284 | 多丽丝·曹谈大脑如何将视觉转化为世界

大家好，欢迎收听《思维景观》播客。我是主持人肖恩·卡罗尔。想必大多数听众都知道我热爱各类科学，但最让我着迷的是那些略带存在主义色彩的科学问题——那些触及意义与现实本质的深层命题。

Hello, everyone, and welcome to the Mindscape Podcast. I'm your host, Sean Carroll. Most of you probably know that I love science of all sorts. But my favorite kind of science questions are the ones that become slightly existential, right? That sort of bump up into issues of meaning and reality at a super deep level.

其中有些问题直接指向物理学或宇宙学，比如：宇宙从何而来？为何存在宇宙？自然界的

And some such questions are straightforwardly physics or cosmology, right? You know, where did the universe come from? Why is there a universe at all? What are

的

the

基本法则是什么？宇宙能否以其他形态存在？是否存在平行宇宙？这些问题都促使我们反思所处世界的本质及其可能性。但还有另一类同样具有存在主义特质的科学问题，那就是关于心智、思维、意识的研究——不仅是哲学层面探讨'作为某种存在物的体验'，更包括其运作机制本身。

fundamental laws of nature? Could the universe have been different? Are there other universes? These all, you know, make you think about the world in which we live and how they could have been different. But there's a whole another realm of science questions that also have that somewhat existential character, which is of course, the mind, how we think, consciousness, but not just consciousness in the sort of philosophy question about it, what is it like to be something, but even just how it all works, right?

我将自己视为拥有观点、情感、欲望和价值观的个体。但若要保持逻辑自洽，就必须承认我也可以被描述为由细胞、神经元等以精妙方式相互作用的集合体，甚至归根结底是粒子或量子场的组合。而我的自我意识、认知能力、与世界互动建模的本领，都必然从这些基础元素中涌现。这里显然涉及大量深刻的哲学思考，我本人十分推崇这种'自然哲学'——即哲学与科学的交叉领域。

I think of myself as a person with opinions and emotions and desires and values. I can also, if consistent and I believe my own rhetoric, I have to believe that I can also be described as a collection of cells, neurons and other kinds of cells that are interacting with each other in these interesting ways, or even just of course, as a collection of particles or quantum fields or whatever. And somehow my selfhood, my awareness, my ability to think about the world and model it and interact with it, it's got to emerge out of all that basic stuff. And there's a lot of juicy philosophy here, obviously, and I'm a big believer in that. But natural philosophy, as I think of it, is the intersection between science between philosophy and science, right?

这种哲学与我们从宇宙获取的经验证据紧密相连。今天我们将略微涉足哲学讨论，但主要会以严谨自然科学家的视角来探讨大脑工作机制。特邀嘉宾周多丽丝是著名神经科学家，屡获殊荣的视觉皮层专家，其最具代表性的研究是关于人脸识别机制——不仅人类，所有动物都不是以像素或视网膜细胞为单位感知世界，而是构建整体图像模型，并有选择地关注环境中的特定要素。

It's the kind of philosophy that engages very strongly with the empirical information we get about the universe. So today, we're going to we'll we'll dabble a little on the philosophy side, but mostly we're going to be hard nosed natural scientists today, thinking about the brain and how it works. Our guest, Doris Tsou, is a major neuroscientist, multiple award winner, who specializes in vision, the visual cortex. In fact, her most recognizable work is in how we recognize faces, you know, the human visual field or the human, not just human, when animals see things, they don't apprehend the world pixel by pixel, or, you know, cells in our retina one at a time, right? We put together pictures, we construct models of what is around us, and we pay more attention to some things than others.

我们尤其擅长关注面部信息，无论是人类还是动物面孔。甚至用寥寥数笔勾勒的简易符号，也能被普遍识别为面部。从生物进化史来看，理解与识别面孔显然具有重要生存价值，因此大脑存在专门处理该功能的区域也就不足为奇了。

We pay a lot of attention to faces, faces of other human beings, of course, but also faces of other animals. And indeed, it doesn't take that many strokes of a pen to draw a symbol, even if you're not a great artist, that everyone will recognize as a face. Understanding faces, recognizing faces is of obvious usefulness in biological evolutionary history, right? We need to be good at interpreting that. It is therefore in some sense no surprise that there are parts of our brains that are devoted to this task.

你知道，他们的工作是识别人脸并帮助解读它们。多丽丝在这方面做了开创性的工作，主要在猴子身上进行研究，但从生物学角度看，它们与我们相差并不远，她精确地定位了大脑在观察人脸时各区域的功能。结果证明这是一场精彩的对话，话题走向了非常有趣的领域，这些是我事先未能预料到的。思考我们在识别人脸时的神经活动，很自然地会引出其他关于大脑如何构建世界模型、抽象思维、意识等问题。所以对我来说，我很高兴多丽丝·曹能参与其中。

You know, their job is to recognize faces and help interpret them. And Doris has done, you know, pioneering work in that and identifying usually in monkeys, but they're not that far away from us biologically, exactly what parts of the brain are doing what when we're looking at faces. And it turns out this is one of those nice conversations that actually goes to very fun places that I was not smart enough to anticipate ahead of time. Thinking about what's going on when we are recognizing faces or whatever segues quite naturally into other questions about how the brain works in building models of the world around it, abstract thought, consciousness, all those kinds of things. So this is a to me, I'm glad that, Doris Tsao was in the spirit of it.

这是一场非常符合《心灵景观》风格的对话，我们深入探讨科学，并在此过程中讨论那些宏大的理念。那么让我们开始吧。劳拉·萨尔，欢迎来到《心灵景观》播客。

It's a very Mindscape y kind of conversation where we both dig into the science, and we get to talk about the big ideas along the way. So let's go. Laura Sal, welcome to the Mindscape Podcast.

谢谢。很高兴来到这里。

Thank you. Good to be here.

我来告诉你这期播客的具体由来。我们曾在加州理工学院共事，我知道你在做很棒的研究。几年前有位听众发邮件提醒我，说我总是从哲学角度讨论意识等问题，应该多采访那些脚踏实地通过实验研究大脑的科学家，而你的名字自然成为了首选。

So, I'll tell you why specifically this podcast happened. I mean, we were both at Caltech at the same time. I knew who you were doing great research and something. But someone a couple of years ago, one of my podcast listeners emailed me to chide me that I was always talking about like consciousness and stuff from this philosophical point of view, but we should talk to people who actually study the brain in a more down to earth experimental science way, and your name was an obvious choice.

哦，真有趣。我本来还想请教你对意识理论的看法呢。不过确实，我们实验室非常关注意识的神经机制，这正是吸引我进入神经科学领域的重要原因。我选择研究猴子是因为它们很可能具有意识，至少它们的视觉意识与人类非常相似，这样我们就能真正触及机制层面的问题。

Oh, that's funny. I mean, I was hoping to talk to you about some your thoughts about theories of consciousness. But indeed, yeah, our lab is very interested in understanding the neural mechanisms underlying consciousness. This is one of the big questions that brought me into neuroscience and specifically to start studying monkeys because I think monkeys are conscious and very likely, at least their visual consciousness is very similar to ours, and so we can really get at the mechanism.

没错。视觉研究领域正是你取得重大突破的方向，这也是今天我想重点探讨的内容。如果我理解有误请纠正——我们将从最基础的概念开始，毕竟我只是个可怜的理论物理学家。但据我观察，很多人通过相机、录像机等设备，把视觉简单地理解为像探测器屏幕上的像素那样运作。

Yeah. And the visual part there is, I guess, where you've really made your money and that's what I want to try to focus on here today. So correct me if I'm wrong, we're going to start very very simple since I'm a poor theoretical physicist. But I get the impression that a lot of people know about cameras and video recorders and things like that and the idea of like pixels in a detector screen. And so they kind of think vision is like that.

人们以为我们只是直接接收像素然后进行解读。但我曾付出过代价才明白，视觉系统远比这复杂得多——我们并非直接检测像素再进行解析。

You know, we just see the pixels and we interpret them like that. But I remember I learned the hard way that, the visual system is is much more elaborate than that. We don't just detect pixels directly and then interpret them.

是的。你知道，眼睛基本上就像一台相机。对吧？光线穿过晶状体落在感光细胞上。然后所有这些来自感光细胞的信号通过视神经传递到视觉皮层。

Yeah. You know, so your eye is basically like a camera. Right? The light falls goes through the lens and falls on your photoreceptors. And then all those signals from the photoreceptors get sent via the optic nerve into your visual cortex.

嗯。视觉皮层是个不可思议的精密机器。在猴子大脑中可能占三分之一。它是个巨大的精密装置。在这个视觉皮层里，有数十个专门处理视觉世界不同方面的区域。

Mhmm. And then the visual cortex is this incredible piece of machinery. In monkeys, it probably takes up about a third of the brain. You know, it's a giant piece of machinery. And within this visual cortex, there's dozens of different areas that are specialized for processing different aspects of the visual world.

就像整个工厂把这些像素转换成你对空间物体的感知。第一个重大发现，我们理解视觉皮层的顿悟时刻来自休伯尔和威泽尔对吧？他们曾是著名神经生理学家史蒂文·库夫勒的博士后，库夫勒一直在记录视网膜神经节细胞活动。这些是视网膜中的细胞。它们具有中心-周边抑制特性，这本身就非常有趣。

So it's like a whole factory that's transforming these pixels into your perception of objects in space. And the first really big insight, the eureka moment in our understanding of visual cortex came from Hubel and Wiesel, right? So they were postdocs with famous neurophysiologist Steven Kufler, and Kufler had been recording from retinal ganglion cells, right? These are cells in the retina. And they had this property of center surround, which was already very interesting.

中心-周边抑制意味着它喜欢光点。但如果呈现弥散光模式，细胞就不会反应，因为它被所谓的周边区域抑制了。视网膜在早期阶段就进行这种冗余减少。然后休伯尔和威泽尔想，接下来会发生什么？于是他们决定：就跟着解剖结构走，看看这些视网膜神经节细胞在大脑中的去向。

So center surround means that it likes spots of light. But if you show a very diffuse pattern of light, then the cell doesn't respond because it's inhibited by the so called surround region. So they're doing this redundancy reduction already in the early stages of the retina. And then Hubel and Wiesel, they thought, okay, what happens next? And so they made this decision, let's just go and follow the anatomy and see where those retinal ganglion cells go inside the brain.

它们首先到达的结构叫外侧膝状体。那里的细胞反应与视网膜神经节细胞非常相似，都表现出中心-周边抑制。然后他们更进一步研究初级视觉皮层，在那里发现了全新的世界。

And so the first place that they go is this structure called the lateral geniculate nucleus. And there the cells responded pretty much like the retinal ganglion cells. They just showed center surround. And then they went one stage further into primary visual cortex. And there they uncovered this whole new world, right?

细胞突然完全不对光点产生反应，而是需要边缘刺激。不同细胞对视野中不同位置的边缘产生反应。这是视觉信息表征方式的革命性转变。就像一道闪电，突然间让人惊叹不已。

The cells suddenly didn't respond to spots of light at all, but they required edges, right? And different cells respond to edges at different locations in the visual field. And so it was this whole new, this dramatic transformation in how the visual information is represented. And that was that was just a lightning bolt. It's like all of a sudden, wow.

