317 | Nicole Rust on Why Neuroscience Hasn’t Solved Brain Disorders

0:00:01.4 Sean Carroll: Hello, everyone, and welcome to the Mindscape Podcast. I'm your host, Sean Carroll. Back when I was writing "The Big Picture" The book, one of the motivations there was to provide kind of an apologia for naturalism. An apologia not being, you say you're sorry, you apologize. It's when you defend a position, mostly coming from theology. Apologetics in theology, is you're trying to defend the existence of God. So I was doing the opposite, or at least the flip side, defending the absence of God, defending the idea that even though we don't know everything about how the universe works, given what we do know, there's overwhelming reason to believe that when we finally know everything, it will all fit in happily to a naturalistic framework where you don't need supernatural things, you don't need God, anything like that. You don't need a spark of life to make life go. You don't need an immaterial soul to make consciousness go, and so forth. And it's always going to be a tricky thing to make a case like that, because you're admitting that you don't know the final answers, so you can't say, here is the final answer. You're making a claim that it is probable or you should have the most credence that when the future final answer comes, we'll take a certain form.

0:01:16.8 SC: And to do that, you have to face up to some of the issues. And of course, the bridge from the brain to the mind is one of the biggest issues that you have to face up to. You can see why there's plenty of people, philosophers and other people, who will want to accept the idea, that the mere physical motion of stuff that makes up the brain is not enough to account for consciousness or feelings or whatever it is that you have your attention focused on when you're thinking about the brain. After all, there just seems like a gap, as they like to say, between a description of, oh, there's this neuron, it's firing, versus saying, oh, there is the experience of being in love or something like that. So the naturalist has to say, sure, we don't understand it yet, but trust us, we will get there. And it is fair for the non-naturalist to say, show me the money, show me some advances in how we've understood things. And it is also fair for the naturalist to provide that. There's plenty of ways in which we see things going on in the brain, in the biochemistry, that show up in the higher level version of the mind that we like to talk about in our thinking, in our consciousness and so forth.

0:02:33.9 SC: We've talked about this a few times down the years, and even very recently with people like Christof Koch. So nevertheless, when you dig a little bit deeper, there are reasons to think that it's kind of a shame or maybe puzzling that we haven't made even more progress in understanding and manipulating the higher level functions of the brain that we think of as the mind. So today's guest, Nicole Rust, who is a neuroscientist at the University of Pennsylvania, has written a new book, and it's an interesting thing because it's not a book just about her research. As we'll talk about, it's her first book, but she didn't just say, "Well, I'm gonna say all the fun things in my research." She really used the opportunity of writing a trade book to explore a problem that she thought was underappreciated, namely... Well, let's put it this way. The title of the book is "Elusive Cures." The subtitle is: "Why Neuroscience Hasn't Solved Brain Disorders-and How We Can Change That." The point being, you might have thought with all that we learned about the brain, we would be much better than we really are, at fixing the brain when it doesn't behave the way that we think it should.

0:03:46.2 SC: Putting aside questions of, what should the brain behave like, that's certainly an important set of questions, but not what we're talking about here today. So that's what we're talking about, both the evidence that it's harder than you think to go from knowledge of the brain to curing disorders of the brain and also suggestions as to how to do better. And I don't wanna spoil too much, but I will say that I'll spoil a little bit. The main suggestion is to stop thinking about the journey from chemicals and biology to behavior as kind of a one-way flow of causal influence. Here is a gene that causes a neuron to do something, that causes the brain to do something, that causes some human cognition going on.

0:04:31.7 SC: That's too simple. In fact, instead, and I promise I didn't know this ahead of time when I invited Nicole on the podcast, the thing that she's advocating for, is thinking of the brain as a complex adaptive system with many layers that have feedback and influence on each other. You can't just start at the level of genes and expect to get everything done. You have to think about behavior and environment, right from the start in addition to thinking about the neuronal basis of what's going on. I love it. I think it's a good way to make progress on these things. Complexity once again for the win. Let's go.

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0:05:26.0 SC: Nicole Rust, welcome to the Mindscape Podcast.

0:05:27.9 Nicole Rust: Oh, thanks for having me, Sean. I'm such a big fan of Mindscape, so it's just a real pleasure to be here.

0:05:33.0 SC: Oh, that's great. You have a new book coming out about a fascinating topic of why neuroscience hasn't been as helpful to attacking brain diseases as maybe it could have been, and we'll definitely get there, but I wanted to give you a little bit of a chance to talk about your research, which is related to that topic, but not exactly on that topic. I get the impression that most of your work has been done in something along the lines of visual object recognition, how we see things, right?

0:06:05.5 NR: Yeah, absolutely. So yeah, I got into the field of brain research really just curious about how the brain works, and I still, on the other side of writing this book, I'm still very much a basic or foundational researcher who's curious about how the brain works, although the things I'm curious about have changed. So yeah, so for a lot of my career, I really got into this career, I was inspired in my second year of college, I read a book that Francis Crick had written, called the "Astonishing Hypothesis: The Scientific Search for the Soul.

0:06:34.9 SC: I have that book.

0:06:37.9 NR: And yeah, it just made me realize that that's a job.

0:06:40.2 SC: Right, you can do that.

0:06:41.1 NR: You can scientifically search for the soul. So I was in, I was all in, and in that book, Francis Crick talks about how seeing and the visual system, can be a really great way into some of the bigger mysteries of the brain like consciousness. And that really planted the seed for me. So for a lot of my career, I studied what's happening in our brain, when we're seeing things, we're trying to identify the things we look at, and I've been systematically marching higher and higher up into things that are kind of more cognitive.

0:07:10.3 NR: So from there, how do we find the things that we're looking for? So if you're trying to find, say a face in a photograph, how do you achieve that? You have to not only recognize what you're looking at, but you also have to have a target. And most recently, how do we remember what we've seen? So we have that really intense experience. We're walking down the street, we see someone, we have that aha moment, like, oh, I know you. So how does that work in our brain? And how do we manage to store not just a few memories badly, but tens of thousands of images of the things that we've seen really well, memories of the images we've seen really well? So yeah, so that's been the majority of my career up to the point of writing the book, was focused on things like vision and memory and that sort of thing.

0:07:53.7 SC: Have you found the soul yet? 'Cause if so, we should talk about that. [laughter]

0:07:56.5 NR: Yeah, no. We haven't.

0:07:58.2 SC: Okay.

0:07:58.9 NR: We're working on it.

0:08:00.6 SC: What did Francis Crick mean by that provocative title?

0:08:04.4 NR: Yeah, let's see if I can. I think I might be able to recite the astonishing hypothesis, we'll see if we get it right. You, your joys and your sorrows, your memories and your ambitions, your sense of personal identity and free will, are nothing more than a vast assembly of nerve cells and their associated molecules. I think I said it right.

0:08:24.9 SC: Right. Good. [laughter]

0:08:26.8 NR: That was the astonishing hypothesis. That you are just your brain basically.

0:08:31.1 SC: And he's doing it, he's phrasing it in such a way as to sort of maximally annoy people who want to emphasize emergence over reductionism. He was a happy reductionist. [laughter]

0:08:41.5 NR: Yes, he was a very happy reductionist.

0:08:43.9 SC: And we'll get into that.

0:08:44.3 NR: He's very much a product of the 1990s.

0:08:46.0 SC: Right. Well, good. Very good. And another thing that it reminded me when you were talking about the vision stuff, it's kind of natural in this day and age, for us to think of the brain as a computer or a camera or some other piece of technology. And we'll see failures of that paradigm later on, but how well does that work just for vision and recognition?

