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维多利亚之声
Welcome to Beyond Lab Walls, a podcast from the Salk Institute. Join hosts Isabella Davis and Nicole Mlynaryk on a journey behind the scenes of the renowned research institute in San Diego, California. We’re taking you inside the lab to hear the latest discoveries in cutting edge neuroscience, plant biology, cancer, aging, and more. Explore the fascinating world of science while listening to the stories of the brilliant minds behind it. Here at Salk, we’re unlocking the secrets of life itself and sharing them beyond lab walls.
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伊莎贝拉
Hi, listeners. Welcome to Beyond Lab Walls. I’m Isabella, and today I got the chance to speak with neuroscientist John Reynolds. John is a professor at Salk, where he studies perception and attention using sophisticated and ever-changing computational tools. Without us even knowing, our brains are constantly processing so much information from the outside world, then making sense of it in the form of an internal representation of that world.
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伊莎贝拉
John’s figuring out how we do that. I’m really excited to dig into his science and story with you all. So let’s get going.
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伊莎贝拉
Welcome, John. Let’s get started with an easy question. Where’d you grow up?
00;01;40;02 – 00;01;58;16
John
I was born in Boulder, Colorado, until I was two, and my parents moved down to the Denver area. I loved growing up in Colorado. I’ve lost my connection to that part of the world because our family has all moved away. So it’s kind of an odd feeling. But, yeah, it was a great place to grow up.
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伊莎贝拉
Were you always interested in science from a young age?
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John
You know, my interest in science has always been there, and my parents encouraged it. I, like, as a little kid, thought that a wind up, fully scaled car would be a good solution, and they were willing to invest in that idea. But I didn’t really take science as a career option seriously. So, you know, we didn’t have scientists in my family, and I really didn’t know what I wanted to do with my life when I was going off to college.
00;02;32;07 – 00;02;49;23
John
And so instead of choosing science as a direction, I thought that I should choose something that would give me options in the future. And so I went to the Wharton School and learned about finance with the idea that I might go work in Wall Street one day.
00;02;49;28 – 00;02;54;25
伊莎贝拉
Wall Street! How did you connect the dots from there to neuroscience?
00;02;54;27 – 00;03;19;15
John
Well, I have to confess something, and that is: I went to work. I did a bike ride with my friends across the country, and I wound up in the East Coast without a job. So I put out resumes to 80 banks, and I wound up working at an investment bank. And I got to know a physicist there who was programing for the bank.
00;03;19;17 – 00;03;46;01
John
And at that time in my life, fresh out of college, like most people do, I started thinking about the meaning of my life and what you can know about the world and how you should live your life. And so I was reading things like Immanuel Kant on, You know, The Golden Rule, essentially, and also a book called Principia Mathematica by Bertrand Russell, another British eccentric.
00;03;46;01 – 00;04;10;05
John
And they were thinking about how math could be derived from first principles. Yeah. And I also read the logical structure of linguistic Theory, which is a book by Noam Chomsky that kind of transformed linguistics into a cognitive science. So about the brain instead of about the language. And I was trying to find out how to think about things in rule based systems.
00;04;10;08 – 00;04;36;08
John
And I went to my friend Mike Risch, who is a physicist at the bank, and I told him about this, and he said, well, that’s interesting, but what’s really cool these days is our neural networks. Right. And so the two of us went to like the mall, and we got copies of magazines like PC World and Byte Magazine.
00;04;36;10 – 00;04;53;18
John
If it had the word neural networks on the cover, which at that point in time was really hot, we would take it back to the bank and read about these things and piecing things together. We were kind of able to figure out what a neural network was. And so by day, I was working as an analyst at the bank.
00;04;53;18 – 00;05;24;10
John
But at night we were writing neural network code on the bank’s computers without the bank knowing that. And we were able to train neural networks to do different kinds of problems. And with another friend of mine, we wrote a proof about learnability, demonstrating that with enough hidden units, which are the neurons in the network, we could map any input space onto any output space as long as the mapping was continuously differentiable.