这套机制实际上在转换像素，处理完边缘后还有更多变化。这开创了整个研究领域，我很幸运能参与其中。

There's this machinery that's actually transforming the pixels and, you know, what happens after edges. And so that launched this whole field that I'm, you know, very lucky to be part of.

这确实会让人不禁联想到深度学习网络，对吧？就像网络中有不同层级负责不同任务那样。

And that does, you know, it can't help but remind one a little bit of, a deep learning network, right, where you have different layers that have different jobs.

是的，虽然对此存在争议，但我认为神经科学家们坚信深度神经网络是受到Hubel和Wiesel关于视觉皮层发现的启发。

Yeah, I think there's like argument about this, but I think the neuroscientists firmly believe that deep neural networks were inspired by Hubel and Wiesel's discoveries about visual cortex.

很好，我很乐意把功劳归于他们。你刚才提到一个值得探讨的观点——猴子的视觉皮层占其大脑的三分之一，我猜人类应该不到这个比例。

Good, I'm happy to give them the credit. And you said one provocative thing there I want to follow-up on. The visual cortex is the one third of a monkey's brain. I'm guessing that it's less than a third of a human brain.

确实，我不想给出具体数字。但如果你问人类大脑对视觉刺激的反应区域占比，基本上整个大脑都会激活。我同事Jack Allen让人躺在核磁共振仪里看电影时，整个大脑都在发光。明白吗？

Yeah, you know, I don't I don't want to put any number out there. But if you ask, you know, what fraction of the human brain will respond to a visual stimulus, it's basically the whole brain. Right? Jack my colleague, Jack Allen, you know, puts people inside FRM scanners and shows them movies, and the whole brain lights up. So you know?

当然其中很多是多模态区域，也会对文字、声音等作出反应。但它确实会对视觉刺激产生响应，所以我倾向于认为这是广义视觉皮层的一部分。

And you can, you know, certainly a lot of that is, like, multimodal, so it'll also respond to text and to, you know, audio and so on. But it's definitely responding to visual stimuli, so I would argue, part of the broad visual cortex.

还有个我认为正确但需要您指正的观点：初级皮层之外的某些神经元会对线条或运动而非单纯像素作出反应。这是否能解释视错觉现象？当特定神经元激活时，我们就会自动补全画面？

And one other thing which again I think is true but you're the expert and correct me if I'm wrong this fact that certain neurons beyond the first level are responding to lines or motion or whatever rather than just pixels. Does that help explain optical illusions? You know, we sort of fill in things if the right neurons light up?

没错，这些特化神经元的存在确实能解释。虽然不知道是否过于专业，但有个叫'反向phi'的酷炫错觉——通过调整对比度就能让自行车看起来持续移动，这完美体现了大脑运动处理区方向选择性细胞的特性。

Yeah, the fact that we have these specialized neurons, I mean, can. Yeah, so there's I don't know if this is getting too much into the weeds, but there's this very cool illusion called reverse phi, where you can make a bicycle look like it's constantly moving just by setting the contrast in the And correct that is beautifully explained by the properties of the direction selective cells in the motion processing part of the brain. So yes.

粗略地说，我们的大脑被设计用来识别那些我们通常所见的事物，因此如果你展示一些非典型事物，就能欺骗它。

So so very roughly speaking, you know, our brain has been designed to see the kinds of things we typically see, and so you can trick it if you show it things that are not the kinds of things we typically see.

没错。关于视错觉这个话题，我的实验室在人脸处理方面做了大量研究。嗯。我最喜欢的视错觉之一是撒切尔错觉，强烈建议大家去了解一下。这个错觉是将人脸的所有特征倒置处理。

That's right. And I I should mention on the topic of optical illusions, you know, my lab has done a lot of work on face processing. Mhmm. And one of my favorite optical illusions, and I strongly encourage everyone to go look at this, is called the Thatcher illusion. And that's this image that you create of a face where you basically, you turn all the features upside down.

明白吗？保持脸部轮廓朝上，但把眼睛、鼻子和嘴巴都倒过来。可以想象那看起来非常怪异。对吧？嗯。

Okay? So you keep the frame of the face upright, but you, like, turn the eyes and the nose and the mouth upside down. And so you can imagine that looks very freaky. Right? Mhmm.

然后当你把这个怪异的脸倒置过来时，突然就不觉得别扭了——它看起来就像一张正常的脸。我钟爱这个错觉的原因是，当你倒置这张脸时，实际上是在人为制造一种'脑损伤'——你的面部识别区域会陷入沉默，因为它们天生无法处理倒置的人脸。这样你就能体验大脑受损的感觉。最神奇的是你根本意识不到信息缺失。

And now you just turn this freaky face upside down, and suddenly it doesn't bother you anymore. It looks like a normal face. And and the reason why I love this illusion is that what's happening when you turn it that face upside down is that you're essentially inducing a lesion in your causing your face areas to become silent because they're just not wired to respond to upside down faces. And so you can experience what it's like to have brain damage. And, what's remarkable is that you just you you feel like you see everything.

你不会觉得少了什么。对吧？所以我常说这其实很令人安心——至少当我精神失常时，我自己也不会察觉。

You don't feel like there's something missing. Right? And so it's kind of, I like to think that it's reassuring. Know, when I lose my mind, at least I won't know about it.

但这确实引出一个事实：物理学家研究宇宙起源是相对客观的领域，而你研究大脑和视觉时——毕竟你自己就拥有大脑和视觉系统——总会有顿悟时刻：'啊，原来我的大脑是这样运作的'。

Well, but it does bring up the fact that, for a physicist studying, you know, the origin of the universe, it's a fairly impersonal, line of research, but you're studying the brain and vision, and you have a brain and you have vision, so there must be moments when you realize like, oh yeah, that's what my brain is doing.

每次都是！作为视觉科学家最美妙的事就是：睁开眼就能看到你试图解释的奇迹。从某种意义上说，我们每个人都是视觉专家。

Oh, every time. I mean, that's one of the most beautiful things about being a vision scientist. You open your eyes and you see the miracle that you're trying to explain. We're all experts on vision in some sense.

非常好。对，好的。实际上，让我们更深入探讨一下，因为你已经提到过，我们所说的视觉皮层是分区的，有V1、V2和V3区，你知道这些不同区域分别承担什么功能吗？

Very good. Yeah. Okay, good. In fact, let's dig a little bit more deeply because I think you've already suggested this, but what we call the visual cortex is subdivided, There's V1 and V2 and V3 and, you know, what roles do these different folks play?

确实。你居然知道V3区让我很惊讶，因为关于它的研究论文大概只有五篇左右。但没错，这些不同区域确实存在。事实上我们知之甚少，部分原因是神经科学家数量有限，而且他们都集中在某些领域研究。

Yeah. I'm impressed that you've heard about V3 because there's been, like, just, you know, like, five papers written about it. But, yeah, there's all these different areas. The fact is we know very little. So and one of the reasons is that, I know there aren't that many neuroscientificial neuroscientists and we they all, like, sort of congregate.

所以有很多实验室都在研究V1区，导致所有人都在研究V1区。这些不同区域到底在做什么？我们有个粗略的认知：V1区负责边缘的早期处理，然后信息会传到中间阶段进行分割处理——比如区分不同物体的边界，分析表面属性和纹理特征，然后继续向前传递。这里要提到一个重要原则：视觉处理实际有两条通路——背侧流和腹侧流，它们功能不同。

So there's, you know, lots of labs studying v one, and so everyone is studying v one. So, you know, what are these different areas doing? I mean, we have some cartoon picture that v one is doing this early processing of edges, and then it goes to some intermediate stage that maybe is like doing segmentation, so picking out the borders of different objects, figuring out the surface properties, the textures of different objects, and then the processing goes forward. And I should say that there's a very important principle, that there's actually two streams of visual processing. There's this dorsal stream and this ventral stream, and they do different things.

腹侧流专门负责物体识别，比如识别那是只豹子，那是我妈妈。而背侧流则是通往运动皮层的路径，负责感知物体位置和三维形状，让我们能以正确方式抓取物体。很有意思的是，大脑将这两种功能完全分离了。

So the ventral stream is specialized for object recognition. Just recognizing that is a leopard, that's my mom. And then the dorsal stream is really the pathway to our motor cortex, Right? So it's involved in knowing where things are and what their three d shape is so that we can grasp them in the correct way. And, it's it's very interesting that the brain has actually dissociated these two functions.

对吧？

Right?

确实非常有意思，不止是有趣，简直令人惊叹。它怎么知道要把这两种功能分开？你说背侧流和腹侧流时，这是指大脑中实际存在的信息传导路径吗？

I mean, it is very interesting. It's more than interesting. It's amazing to me because, how did it know to dissociate those two different functions? So you're saying when you say dorsal stream, ventral stream, does this does this refer to, like, literal pathways in the brain down which information is flowing?

没错，这是两条不同的神经通路。我们之所以知道这种功能分工，是因为有些患者出现特定脑损伤后，会选择性丧失物体识别能力但保留抓取能力，或者相反。

Yeah. Yeah. They're they're two different pathways. And and the way that we know that there's this, division of labor is that, you know, people have lesions and they can become selectively unable to recognize things, but they can still, like, grasp them just fine. Or they can't grasp them, but they can recognize them

确实，从生理角度来说这非常有趣，因为我原本没打算过多讨论意识问题，但这确实强化了一个观点：大脑的不同部位执行着高度专业化的任务，而我们称之为意识的东西，某种程度上是由所有这些协同工作的部分编织而成的。

Yeah, physically that's very interesting because I wasn't actually thinking of talking about consciousness that much, but it certainly does reinforce the idea that there are individual pieces of the brain doing very specialized tasks and whatever we call consciousness is somehow knitted together out of all these various things working in concert.

没错，这正是最大的谜团之一。记得在研究生院时，我的同学曾指出这个未解之谜，至今仍困扰着我。他指出，比如当你观察一个边缘时，任何边缘都显得如此锐利精细，而大脑中只有V1区的神经元分辨率足以表征这种边缘，对吧？

Yes, that's right. I mean, is one of the huge puzzles. You know, I when I was in grad school, I remember my my classmate pointed out this mystery, and it still bothers me. And and what he pointed out was that if you look, say, if you just look at an edge, okay, any edge, it's so sharp and so fine and that the only part of the brain where the neurons have the high enough resolution to represent the edge is probably V one, right?

明白。

Okay.

就像初级视觉皮层。然而你却能有意识地感知它。这怎么可能？难道意味着V1区具有意识？如果是这样，那究竟是什么赋予了它意识？

Like primary visual cortex. And yet you're conscious of it. Like how is that possible? Does that mean that V1 is conscious? And if it is, like what is it that makes it conscious, right?

因为我们所理解的V1区功能，坦白说其处理机制相当普通。比如边缘检测器完全可以用MATLAB编程实现。那究竟是什么让它具有意识？这才是最大的谜团。

Because all the things that we understand about V1 are, I would say, quite, I mean, the processing seems quite mundane, right? Like you have an edge detector, you can program that in MATLAB. Like, what makes that conscious? Like, what is that thing? And so I think that's very, yeah, that's the big mystery.

这让我联想到（虽然不是完全相同的光学错觉），那些模糊图片测试——人们会问你在云中看到长颈鹿还是人脸？而他们最先给出的提示总会影响我的最终感知。

Well, and it reminds me of not quite an optical illusion, but there are these pictures that are kind of indistinct and people will say, what do you see? Like in the cloud, do you see a giraffe or a face or whatever? And if they whatever they say first is what I end up seeing. Right? It ends up Yes.

