Functional Architectonics of the Brain: Co-evolving Structures of Meaning

I will start with the architectonics of the brain, and then I think I will start out with the idea that is difficult to do neurosciences without calling it Constructivism in some sense. I think we saw that very beautifully today in what Beau Lotto said and what Daniel Glaser said earlier, yesterday. I won’t really say that much more about it now. It just seemed to be that if you are a neuroscientist today that’s how you think about it, and one way to put it is the brain basically feels worlds out of the world as the environment is transformed into experiential Buddahs.

And I am sorry, this is how much I am going to talk about experience at this point, because usually  I would go on that trajectory and say something about how experience and experiment relate, but since I was meant to relate to an architect, that would be somewhat off track. Given what Marcos [Novak] just said now, it would have been an obvious thing to do, but I won’t do that.

Instead, I will try to take the other perspective and say because at the same time as the brain feels worlds, we can say that the world also feels brains. And I think that one way to look at it, as what I learned yesterday was a “riff-off,” is by pretending there’s an architecture that has variability, which is at the same time is both rigorous and agile. It is quite clear that the finer details in this interplay are a great mystery and it’s, I think, quite obvious to most neuroscientists that there is a need to work quite carefully with the types of models and  metaphors one uses in trying to describe these processes. What I would like to try to demonstrate to you today is that actually choosing the right metaphors and words is not just a matter of selecting a token model, because the models actually matter. And what I will try to do first is an almost pedagogical exercise simply to demonstrate how different ways of  making models has quite radical consequences for the way one ends up thinking about what the brain is doing and how it is constructed. And I will do that with an example of, of all things, bird brains. And after that I will try to bring in some metaphors that again I riff-off from Marcos’ ideas about liquid architect to say that, well, perhaps there are other ways to think about how the brain is structured, where we can see some parallels between what goes on in architecture and what goes on in neuroscience.

I think that the basic idea that the organisms are bricks that build themselves can, among others, be traced back to Carles Pompeia, a rather terrifying looking German scientist from Estonia, notorious German aristocrat, and in the nineteen century he said something, “ the  organic body is not only changeable, rather it is the only thing that changes itself, or without part, the organism is a mechanical apparatus but is a machine that built up  itself.” We can go back to these ideas  to say that there are strong notions of biology being about constructing itself in certain ways. And in, kind of, textbook versions of what it  is like to feel bodies, Pompeia is very much known for the period of the embryo, that is, during the development of organisms there is a  development from the very general to the very specific. This is usually illustrated in textbooks with a figure like this, which shows that the chordates all look the same at the first stage, overtime they become more and more specialized. This drawing was made by another German, Ernst Von Haekel, who had this novel or strange idea that what goes on in this process is that not only does each species develop overtime from the general to the specific, but also that there is a movement where the ontogenesis, that is, the development over time within the species itself recapitulates the evolution of the species. It turns out to be quite important to understand the way one names and configures the brain, that it’s actually understood along a two-dimensional trajectory, where one is development within the species and the other is development across evolutionary history or into the time of the present. Ernst Haekel cheated in drawing this figure, it’s a purely visual argument and other people have actually looked into it and it turns out that it’s not as simple as that, species don’t look like that at all, but there is a strong element of purely the images is actually doing the argumentation.

One of the things that Ernst Haeel came up with was that in the actual development of the neural system there was a very intriguing kind of development where the outer surface of the embryo turns around itself  to create what we call the “neural fold,” and thereby you can say that the whole neuronal system seems to be changing, the outside becomes the inside. It’s a kind of metaphor for what neuronal systems are like.

But back to the Avian Brains, because there was a quite interesting article written by this group called  the Avian Brain Nomenclature Consortium. It’s a group of 30 or 40 scientists that claim that basically we have to re-think the way one maps out what bird brains are made like. I will just very briefly present the argument.

[shows slide]

What we have up here is a brain of a zebra finch, and what you have here is a brain of a human being. And looking at it at the same size, you can see they look kind of quite similar, the structures look quite similar. But due to the processes I described to you earlier, that is, that the way one thinks about development both includes  evolutionary history and development within species, it has been standard to say that the bird brain as you see here, and the human brain as you see here are very different, as is illustrated in the color coding of this drawing. We all know that in the human brain’s neocortex has to do with all the things that are neo and it is where all the thinking processes go on. What seems to be strange about the bird brain is that a lot of things that are hidden here, deep down in the middle of the brain is that which has expanded up in bird brain anatomy. And this is reflected when you see the human brain, with neo-striations, with neocortex, everything is new and thereby modern and different. We have a lot of  paleocortex and paleo-striations, a lot of old structures in the way you have the brain. And this kind of mapping out of the new versus the old has been one mystery because it seems as if those primitive things are not there. And what people are basically trying to do in the Bird Brain Nomenclature Consortium is to say this model is probably altogether wrong, and their basic argument is that you should conceive the bird brain here [pointing to slide], that all that is green here [pointing to slide] is actually comparable to all that is green here [pointing to slide]. And we should forget everything about the arche- and pale- and all the other types of names that used to be taught onto the way that one would think about bird brains.