0:09:08.6 NR: Yeah, it does a pretty good job. It does better than anything else up to this point insofar as one of the big breakthroughs in that field, happened in around 2012. And it was in computer vision actually. So for a long time, we've been trying to create models of how the brain can look at images and recognize the objects. And the big challenge there is that, an object and an image can be on the right side, the left side, it can be big, small and different backgrounds and different poses. And so that's the big question. How does the brain figure out the identity of the object across all that different type of variation? So we've been trying to build models of that for decades of how the brain manages to do this. And in 2012, there was a breakthrough in computer vision, where they were also interested in solving the problem, but for computer vision purposes. So Google, you wanna be able to type in, give me a picture of a cat with a hat and it will give it back to you. So you need to solve that problem.

0:10:03.8 NR: And they trained these deep neural networks to solve that problem, which was really an engineering breakthrough for computer vision. But it turned out that the way that those models worked, bear is like a striking resemblance in how the brain does it too. So those actually became our state of the art models of how our brains perform the same thing.

0:10:25.3 SC: I actually think I have not heard that story before. We all know that neural networks, the name gives it away, were sort of inspired by actual neurons. But then there's always this worry that maybe real neurons are a little bit different. And you're saying, here's an example where doing it on the computer actually helped us understand the brain. I was not aware of that one.

0:10:47.7 NR: Absolutely, yeah. It's called a task optimized framework. It's not just working for vision, it's also working for the auditory system as well and some components of memory. Yeah, it's been a big push forward for us to have those models.

0:11:01.5 SC: Could you just simply explain what the phrase task optimized framework means?

0:11:06.8 NR: Yeah, absolutely. It's, you specify a task that a neural network has to solve, and then you train it to solve it, and then you compare it's solution to how the brain does it. That's the idea of the task optimized framework.

0:11:18.3 SC: I see. Okay.

0:11:19.8 NR: And so, yeah. Can you, is it, what about seeing, what specific visual tasks could you have to train a brain to perform in order to get it to look like a brain. And so, it turns out that the problem of recognizing the objects in pictures is a pretty good one. Whereas, what color is this shirt or something? It's not gonna give you a whole...

0:11:42.0 SC: Not a very good. Yeah, that's a different, is it too easy, I guess, the color?

0:11:45.8 NR: It's too easy. Yeah, exactly. It doesn't give you enough content.

0:11:49.5 SC: Do we connect the computer version and the real brain version to the level of neurons, or is it more higher level functional?

0:11:55.8 NR: It's more higher level, and that's something that's actually changed in the field over the past decades as well. We really used to focus on the brain and looking at what the individual neurons were doing, but now we've kind of taken a step back and really started to appreciate that it's really how an entire population of neurons, it's the pattern of activity across a big population. So it's really, yeah, an alignment at that level.

0:12:21.4 SC: Okay, great.

0:12:21.5 NR: Are things that are close together when we see two images? So we'll see a horse and a basketball. Oh, sorry, a horse and a cow will look more similar to us, than a horse and a basketball, and there'll be parts of the brain that reflect that too in their population responses. So it's that alignment at that level is what researchers are looking for.

0:12:40.9 SC: Okay, great. And the other thing, just 'cause I follow you on Bluesky, so I know this, you've been thinking about moods lately. Moods, not moos as in cows, but moods as in I'm in a bad mood or something like that. And does that grow naturally out of the work on vision or is it a different angle?

0:12:57.8 NR: Well, it's definitely inspired my approach to studying mood is very inspired by how I used to study vision and memory, but it really came out on the other side of the book. So my career as a researcher has been very much in the weeds studying what I'm studying. The book gave me this opportunity to zoom out and look at all of brain and mind research from a high level. And then I was able to ask, what needs to be done? And so, on the other side, I realized while our progress and understanding how the brain does many things, like see and remember and hear and even motor control move, that seems to be progressing at a pretty rapid clip. But then when it comes to the neuroscience of feelings, like how happy are you, that's not progressing as quickly. And that's really important when we're talking about the psychiatric conditions like mood disorders and depression. So I decided that I would dive in there and help contribute.

0:13:56.5 SC: So you've already done a wonderful job of giving us two super good reasons for professional scientists to write popular books. Number one, inspiring young people, and number two, giving us our own new research directions. It's definitely been true for me.

0:14:08.9 NR: Absolutely, absolutely. And I think that's a really underappreciated component of writing at this level that you would write for a general audience, is yeah, it just gives back to the research program in so many ways. It can get you excited about things you haven't been excited about in a long time. It gives you new perspectives 'cause you have to just pull the pieces together. So yeah, I absolutely, I don't think of writing as a service. I think of writing as kind of selfish on my part.

[laughter]

0:14:35.6 SC: And it also helps sort of remind you of those little bits that aren't well understood, and you've been sort of putting aside because you're focusing on other things, but then, you have to tell the whole story in the book, right?

0:14:46.8 NR: Absolutely, absolutely, yep. You definitely see where the holes are. It makes them really apparent.

0:14:51.7 SC: So good. What's the title of your book?

0:14:53.5 NR: The title of my book is "Elusive Cures: Why Neuroscience Hasn't Solved Brain Disorders and How We Can Change That."

0:15:01.0 SC: And I love the fact that right at the beginning of the book, the super-duper beginning, I guess the preface or whatever, you confront the issue that the phrase brain disorders is gonna get you in trouble if you're not careful about it. So you don't shy away from using it, but you try to be careful about it.

0:15:18.7 NR: Yes, yes. I think that's really important, especially in this kind of a confusing time. There are legitimate concerns that what we have called brain disorders are really forms of neurodiversity that society has wrongly become intolerant to. So things like attention deficit hyperactivity disorder. Is that really a disorder or is that just a form of difference that we should embrace? But that's also a case where, not everyone with ADHD will want or need treatment, but there are some individuals who really do. It can cause severe insomnia. It can cause the inability to hold a conversation. So in broad strokes, I think that for all of these conditions, there are definitely subsets of individuals who want treatment and our treatments fall short of what we should be able to offer them. We want better solutions for them. So that's the way I use that term disorder, is just acknowledging we need better solutions. So it's very empathetic on my part.

0:16:20.1 SC: Yeah, and there doesn't seem to be any reason in principle why we can't say, let's figure out how to help people who want help, while also not stigmatizing those who are doing fine.

0:16:30.8 NR: Exactly, exactly. You've nailed it right there.

0:16:34.5 SC: So just so we're sort of, the audience is thinking along the right ways, what's our set of paradigmatic brain disorders? What are the kinds of things that we're thinking about trying to do better at tackling?

0:16:46.5 NR: Yes, so the field is generally parsed into the neurological conditions, and then the psychiatric conditions. There's an interesting distinction there, where for the most part, something gets piled in the psychiatric condition pile, if we don't have any sort of biological test for it.

[laughter]

0:17:09.4 SC: Yet.

0:17:10.7 NR: Yet, exactly. So yeah, so neurological conditions include everything from multiple sclerosis to Alzheimer's and Parkinson's disease. Those are all neurodegenerative conditions. There are also forms of pain, chronic pain, migraine headache. And then in the psychiatric case, we have conditions like depression, anxiety, schizophrenia, other forms of psychosis. Those would all be psychiatric conditions.

0:17:37.3 SC: How plausible might it be, that this division goes away when we get better at probing the brain?