这个暗示一旦进入我的大脑，我的思维就无法摆脱它的影响。

It goes into my brain, and my brain can't unlock itself from that suggestion.

没错。关于意识有一个理论我认为无法解释意识之谜。我是说，我从未遇到过任何真正能解释意识奥秘的理论。我们可以稍后再深入讨论，因为我对你在这方面的想法很感兴趣。但有一个关于意识机制的理论，人们称之为预测编码理论或生成模型理论。

Exactly. So there's this one idea about consciousness that I don't think explains the mystery of consciousness. I mean, I've never come across any theory that actually explains the mystery of consciousness. And we can get into that later because I'm interested in your thoughts about that. But the one theory of consciousness that I've just like as a mechanism, like what is this I mean, people call it the predictive coding theory or the generative model theory.

其核心理念是我们意识到的一切都是由大脑生成的。所有输入信息经过处理后，告诉我们该生成什么。但我们真正有意识感知到的是自上而下重构世界的过程。我认为这个理论非常美妙，其中一个原因是它解释了为何我们的意识感知在不同表征层级间总是不可避免地保持一致。比如那个著名的空间相位错觉，我想大家都见过吧？

But the basic idea is that everything that we're conscious of is generated by the brain. So all this, you know, stuff goes in and we process it and it gives us the input to know what to generate. But then what we actually are consciously aware of is the top down process that actually recreates the world. And I think this is a really beautiful theory for multiple reasons, but one reason in particular is that it explains this mystery of why our conscious perception is always, like, ineluctably consistent across different levels of represent right? So, you know, if I if you show me this illusion, the space phase illusion, I think everyone has seen that, right?

你可以把它看成两张侧脸，也可以看成一个花瓶。当你视其为花瓶时，不仅高层次感知认定它是花瓶，所有细节也与之相符。比如花瓶边缘的小片段永远属于花瓶而非人脸。而我们知道，这些细节的神经编码区域与物体识别的区域是不同的。

It's like you can see this thing either as two faces, profile faces, or a vase. And when you see it as a vase, it's not only your high level percept of the identity that's, you know, a vase, but also all the details, right? If you look at the little piece of edge at the vase, it's always owned by the vase and not by the face. And those little details we know from, you know, decades of neurophysiology, that's coded different area than the area that's coding the identity. Right?

这种同步性是如何实现的？而且当你视其为花瓶时，两侧边缘总是协调一致的。你绝不会看到一侧是侧脸而另一侧是花瓶，因为那不合逻辑。这究竟是怎么运作的？

How do you get this synchrony? Right? And also, when you see it as a vase, both edges are always consistent. You never see one side's profile and the other is the vase because that wouldn't make sense. And so how does that work?

因为编码边缘归属的B2区中，负责花瓶左边缘的神经元并不直接与负责右边缘的神经元交流。它们为何总能达成一致？永远保持一致？这需要解释。而预测编码理论通过自上而下的反馈生成意识，完美解释了这点——因为生成的意识本身就是协调一致的。

Because this area that's coding the edge ownership, B2, the neuron coding the left edge of the vase is not directly talking to the neuron coding the right edge. So how do they always come in agreement? Always in agreement, right? That demands an explanation. And this predictive coding theory, whereby, you know, consciousness is generated through top down feedback, beautifully explains this because it says that it's generated to be consistent, right?

我知道这是个花瓶，我生成了这两条边缘，所以它们当然必须一致。

I know it's a base and I generated those two edges, so of course they have to be consistent.

这确实有道理。我们采访过安迪·克拉克、阿尼尔·赛斯等研究这类问题的人，但我的理解是逐步推进的，所以不敢说自己有什么宏大理论。简单来说，是否可以这样理解：我们大脑中存在概念和世界模型，不是逐像素存储图像，而是将信息适配到现有概念框架中，然后维持这个框架——比如认定这是脸或花瓶——直到出现矛盾证据。

That does make sense actually. Mean, we talked to people like Andy Clark, Anil Seth who worked on these kinds of things, but you know, my my own understanding nudges forward incrementally, so I won't say that I have any grand theory of this myself. But basically, if I can if I can sort of rephrase, you're saying, we have concepts, right? We have models of the world in our brain, and rather than just having an image that we keep pixel by pixel, we fit it into the box that is given by the concepts we have there, and then we we sort of keep up that box, you know, this is a face or this is a vase until something pushes us out.

是的，没错。这种思考方式很美。我另一种理解是，大脑就像某种游戏引擎。它必须存在于一个现实空间中，你的感知也存在于其中，所有输入只是在调节参数，然后你生成那个现实。

Yeah. Exactly. That's a beautiful way of thinking about it. Another way I think about it is that, you know, the the brain has like a something like a video game engine. Like, there's just a space of reality that it has to live in, like, as well that your percepts have to live in, and all the inputs are doing is turning the knobs, then you generate that reality.

很好。我想在这个细节层面要补充的另一点是，信息流动不是单向的，对吧？不仅仅是光子进入眼睛，传到V1区再到V2区，然后在某处构建现实，而是存在反馈和前馈的交互过程。

Good. And I guess the one other thing at this detailed level I wanted to get on the table is that it's not just a one way flow of information, right? It's not just that we see the photons in our eyes, they go to V1, they go to V2, then somewhere else we construct reality, but there's like feedback and feedforward going on.

哦对，反馈连接太多了。几乎每个区域都有...我也不太确定。

Oh, yeah. There are so many feedback connections. Yeah. It's I mean, almost every area. I don't know.

我记得IT皮层和纹状体之间似乎只有单向连接，是从IT到纹状体的。

I think there's, like, one connection, like, between IT cortex and the striatum that only goes from IT to the striate striatum.

明白。

Okay.

但确实，大脑里几乎每个连接都是双向的。

But I yeah. It's like don't almost every single connection in the brain is bidirectional.

如果我们简单认为V1区只是检测明暗和形状之类的，那么大脑其他部分会如何影响它呢？毕竟看起来它有自己的专属功能。

There something specific about if we sort of naively think of v one as, you know, detecting light and dark and, just shapes and things like that. How would that be affected by other parts of the brain as it seems like that it it has a job and should just do it?

是的。这个预测编码模型的核心思想就像多米诺骨牌效应。比如你觉得在云中看到了一张脸，这会促使V2区域生成这些边缘轮廓，然后反馈给V1区域说'这部分应该再暗些因为这是眼睛'，而V1区域实际上会进行填充处理。

Yeah. Well, so the idea of this predictive coding model is that, you know, it's it's like a whole cascade of dominoes. Like, you you think you see a face in the clouds, then that's gonna, you know, bias v two to generate these edges, and then it's gonna go back to v one and say, oh, that should be, like, a little bit darker because that's the eye, and v one would actually be filling that in.

听起来太棒了，我完全被吸引了。但我们有多大把握确认这个过程真实发生？我们是在观测V1区的单个神经元活动吗？

And how that sounds great. I love it. How well do we know that that's happening? Are we, like, looking at individual neurons in v one?

正如你所知，我们实验室过去五年一直在寻找支持这个预测编码生成反馈假说的证据。坦白说目前仍无定论，学界还在争论中。

As someone you know, our lab has spent, like, the past five years, you know, trying to find evidence for this predictive coding generative feedback hypothesis. I would say we we still don't know. The jury is still out.

这很客观。能承认这点非常好。我常说物理是适合注意力短暂者的科学，而神经科学和生物学需要你在脑中同时容纳海量知识和不确定性。对了，你刚才提到的某个概念我想深入探讨下。

That's perfectly fair. And that's, you know, very good that we could admit that. Right? I mean, I always say physics is the right science to go into for people with short attention spans, but neuroscience and biology require an enormous amount of of knowledge and uncertainty in your brain at any one moment. And so then, okay, you mentioned something, again, I wanna dig it into.

IT皮层，我猜是指颞下皮层吧？

IT cortex. I take it that that is the inferotemporal cortex.

对。

Yes.

我刚在维基百科查的，别太惊讶我知道这个。不过或许你能向听众解释下这是什么？

Which I just looked up on Wikipedia, I mean, a little while ago, so don't be too impressed that I know what it is. But maybe you can explain to the audience what that is.

好的。所以你的大脑有，叫什么来着？枕叶、颞叶、顶叶、额叶，四个脑叶对吧？颞叶就是这里这个东西，就在你太阳穴旁边，靠近耳朵的面部区域。这就是颞叶。

Sure. So your brain has, what was it? Occipital, temporal, parietal, frontal, four lobes, right? And so, you know, the temporal lobe is this, this thing, you know, like right next to your temples, right, your ears, that region of your face. And so that's the temporal lobe.

人类大脑实际上有两个大的，怎么说呢，脑沟。就是大脑皮层上的凹陷褶皱。底部那部分叫颞下皮层，负责视觉处理。而上面那部分其实主要负责语言功能。在猴子身上，它还会对听觉皮层作出反应。我们记录颞下皮层活动时，电极常常会穿过上面这部分，我能知道是因为当我晃动钥匙时，会听到它产生反应。

And in humans, there's actually two big, like, I don't know, sulci. Those are hollows in this, you know, folds in this cortex. And so the bottom part of that, that's infrotemporal cortex, and that cares about vision. And then the stuff above that is really to language, actually, And in in monkeys, it also responds to auditory cortex. When we record from inferotemporal cortex, we often, our electrode goes through this stuff above it, and I would know because I would shake my keys and I would hear it responding.

产生反应后就像在说‘我们还没到视觉皮层’，然后才到达负责视觉功能的颞下皮层——那些细胞

Responding and like okay we're not in visual cortex yet and then we get to inferotemporal cortex where the visual So cells

我觉得你刚刚稍微改变了我的人生观。作为物理学家，我一直以为颞叶（temporal cortex）和时间（temporal）有关。但听你的意思，它其实是因为靠近太阳穴（temples）而得名？

I think that you just changed my life a little bit because as a physicist I always thought of temporal cortex as having something to do with time because it's temporal. But I think that you are implying that it has something to do with being close to our temples.

没错，原因就是这么朴实无华。

That's right. It's more prosaic.

明白了。所以这个颞下皮层比视觉皮层处理更抽象的信息？

Okay, good. So this inferotemporal cortex is is doing a more abstract job than the visual cortex?

啊，是的。我们之前说过腹侧流对吧？这条神经通路始于V1区，一直延伸到颞下皮层。这是大脑中负责物体识别的神经通路。

Ah, yes. So we talked about the ventral stream. Right? This is the pathway that, you know, starts in v one, and it goes it it goes to inferotemporal cortex. And that's the part of the brain, the pathway that's responsible for object recognition, right?

要知道，那是你妈妈，那是你爸爸。你是怎么做到的？知道那些是钥匙，那是铅笔。就是识别物体，无论它们以何种形式呈现都能认出来，对吧？我需要认出我的儿子，无论他是侧面、正面还是后脑勺对着我。

Knowing, again, that's your mom, that's your dad. How do you do that? Know, those are keys and that's a pencil. Like, just recognizing objects and recognizing them invariant to how they're presented, right? I need to recognize, you know, my son, if he's looking profile or looking at me or even the back of his, his head.

