Huberman Lab - 多巴胺与血清素如何影响决策、动机与学习 | 里德·蒙塔古博士 封面

多巴胺与血清素如何影响决策、动机与学习 | 里德·蒙塔古博士

How Dopamine & Serotonin Shape Decisions, Motivation & Learning | Dr. Read Montague

本集简介

里德·蒙塔古博士是弗吉尼亚理工大学弗拉林生物医学研究所人类神经科学研究中心教授兼主任,专精于多巴胺与血清素如何塑造人类学习、动机及决策机制的研究。本期我们探讨了这些神经递质如何影响人们在各类短期与长期目标下的专注投入,以及SSRI类药物和低耗能高参与度活动如何降低多巴胺的奖赏特性,还有AI算法如何革新我们对大脑的认知。 节目笔记详见 hubermanlab.com 特别鸣谢赞助商 AG1:https://drinkag1.com/huberman David:https://davidprotein.com/huberman Joovv:https://joovv.com/huberman Function:https://functionhealth.com/huberman LMNT:https://drinklmnt.com/huberman 时间轴 (00:00:00) 里德·蒙塔古 (00:02:54) 多巴胺、动机与学习 (00:08:49) 奖赏预测误差与期望值 (00:12:24) 赞助商:David & Joovv (00:14:54) 觅食行为、择偶、预期与结果;人工智能 (00:23:36) 多巴胺、预期、动机;前驱动力;多巴胺"冲击" (00:29:58) 基线多巴胺与波动;帕金森病 (00:34:36) 运动行为、紧迫感;ADHD、蜜蜂舞蹈、探索模式vs专注模式 (00:42:29) 赞助商:AG1 (00:43:40) 社交媒体、ADHD;探索者vs任务导向者、对抗行为 (00:50:54) 努力与学习;社交媒体与手机、行为抵制 (01:01:36) 血清素与多巴胺的拮抗作用、SSRIs药物 (01:11:21) 饥饿感与多巴胺;负反馈、学习、创伤;折磨实验 (01:18:34) 成瘾药物与高多巴胺状态 (01:19:48) 赞助商:Function (01:21:35) 创伤与多巴胺适应 (01:27:34) SSRIs药物、多巴胺、积极体验 (01:29:50) 深部脑刺激;人类多巴胺与血清素测量 (01:36:16) 睡眠;离婚;科学是项接触运动 (01:45:14) 长期动机、学习失败之道;工具:儿童与运动 (01:54:14) 赞助商:LMNT (01:55:34) 冥想、呼吸、学习;多巴胺作为通用货币 (02:04:38) 睡眠功能与动机;时间感知与多巴胺、时间追踪 (02:13:18) 大语言模型、AI应用与问题解决 (02:18:33) 未来项目、商业化脑机接口;专注力 (02:25:57) 多巴胺"冲击"?;抑郁症与精神分裂症;戒断行为 (02:30:17) 对多巴胺与血清素的误解;内在满足感;动机机制 (02:35:58) 血清素综合征;致谢 (02:38:31) 零成本支持方式、YouTube/Spotify/Apple订阅、评价反馈、赞助商、实验手册、社交媒体、神经网络通讯 免责声明 了解更多广告选择,请访问 megaphone.fm/adchoices

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如果你实现的任何一个目标——无论是什么,服用药物、吃某种食物、找到伴侣等等——如果那一刻已经足够让你满足,你就不会继续活下去。

If any goal that you achieved, whatever it is, taking a drug, eating a food, getting a partner or whatnot, if that was enough for you right then, you wouldn't keep living.

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你希望这个系统能持续追踪下去。

You want that system to keep tracking.

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一旦它到达某个地方,你就希望它还能有另一个目标可以追求。

And once it gets to one place, you want it to have another place to which it could go.

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否则,你就不会继续活着。

Otherwise, you wouldn't live.

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欢迎来到

Welcome to

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Huberman 实验室播客,在这里我们讨论科学以及基于科学的日常生活的工具。

the Huberman Lab Podcast, where we discuss science and science based tools for everyday everyday life.

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我是安德鲁·休伯曼,斯坦福大学医学院神经生物学和眼科学教授。

I'm Andrew Huberman, and I'm a professor of neurobiology and ophthalmology at Stanford School of Medicine.

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今天的嘉宾是医生。

My guest today is Doctor.

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雷德·蒙塔古。

Reid Montague.

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博士。

Doctor.

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雷德·蒙塔古是弗吉尼亚理工学院人类神经科学研究中心主任。

Reid Montague is the director of the Center for Human Neuroscience Research at Virginia Tech.

