we can test our hypotheses about the computational basis of these different kinds of hallucinations. So eventually, and we're not there yet, but eventually the idea is by doing this, we'll be able to make some predictions about what we might see if we put these people in brain imaging scanners and image what's happening while they
have their hallucinations. That's the next step, And overall the goal is, I think, to put it in this larger frame, you know, when you want to understand something like how we experience the world, the nature of perception, it's often a very good idea to look at those situations where things are a little bit strange, you know, where people are experiencing things differently. You poke around in it and see what happens when things a little bit out of whack.
So the utility of studying hallucinations for me, it's firstly for the people that have them. We can help them understand their lived experience better. But it also reflects back on our understanding of perception in general, because, as we've been saying, fundamentally, it's the same process.
Yes, now, let me drill in on this for a minute, because you and I are both fascinated by individual differences in the reality inside different heads, and I've made many episodes on this topic. For example, the spectrum from a fantasia to hyperfantasia, or the internal voice, or what happens with synesthesia of different types. All these of things indicate that we're experiencing different realities and ways that we can study.
You.
With your colleague Fiona mcpheerson, you launched the perception census. Tell us about that and tell us what you've learned.
Oh, thank you for asking this.
I mean, I'm glad we're talking about this because I think it is probably one of our strongest overlaps. And I have to say a lot of my interest in this area was inspired by conversations with you dating back scarily, I think well over twenty years now when we first started talking about these things, which but certainly the work in synesthesia individual differences, it falls out as a consequence of this way of thinking, and I think this is
worth saying first. If we start with a textbook view of visual perception, it's kind of easy to think that we will all see the world hear the world in roughly the same way. And that's also how perceptual experience feels like. It feels like I just see the world as it is. It doesn't seem to me as though it depends all that much on my brain, or certainly not on the specific because of my brain compared to yours.
But how it seems is never a particularly good guide to how things are and in this view of perception, as this prediction, this controlled hallucination, this generative process, then it's going to be different for each and every one of us. You know, we all differ on the outside in skin color and height and body shape, and we all have slightly different brains too, and so we should
all experience the world to some extent differently. But the key difference here is it's easy to tell whether people are different heights, even if the difference is quite small. You know, I can just look at two people standing next to each other and I'll see if they're one's taller than the other. But if you experience red slightly differently from me, or time slightly differently from me, how will we ever know? Because your experience is private, subjective
to you will probably use the same words. You know, it's read that lasted about a second. It's so much harder to tell. And so we end up assuming, I think, overestimating the similarity of our inner world. And so this project of the Perception Census, with Fiona Macpherson and many other colleagues, Reny by Kovira, a postdoc who really drove it here at Sussex, we wanted to study these individual differences, but we wanted to do it at scale. So this
is not a new idea, David. You've done a lot of this work, contributed a lot to this literature already. But many of these studies focus on one or two or three aspects of perception. Maybe synesthesia, which I'm sure your listeners will know about because you wrote the book on this, literally several books, but you know, or maybe something else like time or ability to discriminate different musical notes.
We wanted to look at lot, lots of things together, and we wanted to look at a lot of people, and people from many places and of many ages, so
we got quite ambitious. We put together over fifty different tasks rather than just two or three, fifty different experiments that people could do, lots of visual illusions, sound had to be things people could do at home, so we couldn't do things like smell whatever, But fifty different things, and overall we were able to get around forty thousand people engaged in the census from ages of eighteen to well over seventy and from one hundred and twenty seven different countries.
Wow.
So it's been a huge data gathering effort and I really see this as a resource, and I hope it's going to be an important resource for the whole community because we're going to make the data entirely open and it can be a bit of a sandpit for testing ideas or hypotheses that people might have. You might want to ask, oh, to somebody with more vivid mental imagery, you know, do they see more different shades of color?
What things tend to go together? And as part of the census, we also have some data on people whether where they reside on some of the more clinical dimensions too, autism, ADHD, things like that, so we can start to understand how
these conditions relate to the normal spectrum of variability. So I've been using the term here perceptual diversity rather than what many people have heard neurodiversity, And I want to just dwell on that for a second, because this idea of neurodiversity has been very important and it's led to a lot of recognition that people with conditions like autism is the one that's most commonly used here as others as well ADHD, that they experience things differently and that
can cause some problems, can give some benefits, but it's different. But ironically, in my mind, the idea of neurodiversity has kind of reinforced the idea that if you're not neurodivergent in some way, then you're neurotypical and you see the world as it is, and it's underplayed I think the reality, or certainly the reality we're exploring with the census.