0:17:43.0 NR: That's the hope. And there's an example of that. It's called NMDAR encephalitis. So it manifests with psychosis like schizophrenia does. And then it was in 2008, researchers discovered it's actually a neuroimmune condition. So for some reason, our immune systems create these antibodies. We just have this big immune system attack on a certain type of receptor in our brains, that causes brain swelling and causes a psychosis. But once they realize that that was the problem, they could go in and come up with treatments for it. So it's only a handful, a very small fraction of psychosis is thought to emerge from this type of brain swelling. But it was one of these conditions where it really demystified what's going on, at least in those patients. And so, we have biological markers for that. So yeah, that's the dream. And the reason that that's the dream, is once we find a biological marker, then there's hope that that will then lead us to a treatment.

0:18:44.4 SC: Yeah, exactly.

0:18:45.7 NR: So we figure out what the problem is and then we can find a solution for it. And yeah, that's the big challenge for the psychiatric conditions is we don't even know what's going on in the brain and the body. So how can we even try to treat it? Yeah.

0:18:56.5 SC: Yeah, and it struck me while reading the book that something like depression or even insomnia, these are two examples of brain disorders in some sense that you mentioned, but they just seem different from Parkinson's or Alzheimer's, not only because maybe it's harder to note a physiological difference, but because they're broader. There's not gonna be a gene for insomnia, because there's too many reasons why I could become insomniac.

0:19:29.5 NR: Absolutely. And that leads us to the problem of precision medicine. So it's clear that some of these conditions, which we give one name like insomnia or depression, they have a multitude of underlying causes. And we've learned from other types of disorders like the lung disorder cystic fibrosis, that that's actually a mutation in a single gene, but every different mutation requires a different drug to treat it. So that's the idea that there's a lot of suspicion that that's happening in brain disorders too, that all the different causes of depression, all the different biological causes of depression, will require different treatments. But that creates this really complicated chicken and egg problem. So how do you find the cause of something if you can't group together individuals with the same cause, because the only way you can define it, is by their symptoms, and that's just one big heterogeneous group. So that's big a problem. The suggested solution for that problem, is what we need to do is we need to measure lots of stuff about that big giant group of individuals that are loosely defined by their mood disorders. And then somehow, if we just do some clustering analysis or something, we're gonna figure it out. But that really depends on getting those measurements right.

0:20:47.0 SC: Sure.

0:20:48.2 NR: So we have to measure the right things. And that's where brain research has been a little bit stuck, is trying to figure out how do you measure something like mood in the brain.

0:20:57.9 SC: Well, you do a very nice job in the book of portraying the present system or the present situation as being in a paradigm, and maybe the paradigm is falling short of some questions that we wanna ask. And that's very understandable. We've all been there before. And you've labeled the paradigm, The grand plan of modern neuroscience. Does anyone else call it that? Is that your name? [laughter]

0:21:20.4 NR: No, I just totally made that up. I needed something pithy.

0:21:24.3 SC: That's good.

0:21:25.5 NR: So, shake the conversation around the grand plan.

0:21:26.7 SC: Tell us what the grand plan of modern neuroscience is.

0:21:29.4 NR: Yeah. So I think every era has a grand plan. But conceptually, what is a grand plan? So the grand plan, it's something I refer to very affectionately. It's not meant to be derogatory. So it's really just this broad strokes description of how the researchers in any era, plan to get from wherever they are to that end goal, whatever it might be. And when I think about brain research, I think about it having not just a single end goal. It has multiple end goals. We wanna understand brains to understand them, because that's a worthy goal in and of itself. We're very curious about ourselves. We wanna understand brains to build things like them, like AI. And we also wanna understand brains to treat brain and mental disorders. And that third one is the one I shaped my book around, because that's the one that seems to be lagging behind the other two, quite frankly.

0:22:16.9 NR: And so, yeah, the book was really inspired by that question, like why? Why is there's this disconnect between what we're discovering and where we think we wanna head? But yeah, so that's a big question. What is the grand plan of our era? When we fast forward 30 years from now, we look back on the 2020s, what are we gonna say was the genius of our era? The thing we all rallied behind and really said, yeah, that's what we did. That was a big breakthrough.

0:22:42.4 SC: And the present paradigm is something about molecular medicine. There's some journey that we imagine taking in the ideal case. And you're gonna say this is not the thing to do, but ideally, we find a gene for something... We cure it.

0:23:00.5 NR: Yes, absolutely. Yeah. And it was really, I think it was... I like to think it was really shaped around two things that might be going wrong in the brain. One of them was, yes, molecular medicine, which was the idea that you might have a mutated gene or a gene that isn't expressed in the right way, and that might cause a problem like... Brain dysfunction. And then the other is, you might have a brain area that has aberrant activity. And so that, would also cause dysfunction. So yeah, in the 1990s, there was tremendous enthusiasm that if we just sequenced genes and we imaged brains, so we had this new technology, FMRI so we could look there under the skull and see what's going on, that we would figure out the causes, of what causes brain disorders and then we would be able. That would lead us to treatments. And that just hasn't really panned out.

0:23:50.2 SC: Well, you tell the very compelling story of the example of Alzheimer's disease, where you might very well have thought it was gonna pan out, and it hasn't. So let's rehearse that one.

0:24:03.0 NR: Yes, absolutely. Yeah. So over 30 years ago, researchers discovered a single gene mutation that leads to Alzheimer's later in life with certainty. And that gene is called APP, and it codes for a protein called amyloid. So researchers knew, going back to Alzheimer himself in the early 1900s, that the brains of individuals with Alzheimer's have these protein clumps. Later after Alzheimer, they realized that they were clumps of amyloid protein.

0:24:34.7 NR: But with this discovery that the gene mutation for amyloid causes Alzheimer's, they inferred that amyloid is the cause of Alzheimer's, not the consequence. These clumps aren't the consequence. And so, they very reasonably set off to do something heroic, and that is to clear these amyloid plaques from the brain. And they did it. It's just one of these just amazing feats of bioengineering. And that's our latest generation of amyloid-clearing drugs that have been approved in just the past few years. So everyone was very excited about them. The tragic story ended with those drugs don't really seem to slow cognitive decline in the way that we hoped they would. So they do slow it down. I think in a disease that has a course of about eight years, they add about eight months to the progression of the disease. They slow it down by eight months. But they're clearly not the magic bullet. It's not just that if you clear amyloid plaques from the brain, you stop Alzheimer's disease in it's tracks. So yeah, the big question is, oh, what's going on there? That was supposed to be the path. Find the gene, and then fix it. And it was supposed to be fixed, and it was not fixed.

0:25:48.5 SC: So what's going on there?

0:25:50.4 NR: Lots of discussion. Yeah. Lots going on there. And it could be that that amyloid hypothesis is wrong. That the gene mutation is really a small, small fraction of Alzheimer's patients. So that's probably a big heterogeneous group with a multitude of causes. That's one possibility. There's another protein people like to point to. It's called tau instead of amyloid. Maybe that's the problem. Maybe that's the toxic protein. But I think more compelling case can be made that maybe there's a single protein that's toxic in the brain stories are a massive oversimplification of what's going on with Alzheimer's. And in fact, the individual who discovered the gene, his team is John Hardy, and he came up with the amyloid hypothesis. And now he really thinks that this is a massive oversimplification. He thinks that we have to be thinking not just about proteins, but how proteins and neurons and organ systems and how toxicity travels through the brain. A really multi-level, complex, dynamical system type of approach is what he's proposing at this point. And I agree with him. I think that that's the way to go.