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他还是动机、决策与学习科学领域的专家,并且是率先开发出实时直接测量人类多巴胺及其他神经调质水平方法的先驱。

He is also an expert in the science of motivation, decision making, and learning, and a pioneer in developing methods to directly measure levels of dopamine and other neuromodulators in humans in real time.

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今天,你将了解多巴胺的真实作用机制——不仅仅是为了调节你的动机水平(这一点我们都听过),更是为了教你东西。

Today, you'll learn how dopamine really works, not just to regulate your levels of motivation, we've all heard that before, but also to teach you things.

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多巴胺不仅涉及学习,也涉及坚持或缺乏坚持。

Dopamine is involved in learning as well as persistence or lack of persistence.

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正如雷德将向你解释的,我们所听到和了解的关于多巴胺的大多数观点,都基于这样一个理念:多巴胺水平会根据我们的预期及其结果而上升或下降。

As Reid will teach you, most of what we hear and know about dopamine is based on the idea that dopamine levels go up or down depending on our levels of expectations and then what happens.

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但他指出,生活、工作、学习、人际关系,以及我们对金钱的追求等,通常都涉及多个里程碑。

But as he explains most aspects of life, work, school, relationships, our pursuit of money, etcetera, involve multiple milestones.

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我们工作,我们等待,然后得到一个结果,这个结果又会影响我们接下来的行为。

We work, we wait, then we get an outcome that in turn informs the thing we do next.

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或者,多巴胺可能在毫无努力的情况下突然出现。

Or maybe dopamine arrives suddenly with no work involved at all.

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换句话说,多巴胺水平一直在变化,这不仅塑造了你当下的行为,还影响了你对近期过去的思考以及你接下来的行动。

In other words, dopamine levels are constantly changing and that shapes not just what you do now, but how you think about your recent past and what you will do next.

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因此,当我们说多巴胺参与学习时,今天你会意识到,多巴胺正在教你如何调整自己的行为。

So when we say dopamine is involved in learning, today you are going to realize that dopamine is teaching you how to adjust your behavior.

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我们当然会讨论如何利用这些知识来提升动机和决策能力,甚至改善社交互动。

We of course discuss how this knowledge can be leveraged for better motivation and decision making, even better social interactions.

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我们还会讨论血清素,以及多巴胺和血清素如何像跷跷板一样相互作用,特别是血清素如何教你应对不理想的结果。

And we also discuss serotonin and how dopamine and serotonin work in sort of seesaw fashion and how serotonin in particular teaches you about unwanted outcomes.

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我们还会讨论你可能会觉得非常有趣的SSRI类药物。

We also have a discussion about SSRIs that you're going to find fascinating.

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正如里德指出的,SSRI类药物会提高血清素水平,但这些血清素常常在多巴胺突触处发挥作用,降低多巴胺的奖赏效应。

As Reid points out SSRIs increase levels of serotonin, but often that serotonin gets used at the dopamine synapses to reduce the rewarding properties of dopamine.

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所以今天关于多巴胺和血清素的讨论,将与你们 elsewhere 听过或读过的任何内容大不相同。

So today's discussion about dopamine and serotonin is going to be vastly different than any that you've heard or read about elsewhere.

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你们将了解这些神经调质是如何运作的,以及它们如何影响你们的日常生活和决策。

You're going to learn how those neuromodulators work, and you're going to learn how they impact your everyday life and decision making.

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正如我们都知道的,如今关于多巴胺和血清素的讨论无处不在。

As we all know, discussions about dopamine and serotonin are everywhere nowadays.

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但在今天的节目中,你们将从该领域的顶尖专家那里了解这些分子真正的作用。

But in today's episode, you're going to learn from a top expert in the field what these molecules truly do.

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这将帮助你们更好地利用自己的努力,引入我们所说的‘刻意延迟’,以及如何利用人工智能等工具来提升你们的动机水平和通过神经可塑性学习的能力。

And that's going to help you better leverage your efforts, introduce what we call deliberate delays, and how to use tools like AI to improve your levels of motivation and your ability to learn through neuroplasticity.

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在开始之前,我想强调,这个播客与我在斯坦福大学的教学和研究工作是独立的。

Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research roles at Stanford.

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但它确实是我致力于向公众免费提供科学及科学相关工具信息的一部分。

It is however, part of my desire and effort to bring zero cost to consumer information about science and science related tools to the general public.

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秉承这一宗旨,今天的节目包含了一些赞助商内容。

In keeping with that theme, today's episode does include sponsors.

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现在,让我们开始与博士的对话。

And now for my discussion with Doctor.