Let's see if it's true that.
There's just variation, and maybe when you get somewhere towards the extreme, if a distribution, a label is slapped on it and it becomes a neurodivergent condition. But I think that if we all understood that each of us experiences the world in our own unique individual way, it will This is not at all to diminish or minimize neurodiversion conditions. I just want to understand them as part of the spectrum in which there's variation among all of us, just
as there is in high body shape anything else. That's what the perception census is empirically trying to look at, because we just don't have this deita yet. How much variation is out there, what does it look like, how does it correlate?
By the way, just for final I'll tell you about my idiothesis. Idiothesis is the term we use in my lab for an idiotic hypothesis. But it's what I've been interested in is, as you know, I'm a lover of literature, and I've noticed that authors like Ernest Hemingway and let's say,
Thomas Hardy have very different ways of writing. And I think this is a I'm calling this retrospective brain scanning, because I think we can tell that Hemingway was probably a fantasic, meaning he didn't picture details in his head and didn't care about them. But somebody like Thomas Hardy or you know, Fenimore Cooper or anybody like that, put so many details on the page of the red curtains billowed, and the flowers were these flowers in this arrangement and
so on. And I happen to be on the a fantasic end of things, and so I can't stand those authors who give tons and tons of detail.
That don't matter.
Now, the reason this is an idiothesis is because I can't ever approve this is true, and there may be other reasons why they wrote in the styles they did, but I like the idea that this is yet another correlation in the world is by looking at people's outputs, the way they talk, the way they described the world, and that might give us some even very rough insight about what's happening internally.
I think that there's something too that I think. One thing that's well known, I mean, you'll correct me if I'm wrong, is that some authors were clearly synesthetic. So I think Vladimir Nabokov was well known as a synaesthete. And that's interesting not only for the perspective of how he might have described the world around him, whether it was detailed, but whether it affected other things, whether there was sort of just more cross fertilization, more associativity in
the way he was writing compared to other people. Because synthesia, which again is something that well you actually did. I think it was the first large scale survey of synesthesia in the synesthesia Battery. So we're looking at cynesesia again, but of course in the same group of people, we're looking at all kinds of other things too, So I'm really excited to see what synesthesia is associated with. Unfortunately, we didn't ask people whether they'd written any great works of literature.
You know, the truth is always struggled with this question about weather. Synesthesia is associated with higher creativity because in a sense, it's not creative. If I always see M as purple and B is orange and so on, that's I'm particularly creative.
It's just an association that I have.
In the case of letting me in a book off he you know, there are little clues that we have. Ever, just as one example, he was a lepidopterist, which means, you know, he studied butterflies, and for him, his favorite butterfly had a particular pattern of yellow black yellow, and so his novel Aida a Da happens to map onto those colors of those letters, where you know A is yellow and D is black.
And A is yellow.
So we see little clues like that, But I don't know if it makes a person more creative or not.
Yeah, there's another example of that. I actually had that writing a piece for a gallery catalog about and an artist ya Yu Kusana.
She's still alive.
She's in a nineties in Japan, and she's very very well known for these artworks that have things like red polka dots everywhere, and that there's this sort of patterns over everything, representations of landscapes and so on and it's a it's a very distinctive style. She also does these mirror infinity rooms. But it seems that she has this way of experiencing the world in which she literally does
see red dots everywhere. At some times there's I forget the technical name for it, but there's there's a you know, a sort of sexual condition where where this happens. And so exactly to your point, maybe her artistic innovation was to some extent a direct transcription of what she was just seeing. Now, I think that is not the full story.
You know, you can you have to. I think it provides the raw materials that people can use to generate pieces of art, whether the paintings, music, novels that have a creative and artistic impact. So I don't think it reduces But also I always agree with you that that disassociation. We have to be careful because if it's automatic and normal, you know, where is the creativity. The creativity is and what you do with it. It's not the thing itself.