00;05;24;12 – 00;05;45;16
John
And so like that’s the point of early neural network theory. And so I wrote this up like it was a scientific paper, as though it was a scientific paper. I didn’t claim that it was. But I included it in my applications to graduate schools, and they hired me as a graduate student. So I got to got in to graduate student through an unusual path.
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John
I guess a little bit different.
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伊莎贝拉
That’s crazy. Was there any point when you’re reading all that philosophy where you thought about studying philosophy, or were you pretty much immediately set on neuroscience?
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John
I mean, yeah, I was kind of interested in getting it was sort of more like epistemology, like went from really understanding what, you know, one can know. And how should I think about myself in the universe? But I was kind of drawn into neuroscience. I mean, it was really thinking about how does the brain enable us to make sense of the world around us.
00;06;16;23 – 00;06;20;24
伊莎贝拉
So then you started grad school. Where were you? What were you focused on?
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John
So I entered graduate school through a program that had just gotten started in computational neuroscience. And it was I was the second year’s-worth of students. That was at Boston University. And yeah, it was a real transition opportunity for me because coming from finance and going into this all of the other people were physicists by training or they had done engineering or they were math, applied mathematicians.
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John
And so, you know, much better qualified than I was to be there. And I remember really working very hard to take I had learned some math at Wharton, a lot of it’s statistical modeling of stock markets and things like that. But this was different. It was it involved a lot more understanding of dynamical systems. So like, how do you write equations down that describe how some physical system might unfold in time?
00;07;13;24 – 00;07;40;13
John
And the math of that is really beautiful. And so but I was unequipped to learn it. And so it was a lot of, you know, staying up until sunrise trying to learn math. And some days where I was coming home on the T at seven in the morning with a headache because I had been up all night wrestling with some problem that other kids and other graduate students had no trouble solving.
00;07;40;16 – 00;07;51;00
伊莎贝拉
Even though you had to work super hard and felt behind in a lot of ways, were there were times where you felt like you were bringing something totally unique and special to the table because of your finance training?
00;07;51;07 – 00;08;13;18
John
I think working in the private sector and having to accomplish a particular pragmatic goal and do it in a systematic way was something that I brought with me to graduate school, and that helped me organize my life in a way that made it possible to live in the company of these much more accomplished people and compete with them.
00;08;13;20 – 00;08;31;09
John
Some of the very smartest people I’ve ever met were in finance. There’s a really fun puzzle that you guys may have heard of called the Monty Hall Game Show puzzle.
00;08;31;12 – 00;08;49;21
John
The setup is that Monty Hall was this guy who ran this game show, and he had all these crazy people wearing all kinds of funny costumes, and he’d go into the audience and if somebody had, you know, some strange assortment of 3 or 4 different things, they were allowed to come on the stage, and then he’d have three doors.
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Monty Hall
Worth $8,757. Is it behind door number one or number two or door number three?
00;08;57;06 – 00;09;12;20
John
And behind one of the doors was a really great prize, like a new car. And then the other two were like a pile of feathers and a bag of fish or something silly. And he would ask you to pick one door and, you know, say the person picked door number one.
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Monty Hall
Door number one, nobody took two.
00;09;15;06 – 00;09;26;18
John
So and then he would build up the tension by asking the audience if the person should switch. And, you know, there’s no basis for making it switch decision at that point. So he would then reveal one of the doors and.
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Monty Hall
So we’ll take a look in the middle and see what’s waiting.
00;09;30;20 – 00;09;47;06
John
And it was always a loser. So it was like the the, you know, bag of fish. And it’s like, well, he’s lucky you didn’t pick door number two. And if you pick that one, you will become, you know, the proud owner of a bag of fish. And then he would ask you if you wanted to switch. And again, you know, the audience is screaming, no, stay.