Why this is important? Why is this interesting? Well, it is important and interesting because tied into the old mapping-out of the brain is the notion of what is old has to be primitive, we have the notions of the bird brain and the lizard brain and other things too. And what has become the major obstacle in the understanding of the bird brain is how come something that is so old and so conservative can actually do other things that brains are up to doing. It has become quite obvious during the last years of research of crow cognition and other types of cognitions, that they can do all these things that monkeys can do: they can do cause and reasoning, they can do imagination, they can do prospection, they can do complex cognition, they can do various sorts of flexibility issues. But to some extent, due to the way we have thought about it the bird brain as basically an expansion of old structures, these things seem to be really difficult to figure in. And what we see really developing is another way of drawing out what the map of what brains look like.

I think this is just one instance of how actually thinking about how the brain is being organized we can begin by taking in metaphors from other areas of construction and mapping. You can say that a lot of this notion of what the brain is like is still based in some modular hypothesis. We can call the modular different things but still we have rigid structures in different places that just seem to be there and do not hook up to each other. I think one of the great challenges in current neurobiology is really to break with that notion of what the brain looks like, and that’s where I would like to say that maybe some of the concepts like liquid architectures can be other ways of thinking of what the brain looks like. This one instance of a liquid architecture image. And as you also saw in Marcos Novak’s picture, this actually looks quite like some of the things you can draw out of brains if you are interested in other things than modules. This is a relatively modern technique called Neuro Fiber Tracking, where based on a rather complicated measure of treatment of these fMRI images, you can map out not only the regions, but how different regions connect to each other. You can figure out the kind of network that seems to be existing between different regions of the brain. What they had looked at here is one version of corpus callosum that connects the right hemisphere to the left hemisphere, and if you see that structure away from the brain, we have these strange structures and if you do kind of more complete mappings of it, you get these very beautiful structures that are basically reconstructions of the way that things connect to each other and here is a completely different understanding. This is not more a matter of individual modules that are aligned in different places, but much more that how these different modules are connected to each other, and I think the theoretical forms that look remarkably similar to some of the things we just saw earlier. Back to that idea, why the liquid architecture idea again might be equal to this understanding of the brain, is that where once one thinks about modules there is a certain rigidity, a fixedness to it, but if we try to take serious Marcos’ idea that this architecture has a variability that is both rigorous and agile, then we can actually see in the dynamic processes in brains this interplay between the rigorous and agile.

So what you have here is an fMRI of a person who has had a stroke in this part of the brain, at day 4, day 30, and day 90. And what we have tried to reconstruct how the different parts of the brain or how the fibers develop around this, and what you can basically see is the fiber changes over time from day 4 to day 90, as the brain reconfigures itself along these tracks. In another instance some of these metaphors might be really useful to think about the type of processes that go on in the brain.

I think liquid architecture idea is only the first step in it, because again, here, we are very much focused on how the things connect to each other, there is a certain rigidity to the type of structures that are in it. I have tried to riff-off another quote from Marcos, which is about disembodiment and disconnections, and I will not read through them or try to read them, as I must admit that in my first reading I had some difficulties in finding out how should I translate that into some of the phenomena that I was working with. But it turned out to be quite productive. Francisco Varela, apart from doing all the stuff about autopoiesis, has done also very fundamental work about how does the brain actually create patterns of organizations that are established through simple or complicated vacillations in the brain. Then, I read an article in a journal of Neurosciences written just before he died.  He presented some of his work here, and I will very briefly take you through this figure.  So, the experiment was a relatively simple one. People were presented with what are called “MUNIfaces,” and either you can in some instances see a face here (and I must admit I find it terribly difficult to see a face in the image, but some people can actually see a face) and in the other situations you were presented with nonsense images. And the task was really simple, you are  asked to press a button if you saw a face and another button if you didn’t. And what Verela did was to, using a technique called “Imagetry,” look at areas of the brain that were oscillating in parallel to each other as a consequence of the stimulant. What is interesting here is what I’ve mapped out here [indicating slide]. The redder the image gets, that means something oscillates together. And what Varela reports is that this is a subjective rhythm, after about 200 milliseconds, a strong pattern of synchrony here that doesn’t exist over here. It is as if there is an immediate bringing together of connections that oscillate over time. And this is illustrated in this kind of pictogram of the brain, where the lines indicate where areas of the brain start to oscillate.

Well what is equally important is that just after you have had this bringing together of oscillations, you get these massive green areas which are actually de-synchronizations, so that the pattern that has been established because something was synchronized with each other, it must just after that be broken off. It’s about both the inscription and dis-inscription. And again, then we see after 800 milliseconds people get around to pressing the button and we see button pressing synchronizations across both images.

I think these notions of disembodiment as a loss of inscriptions, that is the agile shedding of one inscription in favor of another, or the notion that there are some threads and links that string each temporary, autonomous pattern together. This is a very usual metaphor for describing some of the phenomena that is happening here. It seems quite obvious to me that in order to move into a very dynamic understanding of the brain, which is what all brain scientists are trying to do right now, there can be very few fruitful exchanges of ways of describing and discussing these things. Because it is quite obvious, and that is what I was trying to describe to you earlier, the models matter a lot in science. It matters to an enormous amount of things whether you describe the bird brain as an archeo or  paleo old structure or you say well it has a different name, it might take a different route but it looks quite like the old patterns. Words matters, models matter, in science as much as art.