0:27:00.5 SC: So just to understand it completely, if you have this particular mutation, you said that with certainty, you're gonna get Alzheimer's?

0:27:06.6 NR: Yes.

0:27:07.1 SC: But not all people who get Alzheimer's have that mutation?

0:27:11.0 NR: Exactly, exactly. And for most, so there are a couple different types of Alzheimer's. There are the couple of genes that if you inherit them, you will get Alzheimer's with certainty. There are other genes that increase the probability that you'll get it, but they do not ensure it. And then there are other cases where we just can't even find any sort of genetic cause. Yeah, so three different categories.

0:27:35.9 SC: But okay, is it possible that in the case where you do have that mutation, and you are 100% gonna get Alzheimer's at one point or another, is it possible that the gene really is doing the work, but it's doing it through some mechanism other than this protein?

0:27:53.2 NR: Yeah, absolutely. So there's no question that in those individuals, the genetic mutation is causing Alzheimer's. There's no question about that. It's just the question of, will an amyloid-clearing drug actually help those individuals? The suspicion, there is still hope for those families, that maybe those drugs were just given too late, because you start to see signs of this accumulation 20 years before you see the onset of symptoms. And that's when those drugs were given. So there is some hope for those families, that maybe if they can just keep the amyloid plaques out of there, that will help. But it's not clear that that's gonna work either.

0:28:34.8 SC: And just because we don't assume that we know a lot of biology here, there's no way to go in and fix the mutation in all the cells in your brain?

0:28:46.1 NR: Not yet. There's hope that there will be a gene therapy for this someday. But yeah, you're born with all of the neurons that you have, and you're ever gonna have for the most part. That's debated maybe a little bit of neurogenesis later on, but for the most part, you're born with them all. And so, you can't do, for example, what they're doing with sickle cell where they're taking the blood cells out of the body or the bone marrow, and doing something and then putting them back in. That's not gonna work for a brain. And yeah, we're just not good enough at gene editing techniques yet to go in and edit all of the genes so you can fix the mutation. Yeah, I think we're probably a ways off from that one.

0:29:30.5 SC: If we could do it at the embryo level or something like that, maybe just change a couple of genes, and then the grown up would be okay. But once you have 85 billion neurons in your brain, that's gonna be your neurons. [laughter]

0:29:44.5 NR: Yes, absolutely. You got what you got.

0:29:47.1 SC: Okay. [laughter] So that's a very good example of something that seemed perfectly plausible that we would really just cure it. It didn't work. How do you conceptualize the reasons why, not just for Alzheimer's, but in general, what are the flaws in this sort of, you had a phrase for it, like the domino Chain of going from genes to neurons to brain function to results?

0:30:14.3 NR: Yeah. So I think of the 1990s way of thinking is really, it is set up as a domino chain of causes that lead to effects, like how genes then lead to proteins, lead to neurons. It's also, there's another way of thinking about that too, is like how information propagates to the brain. So information comes through the eyes and it goes through one brain area and the next. And in both cases, they're a domino chain of causes that lead to effects. And the goal then, is to go find the broken domino in the chain, 'cause that's the presumption, there's something in that chain that's wrong. And so, we wanna pinpoint it, and then target it for a fix. So if it's a mutated gene, that would most likely be a drug or maybe a gene editing type of technique. And if it's a brain area that has abnormal activity, then we might go in and target it with brain stimulation, which could either happen non-invasively or it could be happening like lowering electrodes in the brain. But yeah, I would call that find the broken domino and fix it. That was kind of the pithy phrase of the... That was the grand plan in the 1990s.

0:31:10.1 SC: Right.

0:31:10.9 NR: Yeah, and it hasn't panned out. And so, then we can ask, why didn't it pan out? And upon reflection, researchers are really realizing it was a massive oversimplification of the brain. The brain is held up as the most complex thing we know about in the universe. And so a domino chain is not super complex, even if it has a whole lot of levels to it. So what is so complicated about the brain? Well, the brain is full of these big feedback loops at all levels. So between the levels and within the levels. So for example, if you have brain area A that sends information to brain area B, brain area B sends information back to A again. So now you have a system where you don't just have causes leading to effects, but you have those effects feeding back again on the causes. So this is a whole different type of system. It's a complex dynamical system. And we know so much about these systems because we've studied them in other contexts, things like the weather and ecosystems and nuclear reactors.

0:32:12.3 NR: They're the stuff of physics and ecology and meteorology and oceanography. Yeah, and so those systems can go awry in ways that cannot be attributed to broken dominoes. So they really, their emergent surprising properties follow from the interactions between their parts, not just the individual dominoes in the chain. And so yeah, I think there's every reason to suspect that these, especially when we get to things like the psychiatric conditions. It's not surprising to think, oh, consciousness is the emergent property of a complex system. Well, of course it is. Of course it is. Nobody would doubt that. So yeah, I think that's where the research program has really been going awry is oversimplification.

0:32:57.7 SC: And so, the general idea would be to treat the system more holistically rather than as a simple linear chain?

0:33:04.1 NR: Yeah, holistically. And we can break down exactly what that means. But yes, I think definitely capturing the interactions between it's parts in that sense. So measuring the parts all at the same time, as opposed to one at a time, and also approaching it from the top. So here's a phenomenon that needs to be explained, like some brain function. And so, how does the brain give rise to that, as opposed to if we just understand how the neurons work, then from the bottom, we can kind of build up and then out will come the mood. [laughter]

0:33:40.7 SC: Yeah. You can kind of see as the book goes on, you're hopping aboard the complex adaptive systems train, and you realize like, yes, this is a good paradigm for thinking about these things. We need to bring this more into neuroscience.

0:33:54.5 NR: Absolutely. And I will be honest and admit, I was not on that train before it reached at this point.

0:34:01.1 SC: That's good.

0:34:01.6 NR: I did some of this type of work when I was, before graduate school. And I just thought, I don't know, if the brain is oscillating in some way, if it's walking or breathing or something, I get these dynamical systems types of approaches, but I didn't get it until I sat down and realized like, oh, these are complex adaptive systems gone awry. That's really what's causing brain disorders.

0:34:23.4 SC: Well, and you do a good job though, of pointing out that even though we are gonna label something, a complex system, we often model it in a very simple way. You can still oversimplify even while saying you're doing complex systems?

0:34:36.3 NR: Yes. And so, yeah, all models are wrong, but some are useful. The famous phrase...

0:34:41.5 SC: Exactly.

0:34:42.8 NR: Yeah. And I think getting that right, that threading that needle, that is one of the big challenges of our era. Is how do you get that right? And that's a challenge for all of science.

0:34:51.2 SC: Sure.

0:34:51.6 NR: Yeah. Not unique to brain research.

0:34:52.6 SC: And another problem that you mentioned, about the sort of the domino chain grand plan, is we can't fail to admit that we are studying neurons, but we still fail to understand how they give rise to a mind.

0:35:07.8 NR: Yes.

0:35:08.8 SC: And maybe that matters. Maybe that's important. [laughter]

0:35:11.8 NR: Yeah. And I think that really gets into another topic that I talk about in the book. And that is this concept of epistemic iteration.

0:35:22.9 SC: Lay that on us.