00;09;47;06 – 00;10;08;27
John
Stick with what you’re you know, you know, stick with your first choice and switching it. So the question was, should you stay or should you switch? And that’s a very interesting problem, which I will not give the answer to in case anyone is listening and interested in it. But puzzling over that is fun. And the first person I know who solved that problem and could explain it clearly was an investment banker.
00;10;08;29 – 00;10;45;16
John
So I just was really surrounded by very bright people and I was enjoying what I was doing, but it didn’t really feel like it was my calling. And what I was really interested in was more of an introspective journey about myself. I mean, not to sound too self absorbed, but you know, I was more interested in thinking about where I was in the universe and what the universe was about, and I didn’t see myself solving that problem or coming to terms with that problem by doing more investment banking.
00;10;45;18 – 00;10;52;28
伊莎贝拉
When you finished the Ph.D., did you feel like you knew exactly what you wanted your research to be? Did you have your next steps planned out?
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John
So I heard Bob Desmond, who was my future postdoctoral advisor, give a talk at a meeting that was organized by my university, and he was studying the problem of how neural signals in the brain change when we direct our attention to something. And he was able to show, remarkably, that when you deploy attention to one object and another object is sitting in the we call it the receptive field of a neuron, the area that the neuron sort of sensitive to, like its window on the world, if that window contains two objects and you attend to one of them, the neuron responds a lot
00;11;31;16 – 00;11;55;21
John
like that’s the only thing in its receptive field. It’s like it filters out the other. And so at the level of like spiking activity, neurons talking to each other, those signals become about the thing you attend to. And I was so blown away by that talk that I decided I wanted to work for that guy. And so I was still a year out from my graduation and defending my thesis.
00;11;55;27 – 00;12;31;14
John
But I was enrolled in a class and the class had a project. And so I took his best and most famous paper, and I came up with a different interpretation of the of the result than he had. And it was a model of learning instead of a model of attention. And that was step one. I wrote a paper about that in class as my project, which I would present to him later to get the job, and I also found out his personal connection with one of the professors in my university who was an anatomist.
00;12;31;17 – 00;12;55;19
John
And I made a point of doing a sort of directed study with her so that she, well, could teach me about anatomy, primarily, but also she could get back to him through his wife, who was also a scientist, and say that John Reynolds doesn’t have two heads. And then when the time came, I got her to give me an audience with him, so to speak.
00;12;55;21 – 00;13;14;03
John
And then in the course of the discussion, I let him know that I thought his attentional effect was not an attentional effect. And it was a learning effect. And I explained why. At first he dismissed it out of hand, and then I said, no, no, no, really the way this was structured. And I explained how you could explain what he had done with a model that wasn’t an attention model.
00;13;14;05 – 00;13;25;13
John
And and then he wound up offering me a job, but it was very Machiavellian. I was going for that job and I took a year to line up. Then I shot and I took it and got into his lab as a postdoc.
00;13;25;15 – 00;13;26;27
伊莎贝拉
That’s the finance training.
00;13;27;00 – 00;13;29;21
John
Yeah, exactly. Right.
00;13;29;24 – 00;13;34;29
伊莎贝拉
So then, okay, so you were finally in a computational neuroscience lab. What was that like?
00;13;34;29 – 00;14;00;16
John
It was great. I mean, that was a time a very pleasant and intense but exciting time of life. You know, I came in to his lab having never done any experiment in my life. And so, again, I was, like, surrounded by people had been doing neuroscience in the experimental side for their PhDs, and they all came equipped with kind of understanding how to do experiments.
00;14;00;18 – 00;14;26;17
John
And I showed up with as a sort of mathematically oriented person. Right. And so, again, I was kind of again, way out of my depth. But it was really fun. And we were super hard at work. I mean, I would be sometimes returning home after midnight, and it was really something. My advisor was very hands off but always available, which was perfect for me.
00;14;26;17 – 00;14;48;00
John
I was able to find the space to kind of develop my own thoughts and my own ideas, but if I got stuck, I could always rely on him to be there. And and that was perfect for me. Now that I’m a PI and I evaluate people to become graduate students or postdocs, I’m always very sensitive to the fact that they’re going through that same process.