那么你是怎么做到的呢？这是个巨大的计算难题。我认为颞下皮层正是大脑中解决物体识别问题的部分。

So how do you do that? That's a huge computational problem. And, I think infotemporal cortex is the part of the brain that's solving that problem Over of object

从进化史来看，这是否比视觉皮层出现得更晚？听起来像是更高级的处理过程。

evolutionary history, did that come later than the visual cortex? It sounds like a higher level process.

对，这是个非常有趣的问题。我们刚完成对树鼩的研究，因为我们正好对这个进化问题感兴趣。树鼩是原产于印度尼西亚的动物，它们是非灵长类动物中与灵长类亲缘最近的物种之一。

Yeah, yeah, that very interesting question. We've actually just finished the study on on tree shrews because we're exactly interested in in that question about evolution. So tree shrews are are these animals that I think they're native to Indonesia, and they they're the close they're one of closest relatives to primates that are not primates.

好的。

Okay.

对吧？它们的视觉系统非常发达。很多实验室研究老鼠的视觉，但老鼠的视力很差，它们大脑负责视觉的区域很小。而树鼩有大眼睛，视力非常好，分辨率很高。

Right? And so, and they have really, really good visual systems. So, know, there's, like, tons of labs studying vision in mice, but mice are, like, terrible at seeing. Like, there's a tiny Their brain is responsible for vision. But tree shrews have giant eyes and they really see very well, have high acuity.

所以我们特别关注这个问题：树鼩是否存在颞下皮层？我们发现了令人惊讶的结果——你之前提到的V2区（紧邻V1区的区域）似乎具备IT皮层的许多功能，甚至在树鼩V2区发现了面部识别细胞。这让我们思考这个功能是如何进化的，我们认为它最初来自很浅的层级结构，后来才逐渐深化。

And so we were interested in exactly that question. Does inferotemporal cortex exist in tree shrews? And we found this very surprising result that V2, which you mentioned earlier, you know, the area right after V1 seems to have many of the functions of IT cortex. There's even face cells in tree shrew V2. So, yeah, it's interesting to think about how this evolved, but we think that it started from a very shallow hierarchy and being deeper.

我明白了。所以可能树鼩没有颞下皮层，但它们在其他部位完成了同样的功能，在进化过程中逐渐分化。

I see. So maybe the tree shrews don't have an inferotemporal cortex, but they do the same job elsewhere, and then over history, it sort of gets differentiated.

对对，看起来是这样。

Yeah, yeah, that's what it looks like.

擅长这方面的人——或者说树鼩中更擅长的个体更容易生存下来。我猜我们甚至还没讨论听觉输入的问题。早先我在播客里采访David Eagleman时，他讲过这个故事，我很想听听你的见解。比如你看到有人运篮球，篮球撞击路面的声音传到耳朵的时间显然比视觉信号慢（光速比声速快），但大脑会把两者同步处理，让你感觉它们是同时发生的。直到运球者距离远到这种同步显得不真实时，大脑会突然切换模式，让你意识到两者其实是分离的。这听起来熟悉吗？

The people who are better at it, the shrews who are better at it become better survivors. And I guess we didn't even talk about the audio input. Way back when I had David Eagleman on the podcast and he told me this story, I would love to hear your picture of it. But if you see someone dribbling a basketball, and it takes longer for the sound to get to you of the basketball hitting the street than the vision, obviously, speed of light faster than the speed of sound, But your brain matches them up, so it looks like they're happening at the same time until the person juggling the basketball gets so far away that that becomes unrealistic, and then suddenly you snap into this mode where the two are unrelated to each other. Does that sound familiar?

是的，这非常合理。我认为这支持了预测编码生成模型的理念——即你所见之物是被构建出来的。各种信号在时间上不同步，但大脑能从中构建出这种推断。

Yeah. That sounds very reasonable, and I think that think that also gets I I think it supports this idea of predictive coding generative model, the fact that what you see is generated. Right? So you get all these signals. They're mismatched in time, and then from that, you build this inference.

其实回到意识问题，我们认为那个整合所有信息并构建出你主观认知的推断步骤，是发生在离散时间点上的。虽然意识感觉是连续的，但我们认为它是离散发生的。而中间过程就是你在进行各种测量的时刻。关于时间感知的形成有个很有趣的理论，但我认为它是被构建出来的——绝对不是信号输入的瞬间就是你感知到事件的时刻。

And, actually, you know, getting back to consciousness, so we think that inference step where you put all this together and then build, you know, what you consciously see, we think that occurs in discrete time points. It's actually even though consciousness feels like it's continuous, we think it's happening discreetly. And in between, that's when you're taking all these measurements. So there's a very interesting story there about how you know, how you perceive time, but I think it's constructed. You know, it's definitely not, like, when the signal comes in, that's when you perceive thing as happening.

David Eagleman确实在这方面做过精彩的演示实验。

And and David Eagleman, you know, has certainly has beautiful demonstrations of them.

好吧，这太迷人了。我要脱离原定话题了，因为想了解更多。我原本理解的是大脑整合画面需要时间延迟，但你说了个我从没听过的有趣观点——我们对时间的感知就像是电影胶片？

Well, the okay. But this is fascinating. I'm I'm gonna go off script here because I wanna hear more about this. I understood that there was a delay in time, you know, takes time for the brain to put that picture together, right? But you're saying something very interesting that I don't think I've heard before that our perception of time is kind of like a filmstrip, right?

当存在一组彼此略有差异的离散帧时。数量如此之多以至于在我们看来是连续的，但确实存在一个数值，你知道的，就是我们意识体验中不同时间点之间的离散性。

Where there's a discrete set of frames a little bit different from each other. There's so many of them that it seems continuous to us, but there is some number, you know, the discreteness between our conscious experience of different moments of time.

没错。确实存在离散帧。而且我认为我要说的观点比这更激进——这些离散帧不像电影胶片那样是连续的。它们之间被类似你无意识状态的片段所切割，然后你才重新恢复意识。

Yeah. That's right. There's discrete frames. And, I think I think I'm saying something even more radical than that, which is that, there's discrete frames, those discrete frames, unlike in a film strip, are not consecutive. Like, there's, like, spliced with stuff, like, where you're basically unconscious, you know, and then you become conscious again.

但电影胶片仍在继续播放。是的。只是因为你处于无意识状态，甚至没意识到中间发生了这些你无法感知的事。所以你只能意识到那些你有意识的帧画面。明白吗？

But the film strip goes on. Yeah. But because you were unconscious, you didn't even realize that, you know, this thing happened in between where you're not conscious. And so all you're aware of is the, you know, frames where you are conscious. Right?

所以我们认为这就是真实发生的情况。

So we think that's what's happening.

随着 随着

With with

这又回到错觉现象上——你知道马车轮错觉吗？比如你拿个圆盘，在上面以不同半径画上不同频率的黑白条纹。如果旋转它，由于混叠效应，部分图案看起来会反向移动。如果用电影胶片逐帧拍摄旋转画面，也会出现类似反向运动的效果。

And there's there's a going back to illusions, there's like do do you know the wagon wheel illusion? Like, if you just take a disc where you have I don't know. You you you paint, like, different frequencies of, like, white and black at different radii. Uh-huh. If you spin it, it'll look like part of it's moving backwards because of alien if you and and if you spin it and you you take frames like that with a film strip, then it looks like part of it's going backwards or if it's aliasing.

但你其实能在现实生活中观察到这种现象。发展神经科学家戴尔·珀维斯对视觉现象产生兴趣后，他做出了惊人的推理——从马车轮错觉的现实存在，直接推导出人类意识具有离散性。哇，就像是被采样的一样。

But you can actually see this, like, in real life. You know? And and Dale Purvis, who's a, you know, developmental neuroscientist who became of interest in vision, he he made this amazing leap of inference, like, from the fact that you can see this wagon wheel illusion in real life to the conclusion that our consciousness is discrete. Wow. It's, like, sampled.

对吧？就像电影胶片一样。是的。

Right? Just like a movie strip. Yeah.

但当你这么说时，确实，现在完全说得通了。这实际上就是实证证据。很好。所以我得问，我失去意识多久？两次有意识感知之间的间隔是什么？

But when you say it that way, yeah, now it makes perfect sense. That is actually evidence for it empirically. Good. So I I gotta ask, how long am I unconscious for? What is the space in between two moments of conscious perception?

我认为这取决于刺激，比如它传入的速度。但是，你知道，在我们研究过的情境中，我们发现存在长达几百毫秒的时段，那时你

I think it depends on the stimulus, like how fast it's coming in. But, you know, for in in the in the situation where we've studied it, we've high find epochs, you know, up to a few 100 milliseconds where, you're

100毫秒。

100 milliseconds.

这很正常。神经元并不代表你有意识看到的东西。不是的。

That's fine. Neurons are not representing what you're consciously seeing. No.

哇。那真是相当长的无意识状态。好吧。大家都同意这点吗？还是说这是某种前沿推测？

Wow. That's a lot of unconsciousness. Okay. Does everyone agree with this? Or is this sort of cutting edge speculation?

这个我们甚至还没发表呢。

This is we haven't even published it yet.

好的，很好。那些内容非常酷。我很想听听接下来的部分。不过，好吧，信息量有点大。我们先暂停一下，喘口气。

Okay, good. That would be that's very cool stuff. I want to hear about that coming in. But, okay, so this is a lot. Let's pause and take our breath here.

我是说，可能只是我对计算机或人工智能理解不够深入，但人脑的运作方式似乎更为精妙，对吧？有各种不同的信息流在并行处理不同任务，匹配各种模式等等。这是一幅相当惊人的图景——从进化论角度来看，不同能力在生物进化的不同阶段各司其职，这种解释倒也合理？

I mean, it sounds like maybe I just don't understand computers well enough or AI well enough, but it sounds like what the human brain does is kind of more subtle, right? I mean, there's a lot of different streams doing different things, matching on to various templates and so forth. It's- it's kind of a remarkable picture that I guess makes sense from an evolution point of view that it all, you know, different capacities become relevant at different stages in the in the biological evolution?

我不确定是否认同这个观点。我认为视觉系统是精妙的机械装置，我们终将能理解它运作的基本原理。

I'm not sure I resonate with that. I think, my my hope is that, you know, the visual system is this beautiful piece of machinery, and we'll be able to understand the compass, you know, fundamental principles that it's implementing this.

哦，这一点我完全同意。我只是说现有的计算机相比这个精妙的大脑显得更简单。我完全相信大脑是物理机械结构，理论上我们能造出功能完全相同的计算机。但你知道，我们的计算机是智能设计的产物。

Oh, that I a 100% agree with. I'm just saying, like, the actual computers that we have seem to be more simple minded than this this beautiful brain. I'm very much a physicalist, a mechanist about the brain. Can imagine that we build a computer that does exactly what the brain does. But, you know, we intelligently design our computers.

所以我们把计算机设计得直接且尽可能简单，而大脑经过数百万年进化，将各种功能以实用方式整合在一起。

So we make them, you know, sort of direct and as straightforward as possible, whereas the brain grew up over millions of years to, you know, lump together different capacities in in useful ways.

是啊。作为实验神经科学家，我必须承认大脑组织的精密程度总是令我震惊。

Yeah. I mean, as an experimental neuroscientist, I would have to say, I don't know, the brain just astonishes me with how precisely it's organized.