0:35:23.9 NR: Yeah. So this one I've thought about a lot, especially as I transitioned to studying something very mysterious mood. And the problem there is, how do you measure something? 'Cause that's really what you're getting at. How do you study something? What should you be studying about it? If we don't know how a brain gives rise to a mind, which way would we measure? Should we measure the mind or the brain? So the problem of epistemic iteration is, once we understand how something works, we'll know exactly how to measure it. But you need measurements to create understanding and you need understanding to create those measurements. So where do you even begin? And Hasok Chang did a beautiful job in this book, Inventing Temperature, of describing how researchers in the 16th century traversed from a sense of hot and cold and some observations like puddles freeze through these rudimentary thermometers, all the way fast forward to thermodynamics and statistical mechanics and the ability to measure temperature with exquisite precision near absolute zero. And we did that across 250 years. So how did we do that? How do you make this happen? And it's the same question really for mood and depression.

0:36:36.0 NR: We have a sense of what depression is. We have some very rudimentary ways to measure it, like these depression scales, which ask you, are you feeling sad? And do you have insomnia? And we want the thermodynamics of mood. So how do we get there? And so, Chang argues that in science, we just have to jump in and take our best guess at how to measure something. And we just have to hope that that's gonna get us close enough. But what we have to do is be committed to refinement. That's really important. You have to be committed to making your measurements better and better. And at some point, you're gonna integrate those and use those to inform theory. And there'll be an interaction between measurement and theory. And this is how we make progress. But going back to the example of depression, it's been noted that in clinical trials for antidepressants, the measurement we're using for depression was developed in the 1960s. And as Eiko Fried and his colleagues say, "Since then, we put a man on the moon."

0:37:34.2 SC: [laughter] Things have happened.

0:37:35.0 NR: We put them in our pockets. We're globally connected. And we're still using this very rudimentary scale. Like, what's that about? And it turns out that it's not that we haven't thought to make a new one. There are actually 250 different scales for depressing.

0:37:50.7 SC: That's depressing.

0:37:52.6 NR: Yeah.

[laughter]

0:37:53.0 SC: That's depressing. Yes.

0:37:54.3 NR: No, it is. It's crazy. And so, I'll stick my neck out and say, I don't think the next big breakthrough in that research program is gonna be creating the 251st scale. I think we need a new way to measure depression. So yeah, that's the next big step. But this gets to your kind of question. How do we even study something if we don't have knowledge of, if we don't know how the brain gives rise to the mind, how can we make any progress? And it's like, well, Sean, we just got to jump in with our best guess, that it does.

0:38:27.1 SC: This is already, yeah. This is exactly my philosophy of science, which I'm very happy to hear because, philosophers of science are no more innocent than scientists are about oversimplifying things. And people like Karl Popper or even the old logical positivists, they had a view of figuring out what was right and wrong in science, which was a little too clean. And what you, this epistemic iteration that you just talked about, it seems much closer to the best reality of it for me.

0:38:58.5 NR: I agree. I agree. It also, for me, another thing that epistemic iteration really shed insight on, is across the years, as I would go to the same meeting, the annual meeting with 30,000 researchers, the Society for Neuroscience meeting, I would just look and I had this idea that what we were doing is any generation would lock down some knowledge, and then we would move on to the next question. But I just saw, we just keep asking the same questions again and again, like some brain area. We're just stuck in this one brain area, just trying to figure out this brain area. We're never moving on. What's going on there? [laughter] And I think epistemic iteration, it suggests like, yeah, we're gonna continue to ask the same questions, but we're gonna refine the answers. So the answers are gonna get better and better. It's not that the questions are gonna necessarily change. That was really hopeful for me. It just made me reinterpret what we were doing in the best way.

0:39:47.2 SC: Good. Yeah. And I guess there's a parallelism between sort of the pure research idea of the dominoes falling from genes to neurons to brain function or whatever. But then there's also this more clinical aspect. You talk about the, what is it, the bench to bedside paradigm, how you go from a basic researcher like yourself, to actually implementing things. And that also seems to be an oversimplification of the right way to make it work. It's less successful than you might think.

0:40:21.3 NR: Yeah, I think that's a great point. It is also very much set up as a domino chain that just that phrase bench to bedside.

0:40:29.3 SC: There you go. Yeah.

0:40:29.5 NR: And yeah, if you look back on the history, so to do the research for this book, just to wrap my head around what's going on, I took every therapy we have for every brain disorder, every single therapy, and I traced back their development story to figure out where they came from, like what was the discovery that led to them? And then what happened next? And that was just really, really insightful. It made me realize how few drugs really have been developed via bench to bedside research. So one example, is the first antidepressant that we ever discovered was a clinical trial for the lung infecting bacteria tuberculosis. And in that clinical trial, people were dancing around and happy. And so, they said, oh, well, maybe this would be great, as for mood and depression. And this is a time before we understood basically anything about the brain at all. And so many of our drugs you can trace back to there was a serendipitous discovery that happened in the 1940s or the 1950s. And then we continue to refine the drugs to make them better. And sometimes those refinements really did depend on knowledge about how the brain works, but they still work in the same way fundamentally as the other ones.

0:41:42.9 NR: So those are some cases. And then there are other cases. There are a minority of cases, but there are these epic discovery stories of drugs that really were there's some big discovery about the brain that led to some new drug. So those do happen. They're just more rare.

0:41:57.0 SC: What is your favorite example of that success story? We should give the reductionists their kudos.

0:42:02.6 NR: Yeah. So in the book, I talk about the drug Suvorexant, which is a drug to treat insomnia. And it was traced back to decades of research that led to the discovery of a new type of chemical in the brain, that allows brain cells to communicate. It's called orexin. And what they realized with the discovery of orexin, was there, it's a chemical that actually keeps you awake. So they already knew about chemicals in the brain that put you to sleep like melatonin. So this does the opposite. So when orexin binds to it's receptor, it keeps you awake. And so, this discovery of this drug, like I said, it was decades to get up to that point of understanding what was going on there. It triggered this flurry of interest by the pharmaceutical companies, thinking that maybe some people suffer from insomnia, because they have too much orexin binding to the orexin receptors. So then the goal was to block those receptors so the orexin can't bind.

0:43:02.9 NR: To do that, we had to screen two million different compounds to figure out one that would block the orexin receptors, and then put that through clinical trials. I believe it cost something like a billion dollars, but then the drug suvorexant was born. So you have decades of academic research, another decade in the pharmaceutical industry, and then you get a drug. It's just a really epic tale of how many people and hours went into the development of that.

0:43:33.1 SC: But nevertheless, despite success stories like that, you're saying that, and despite or notwithstanding all of the truly impressive progress we've made in understanding the brain, mapping the connectome or parts of it, et cetera, still mostly, our successful drug therapies are either serendipitous or at least they're looking at the high level thing. They're working at the emergent level, not at the reductionistic level. They're saying, "Well, yes, this chemical has this effect on how people behave." I don't know what it does in the neurons, but it's the best thing we can do right now?

0:44:09.6 NR: Yeah. And I would say that there are classes of disorders that seem particularly impenetrable, and they are the psychiatric conditions for the most part, which the drugs were, for the most part developed. They were serendipitously discovered back in the day. Our neurodegenerative conditions, where we do have some drugs to treat conditions like Parkinson's, but we can't slow the neurodegeneration and we don't have really great treatments for, say, Alzheimer's disease. And then yeah, our neurodevelopmental disorders, so conditions like intellectual disability or forms of autism spectrum disorder. Those are the classes that seem to be really resistant to treatments, whereas other types of conditions seem to be more suitable for that, find the broken domino and fix it type of approach. One of those might be migraine headaches, for example.