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John
So I try to encourage people to not ask, is this a great mentor? But, who’s the best mentor for me? Like, you know, there were people in my postdoctoral time who would have benefited from more mentoring and they would have done better in another lab. When I person wants to come into my lab, I think with them about what they’d like to do.
00;15;11;02 – 00;15;35;16
John
But I also encourage them to talk to people currently in the lab and also people who’ve gone on to set up their own labs and get their perspective on what it’s like here. Because again, it’s not, am I a great mentor or a terrible mentor? But am I a good mentor for you? And you have to make that decision for yourself.
00;15;35;19 – 00;15;38;11
伊莎贝拉
So how did you wind up at Salk?
00;15;38;13 – 00;16;02;08
John
Well, I was very lucky. So I, my mentor, Bob Desmond’s mom, became ill and he had to pull out of a meeting that was taking place in Madrid, and he sent me in his place, and I had this wonderful opportunity. The caliber of the scientists. There they were all world leading scientists except for me. And so I had this opportunity to prepare a talk that would introduce me to them.
00;16;02;11 – 00;16;26;18
John
And I took that opportunity very seriously. And I prepared a fantastic talk, if I don’t say so myself, I had this very privileged opportunity to speak about the work that I had done as a postdoc, and I wound up walking through the streets with Tom Albright, who was here as a faculty member, and I knew all about his work.
00;16;26;20 – 00;16;47;04
John
And and we talked about our work, and we had a great intellectual discussion over the course of several hours of wandering through the streets and wound up getting dinner and he was on a recruitment committee for UCSD. So I said, well, can I apply for a job at Salk? And he said, you have to not get the job at UCSD first, so you have to apply there first.
00;16;47;04 – 00;17;09;12
John
And so I applied to UCSD, which would have been a great place to be. But it wound up they didn’t have any interest in hiring me. And so Tom said, well, there is no position at Salk, but if you come and give a talk, you might be able to convince people to create a position for you. And so again, I had this like once in a lifetime opportunity to speak here at the Salk.
00;17;09;14 – 00;17;25;07
John
And they asked, would you like to meet with anyone in particular? And I went through the list of people I wanted to meet with, Terry Sejnowski. I wanted to meet with 埃德·卡拉威. I wanted to meet with EJ Chichilnisky and a few others. And I said, and of course, if he were available, I would love to have the chance to talk to Francis Crick.
00;17;25;07 – 00;17;49;14
John
But I realized he’s, you know, probably very busy. Well, it turned out he was willing to talk to me. And and he was very you know, he had of course, his major contribution was understanding the structure of, of DNA. But he was also very committed to understanding the neural mechanisms of consciousness. And that was what I had been studying as a postdoc.
00;17;49;14 – 00;18;17;17
John
And so he was very happy to meet with me, remarkably. And you get imposter syndrome, of course. And so he invited me over to his house, he and Christof Koch and I thought, oh, well, this is when they discover I am a total fraud. And, you know, I had heard that Francis would ask pointed questions and he wanted to know, like, how many neurons are in this brain area because not maliciously, it was just trained as a physicist, and he wanted to know what kind of order of magnitude what we’re talking about here.
00;18;17;20 – 00;18;30;17
John
But I was very nervous. And I went up to his house and his wife, Odile, prepared sandwiches, and we had a delightful time. And he was a gracious host. And Francis and Christof and I just enjoyed talking to each other.
00;18;30;19 – 00;18;42;17
伊莎贝拉
I cannot even imagine I have second hand like star shock. And after that you were able to give your talk on campus?
00;18;42;20 – 00;19;06;08
John
Funny story. So I gave my talk and Francis was sitting in the front row, and I’m sitting there feeling very nervous, and I give this talk and I start talking about receptive fields and how as you go from the retina down into the brain, the windows, the receptive fields that cells see through, so to speak, grow bigger and bigger.