没错。哦，确实。好的。那么，我们接下来讨论它最令人印象深刻的能力之一——面部识别。

Yeah. Oh, yeah. Okay. Very good. Well, and let's get on to one of its most impressive abilities, which is recognizing faces.

这是你一直非常活跃的领域。我的意思是，我们想要识别人脸的原因显而易见。大脑是否有专门负责这项功能的特定区域？还是说这个功能也分布在不同区域？

This is, something that you've been very, active in. So is there a I mean, it's obvious why we would want to be able to recognize faces. Is there a specific part of the brain that does that? Or is that also distributed through different parts?

是的，我们识别人脸的能力可能是最明确归属于特定大脑皮层区域的功能之一。最早的证据来自病变研究，比如中风患者突然无法识别人脸，但其他识别能力完全正常。这强烈表明存在专门用于识别人脸的皮层区域。

Yeah, This is probably you know, our ability to recognize faces is probably one of the functions that's been most clearly ascribed to a specific piece of cortex. Right? And so, the earliest evidence for this came from, again, lesion studies, you know, people with strokes. And suddenly they can't recognize faces anymore, but they can recognize everything else just fine. And that just shouts that there's a piece of cortex that's dedicated for seeing faces.

这个现象早已为人所知。1997年，麻省理工学院的Nancy Kamwisher发表了那篇里程碑式的论文——它是《神经科学杂志》被引用次数最多的论文。她通过MRI扫描正常人类受试者，向他们展示人脸和物体图片时发现，所有受试者的右侧颞叶都有一个区域对人脸的反应远强于其他物体。这个区域约蓝莓大小，在每个受试者大脑中的位置都相同，对人脸会产生强烈信号。

So that was, you know, that was known. And then in 1997, Nancy Kamwisher at MIT published this landmark paper. It's like the most cited paper in the Journal of Neuroscience, where she reported that human patient just human subjects, normal human subjects that she scanned, you know, instead of MRI scanner, she showed them pictures of faces and objects. They all showed this region in their temporal lobe, in their right temporal lobe, that responded much more to faces than other objects. And it was like, you know, the size of a blueberry, and it was, like, in the same place in every single subject, and it just showed this huge signal, in response to faces.

因此这成为了存在专门负责面部识别的神经回路的强有力证据。

And so that was, like, you know, really strong evidence that there is a piece of dedicated cords for representing face.

这个区域有名字吗？

Does it have a name?

有。她将其命名为梭状回面孔区，因为它位于颞叶中被称为梭状回的部位。

Yeah. So she called this the fusiform face area because it's in this part of the temporal lobe called the fusiform gyrus.

好的，非常棒。真令人惊讶，这些发现直到1997年才出现，这一切都如此新颖有趣。

Okay. Very good. It's amazing to me that was only 1997, that this is all so new and fun, really.

是啊是啊，那时我还是个研究生。我记得读她的论文时，觉得特别奇怪。为什么大脑会有一块专门处理面孔的皮层呢？

Yeah. Yeah. I was a grad student then. I remember reading her paper, and it seemed, like, so weird to me. Why why does a brain have a piece of cortex, you know, for faces?

面孔看起来和其他东西没什么不同。所以当时我完全没想到自己会深入研究到这个程度。

Faces don't seem that different from anything else. And so, yeah. Little did I know how deep I would go down that.

没错。但你们确实做到了。自1997年以来，我们对此机制有了更多了解。这是否又是一个关于梭状回基底区亚结构的故事？就像不同部位负责不同功能那样？

Right. But you have. So we've been, since 1997, learning a lot more about how this works. And is it is it another story where we're discovering substructure in the fusiform base area that, you know, there's different parts doing different things?

确实，揭示这个区域的工作细节是个惊人的发现。我读研时其实在用猴子研究三维视觉，后来突发奇想给它们看面孔和其他物体，想找找看猴子是否也有面孔识别区。没有也无所谓，反正fMRI实验很容易做。

Yeah. So it's it's been an incredible story figuring out, you know, the details of how this area works. So the you know, when I was a grad student, I I was scanning monkeys, actually studying three d vision, and then I decided to show them faces and other objects, look for a face area just for fun, see if monkeys also have have a face area. You know? Not a problem if they don't because f m r experiments are, you know, very easy to do.

结果它们不仅有，而且有六个！我当时就震惊了——这六个区域各自在干什么？因为研究对象是猴子，我们可以往每个区域插入电极研究神经元活动。你刚才问是否存在功能特化...

And and there they did. And not only did they have a face area, they had six of them. And so it was like, woah, there's these six regions, what are they doing? Because we're working in the monkey, we can insert an electrode into each of these regions and study what the neurons are doing. And you asked if there's functional specialization.

事实上这六个区块确实各司其职：最靠后的区域对眼睛特别敏感，就是轮廓里的黑色圆盘；相邻区域处理特定角度的面孔；再往前...

And indeed, each of these six patches seems to be performing a different function. So in particular, the most posterior one, it seems to really like eyes, right? Just like a dark disc inside this outline. And then the next one cares about faces but at specific views. And then you go even more anterior.

有个区域对镜像对称的面孔有反应，喜欢左右侧脸或正脸；最前面的区块则有这种神奇细胞——只要身份相同，无论面部朝向都会响应。这种分工简直精妙绝伦。

It responds to faces in a mirror symmetric way, so it likes left profiles and right profiles, or faces looking straight, and down. And then the most anterior patch, you have these incredible cells that respond in a view invariant way, so they don't care which way the face is pointed, but as long as it has the same identity, it'll respond. So there is this remarkable division of labor.

我大脑的某个部分正在专门注意眼睛。

There's a part of my brain that is just noticing eyes.

嗯，或者其他特征，但眼睛确实非常突出。是的，很多细胞，比如这个面部识别区域里大约70%的细胞，都对眼睛的大小特别敏感。你甚至只需要展示一个简单的卡通脸，改变那两个点...对，那些区域，它们的反应就会越来越强烈。没错。

Well, or and other features, but eyes are so prominent Yeah. That, yeah, a lot of cells, like 70% of the cells in in in in, you know, this one face patch are tuned to, like, the size of an eye. You show you can even show just a simple cartoon face, and you change that those two pics Yeah. Regions, and they start responding more and more. Yeah.

我必须问一下，你们给猴子看的是猴子的脸还是人类的脸？这有区别吗？

And I I have to ask, are you showing the monkeys pictures of monkey faces or human faces, or does it not matter?

是的。实际上...我是说，确实有区别，但它们用相同的原理来编码所有这些不同的面孔。它们甚至会对卡通脸、云朵形成的脸产生反应。

Yeah. It turns out that it doesn't I mean, it it does matter, but, they're using the same principles to code all these different faces. And they even respond to cartoon faces and faces and clouds and yeah.

这就是我接下来想问的。这是否解释了为什么漫画里几笔简单的线条就能如此传神——如果它们看起来像张脸的话？因为我们的大脑似乎被设定成会注意到这些微小差异？

Well, this is why I I was gonna get there. I mean, is does this help explain why a few dashes of line in a cartoon can be so expressive if they're supposed to look like a face? Like, our brains are sort of tuned to notice these tiny differences?

没错。正是如此。很可能就是这样。

Yes. Exactly. Yes. Probably Yeah.

或许这其中还涉及到这些大脑区域如何与更情绪化...或者说更感性的大脑区域进行交流的故事。

Probably there's some story of how those parts of the brain are talking to more emotional or or, romantic, I don't know, parts of the brain.

是的，我们对于身份特征的呈现方式了解得更多，而对于表情特征的呈现方式则知之较少。不过，我们确实拥有专门用于观察这些不同维度的机制。对吧？因为人脸是多维度的。

Yeah. That that we know much more about how the identity is represented than how the, expression is represented. But, indeed, you know, we have the specialized machinery for for seeing all these different dimensions. Right? Because faces are multidimensional.

要知道，要创造一个高度逼真的形象至少需要50到200个维度。而我们能同时感知所有这些维度，这确实非常了不起。对吧？就像颜色有三个维度那样。

You know, you need at least, like, 50 or 200 dimensions to create a really good likeness. And we can see all those dimensions simultaneously. So that's, you know, really remarkable. Right? Like, color has three dimensions.

不知道你是否听说过切尔诺夫脸谱。这是一种将多维数据集映射到人脸特征上的可视化方法，通过观察面部变化就能看出有三个维度在变动。

And I don't know if you've heard of Chernoff faces. No. Like, it's it's like this method for visualizing multidimensional datasets where you map them on to faces, and then you can see, oh, There's, three dimensions that are changing because you can see that in the faces.

哇，我该了解这个的。好的，非常棒。我得趁机插一个专业术语进来。

Wow. I should know about that. Okay. Very good. And I I gotta get one vocabulary word in there.

显然，大脑这个区域的神经元集群被称为'神经球'。

Apparently, the name for a cluster of neurons in this part of the brain is a glob.

对，我们称它为'神经斑'。所以既有'神经球'也有'神经团'这样的说法。

Yeah. We we call it a patch. So there's also yeah. There's, like, globs and blobs. Yeah.

等等...在大脑V4区有专门处理颜色的特定子区域，那些被称为'颜色球'——就是那些彩色的小球体，它们位于大脑不同区域。嗯。

We we wait. There there are these colored globs that that so that's in in in in in a different part of the brain. In v four, there's these specific subregions that care about color, and those are called color globs. Mhmm.

团块。团块和斑块。那么梭状回面孔区是视觉皮层的一部分吗？

Globs. Globs and patches. And is the fusiform face area part of the visual cortex?

是的。梭状回面孔区位于人类大脑中，猴子大脑中我们认为也有同源区域。梭状回面孔区属于腹侧视觉皮层，属于高级视觉皮层。它位于V1、V2区之后。

Yeah. So so so fusiform face area is in the human brain, and then, you know, monkeys, there's, we think, homologous region. And then the fusiform face area is, yeah, it's part of the ventral visual cortex. It's like high level visual cortex. So it's beyond your V1, V2.

好的，明白了。你刚才提到的这项研究是什么时候进行的？有多久了？

Good, okay. And when was this research that you're just mentioning being done? How old is this?

哦，记录所有这些不同的面部斑块数据大约是在2000年。我们关于这个层级结构的论文，我记得是2010年发表的。

Oh, so recording from all these different face patches, that was, like, you know, 2000. We published the paper, I think, in 2010 on the this hierarchy.

好的。嗯。这个问题可能不太公平。我是说，识别面孔甚至...抱歉。

Okay. Good. Yeah. And do we maybe this is an unfair question. I mean, recognizing faces or even rec sorry.

让我重新表述一下。梭状回面孔区的功能更多是识别这是谁的脸，还是识别脸部的特征？比如这是皱眉的脸，这是笑脸，这是友善的脸。

Let me let me back up. Is the job of the fusiform face area more to recognize whose face this is, or is it to recognize this is sort of the aspect of the face? This is a frowny face. This is a smiley face. This is a a friendly face.

我认为它本身并不处理情绪，而是处理面部的物理特征。比如眼距是多少？质地如何？脸型是什么样？

I think it's, it's it's it's not processing emotion per se. It's processing the physical features of the face. Like, what, you know, what is the inter eye distance? What is the texture? What is the shape of the face?

它尚未达到明确识别的层次。我们认为那会在稍后阶段出现。

It hasn't yet reached the level, of the explicit identity. We think that happens later on.