That's right.
And by the way, Kandinsky, the visual painter, he had a very rich synessiege that was triggered by sound, and so what he would do is crank up his phonograph and stand in front of the canvas and paint what he was seeing. And what's interesting about that, that's an example where he's just transcribing what his perception is. What's interesting is, given that we all have different internal worlds,
it's nice to find ways to share like that. And I do think in let's say, literature and novels, you are getting to step into the shoes of someone who sees the world differently than you do, and that's why we love to share stories with one another.
Yeah, I think again, something that you and I no doubt agree on is that, you know, when when we face the challenge of understanding consciousness, you know, in the large in the sort of most expansive way, we want to understand what it is like to be me or
to be you. And sure we can study visual perception or auditory perception or something like that, but for a lot of people, the experience of being who they are is tied up with the self, that's tied up with some kind of internal narrative, distinctive way of being in the world. And literature has done, i think, more than science to explore examine that aspect of consciousness.
I'm so glad you brought this up because I was going to ask you about this. So in your book Being You, you talked about the way that we build a model of the outside world by minimizing the prediction aris, but also we build models of the inside world.
So tell us about that.
So this is another INVERTI if you like a conceptual upside down move, We've already had one, which is the idea that instead of experiencing the world in this kind of outside in direction where the world just pours into the mind, it's this act of construction, this controlled hallucination. Now, another common assumption or sort of it might seem an obvious way of thinking about things, is when we think about the self, and it might seem just intuitive to
say that the self what it is to be me. Well, that's the thing that does the perceiving. There's something, there's some essence of me inside my skull. That is the recipients of all these perceptions, however they're constructed, that takes them in, figures out what to do next, does something, and we sense, we think, we act.
And go round and round and round.
Now, I think this is not the way to think about things, I think is very different. Rather than the self being that which does the perceiving, I think it's more correct to say that the self itself is a kind of perception. So there's just a same process going on. The brain is making inferences about sensory signals from different
places and over different time scales. Some of those inferences underlie our experiences of the world, and some of those inferences, some of those controlled hallucinations, are what the self actually is. The self is this collection of perceptions that have and I think this is the key, you know, So why is the self different from the world. What's special about the self? Well, one of the things that's special about
the self is the body. So perceptions of self, for me anyway, are rooted in the brain's perception predictions about the body, and all our aspects itself are built on that.
Great So your brain is monitoring the outside world, and it's monitoring the inside world inside the body.
And he made the argument that.
It not only tries to predict, but eventually becomes good at saying Okay, look, this is my model is that let's say the body temperature should be at this, so if it fluctuates, this is what gives you the ability to do homeostasis to keep things in order because you have a well established model at this point.
That's absolutely right.
And I know you recently had Lisa Felman Barrett on the podcast, and she and I have a pretty similar view about this, but I think we came to it from very different directions. I mean, Lisa has always been interested specifically in emotion and pushing back against these Diarwinian ideas of hard coded emotion circuits in the brain. I came to these kinds of ideas by just saying thinking about, well, how does the brain perceive the outside world, Well, maybe
there's something similar happening about emotion. Building actually on some very early ideas of William James and Carl Langer, who talked about emotion as a process of the brain's appraisal or interpretation of the physiological condition of the body. But where we end up is somewhere. It's not exactly the same.
There are differences between how Lisa and I see things, But where we end up is one fundamental realization about what brains are for that really I think casts everything we think about perception consciousness in a different light, and this is that brains are not for creating art, or writing poetry, or doing complex math, or even having conversations. If you think about what the primary duty of any brain is, it's to keep the body and itself alive.
If you don't do that, you don't do anything. And to keep it an organism alive is a difficult thing. I mean, that's why evolution has shaped all these weird and wonderful creatures. But it usually well. In fact, it always requires keeping certain physiological variables like heart rate, blood pressure, blood oxygenation within very tight ranges. You've got to regulate your physiology. If your blood oxygen drops, you won't last very long if it drops too much. And so how
does the brain do this well? Any control engineer will tell you that a good way to regulate something, to keep it where it needs to be, is to have a predictive model about it, because if you have a predictive model, you can anticipate deviations. When we both finish recording and we stand up, the brain is anticipating that our blood pressure will drop a bit, so it transiently
increases the blood pressure. It constricts our vessels, so our blood pressure in fact remains pretty much exactly the same. We don't faint, So the ability to control and regulate is done best through prediction. And so for me that that's the fundamental reason why brains work this way, why perception works this way. It's all built on this fundamental imperative of the brain to regulate homeostatically, allostatically the physiology
of the body. And I think the way I like to put it in my book is we experience the world and the self with through and because of our living bodies.