00;19;06;08 – 00;19;25;10
John
And so with the retina, they’re very tiny. But by the time you get deep into the visual system in the inferior temporal lobe, they covered huge, vast spaces of your visual field. And I, this was more like motivation at the beginning of the talk. But I said, you know, the cells have a finite bandwidth. They can only convey so much information per unit time.
00;19;25;13 – 00;19;42;22
John
And when they fill the whole room, there’s a lot more information there than they can process. And so we need mechanisms of attention to enable the cells to be about the thing you care about. And so you need a flexible system that can be deployed to grab just the information you need right now. It was just a story to get people into the right frame of mind.
00;19;42;22 – 00;20;08;14
John
And so at the end of the talk, this person in the back row who I remembered clearly as Leslie Orgel, raised his hand and he said that part you said at the beginning was very nice. But in fact, isn’t it also true that as you go through the visual system, the specificity of the neurons becomes increasingly more refined?
00;20;08;14 – 00;20;34;22
John
So you might be in primary visual cortex, you might have cells that care about edges, but by the time you get down into the temporal lobe, they’re about complex things like a person’s face. So what’s the big deal? Why do you need attention? And I thought, what a wonderful question. I was just inhaling to answer it when Francis stood up and turned on this poor guy and he said, well, I didn’t understand that question, and I doubt John did either.
00;20;34;24 – 00;20;56;04
John
Here’s how it works. And he laid out the Hubel and Wiesel way of thinking about the hierarchy in the visual system, and he just laid waste to this poor guy in the back row. And so I’m standing there on stage in front of the people who are about to decide whether to offer me a job. And the most famous living biologist just tore a hole through my Q and A.
00;20;56;04 – 00;21;22;07
John
And so years later, I came up for tenure and I had to give a talk again. It was my promotion talk, another high pressure situation. I thought, well, I’m going to go back and look at what I said when I started here. They videotaped it. Francis is sitting in front of the room, the picture of Jonas Salk, and I go to the very end and sure enough, there’s this question that comes in from this very astute observer in the back row.
00;21;22;10 – 00;21;53;09
John
Well, I had totally misremembered who it was, and in fact, it was not Leslie Orgel, it was Harvey Karten who is a neuroscientist across the street at UCSD. And in my memory, there was a totally different person. The videotape didn’t lie. I had totally concocted this memory in my mind. And so to me, this is really an illustrative point because we don’t perceive the world by sensing it and we don’t remember the world by recording it.
00;21;53;11 – 00;22;07;14
John
We construct internal models of the world we live in, both in perception and in memory. And they can be as compelling as can be. But they are constructs that we make up inside our heads.
00;22;07;17 – 00;22;25;16
伊莎贝拉
That story is completely insane, and I love it. And it’s also very interesting. And it kind of works as a perfect segue or explainer for your research. How do you even begin to study these things like consciousness and perception or attention that are so abstract?
00;22;25;21 – 00;22;54;16
John
We’re at the boundary of what’s known. It can be a little disorienting. And one thing you do as a scientist is you try and think in a reductive way, like, what am I actually going to measure at the tip of my electrode? Or how do I formulate a testable hypothesis? What is a model that would explain what we know and makes a particular prediction that I can test empirically, but at the same time, perception, memory formation, memory readout.
00;22;54;16 – 00;23;30;12
John
These are not things that can be ultimately reduced to molecules. They are playing out at a level of organization that spans everything from molecules to the whole organism. And so you have to think in terms that are more holistic to really understand how to approach the question. That’s really the challenge when you’re dealing with something as abstract as memory or perception, how do you how do you do something productive without while maintaining, while honoring the complexity of the problem that you’re studying?
00;23;30;15 – 00;23;32;11
John
And that’s the trick.
00;23;32;13 – 00;23;42;05
伊莎贝拉
I know you use this one technique called optogenetics to study the brain and ask these complex questions. Can you kind of explain what optogenetics is?