那发生在其他地方。好的，非常好。我是说，我们现在是在研究单个神经元的功能，还是说那是个技术挑战？

That happens somewhere else. Okay. Very good. I mean, are we down to looking at the jobs of individual neurons, or is that a technological challenge?

是的。我是说，我们所有的记录都是针对单个神经元的。明白吗？这些非常细的导线除了尖端外都绝缘，尖端大约10微米宽。所以我们现在可以捕捉到数百个单个神经元的电活动。

Yeah. I mean, all our recordings are of single neurons. Right? These very thin wires are insulated everywhere except the very tip, and the tip is, like, 10 microns wide. And so we can pick up the electrical activity from many, you know, hundreds of single neurons now.

所以没错，我们可以探究单个神经元的选择性是什么？

So, yeah, we can ask what is the selectivity of single neurons?

我是说，听众中可能没有专业科学家。所以我们来深入探讨实验本身。你提到了fMRI，现在又提到探针。这是两个非常非常不同的概念，对吧？

I mean, of the audience listening is probably not professional scientists. So let's dig into the experiment itself. I mean, mentioned fMRI and now you're mentioning probes. These are two very, very different ideas. Yeah?

是的。fMRI，人们说它测量的是大脑的'管道系统'，只是测量血液流向哪里。结果发现当你使用大脑某个部分时，会有更多血液流向那个区域。

Yeah. So fMRI, people say, know, it's measuring the brain's plumbing. It's, just measuring where the blood is flowing. Right? And turns out that when you use a part of the brain, there's more blood flowing to that part of the brain.

这就像一种稳态机制。所以它非常粗略，测量的是以立方毫米为尺度的神经活动，其中包含10万到100万个神经元。而我们使用的另一种技术，一旦发现这些面部区域或颜色区域等，我们就想了解具体细节。

It's like homeostatic mechanism. So, yeah. So it's very coarse. It's measuring neural activity at a scale of a millimeter cube, and that contains 100,000 to a million neurons. The other technique that we use, like once we find these face areas or color areas or so on, then we want to know what the details are.

你知道神经元是如何具体表征面部信息的吗？仅通过毫米级脑部研究是无法解析的，必须研究单个神经元。为此我们植入电极来捕捉神经活动。如今我们使用一种叫神经像素探针的电极，这个概念就像是让你观看大脑的'电视'，明白吗？

You know, how are the neurons actually representing the face, right? You can't figure that out by studying the brain in millimeter sized You need to study the single neurons. And so to get at that detail of information, then we insert these electrodes that let us pick up neural activity. And these days, we're using these electrodes called neuropixels probes. And the idea is sort of like, they let you watch the TV of the brain, right?

这种神经像素探针拥有约4000个接触点，采用硅基制造技术。通过这些硅探针，可以同时记录数百个神经元的活动，这实在是...令人振奋

So neuropixels. And these have like 4,000 contacts. So they're using this silicon fabrication technology. So there's these silicon probes, so you can actually record from hundreds of neurons simultaneously, which is a really And exciting

我们能否逆向推演？通过观察神经元活动来反推生物体正在注视什么？

can we kind of go backwards? Can we just look at what the neurons are doing and work out for ourselves what is being looked at?

没错。许多实验室都致力于解码神经活动，试图还原视觉信息——比如你在看什么，外界发生了什么。我们在面部识别领域实现了突破：仅用200个神经元的信号就能精确重建猴子看到的面孔，重建效果逼真到无法区分真实刺激和我们根据神经活动合成的图像。

Yeah, yeah. So there's, you know, many labs are motivated by that goal to decode the neural activity and try to recover, you know, what are you looking at, what's happening in the world. And so we've done this in the realm of, you know, these face areas, and that was, you know, a really satisfying accomplishment to be able to take just the neural activity from 200 neurons and from that be able to reconstruct precisely the face that the monkey was seeing, you know, and creating a likeness that you couldn't even tell which one was the real stimulus and which one was the reconstruction that we made from his neural activity.

这显然能应用于脑机接口技术...前提是我们能把探针植入大脑。

So there's an obvious technological application of this to computer brain interfaces. Yeah. Yeah. But only if we can stick probes inside our brains.

很遗憾，确实如此。

Unfortunately, yes.

好吧。虽然我是个彻底的物理主义者，但想到如果有人能探测我所有神经元就能读取思想，还是有点毛骨悚然。但你们正在实现这个目标，我们得学会适应。对了，这能帮助我们解释之前你提到的脑损伤现象吗？

Okay. But, you know, it is a little even even though I am a thoroughgoing physicalist, it is still, slightly spooky to me that if someone could, like, probe all of my neurons, they could figure out what I'm thinking. But that's what you're on the road to doing. So we'll have to we'll have to learn to deal with that. So does this help us explain you mentioned lesions before.

这能帮助我们考虑到各种残疾情况吗？我知道有些人存在面部识别障碍。

Does this help us account for various disabilities? I know that some people have trouble recognizing faces.

没错。人们研究过这些所谓的面容失认症患者——他们难以辨认面孔。其中部分人有脑损伤，但大约4%的人群虽然从未中风，却极度不擅长认脸。是的，如果研究他们的大脑活动，会发现有些人面部识别区域选择性差，或者该区域面积较小。

Yeah, that's right. So people have studied these, you know, so called prosopagnostics who have trouble recognizing faces. And some of these people have lesions, but I think there's like four percent of the population, some very high percentage don't have any, didn't have any stroke but they're just like really, really bad at recognizing faces. Yeah. And indeed if you studied the brain activity in these people, some of them have, you know, poor selectivity in their face areas or small face areas on things

像这种情况。现在有改善的希望吗？还是说这个目标太宏大了？

like that. Is there hope for improving it, or is that too ambitious right now?

哦，这很有意思。或许可以。我提到过人类的视觉空间处理区域位于右脑。

Oh, that's very interesting. Maybe. You know, I mentioned that the space area in the human is in the right hemisphere.

嗯哼。

Uh-huh.

而左脑对应的皮层区域实际上负责字母识别。这说明人类视觉系统具有惊人的可塑性。所以我在想，或许通过某种训练...

And and the corresponding piece of cortex in the left hemisphere is actually responsible for recognizing letters. And so there's this remarkable plasticity in the in the human visual system. And so, I don't know, maybe with some kind of training.

好的。我是

Okay. I'm a

起初没什么进展。是啊，我也不确定。

little happened early on. Yeah. I I'm not sure.

不，那太棒了。但现在我真的很惊讶，当你说我大脑中有个蓝莓大小的部分专门负责识别人脸时，我会点头赞同说，没错，这完全解释了它为何会进化出来。而我大脑还有个类似区域是识别字母的，这看起来更受文化背景影响。

That no. That that's great. But now I'm I'm amazed at so when you say that there's a little part of my brain, size of a blueberry, whose job it is to recognize faces, I nod along and say, yes, that makes perfect sense why that would evolve. Now there's another part of my brain that is similar that is recognizing letters. That seems a lot more culturally, contextualized.

比如，在我们有文字之前，大脑那个部位是干什么用的呢？

Like, you know, what if I well, what about before we had letters? What was that part of the brain doing?

是的，我们认为它原本是用来识别人脸的。猴子面部的毛发是完全对称的。有趣的是，不识字的人——那些不认识字母的人——他们大脑的面部识别区也是对称的。

Yeah. We think it was recognizing faces. So in, monkeys, the face hairs are perfectly bilateral. And what's amazing is that in illiterate people who don't recognize letters, you know, that they also have bilateral face areas.

哇，所以明显结论是我们把原本用于识别人脸的大脑区域改造用来识别字母了。这太神奇了。好的。

Wow. So the obvious conclusion is that we have repurposed part of the brain that was helping us recognize faces to help recognize letters. Yeah. That's amazing. Okay.

非常好。因为这意味着——谁知道我们接下来会改造什么功能呢？我们的能力退化了吗？识字的人比文盲更不擅长识别人脸吗？

Very good. Because that means that, yeah, who knows what we'll be repurposing next. Are we worse? Are are people who are literate worse at recognizing faces than people who are illiterate?

我不知道，但这似乎是个合理推论。是啊，应该有人研究这个。没错。

I don't know, but it seems like a logical conclusion. Yeah. Someone should test it. Yeah.

好的。明白。不错。不过这也让我们触及到你著作和讨论中一些更具争议性的内容。从某种意义上说，我们可以基于这些观点来尝试理解抽象思维，或者说大脑中符号思维的起源？

Yeah. Okay. Good. And but it also brings us to some of the more provocative things that I've read in in your work and in discussions of it. In some sense, we can build upon these ideas to try to help us understand abstract thought or the the, you know, the the sort of origin of symbolic thought in the brain?

我可能表达得不太好，因为我自己也不确定是否完全理解这个概念。

I'm probably saying this badly because I'm not sure I completely understand it.

哦，其实我研究抽象思维起源的方法与面部识别这项工作是彻底分开的。我们要讨论的是背侧视觉流对吧？面部识别是在腹侧视觉流处理的。我开头提到过，背侧视觉流是动作行为的基础，明白吗？

Oh, well, the way I I'm tackling this problem of how abstract thought arose is actually totally independent of this work on faces. Okay. And we're going to the dorsal stream, right? So faces are are are processed in this ventral stream. You know, I mentioned at beginning there's this dorsal stream that's that's the basis for action, right?

那么我们如何知道如何在世界中行动？我认为必须要有一种压缩的符号表征，比如基于事件的理解。这些就是客体对象，它们赋予我们这种能力。

And so how do we know how to act in the world? I think we have to have a compressed symbolic representation, like an event based understanding. Right? We really and so those are the objects. This is what they allow us to do.

现在我要去拿香蕉了。我认为理解符号思维起源的最大挑战，就在于理解这种具体的物体追踪机制。当所有像素信息进入眼睛后，我们如何将其转化为持久存在的物体对象？

So I'm gonna go pick up the banana now. And so I see the big challenge to understanding how symbolic thought arose as understanding this very concrete problem tracking. Right? So we have all these pixels going into our eye. How do we transform that into objects, into persistent objects?

对吧？嗯。一旦完成这个过程，我们就能给物体贴标签、建立关联并进行思考。但在那之前，比如肖恩还在房间里，我走开时他依然存在。

Right? Mhmm. Yeah. Like and once we do that, then we can assign labels to them, and we can associate them, and we can think about them. But before we know that, you know, that's Sean and, you know, I can walk around, Sean is still in the room.

在没有形成物体概念之前，我们甚至无法进行任何思考，眼前只有模糊的感官信息。我认为这是关键的一步转变。但我们完全不明白大脑是如何从这些感官特征中构建出离散物体的——在我看来这仍是未解之谜。

Like before we have that concept of, you know, objects, we can't even think about anything, right? It's just like this sensory blur. So I think that's like the key step. And we don't understand that at all Good. In my opinion, like how the brain actually goes from all this sensory stuff and all these features to these discrete objects.

是的，我们正在处理这个问题。

So yeah, we're tackling that.