0:45:03.8 SC: Okay, yeah. Beyond the dominoes falling, is there some light, is there some area where we might just say, the right treatment for this condition has nothing to do with pharmaceuticals? Maybe it's therapy, or maybe it's just a change of environment or taking a vacation or a healthier diet? I don't know.

0:45:29.7 NR: Yeah, absolutely. And certainly when we get to a subset of the psychiatric conditions, like depression and anxiety, there's a big question about what causes them. And so, are those causes external to us? So for example, traumatic events that happen to us, or in the case of anxiety, maybe it's just chronic stress. And so, that is an external cause. And if you can alleviate that external cause, then you can maybe help with the depression and anxiety. There are also internal causes to the brain. So there are these cases where it's not clear that anything incredibly traumatic or stressful happened to somebody, and yet they are suffering from these episodes. Or, maybe they just are more sensitive to those external conditions in a way that you just can't prevent bad things happen to good people sort of thing. And so, those would be examples of where we wanna look inside the brain. For me, I really do, as I think about complex dynamical systems as what the type of thing that the brain is, you begin to think that the problem really amounts to, of a treatment, is what you're trying to do is really influence the brain to shift it from one place to another.

0:46:42.7 NR: So it's in a depressive state, you wanna shift it out of that. That's what engineers would call a control problem. You're trying to shift the system between states. We know that control of complex dynamical systems is really, really, really tricky. We can't control the weather, for example. And so yeah, when I think about that as a control problem, and I think about what depression is, I think there's a lot of evidence that what will be required is doing something like reprogramming the brain. It's the adjustment of thousands, to ten thousands, to hundreds of thousands of strengths between brain cells and how they connect together. And there's just no way we're gonna be able to go into the brain with a drug or a brain stimulation and do that. The best therapy we have in some cases, is a behavioral or talk therapy. So that's a form of just reprogramming the brain by learning a new thing. That's what so much of that type of therapy is designed around. But that doesn't work for everybody. And so, the hope is, that maybe we'll be able to come up with drugs that can enhance the plasticity of the brain to help those therapies along, maybe help them just go a little bit more quickly, or maybe if somebody's resistant to that type of treatment.

0:47:52.5 NR: And that's really what the psychedelic drugs are all about. So that's the hope behind those is, they're gonna enhance the plasticity so talk therapy will work. That said, there's so much to figure out there and there's so much research to do, because you're just as likely to wiggle the brain out of a depressive episode as you are to make it worse. So you have to be really, really careful. People shouldn't be messing around with this stuff. [laughter] I worry so much when I talk about this, and it's my optimism behind it. But I think we have so much work to do to, get that therapy right. But yeah, that's kind of what I would call a benevolent reprogramming of the brain. But that's something right, that's a learning type situation in those conditions where just changing the environment and removing the bad stuff doesn't seem to be effective.

0:48:43.8 SC: Is there a general consensus among neuroscientists, who go in there and study things at a tiny little microscopic level about the efficacy of talk therapies for conditions that we have? Is there some skepticism that it's a little old-fashioned and eventually we'll know better? Or are people sort of, well, the data say that it works and we can respect that?

0:49:07.8 NR: So when you got halfway through your question, I almost interrupted you. Is there a general consensus among brain researchers? And I almost said, whatever he's gonna say next, is gonna be no.

0:49:17.1 SC: No, yeah. [laughter]

0:49:19.4 NR: And when I listen to you, and I listen to Mindscape, I just, I'm so jealous all the time. If you can talk about how things actually work in consensus in the field and what everyone kind of agrees with, like there is no consensus in brain research other than the brain has neurons in it. So I think that there's a lot of debate about all of these things, including how effective are antidepressants? How effective is talk therapy? And part of the reason there's so much debate around it, is a question of like, what's the control group? So there'll be some fraction of individuals whose depression will resolve on it's own with no type of intervention. But those individuals are also experiencing things. So are they talking to their friends? Like, so what's the right control group? You can't put somebody in a cave where they have no experience.

0:50:12.2 SC: Yeah. Not allowed, yeah.

0:50:15.0 NR: Yeah. So that's one of the big debates. But I think I would be surprised to learn that there are brain researchers who do not believe in the evidence-based approaches like cognitive behavioral therapy, because I think the evidence is just really clear that for some individuals, those are very effective treatments. The question is, who are those individuals? And it's unquestionable that they don't work for everyone. And that's one of the big problems in this entire field. Researchers are scrambling to try to figure out if a psychiatrist or a psychotherapist sees a patient, how do you identify what treatment they should have. Ideally, we would wanna know, this person's a good candidate for antidepressants. This person's a good candidate for cognitive behavioral therapy. That's not how it works.

0:51:05.3 SC: We're not very good at that right now. Look, the brain is the most complicated thing we know. [laughter] I'm not surprised that it's taking us this long. I did want to, you mentioned this, and it's something I wanna dig into a little bit more deeply, which is the development of the brain. We're all taught that memories are stored in the strengths of connections between neurons. And that's obviously something that you're not born with. You're not born with, it develops over time. You're certain, we had Alison Gopnik on the podcast recently.

0:51:36.6 NR: That's a good one.

0:51:36.9 SC: And she explained, yeah, very, very good. That you're building more and more connections up to the point where you start pruning connections 'cause you're old and now you're gonna get stuck in your ways. And that doesn't seem like something that we could possibly, well, are there conditions that come about because of that environmentally inflected development that can't possibly be tackled by thinking about the genes, 'cause the genes are there already when you're born?

0:52:08.1 NR: Yeah, absolutely. Case in point, schizophrenia. So if one twin has schizophrenia, the chances of the other genetically identical twin having schizophrenia are only 50%. So right there, we know that this isn't just about genes 'cause they have the same genes. They even have the same womb environment. It's also the case with schizophrenia that it is linked to it's risk, it's incidence is linked to traumatic things that might happen in the wound. So for example, when a population goes through a famine on the other side of that, if women were pregnant, there is an increased risk in schizophrenia and their offspring. So developmental trauma of some sort, but we can't predict yet. We don't know exactly what's causing that. We can just say, oh, this leads to increased risk, but we don't have a really great understanding of that. I do think about that as, again, going back to the idea of complex systems, that adaptability is really the brain's superpower. It's really what those complex adaptive systems are all about. You put us in a new country, we'll learn a new language. It will take some time. If you show us a tiger, our bodies will go into a completely different mode, we will run.

0:53:31.0 NR: And development, is this interesting form of adaptability where clearly the system is adapting to the conditions that were happening during development at all stages. In the womb, and then outside the womb. So in some senses, it is a superpower, but this adaptability also comes at the price of fragility. And some of those fragilities can be linked to the consequences of the adaptability. So we don't have a good theory of that, I would argue, yet for schizophrenia. Like why does schizophrenia, why is that the fragility of, what is the system adapting for? But in the case of something like see a tiger and run, you would want your brain to go into a different mode 'cause it will be more effective at running or fighting or whatever it's going to do. But that's a system that then can burn out. So chronic stress can burn out that adrenaline, cortisol, those are the hormones involved in the system. And that can have consequences. For example, it can interfere with your sleep. So you can become insomnia, you can have insomnia. And during sleep, is when your body heals itself. So that can lead to other problems.