00;23;42;10 – 00;24;16;29
John
Sure. Yeah. So that’s an example where you can use tools to perturb this ultimately complex system of the brain. Optogenetics is a term that refers to the use of optics, light, in science, in neuroscience, and driven by genetic tools. So optogenetics and the idea is you take from biology sensors for light, such as the light sensor that an algae uses to orient itself towards the sun.
00;24;16;29 – 00;24;55;21
John
So phototaxis. And you take the DNA that tells the algae how to make that sensor, and you put it into a neuron. So typically these sensors, when they’re opened by light, either allow ions to flow in one direction or another and that either activates or inactivates the cell. And so if you can use methods to deliver those little light sensors to a particular type of neuron, you’re in a position to regulate the activity of that neuron very precisely, like down to the levels of milliseconds.
00;24;55;24 – 00;25;20;28
John
And you can play an orchestra, so to speak, out of light on the brain and effect, it’s, the timing of its signaling in ways that let you test different ideas. So, for example, one of the things that we discovered years ago was that when we deploy attention to a stimulus, the biggest effect, perhaps, is that you affect the timing of neural activity in a certain way.
00;25;20;28 – 00;25;45;20
John
So neurons tend to be correlated with one another in their spiking. So if you’re firing your action potentials, your next door neighbor is also firing their action potentials. And it turns out that that places a boundary on how much information you can process about the stimulus that you’re looking at. So you can imagine, like, let’s say, you know, we are all three,
00;25;45;20 – 00;26;01;10
John
if we’re all saying the exact same thing and you combine the signals from all three of us, you’ve learned nothing like, you know, we’re redundant with each other. But if we’re speaking independently, we each bring our own message. Then you can learn more by listening to all three of us. And you could learn from listening to one of us.
00;26;01;12 – 00;26;33;05
John
And so the same kind of concept applies in neurons. If they’re speaking the same exact language, there’s nothing to be gained from pooling the information across them. And so it turns out that when you deploy attention to a stimulus, this causes the neurons to become de-correlated with one another. So they’re providing more independent information. And so we hypothesize that that the reason that attention down regulates this correlation between the neurons is to increase the amount of information there is, that the neurons are conveying.
00;26;33;07 – 00;26;56;16
John
It’s an interesting idea. It’s possible. And there was a lot of theoretical work that had led to the idea that this was true, but no one had ever tested it directly. And so we used optogenetics to test that. So we used optogenetics to reintroduce that correlation that the brain had through its attentional mechanisms, removed. And we tested whether that would impair perception.
00;26;56;16 – 00;27;21;19
John
And indeed it does. However, attention doesn’t down regulate high frequency correlations. And so we could instead introduce high frequency correlations. And if we were right, that should not impair perception because the correlations that are being filtered out are not in that frequency range. And indeed that did not do that. And so it was a way of testing a specific hypothesis that came from a mathematical model of neural signals.
00;27;21;21 – 00;27;31;06
John
So optogenetics is one of the tools that’s come into play in the last 15 years that we, you know, we use for these kinds of things.
00;27;31;09 – 00;27;34;20
伊莎贝拉
Is that the most common tool that you’re using in the lab, or?
00;27;34;21 – 00;28;00;25
John
Every single experiment we do always involves a new set of tools that we’re developing. We’ve more recently been been developing ways of visualizing patterns of activity across the brain. So we have recently made the discovery that just as you’re sitting there in your brain in multiple brain areas, you have waves of of activity that are traversing each of your brain areas.
00;28;00;25 – 00;28;21;08
John
several times a second. And it turns out that the that these waves have a big impact on perception. So if if you were to look at a computer screen and see a very faint stimulus appear on the screen, the question of whether you see it or not depends upon the phase of the wave at the moment that the stimulus appears, and it’s a very big effect.
00;28;21;10 – 00;28;43;27
John
But we don’t think that evolution went to all the trouble of creating these metabolically expensive waves to allow you to detect a faint stimulus on a computer screen, and they’ve been thinking about what they may be doing. Terry Sejnowski has a good analogy. When evolution finds a mechanism, it tends to deploy that mechanism in a variety of different ways.