And so impact that just a little bit more.
So, there's I mean, this whole question of what emotions are, how they come about with their force is super super interesting. But they kind of polarize two extremes, and one extreme you have Darwin, or at least a kind of caricature of Darwin, which says that there are certain there's a certain repertoire of emotions happiness, anger, sadness, discussed things like this.
They're pretty much hard wired into our brains. They're kind of different from cognition, from thinking, you know, they're more physiological like survival reflexes that feel particular ways, and they're pretty fixed and conserved. The ideas across time across cultures, and this has been kind of the mainstream view, I think, in one way or another for a long time. And then on the other hand, you've got the idea of emotions as being somewhat constructed. Now this has also got
a long history. William James, we mentioned a minute ago, he realized over one hundred years ago that emotions were very, very deeply embodied. That you know, he proposed the idea that if say, a bear comes charging into the room, we will feel afraid and then we might run away, and it might be normal to think that, you know, it's the sight of the bear that causes the feeling of fear, and then the feeling of the fear causes me to run away, and James is becoming a common
theme to our conversation. Now flips this around, right, So, for William James and also Carl Ager, the bear comes charging into the room, my brain registers the presence of the bear. This puts my body into a particular physiological state, and adrenaline shoots up, courts all starts racing around. And then my brain perceives this change happening in the body in the context of a bear being there, and that is the emotion of fear. So fear in this case follows or is at least part of the change in
the body. It's not that fear then causes the change in the body. The experience of fear is the perception of what's happening in the body in this context of something dangerous happening. So that's that's the way I think of that. I've come to think about emotions as grounded in this this imperative for regulation. And you know, just as with the perception census, there will be variation, but there will be also a lot of similarity. There's a
lot of similarities in the way we see things. So you know, I tend to always land in this this sort of happy or unhappy medium where there may be some amount of biological conservation going on. There's sort of good reasons for that, but there might also be more variation than we might think.
Given the way that you are thinking about consciousness, what do you think about other animals having consciousness?
And what to take on AI becoming conscious.
Two super important and increasingly timely questions. I mean, there's so much excitement, height and some amount of anxiety and fear about AI and.
Things are changing.
Animals, of course, have been around for a very long time, and we've had over history varying views about their status as conscious creatures or not, and I think they pose us very different challenges. So we humans, we tend to see the world through the lens of being human. We're very anthropocentric, and not only that, we're very anthropomorphic. We tend to project human like things into other systems on
the basis of what might be superficial similarities. So this is to say that when it comes to other animals, if they're different from us, we tend to withhold from them things that we think are distinctively human or matter to our humanity, like intelligence and consciousness. And I think it's this combination of biases that can get us into trouble here. Because we see things through a human lens.
We've tended over history to associate something like consciousness with other things that we think of as distinctively human, like intelligence and language. So if we do that and we look at non human animals, we tend to reserve consciousness for those animals that seem the smartest. And in fact, you know, we've done worse than that. It wasn't that
long ago that people didn't give babies anesthesia. I mean, this seems crazy now that it was not common practice until a few decades ago, there was this sort of assumptions. I didn't really feel paid, and I think that just shows how deeply our assumptions like this can affect our practice. And we have exactly the opposite situation now with artificial intelligence. So AI systems like chat, GPT or Claude can speak to us fluently. Whether it count as conversations, I'm much
less sure. I mean, Sherry Turkle has talked about this beautifully and said, when we converse with a machine, we unthinkably simplify what we mean by a conversation. It's a different form of human machine interaction. But because words are being exchanged and some of the things that language models can say, it really are quite surprisingly articulate and informative.
We tend to project qualities like consciousness into these machines because if it was a human being talking to us like that, well that human being would clearly be conscious.