我确实在播客中邀请了《因果论》作者朱迪亚·珀尔，他提到婴儿会竭尽全力构建对世界的因果认知图。他们不断探索事物，观察结果，追踪各种影响。虽然这不能说明大脑内部的具体运作，但与我们试图通过经验构建认知模型的理论非常吻合。

I did have Judea Pearl on the podcast, the causality guide, and he says that what babies do is they work as hard as they can to construct a causal map of the world. They keep poking at things and seeing what happens and seeing what leads to other influences and so forth. That doesn't say what is happening in the brain, but it fits in with the story that we're kind of trying to construct this model out of our experiences.

没错，正是如此。

Yes, exactly. Yes.

这让我想到你最近与父亲合写的论文——我觉得父子共同研究特别温馨。请问令尊从事什么职业？

And the this brings us also to, you know, you wrote a recent paper with your father, which I thought was very charming that you wrote a paper with your father. What does your father do for a living?

他是数学家。

He's a mathematician.

难怪论文数学味这么浓。里面的微分几何内容让我印象深刻，不知这是你论文的常规风格，还是你在引导合作者？

Okay. Because the paper was very mathy. I was impressed at the amount of differential geometry in this paper. I don't know if you usually have that in your papers or you were leading your collaborator.

说起来很有趣。当时我还在加州理工学院读本科，选修了微分拓扑这门课。

It was kind of funny. You know, I was I was I think I was an undergrad. Yeah. Undergrad at Caltech. You know, I took this class on differential topology.

我把课本带回家了，然后我父亲，呃，研究了它，他意识到，嗯，这些想法和愿景都有实际应用，最后一切都很顺利。是的。

I brought my textbook home with me, and my my father, like, studied it, and he realized, like, they had applications to these ideas and vision, and it it all worked out. Yeah.

所以，如果我对这篇论文的简短理解没错的话，你试图解释的是我们如何知道世界上存在同一个物体，即使，你知道，它暂时走到障碍物后面我们看不见，然后又从另一边出来。但在我们大脑中，那是一个持续存在的链条。

So, if my very brief understanding of this paper is you're trying to understand something you just mentioned that sort of how we know that there is the same object, in the world even though, you know, it temporarily walks behind an obstacle and we can't see it and it walks out the other side. But but in our brains, that's a continuous chain of being there.

是的。或者，比如，你知道，如果我绕着你走，我知道你是同一个人。我该怎么解决这个问题？结果发现，就像计算机视觉领域的人说的，你只需要大量样本，大量训练数据，然后就能神奇地学会。而我们在论文中说，不，你根本不需要任何训练数据。

Yeah. Or, like, you know, if I walk around you, I know that you're the same person. How how can I solve that? And and it turns out, like like people in computer vision, they say you just put lots of samples, just lots of training data, and then you just magically learn. And what we say in the paper is that no, you don't need any training data.

这实际上是一个非常优雅的数学问题，直指曲面的定义，对吧？就像曲面是这些图表的集合，重叠的图表，所以重叠是关键，对吧？当我绕着你走时，我计算这个图表，并改变视角——要么因为我有两只眼睛，要么因为我移动了——然后找到这个重叠的图表。所以这是同一曲面的一部分，我可以一直这样做。我可以绕着你走一圈，从而形成这个以重叠为等价关系的图表等价类。

It's actually really elegant mathematical problem that goes to the very definition of a surface, right? Like a surface is this collection of charts, overlapping charts, and so that overlap is the key, right? So as I walk around you, I compute this chart and I change my perspective either because I have two eyes or I move, and then I find this overlapping chart. And so that's part of the same surface, I can keep doing that. I can walk all around you, and so I can form this equivalence class of charts where the equivalence relation is overlap.

所以这就像是一个关于物体如何产生的非常美妙的数学理论。

And so it's it's like it's a really beautiful mathematical theory of how objects can arise.

太棒了。你学会了我教广义相对论时微分几何第一章里的所有流行术语。这很酷。不过，说大脑更容易将物体概念化为同一个物体——即使你从不同角度观察——而不是想象每一步都是不同物体，这种说法会不会有点夸张？

This is great. You've learned all these buzzwords that are in the, you know, chapter one of my general relativity textbook when I'm teaching people differential geometry. So that is cool. So is but is it would it be an exaggeration to say that, you know, effectively what what the the point is that it's kind of simpler for the brain to conceptualize the object as being the same object even as you're looking at it from different points of view than to sort of imagine distinct objects at every step along the way.

是的。完全正确。我是说，视觉系统最大的任务就是解决这个不变性问题，弄清楚什么对应着同一个事物。对吧？

Yeah. Absolutely. Yeah. I mean, the the biggest job of the visual system is to solve this invariance problem and figure out what is corresponding to the same thing. Right?

因为，你看，信息变化得太快了。对吧？你只需要，比如，动动脑袋

Because, you know, the the information is changing so much. Right? You just, like, move your head

是啊。

Yeah.

就像，发丝般的距离所有像素就都变了。你必须，比如，能够抵消这种变化。对。

Like, by hair's width and all the pixels change. You have to, like, be able to counteract that. Yeah.

所以在某种意义上，这就像是个压缩问题。对吧？我是说

So in some sense, it's an it's like a compression problem. Right? I mean

没错，正是这样。

Yes. That's right.

是啊。再随便猜一下，这和贝叶斯大脑假说有关吗？我们曾在播客里采访过卡尔·弗里斯顿。

Yeah. And, again, stab in the dark here. Does this have anything to do with the Bayesian brain hypothesis? We talked to Carl Friston once, on the podcast.

是的，是的。我认为关系很大。明白吗？我们理论的工作原理，比如你实际计算这些重叠的方式，对吧，这些微分同胚，所以我们问，数学问题就是你怎么知道这个视觉区块的视角是那个区块的转换视角呢？

Yes. Yes. I think it has a lot to do with it. You know? So the way our theory works, like the way you actually compute these overlaps, right, you know, like these diffeomorphisms is so we're asking, so the mathematical problem is how do you know that this view of a patch, a visual patch, is a transformed view of this patch, okay?

我们解决这个问题的方法是引入所谓的动态感受野，本质上大脑的测量过程就像将图像块投射到感受野函数上，其实就是内积运算。这样你就能进行转换——可以建立动态系统来调整感受野函数，从而抵消图像的变化。举个简单例子，比如左眼图像块相比右眼图像块偏移了约10个像素。

And the way we figure that out is to introduce these things called dynamic receptive fields, essentially you can So the measurement that the brain makes is basically like the projection of the image patch onto a receptive field function, Projecting, just inner product. And so you can actually transform. You can set up a dynamical system to transform the receptive field functions to counteract the change in the image. Right? So a very simple example, like say you the left eye image patch is shifted compared to the right eye image patch by like 10 pixels.

如果我把感受野函数也偏移10个像素，就能得到完全相同的测量结果对吧？这就是核心理念：通过给感受野函数引入动态特性来补偿这些变换。据我理解，这正是贝叶斯推理过程中发生的——你有这个试图预测感官信号的自上而下信号。

Well, if I shift my receptive field function by 10 pixels, then I'll get the exact same measurement, right? And so that's the idea. Like we introduce these dynamics on the receptive field function so we can compensate for these transforms. And to my understanding, that's exactly what's happening during Bayesian inference, right? So you have this top down signal that's trying to predict your, sensory signal, right?

对，所以，

Yeah, so,

让我试着重新表述来确认理解：如果把我当前看到的视觉场理解为由不同数值的像素组成，这里包含着海量信息。当我稍微改变视线方向时，有两个选择：要么完全重写并替换成另一套庞大数据，要么认为这和你之前看到的几乎相同，只是发生了特定位移。

you know, again, I'll try to sort of resay it so I think that I understand it. If I think of what I'm looking at right now as, you know, my visual field as being represented by a number of pixels with different values, there's an enormous amount of information in there. And if I change the direction in which I'm looking by just a little bit, I have two choices. One choice is to completely rewrite that and replace it with a different huge amount of information, or the other choice is to say, it's almost the same thing you were looking at, but shifted by this amount.

没错，正是如此。

Yeah, exactly. Right. So, yeah.

这在能耗和信息处理等方面能带来巨大节省。这是否在引导我们...都怪你提起意识这个话题（也可能是我说的记不清了）...这是否让我们更接近理解意识本质？理解我们这种在更抽象层面概念化世界的能力？

And that's an enormous sort of saving in terms of energy and information processing and all those other good things. And is this nudging us? It's your fault because you brought up consciousness, or maybe I did, I don't remember. But is this nudging us toward a better understanding of consciousness, of who we are, like our ability to conceptualize the world at this more abstract level?

希望如此。我认为如果能解决神经活动如何表征视觉信息这些基础机制问题，我们就在理解意识的道路上迈进了一大步。

I hope so. I think if we can solve you know, the nuts and bolts Yeah. Of how neural activity is representing what we see, we will be a long ways to understanding consciousness.

对。

Right.

其实我想问你一个问题。

And I want to ask you a question, actually.

现在播客已经超时了，我们可以放松下来，随心所欲地聊。

We're we're late in the podcast now, so we can let our hair down and go wherever you want.

所以我想听听你对这个问题的看法。我们进化是为了生存，对吧？我们的基因根本不在乎我们是否有意识。

So here's my I wanna get your take on this. Okay. Like, we evolved to survive. Right? Our genes don't care at all if we're conscious or not.

这不会影响自然选择，对吧？所以在我看来，它们只关心我们的行为。如果我们像僵尸一样行动，我们的基因传播效果和有意识时完全一样。

Like, that doesn't affect selection. Right? So it seems to me that either so they just care about our behavior. Right? So if we're like a pea zombie, our genes would be propagated exactly the same as if we're conscious.

因此我认为，要么意识是我们极其幸运的巧合——恰好具有我们这种行为模式的大脑同时拥有意识；要么任何能实现我们所有能力、能像我们一样复杂地表征世界（比如识别移动车辆和人并导航）的系统，都可能具有意识。你同意吗？

Therefore, I would argue that either consciousness is like we're just incredibly lucky and it just happened that, you know, brains with our behavior also happen to be conscious. Or any kind of system, any kind of complex system that does what we are capable of doing and represents the world with, you know, as sophisticated way as we can and, you know, can can see moving cars and people and can track them and navigate. Anything that has all of our behaviors is likely going to be conscious. Would you agree with that?

我百分百同意。完全站在你这边。当然也有很多人会反对——我不想量化具体有多少——这就是意识研究中僵尸论证的起源和影响。这个观点被大卫·查默斯推广，其核心理念是：我能想象一个行为与我完全一致但缺乏内在意识体验的存在。

I would agree 100%. Yes, I'm entirely on your side. There are plenty of people, let's just say I don't want to characterize how many, are plenty of people who would disagree, right? I mean, that's the whole origin, the impact of the zombie argument in consciousness studies is people, you know, it was popularized by David Chalmers, it goes back to other people. And the idea is, I can conceive of a being that acts in exactly the same way that I do but doesn't have inner conscious experiences.

这就是我称之为僵尸的概念。如果我能想象出这样的存在，那就意味着无论内在意识体验是什么，它们都不能简化为神经元或体内原子的行为。我们讨论的必定不仅仅是物理行为。我的回应基本上正是你暗示的方向。我会说，不，如果你真的严肃对待僵尸表现得完全像有意识的生物这一观点，包括当我问它'你有意识吗？'时——

That is that is what I label a zombie. And if I can conceive of that, it must follow that whatever inner conscious experiences are, they can't be reduced to the behaviour of the neurons or the atoms or whatever in my body. There must be something other than the physical behaviour that we're talking about. But my response is more or less exactly along the lines of what you were hinting at. I would say, no, you know, if if you really take seriously the idea that the zombie is behaving exactly like a conscious creature would, including when I ask it, are you conscious?