00;28;43;27 – 00;29;13;20
John
And the example that he gives is blood, it evolved initially to provide something like the environment of the sea by bringing that into the cell. And then that led to the development of the circulatory system in multicellular organisms. But the blood system delivers immunological responses, it clears away waste, it provides oxygen, it provides nutrition. It does a lot of different things all at once.
00;29;13;22 – 00;29;49;04
John
And I think the same is true in in the nervous system. And so what could this wave system that we’ve discovered be doing? And one of the things that we’ve realized is that these waves are complex in space and time. And so they endow the brain with the capacity of representing complex things in the world. The idea is we can use the complexity of the spatial temporal dynamics of these waves as a way of endowing the brain with the ability of storing in its synapses spatial temporally complex things, and then replaying them.
00;29;49;04 – 00;30;13;20
John
So like the you know, recently I was walking across the street with my two kids, and my daughter is five, my son is six. My wife was in front of us, out of reach. My son, Bridger, was 2 or 3 steps ahead of me, so also out of reach. And I was holding Ellie’s hand. And this car came in from right at high speed, alarming moment.
00;30;13;20 – 00;30;40;07
John
I didn’t know whether it was slowing down for the speed bump or slowing down because the driver had seen us. Fortunately, no one was killed. But I have this memory of that whole event, and I can see it unfolding in time. As I’m telling you this, there’s a trolley going on the bridge above us. That whole event is crystallized in the synapses of my brain and in parts of the brain that have the ability to encode sensory information.
00;30;40;10 – 00;31;12;03
John
And so how is it that you, you can encode a complex event like that and then later replay it from inside the brain’s own circuits? Right? So this mathematical model tells us how that can be done. And it’s a mathematical model that shows how to place into the synaptic connections between neurons the information about how to reconstruct that whole thing, so that you can present the mathematical model with the first few frames of a movie, and it will play out the whole movie from its own internal dynamics.
00;31;12;06 – 00;31;18;22
John
So it’s a really exciting and new way of thinking about how memories could be encoded and how they could be replayed.
00;31;18;24 – 00;31;44;05
伊莎贝拉
Wow. Yeah, it’s really incredible how memories work, how our brains recall these really clear scenes from our past. Kind of, I don’t know, it’s really crazy when you start thinking about thinking about thinking about thinking. Are organoids ever useful in your work? And those, for our listeners, are essentially 3D miniature model brains that researchers can grow in the lab to study brain development and function.
00;31;44;08 – 00;32;09;06
John
Yeah, well, not in my lab. For our purposes, we’re looking at patterns of brain activity that we observe in the two dimensional surface of the cortex. And so the most natural way of thinking about that, and the way that we’ve developed models to think about this and for which we have evidence, is that these waves are being they’re playing out on the surface of the brain through these horizontal fibers that connect neurons to one another.
00;32;09;09 – 00;32;19;18
John
And so that is a two dimensional problem.
00;32;19;21 – 00;32;32;29
伊莎贝拉
So something really cool about you and your science is that you’ve done lots of collaborations with artists. Can you speak to that a bit? And what it’s like being in that space where science and art are meeting?
00;32;33;02 – 00;33;02;22
John
I think there’s a lot of value to experiencing something yourself, and if you work with artists, they are very playful and they, and you have a lot of freedom to think about how to approach problems in ways that are not as rigorous as you do in the lab. And I visited a friend of mine, Patrick Cavanagh, in Paris, and he had set up a lab there, and he took me into his lab, and we sat in the dark for ten minutes.
00;33;02;25 – 00;33;28;22
John
And during that time period, your visual system gets sensitive to light and it sets up the conditions to create an illusion that allows you to see your brain at work. And we took that experience and we brought it into a context of some artists here at San Diego who are really interested in using art as ways of connecting to science, and scientists.