But it's not.
It's something very, very, very different. So I think the first thing we have to do is recognize how much our intuitions about the circle of consciousness, how far these intuitions are shaped by our biases, and that we can't just crawl out from under them, We can't get away from them. These biases might be what we might call cognitively imped like some visual illusions. You know, there are some illusions that even when you know two lines are
the same length, they will always look different. This is the Mullaalaya illusion. So even if we know we're biased in these anthropocentric ways, we will still be unable to resist these intuitions. So we need to just surface that and then ask the question, so what's actually most likely the case? And here I think there's extremely good reason to believe that consciousness is pretty widespread in non human animals.
If you look through all mammals, whether it's a tree, shrew or orangutang, they have the same basic neural architecture that we know is important in human beings for consciouness. I think things get really tricky when we look at birds, when we look at fish, when we look at insects. And here I just think we have to we can't be determined, as we don't know one way or the other. But we just need to keep updating our credence in
consciousness in these things. And I think the key thing is we also have to ask, well, what kind of consciousness matters. It may well be the case that not many non human animals have fully developed reflexive, reflective experiences of being particular individuals. I mean, we don't know yet, but it seems unlikely. But ethically what matters is whether they have the capacity to suffer, to feel pain. This is a very utilitarian perspective, but I think it's a
sensible one. So I think we underestimate probably the extent of animal consciousness, and I think we overestimate the likelihood of AI being conscious. And there are many reasons why I'm very skeptical of this, but fundamentally, my great basis for the skepticism is I think we've just overused the metaphor of the brain as a computer. It's a beautiful, brilliant,
powerful metaphor, but it's a metaphor. We've always used a dominant technology of the day as a metaphor for the brain, and we always get into trouble, or we usually get into trouble when we start confusing a metaphor with the thing itself.
What do you see, is the biggest unanswered question in consciousness research and what excites you the most about where the field is headed?
Oh wow, I mean the biggest unanswered question is it's still the old question. How does it happen? We still don't really know. I don't think. I mean, there's progress, and to be honest, and I don't know. I'd be interested if you feel the same way that id David. We've been doing this more or less for the same amount of time, long time now decades. Some days I feel like, ah, it's still a complete mystery. You know, we have neurons, chemicals, electrical signals. Why do I experience anything?
Why is there experience in the world, in the universe at all? Those days, you know, we'll have a cup of coffee and get on with things. But then on other days I think back to where we were in the You know, when I started studying and in the early nineteen nineties, consciousness wasn't even on the menu if you wanted to look at psychology and neuroscience.
It was.
It was ostracized completely. I mean we met because I came to San Diego in the Lake in the early two thousands, which was at the time one of the only places where you could study consciousness legitimately with the approval of a PI in a lab, and was still
a pretty rare thing to do. And so looking back through that lens and looking at the theories that we now have and the kinds of experiments that have been done, and how we've learned more about different kinds of consciousness, you know, I then worry less that this big metaphysical existential question is still waiting in the wings.
And so I think that.
Maybe the way to put it, I haven't thought about it in quite this way before, But maybe the biggest unanswered question in consciousness research is whether there will turn out to be a big unanswered question in consciousness research or not. In other words, as we just understand more and more about different kinds of experience, what happens in anesthesia, maybe the question of consciousness will turn out to be a little bit like the question of life.
You know.
One hundred and fifty years ago, many people thought that life was something beyond the reach of science, that there had to be something supernatural, some elan vital, some spark of life to explain the difference between the living and the non living. And of course We don't think that anymore. I mean, life is still not a completely written book. We don't understand everything, but there's no conceptual mystery. That life is part of nature, and even its origin seems
increasingly within reach to explain and understand. And what happened that wasn't that anybody proved that life didn't exist or found the spark of life in some Eureka moment. Noe biologists started just to make progress, explaining this property of living systems homeostas is this property reproduction, this property metabolism, And little by little we learned about the nature of life and we stopped worrying that there had there was
something fundamentally inexplicable about it. And progress in science is often like this. You know, sometimes it's not only the answers that change, but it's the questions that change too. So that's what I've got my own. That's what gives me hope. I think we understand more when the questions we ask start to look different.
I totally agree with you. And what's interesting.