0:54:38.9 NR: It also can cause damage to structures like your hippocampus is where your brain stores memory, is where a lot of your cognitive function resides. So this is really an adaptability that comes at the price of fragility. And the fragility follows from the fact that you're working here with a system that has all these interdependencies in it. Things depend on other things. And so, while that makes us strong in some ways, it makes us weak in others. Yeah, and so it would be interesting to see a theory of schizophrenia emerge that actually can account for schizophrenia in the same way, but I haven't yet seen a good one.

0:55:16.4 SC: Well, just from the perspective of enjoying cool science, it did give you an opportunity in the book to talk about control theory, and you talk about homeostasis and allostasis. I wasn't really familiar with allostasis, but it makes perfect sense in retrospect, so why don't you share that with us too?

0:55:33.7 NR: Yeah, so homeostasis is really adapting to conditions. So when your body starts working out, you produce heat, and so your body needs to do things like sweat to cool itself. So that's really homeostasis. Something's changing and you wanna react to that. Allostasis is anticipating a change that is about to happen and changing your physiology in order to anticipate that change. So I was really interested to learn that, so when we eat and our blood sugar raises, we release insulin to deal with that, we can have anticipatory releases of insulin, so our body will release insulin in anticipation of the meal times that we have, habitually have. Another great example is when we are lying down and we get up, we have to increase our blood pressure so that all of the blood doesn't fall away from our heads and we faint, but that actually happens in an anticipatory way when we're getting ready to stand up before we actually have, so it's not a drop in blood pressure, oh, let's increase it again. It actually, those mechanisms kick into play. So that's the concept of allostasis, is that we're anticipating what's gonna happen next, and then our bodies are reacting to that. So it requires some prediction of the future in order to do it.

0:56:53.7 SC: And is the hope or is the actuality that thinking in these terms, these sort of engineering complex systems, control theory terms, will be helpful when it comes to addressing some disorders of the brain?

0:57:08.7 NR: Yeah, I think for sure. I think it's already been helpful, unquestionably. So there's a wonderful example of that in a treatment for Parkinson's disease. So Parkinson's is clearly one of these diseases that has a bunch of heterogeneous causes. For a subset of individuals with Parkinson's, it's tied to a gene called GBA1. And GBA1 is an enzyme that takes one fatty molecule and turns it into another fatty molecule. So there's one that turns A into B and then the other one turns B into A. And it's involved in doing things like clearing out the gunk from our cells and making them healthy.

0:57:50.0 NR: So the enzyme is a mutation in these individuals with this type of Parkinson's disease. It doesn't lead to Parkinson's with certainty, it just increases the probability of it and increases how bad it is. And so, researchers developed a drug that said, okay well, that gene is mutated. And so, they worked out, okay well, it's A to B, so let's do this in a certain way. It was very domino-chaining. It's kind of the short story. That drug failed in clinical trials. And so then, another group of researchers said, "Well, why don't we map out, it's not really just A to B with one enzyme. There's like a whole chain here, and it's actually this big feedback loop and some of it happens in this thing and some of it happens outside." So they modeled the whole thing as a complex dynamical system. And they could see exactly why that drug that was originally formulated wasn't working, and they could see exactly what to do next. And so, that drug is in, that new drug is now in clinical trials, which I think will be completed, I think in 2026 or something. So fingers are crossed, but this is the type of approach I think that we increasingly will be adopting.

0:59:00.0 NR: Like let's model the whole system as a complex dynamical system. And from that infer, what is gonna work in terms of controlling things. The system is in a state, we wanna move it to some other state, we have to do a thing, what are we gonna do? As opposed to, let's just assume that that thing is mutated, so we have to go in and try to target that. It just didn't work in that case.

0:59:20.6 SC: I love that story because I'm very interested in complexity. I'm part of the Santa Fe Institute, et cetera. And I always do, people are sometimes skeptical as I'm sure you've run across, as I'm sure we've experienced ourselves, that I think the skepticism comes from wondering whether or not there is a thing called complexity versus a bunch of complicated things. [chuckle] We have a lot of relationships between them. But I think you've just given a wonderful example of how thinking of the fact that something is complex, rather than it's specificity as a system is super helpful in controlling it or fixing it in some way.

1:00:01.6 NR: Yeah, and now that you bring that up, yeah, just to riff off that a bit, I've thought a lot about that too. So to what degree are there gonna be general principles or tools that are gonna help us. So that's been one of the big criticisms of complex system. Like if we understand slime molds, is that gonna help us understand the economy? And it's like, oh, that seems like a stretch. [laughter] But yeah, in the brain, if we understand one brain function like vision, how much is that really gonna help us understand another brain function like mood? So that seems like less of a stretch, but in what situations should we be lumping versus splitting or be inspired by? And I think that's a really important question.

1:00:43.8 SC: So you did mention plasticity. I don't wanna forget that, because it kind of vaguely reminds me of the discussion we had with Jim Allison about tackling cancer through immunotherapy. Basically, he's using the body's existing resources to fight cancer, and you just have to trick the immune system into fighting the cancer in the right way without doing deleterious effects elsewhere. So can we use the brain's existing ability to change itself? Can we coax the brain into curing itself of some of these diseases?

1:01:23.5 NR: Yeah, and I think the talk therapy coupled with plasticity, I think that's an important one. And it's not just plasticity is not just relevant for psychiatric conditions. It's also the case that after a stroke happens, there's a lot of damage in the brain, and it can lead to paralysis. So if you have a stroke on the right side of your brain, it often leads to paralysis on the left side, perhaps your hand and your arm. And one of the therapies going back to the early 1900s, is what you wanna do is you want to encourage the use of that damaged limb, that arm, in order, so you tie down the one that works, so you're forced to use the one that doesn't work. And that can be effective in a lot of cases, but sometimes you don't have that full recovery. And so, one of the questions is, well, how then do you enhance recovery for individuals that aren't fully recovering? Is that even possible? There's this wonderful therapy for stroke rehabilitation, which is based on an observation that not everyone knows. I didn't know it before I read about it. And that is normally we think about one side of the brain, like the right side of your brain, controls the left side of your body, 'cause that's just how it works.

1:02:34.1 NR: But it turns out that there are also signals on the same side of your brain to control the same side of your body. So this therapy called IpsiHand, the way it works is it decodes those signals on the same side. And then you learn through a robotic assisted device that's guiding your hand. You spend an hour a day just trying to think and move your hand, and it actually works for some individuals that can learn how to use that stuff that's residual in your brain. So that's just a plasticity. And you're learning via this kind of feedback about how to tap into those things that you've never really tapped into in a conscious or intentional way before. So I think it's a great example of what you're talking about.

1:03:11.4 SC: Is that something where neuroscience will aspire to help us out in the sense that, can we, as neuroscientists, find examples of how to be clever like that and using the brain's plasticity to shunt around problems that it's having?

1:03:31.0 NR: That would be the hope. That neuroscientists would... And plasticity, and I would also say in that realm, there's kind of a plasticity and there's like a homeostatic plasticity, which is really about brain balance. So I think so many of the disorders seem to be a brain that's become unbalanced. And there are these mechanisms in the brain to make it right again. So there's a great example of that in the case of the question, what is sleep doing? So sleep, it turns out, one of the functions of it looks like it probably is reestablishing the balance of the brain. And so, being able to measure that, is a brain in balance? Like my dream would be, we would all wake up in the morning and we would put on our little cap, where we're brushing our teeth. And we'd be like, how balanced is your brain? How sleep restored is your brain this morning? So if that's going awry, we can actually catch it before it gets too far.