它会回答'有'。当我讲一个悲伤的故事时，它会哭泣，诸如此类的表现，那我们干脆就称其为有意识。对于物理主义者来说，他们认为意识不过是种涌现的高层次描述方式，除此之外并无更多内涵。

It says yes. When I tell it a sad story, it starts crying, like all of those things, then we would just call that conscious. That is that it to a to someone who is a physicalist and does think that, consciousness is sort of an emergent higher level way of talking about things, there's not more to it than that.

是的。好的。很高兴你同意这点。你知道你写过一篇非常有趣的论文，探讨物理学家能否解释为何存在万物而非虚无？我一时想不起...

Yeah. Okay. I'm so glad that you agree. So, you know, you you wrote this very interesting essay about, like, can physicists explain why there's something rather than nothing? I I forget.

你的论文标题是什么来着？

What was the what was the title of your?

标题直白就叫《为何存在万物而非虚无》。

It was literally just why is there something rather than nothing.

对。我特别喜欢这个。我猜——我是否正确理解你的核心观点是他们其实无法解释这个？

Yeah. And I I I love that. And I I mean so and I think the am I correct that your your your message was that they can't? They actually can't explain that.

事实上我要更进一步，用你自己的话说，我认为这甚至不是个可解答的问题。不是我们缺乏解答能力，而是'为何存在万物而非虚无'这类问题本质上就没有答案。不存在某个'为什么'，也不存在某天我们会发现的宇宙存在的理由。

In fact, I would go again, I would be even more radical, in your own words, I would say, it's not even an answerable question. There's it's not, not that we don't have the ability to answer it. But it's the kind of question, why is there something rather than nothing that literally does not have an answer. There is no why, there is no reason that we're going to discover someday why the universe exists rather than doesn't.

好的，那么让我来问你。因为我对意识的理解也大致相同。我认为我们终将发现神经元需要如何配置才能产生意识，这本质上是个科学问题。

Great. So, okay, let me ask you then. So, because I think of consciousness in much the same way. Like, I think that we are gonna discover, you know, exactly how a set of neurons needs to be configured to be conscious or not. Like, that's a scientific question.

嗯。

Mhmm.

但对我来说，意识本身似乎是某种被赋予的东西。这个观点你是否有共鸣？

But to me, it seems like consciousness itself is is something given. Is is does that resonate at all with you?

我们需要先探讨你说的'被赋予'具体指什么。但对我来说，这确实是一种描述大脑内部活动及其宏观行为表现的方式。

Well, I we're we're gonna have to interrogate what you mean by the word given, but to me, it is certainly a way of talking about what is going on both in our brains and then in our macroscopic behavior. Right? I mean

就像物质存在一样，你必须承认某些复杂系统具有意识。不能追问'为什么会有意识'，意识存在这个事实——主观体验和客观体验一样都是必须接受的基本事实。你可以研究如何转化和创造不同类型，这些都是科学问题，但主观体验存在本身是必须接受的。

that it's something like the existence of matter. You just have to accept that certain complex systems are conscious. You can't ask why is it conscious. The fact that it's conscious, subjective experience as much something you have to accept as objective experience. And you can ask how you can transform it and create different types and all of that is scientific questions, the fact that subjective experience exists is like something you have to accept.

我不确定。这个观点我需要再思考。虽然很有趣，但和我本能想到的不完全一致。如果我是从未听说过意识概念的'火星人类学家'（如奥利弗·萨克斯设想的那样），通过观察人类行为会发现：他们有时对某些事物有觉察，有时则没有。

I don't know. That's I will have to think about that one. I think it's an interesting perspective. It's not exactly what I would have said automatically. What I would have said is, you know, if I had never heard of the idea of consciousness, but I was, you know, an anthropologist from Mars, as, Oliver Sacks once imagined, and I came down, I interacted with human beings, I would notice that they are they seem to react and behave in ways that indicate they are aware of different things sometimes, unaware of things other times.

我会用'心理状态'这个概念来解释他们的行为。因此即使不了解意识，我们也会发明出'意识状态和行为'这个概念。这是对我们称为'人类'的这种精妙涌现现象的有效描述。

They have what I would label as mental states that help me explain their behavior and things like that. So, I think we would have invented the idea of conscious states and behaviors even if we didn't know about it. I think that it's a useful description of this this incredibly elaborate emergent thing we call a human being.

关于这个再多说一些。

More about that.

我确实写过一篇论文，原以为会成为你们引用的那篇，题为《意识与物理定律》。但说实话，对于这类话题，我总强调自己其实对意识一无所知。我唯一能确定的是，我们无需为了描述意识而发明新的物理定律——因为我们对物理定律的理解远比对意识的理解要深入得多。本末倒置地认为应该修改物理定律来帮助理解意识，这种想法非常非常荒谬。

Did write a paper that I thought is gonna be the one you're going to reference called consciousness and the laws of physics. But really, what I always say about these things is I don't know anything about consciousness. All I know is you don't need to invent new laws of physics to describe it, because we understand the laws of physics much better than we understand consciousness. It's very, very cart leading the horse to think that we should change the laws of physics to help understand consciousness.

哦，这很有趣。好的。因为...这是我最后想问你的问题。对我来说，意识真正神秘之处在于：作为物理学家、化学家和生物学家，我们都在不同层次上解释这些系统，对吧？

Oh, that's interesting. Okay. Because I I this is the last question I wanted to ask you. To me, something really mysterious about consciousness is that, like, as a physicist and chemists and biologists, we explain these systems at different levels. Right?

比如你在最基础的层面解释，我们在光感受器、视觉皮层等层面解释。但我们认为这只是不同层级的解释——所有解释都是自洽的，你可以在你的层级上预测系统的所有行为。

Like, you explain it at this very fundamental level, we explain at the level of there's photoreceptors and visual cortex and stuff. And, but there and but we think that there's just different levels of explanation. Everything is consistent and, you know, you can explain everything. Mhmm. You you can predict everything about the system, like, at your level.

然后就会发现用更简化的方式就能解释。

And then it's just like more it's just more simple to explain.

在更高层级上粒度更细。

More grained at a higher level.

在更高层级上粒度更粗。但在我看来，我们具有意识这个事实本身就在反驳我们——我们能够意识到红色和周围物体，这似乎暗示着物理系统存在一个正确的解释层级。你不能只把它看作随机碰撞的原子，而必须在那个产生意识知觉的层级上思考。

More coarse grained at a higher level. But, and it to me like there's a the fact that we're conscious speaks against us. It's the the fact that we're conscious of red and the objects around us, that seems to suggest that there is a correct level of interpretation of a physical system. You can't just think of it as random atoms bopping around. You have to think of it at that level where your conscious percept exists.

是这样吗

Does that

呃，说实话我不确定。不，我认为这两个层面都非常合理，它们各自独立存在。如果我是拉普拉斯的恶魔，拥有这种神奇能力能理解我体内每个原子、电子和光子的完整状态，那么我想我可以成功预测我的身体接下来会做什么，或者在一段时间内的行为，而完全不需要使用'意识'这样的词汇，同样也不需要'熵'、'温度'或其他更高层次的术语。我只谈论原子及其行为。

Well, make I don't know. No, so I would think, I would suggest that both levels are perfectly good and they stand on their own feet independently. So if I were Laplace's demon, if had this magical ability to understand the complete state of every atom and electron photon in my body, then I think I could successfully predict what my body was going to do next or over, you know, some period of time without ever using words like consciousness or or for that matter, words like entropy or temperature or any of those other higher level words. I would only talk about the atoms and what they're doing.

是的。但你无法解释内在意识。对吧？因为你是...你懂我意思吧？

Yeah. But you couldn't explain the internal consciousness. Right? Because you're you're you know what I mean?

我...也许我明白你的意思，也许不明白。我是说，我能仅通过列出桌子的所有原子及其相互作用来解释桌子是什么吗？我是说...

I well, I maybe I know what you mean. Maybe I don't. I mean, can I explain what a table is just by listing all of its atoms and how they're interacting with each other? I mean, I

可以，你能解释。但问题是，当涉及大脑时，不仅仅是大脑本身，你还有这种意识体验，它似乎存在于特定层面。

Yes, you can. Okay. Can't explain, like but but there's this like, the table's not when when when it comes to the brain, it's not not just the brain, like you have this conscious experience and that seems to exist at a specific level.

对，所以我的观点是意识就像桌子一样。它是对那个层面现象有用的集体描述方式，但这个层面完全兼容另一种描述——在那里我根本不用这些词汇也能完整描述。我一向乐于被说服改变观点。让我换个说法，或许这与'为何存在万物而非虚无'的问题相呼应。意识的难题被认为超越大脑的物理行为，对吧？

Right, so my view is that consciousness is just like the table. It is a useful, collective way of describing what happens at that level, but that level is completely compatible with saying there's another level where I don't use those words at all and still have a complete description. I'm as always happy to be talked out of these things. So let me put it in yet another way and maybe this is vibing with the question about why is there something rather than nothing. The hard problem of consciousness is supposed to be over and above the physical behavior of the brain, right?

我是说，热衷意识难题的人的核心观点在于：即使我知道关于神经元运作、互动及驱动身体的一切知识，仍然无法解释作为蝙蝠、人类或其他存在的主观体验是什么感觉。而我的态度是，就像'为何存在万物而非虚无'这个问题一样，我们不会解决这个难题——随着我们对神经元及其行为的理解越来越深入，这个问题会自然消解。我们会说：其实没有额外的东西，当这些神经元以特定方式活动时，我们就称之为'大脑正在体验红色的感觉'。

I mean, the whole point of people who love the hard problem, why, you know, how do we explain what it is like to be something to have this inner first person subjective experience is that they would claim that I could know everything there is to know about what the neurons do, how they interact, how they push the body around, and still I have not accounted for what it is like to be a bat or a human being or whatever. And my attitude is that just like the why is there something rather nothing question, we're not going to solve that problem. It's just going to dissolve away as we understand better and better what the neurons are and what they're doing. We will say, well, there isn't anything extra. It's just that when these neurons are doing this kind of thing, we call that the brain is experiencing the redness of red.

我完全同意这一点。我认为随着人工智能的成熟并获得意识，我们将能够创造这些新的感受质，并真正发现支配这种关系的规律。正如你所说，这一切终将彻底消融，我们会看到意识其实是复杂系统的基本属性。是的。

I agree completely with that. And I think that as AI matures and becomes conscious, we'll be able to create these new qualia, and we'll really discover the laws that govern this relationship. And like you say, it's gonna completely dissolve away, and we'll see that consciousness is this is this basic property of complex systems. Yeah.

既然如此，我想不出比你刚才那句话更完美的结束语了。我原本就期待这次对话会非常有趣，但实际交流的精彩程度远超我的预期。多丽丝·萨尔，非常感谢你参加《Winescape播客》。

In that case, I cannot possibly think of a better closing line than that one that you just gave. So this was I expected this to be super interesting. This is even way more interesting conversation than I hoped it would be. Doris Sal, thanks so much for being on the Winescape Podcast.

这次谈话太愉快了。谢谢你，肖恩。

That was so much fun. Thank you, Sean.