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里德·蒙塔古。

Reid Montague.

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博士。

Doctor.

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里德·蒙塔古,十五年不见,很高兴见到你。

Reid Montague, great to see you after all these fifteen years.

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十五年。

Fifteen years.

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你当初拒绝了我们的

You turned us down for a

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工作邀请。

job offer then.

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我确实拒绝了,但我们都过得不错。

I did, but we both turned out okay.

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嗯,我希望如此。

Well, I hope so.

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我们走着瞧吧。

We'll see.

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你确实过得很好,而且看起来状态很棒。

Well, you certainly turned out okay And you look great.

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看到一位同事如此健康有活力,还成功养育了五个孩子,这总是令人欣喜的事。

It's always great to see a colleague looking so fit and healthy who also raised five children successfully and all those things.

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我们稍后可以聊聊你的生活,也许还有你的运动生涯,但我想先谈谈多巴胺。

We'll talk a little bit about your life and maybe your athletic life a little bit later, but I want to talk about dopamine.

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现在全世界都对多巴胺着迷。

The world is obsessed with dopamine now.

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直到最近,人们还认为多巴胺是一种奖励机制。

Until very recently, people thought about dopamine as a reward.

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现在人们正逐渐开始意识到,多巴胺的作用不仅限于让人感觉良好,还涉及动机、运动等方面。

Now slowly people are starting to understand that dopamine is involved with things other than feeling good, such as motivation, movement, etcetera.

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你如何看待多巴胺这种神经调质?

How do you think about dopamine, the neuromodulator?

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然后我们会转向你研究多巴胺的背景。

And then we'll move into the context in which you study dopamine.

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但当有人问,多巴胺是做什么的?

But when somebody says, what does dopamine do?

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你会怎么思考和回应

How do you think and respond to

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这个问题?

that question?

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过去,人们认为多巴胺等同于愉悦。

Well, it used to be that dopamine was thought to equal pleasure.

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多巴胺升高,你就感觉良好。

Dopamine goes up, you feel good.

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多巴胺降低,你就感觉没那么好。

Dopamine goes down, you feel less good.

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好的。

Okay.

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关于它的研究已经大量涌现。

There's been an explosion of work on it.

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大多数非心理学领域的新研究都来自人工智能领域,也就是现在所说的人工智能。

Most of the new work that's not psychological has been out of the artificial intelligence world, what's now called artificial intelligence.

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首先,它明确是一个学习信号。

It's very clearly a learning signal, number one.

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因此,多巴胺的高低波动控制着学习过程。

So dopamine fluctuations, high and low, control learning.

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它还扮演着多种角色。

It's also playing multiple roles.

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它在动机中起作用,也可能影响你的感受。

It plays a role in motivation and it may also play a role in the way you feel.

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多巴胺如何通过改变你的神经系统来影响你的感受状态,其机制尚不十分清楚。

It's less well understood how the sort of mechanics of what dopamine does for changing your nervous system relates to your feeling state.

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你可能会有良好的情绪状态,但看到的事情并不一定与多巴胺有关。

You can have a feeling state that's good and see things that don't correlate with dopamine being the cause of it.

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让我们谈谈多巴胺在学习中的作用,因为我认为大多数人不会把学习和多巴胺联系起来。

Let's talk about dopamine in the context of learning, because that's something that I think most people don't associate with dopamine.

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关于多巴胺在学习中的作用,我们已知的几个例子有哪些?

What are a few examples of what we know about dopamine and its role in learning?

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这个领域我根本没法简单地概括出来。

That's a world I can't even summarize in a quick way.

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现在研究啮齿类动物的人会使用基因改造的老鼠,研究多巴胺释放与动物学习行为之间的关联。

People that work on rodents now will take a genetically modified rodent and they will study the way in which dopamine release correlates with something the animal is learning.

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动物可能会学会在看到灯光时向左转。

The animal may learn to turn left when it sees a light.

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它可能会学会朝食物跑去。

It may learn to run toward food.

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它可能会学会跑出迷宫。

It may learn to run down a maze.

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所有与动物相关的学习任务都与你大脑中多巴胺的波动有关。

All kinds of learning tasks associated with the animal are associated with dopamine fluctuations in your brain.

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这些波动并非全局性的,而是遍布大脑各处,但在大脑的不同区域可以观察到不同类型的信号。

Now these aren't global, they're all over the place, but there are different kinds of signals that you can find in different spots in your brain.

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我们已经开始将多巴胺理解为大脑运行算法的核心参与者。

And we've begun to understand dopamine as a central player in the algorithms that your brain runs.