1:04:36.2 SC: Yeah. So as a longtime Mindscape listener, you know that at the end of the podcast, we're able to be a little bit more speculative and let our hair down. So you already mentioned the idea of consciousness and how we're not really very good at connecting neuronal level things, knowledge that we now have to the big picture of consciousness. Do we need to? Do you think that that sort of quasi-philosophical quest to understand? I guess going back, not just philosophical, going back to Francis Crick and the search for the soul. Is putting that big picture together going to feed back into down and dirty therapies for ways that our brains aren't quite up to snuff?

1:05:28.2 NR: That's a great question. So certainly, there's a whole realm of consciousness that's obviously clinically relevant. And that's like a coma and anesthesia. And so, there's...

1:05:39.9 SC: The presence or absence of consciousness, yes.

1:05:41.1 NR: Yeah. So we're definitely making progress in that. So being able to figure out how do you determine from brain activity whether someone is actually experiencing something when you can't actually measure their behavior. So at the late stages of a neurodegenerative condition, when you're locked in, you're paralyzed, but you can't move. How would we figure out whether somebody is in there and they're conscious? So that's like kind of a question about consciousness level. What you're asking me, I think is something more subtle and that it's very relevant to this new field I'm moving into. So what makes mood harder to study than, for example, memory is when we study memory, there's actually a task we can... I can give you a memory task and there's an objective ground truth to the questions I ask. Like I show you pictures, and ask you, have you seen them before? So we could shape a task around that. But when I ask you about mood, that's a purely subjective experience. The only way I can measure that, is I have to ask you, how happy are you? And so, then it's getting deeper into it.

1:06:39.1 NR: This isn't just a behavior. This is just that there's something about what are you tapping into? And how would we even know? And it does get into the weeds there, and it very quickly can become unscientific and fuzzy. I'm starting to discover. And so, how do we rigorously study something that can accurately capture the awe and the amazingness of our experience, but be rigorous about it? And that's the big question, I think. How do we be impactful for individuals, especially with psychiatric conditions like suicidal ideation, and just fear and trauma? I think we're gonna have to step closer than we are right now, but I also think we can't wait to study these things until we've figured it all out. We have to really be committed to epistemic iteration. We just got to jump in and start trying to figure this stuff out, and we'll get there.

1:07:49.2 SC: I don't know if you've seen these surveys of happiness levels in different countries in Europe, and there was controversy because recently, Finland came out as the happiest country in Europe, and anyone who's been to Finland knows that's not true, right?

1:08:06.2 NR: Yeah.

1:08:06.9 SC: There's clearly some lack of objective measurements going on. [laughter]

1:08:09.6 NR: Yeah. There's an entire book written. The title is called "Against Happiness." [laughter]

1:08:16.6 SC: Yep. [laughter]

1:08:18.4 NR: Which is just about against the idea that you could measure it. Yeah, that's what you're trying to maximize. So the argument there, just to complete the thought, is maybe we're not trying to maximize the mean happiness of a population. Maybe we're really worried about the variance or the lowest quartile or something like that. So it's a discussion about what is it exactly we're trying to measure.

1:08:41.8 SC: Good. Moral philosophy normativity comes right in. We've had these discussions. The other slightly wacky question I wanted to ask was, near the end of the book, you used the phrase, don't speculate, just show. And not necessarily as you're advocating it, but you're discussing that philosophy, and I don't think you said it in the book, but it totally reminded me of, shut up and calculate in quantum physics, where there's a way to make progress where you don't worry about what's going on in your theory of how the brain works. You just do in and out. You just treat it like a black box, and maybe in some cases, that's more effective.

1:09:24.4 NR: Yeah, absolutely. I think, yeah, in the book I use that in the context of a colleague who experienced a whole career of learning stuff about the eye and how it works, and then you get to the end and you're like, does any of this stuff matter? And so, how would you know that? Well, one way to know that, might be a therapeutic intervention. Where if you can go in, and you know enough to very intentionally change things, then don't speculate, just show. Just get in there.

1:09:55.1 SC: And you told the story of giving a talk in front of the summer school for engineers, and the style of the neuroscientist talking was just not what the engineers were prepared for?

1:10:10.2 NR: Yes, absolutely. That was an interesting experience. Yeah, so it was a summer school for robotics, and they brought in a bunch of neuroscientists to talk about how the brain works with the idea that it might inspire some engineering, and us neuroscientists, we sat there and we kind of debated what we were saying, and the quality of what we were saying and the inferences we were making, and the engineers were just absolutely puzzled by that to the point that one of them raised their hands at the end of my talk and said, "I'm so upset about how this went 'cause I wanted to hear what you had to say, and you guys wasted all of this time." Yeah, when I watch the engineering talks, they're different. There's a demo at the end. Like they say, "This is a robot I built, this is a problem I tried to solve, and everybody will see whether it works or not in the demo." Don't speculate, just show.

1:11:00.1 SC: Okay, I guess the final thought then would be, we talked about the journey from bench to bedside, and how it's not quite as unproblematic as maybe you would like it to be. What is your vision for what that journey should be like? Maybe it's not just a one-way journey, but are we getting better at epistemically iterating and learning from both sides of that equation how to improve both of them?

1:11:30.0 NR: Yeah. I'm still very much a foundational or basic researcher. I still very much believe in the idea that one of the big roadblocks to impacts for society, is we just don't know enough about the nuts and bolts of how the brain works. Insofar as we have a manual for how the brain works, it's full of all these empty pages, and we need curiosity-driven brain researchers to fill it. At the same time, what has changed a little bit in my perspective, is I don't know that curiosity-driven research has to happen so much in the absence of consideration of what the end goals are. So I've been a brain researcher for decades, and I just really never took that kind of perspective really seriously. Like, okay, here's the nature of the thing we have to solve. Let me work backward and figure it out. I thought about it in a very shallow way. So there are memory disorders, so I'm gonna go understand memory, but not in a deeper way. And for me, that's been one of the things that's been very perspective-changing for me. And I guess that's something I wish we could have a more sophisticated conversation around as a community.

1:12:46.3 NR: Like, still very much championing curiosity-driven research. My book is full of termites and cyanobacteria and bugs and worms and all these things. I'm a champion for all of that research. But also, just kind of conceptualizing as a community the problems we need to solve. We need to figure out how to control a complex dynamical system. That's really hard. We need physicists and mathematicians and we need math and all sorts of things to happen. I'm hopeful that there's more in the complex dynamical systems community embracing kind of those ideas, that we're looking for principles, and those principles will be found in simpler systems than they will, in more complicated. We can't take on everything all the time.

1:13:34.8 SC: Are there neuroscientists who are sympathetic to the philosophy?

1:13:40.5 NR: Yeah, I think. Yes, that certainly the book that I wrote, was not written from Nicole's gonna swoop in here and lay her genius on everyone. It was very much channeling the ethos of this era of brain research. Yeah, so I think it very much reflects a very large community of researchers who think this way.

1:14:01.5 SC: I'm not gonna argue with any of it. You're preaching to the choir in this particular case. So I think...

1:14:07.7 NR: I imagine.

1:14:08.3 SC: I hope that people do read this book if they're interested in these things. And this is, unlike the birth of the universe, this is something that affects all of our lives very directly. So it's both fun at the theoretical level and the applied level. So, Nicole Rust, thanks so much for being a guest on the Mindscape Podcast.

1:14:23.7 NR: Thanks so much, Sean. It was a great conversation. I appreciate it.

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