00;33;28;24 – 00;33;57;00
John
And what we did was we created a an illusion chamber where people could come and sit in the dark for ten minutes or so. They would become sensitized to light. And then we had a flash that lasted 60 microseconds. And so imagine you’re sitting in the dark. You’ve been sitting there, your visual system, including your pupil, but also the neurons on your retina and the neurons they project to downstream throughout your whole visual system.
00;33;57;01 – 00;34;26;29
John
They’re all receiving no input. It’s total darkness. And so they become hyper sensitized. When the flash occurs, it activates your photoreceptors, your cones encode color, your rods encode monochromatic–they’re moonlight vision. So they let you see and in moonlight, your experiences, you know, the colors go away and you just see kind of silvery color. So your immediate experience is that you’re looking at a friend in the room with you, and your friend is in color for about a half a second.
00;34;27;01 – 00;34;52;03
John
The cones turn off and the rods remain active. And now you have a moonlit friend sitting across from you. And so you get to see that experience, which is interesting. But we then use that as a kind of way of playing with perception. So for example, if you put your hand in front of your face sitting in the dark and the flash occurs after half a second, you’re looking at this moonlit marble hand of yours and it’s close to your face.
00;34;52;06 – 00;35;17;12
John
So imagine this huge hand that’s sitting there in your visual field. If you then slowly move your hand away from your face, your proprioceptive system which says where things are in your body now says, oh, it’s two feet away from you, three feet away from your face, but your retinal image is still enormous. And what you experience as you watch this is your hand expanding to the size of a pillow, because it’s the only way of reconciling these two different sources of information.
00;35;17;12 – 00;35;39;29
John
And now as unlikely as it seems that your hand would do that, it’s the only mathematically correct solution, and you get to see your brain make that happen. And people who witnessed this scream, you know, we have done this now with thousands and thousands of people and, you know, especially appealing when like younger people, college kids come through and they just walk out thinking, I had no idea
00;35;39;29 – 00;35;56;01
John
my brain did that. But that’s really that’s really what it is. Your brain is making an internal model of the external world, and that model has to reconcile all the different sources of information and bring them together and into a tidy explanation. And that explanation is the one you experience in your life.
00;35;56;08 – 00;35;59;07
伊莎贝拉
That is crazy. I think that I would scream.
00;35;59;09 – 00;36;02;10
John
It’s very scream-able, it’s totally scream-able.
00;36;02;13 – 00;36;14;15
伊莎贝拉
John, thank you so much for talking with me today. This was so interesting and I will be ruminating on faces I’ve misremembered and what my hand would look like if it was the size of a pillow.
00;36;14;18 – 00;36;30;19
John
Thank you for having me. It’s good to see you in person and I hope people have enjoyed hearing whatever this is.
00;36;30;21 – 00;37;01;02
伊莎贝拉
Where are we in the universe? It’s clear when talking to John Reynolds that he’s still a deeply philosophical person and scientist. His search for meaning has led him to incredible discoveries about our brain and how he makes sense of the world around us, like how traveling waves of neural activity influence how sensitive we are to stimuli. It’s also made him a guiding light in his field, as he created the first unified quantitative framework for understanding the neural mechanisms that our brains use to decide what we pay attention to.
00;37;01;04 – 00;37;23;22
伊莎贝拉
John’s stories and insights are a reminder of the powerful feat of nature that the human brain is. There’s still a lot of work left to be done to understand this complicated and, as John would probably say, mathematically beautiful organ. It’s exciting to hear how John and other legends have contributed to modern neuroscience. But it’s also exciting to think about what we’ve got left to find out.
00;37;23;24 – 00;38;01;11
伊莎贝拉
As we learn increasingly more about the brain and our models become more complex, our questions are going to quickly become more complex, too. Holding philosophy and art and neuroscience together will soon be essential as we ask bigger, bolder questions about consciousness, belonging, and humankind. Thankfully, John has already set his sights on that future.
00;38;01;13 – 00;38;31;27
维多利亚之声
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