What's been interesting for me is I also feel the way you knew many mornings where I think, gosh, yeah, when you and I were in San Diego and the early thousands, the questions that were being asked were mostly the same, but things have changed slowly. And just as one example, at that time, we all sort of every all neuroscientists were sort of snarky about artificial intelligence because they felt like, Okay, we've been at this for a long time, it's.
Not really happening.
There were artificial neural networks with the same principles that we have now, but it seemed like it's never gonna happen. And now we look at you at GPT every day and do experiments on it, and we find, wow, it's it's actually working in a way.
Now. Who knows if it's conscious.
I think we share the view that it's probably not conscious, but boy is it impressive. And so because of improvements in our technology, in our ability to measure things in biology, in you know, in just data gathering and ways of doing things bigger and better, we we find different views now than we did one quarter century ago.
I think that that's right.
By the way, I have to just one other aspect of the whole AI think that I think is really useful to think about. So there's this whole debate about whether chat GPT or language models might be conscious. People ask the question, right, and some people think that they are. But just yesterday I was lucky enough to visit deep mines in London and that's where alpha fold was developed, which is another AI system that's able to predict protein
structure from sequence I mean acid sequences. The protein folding problem has been one of the biggest challenges in biology for a long time. Alpha fold basically sorts that out. Now, isn't it interesting that no one thinks that alpha fold is conscious. I've not heard anybody suggests to me that alpha fold might have experience.
Yet.
You know, there's some differences, but they're very, very similar to the architectures. I mean they're made out of that. They're both computer algorithms. Then you're on network based with some other stuff that they even have transformer architectures. They're really not that different. Yet our intuitions about the two are so different. I think that really, to me highlights how much of what we think is driven by our
psychological bias. I think the other thing is is that, yeah, there can be this interesting nonlinearity here.
Right.
AI seemed to flatline for a long time, and there's this sudden rush of discovery and invention and increase incompetence. Maybe this is going to happen in the neuroscience of consciousness too, And there are some super exciting developments over where you're part of the world in Stanford, there's so much exciting work going on in optogenetics and in synthetic biology.
People developing brain organoids, these these collections of brain cells in dishes that are derived from human embryonic stem cells, things that really, as I think you said, that give us different perspectives, different views, different tools, and science often
needs that. Yeah, you can have ideas, you can have theories, but a lot of advance historically in science is when people acquire optit invent new tools, and I think we're seeing a lot of that in neuroscience now, So I am actually pretty optimistic for the future.
That was my interview with Analseth, professor of cognitive and Computational neuroscience at Sussex and the author of Being You. We explored here how our brains create our reality, from control hallucinations to the rich diversity of individual perceptions.
What I want to.
Leave you with is an idea that you've heard me talk about many times before on this podcast, which is that consciousness is not just about directly experiencing the world, but instead it's about actively constructing it. While consciousness remains one of the central mysteries and neuroscience, today's conversation, I hope gives us a lens through which to view it not as something mystical or otherworldly, but as a grounded biological phenomenon rooted in the brain's continuous dance of sensory
input and its own predictions. Now, thinking about our perception of the world not as a direct reflection of reality, but a construction of the brain, the inner world meeting the outer world. This is really the single reasonable way to understand it, and in a sense, it's a little strange that this is still rare in textbooks or in
common knowledge. And note that this process of trying to predict signals applies not just to our perception of the outside world, but to the swirling world inside our bodies as well, which sheds light on how we experience emotions and maintain homeostasis. In this way, the self is not a fixed entity, but an ever changing construct. And one of the other themes that emerge today is that each of us carries around a slightly different version of reality,
shaped by our biology and our experiences. This is a reminder of how subjective and varied human experience can be, and how much we still have to learn about the minds of others. That includes other humans and animals, and possibly at some point ai are we overestimating the sentience
of machines or underestimating that of animals. So, in closing, as Annel mentioned, just as we once demystified the life itself, step by step through the patient work of science, we may one day come to understand consciousness in a similar manner. The key, as it is so often in science, is not just about answering the big question, but can continually asking smaller, better ones. Go to Eagleman dot com slash podcast for more information and to find further reading.
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Until next time.
I'm David Eagleman and this is Inner Cosmos.