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这就是像我这样的人——计算神经科学家——所建立的联系。

And that's where people like me and people like me, computational neuroscientists, have made a connection.

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这种联系在于你大脑中以及地球上所有移动生物大脑中所内置的学习规则和学习机制,与多巴胺波动之间的关联。

And that's the connection between the kinds of learning rules and learning procedures that are installed in your brain and installed in the brain of every mobile creature on the planet and dopamine fluctuations.

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这种紧密的联系在过去三十年中已被逐步阐明。

So that's a strong connection that has been worked out over the last thirty years.

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这些算法本身已经得到了充分理解。

The algorithms are well understood.

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三十年前尚未被充分理解的是,这些相同算法所能学习的惊人能力。

What wasn't well understood thirty years ago was the kind of remarkable things those same algorithms can learn.

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我稍后再回到这一点。

I'll come back to that.

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我的意思是,强化学习领域近年来出现了一系列重大突破。

I mean, there've been a bunch of modern breakthroughs in what's called reinforcement learning.

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而强化学习最主要的生物学关联就是多巴胺。

And reinforcement learning's main biology partner is dopamine.

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这是第一次重大突破。

It's the first big hit.

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现在,这已经是一个科学领域了。

Now, it's an area of science.

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那么,当你有一个看似能解释很多现象的重大发现时,人们会蜂拥而至试图挑战它,会发生什么?

And so what happens when you have a big finding that looks like it explains a lot of things when people come rushing in to sort of beat it up?

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这就是他们的工作。

That's their job.

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他们的工作就是不断质疑和拆解。

That's their job to hack away.

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哦,真的是这样吗?

Oh, is it really this?

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它在这种情况和那种情况下作用方式一样吗?

Does it work the same in this context and that context?

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但我认为关于多巴胺作为学习规则的描述基本上是正确的。

But I think the description of what dopamine does as a learning rule is pretty much true.

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让我给你举个例子。

Let me give you an example.

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自巴甫洛夫时代以来,心理学家就理解了动物如何生成预测并与结果进行比较的意义。

So psychologists since the time of Pavlov have understood what it means for an animal to generate a prediction and to compare it to an outcome.

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明白吗?

Okay?

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例子是,今天是星期三。

The example is so today's Wednesday.

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假设这是里奇·萨顿的例子。

Suppose and this is Rich Sutton's example.

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假设我今天预测周六会下两英寸的雨。

Suppose I make a prediction today that it's going to rain two inches on Saturday.

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明白吗?

Okay?

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现在我们快进到明天,我会根据新获得的信息更新我的预测。

Now we're going to fast forward to tomorrow, and I'm going to update my prediction because I have new knowledge.

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我会说周六会下十英寸的雨。

And it's going say I'm going rain 10 inches on Saturday.

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明白吗?

Okay?

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还没有任何强化反馈。

There's been no reinforcing feedback.

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还没下雨,因为周六还没到。

It hasn't rained yet because now Saturday yet.

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我正在对周六做出预测。

I'm making a prediction about Saturday.

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但这种预期和那种预期之间存在差异。

But there's a difference between this expectation and that expectation.

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这些差异是由多巴胺编码的。

Those differences are encoded by dopamine.

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这被称为时间差误差。

That's called a temporal difference error.

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多巴胺似乎就是编码这种误差的。

And dopamine seems to code that.

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在你到达最终回报之前,想象一下你在玩跳棋这样的游戏。

Before you ever get to the terminal return, imagine that you were playing a game like checkers.

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你在游戏中走一步,可能要走大约40步才能赢得比赛。

You make a move in the game, and you might make, I don't know, 40 moves before you win the game.

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假设赢得比赛就是奖励。

And suppose winning the game is the reward.

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那么你可能会有一些预期。

Well, you may have some prediction.

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当你从一个棋盘局面移动到另一个局面时,你的大脑会预测你将赢得比赛,而这是一个波动的量。

Your brain makes a prediction when you play board position to board position that you're going to win the game, and that's a fluctuating quantity.

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这是一种不同的学习规则。

That's a different kind of learning rule.

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心理学家所谈论、你在日常生活中会想到的学习规则是:今天会下两英寸的雨。

The kind of learning rule that psychologists talk about that you think about in your everyday life is it's going to rain two inches today.

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好的。

Okay.

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下了多少雨?

How much did it rain?

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好的。

Okay.

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所以这是结果与你的预期之间的比较。

So that's a comparison between an outcome and your expectation.

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里奇·萨顿和安迪·巴托所做的就是说,你真正想做的是在两者之间保持联系,也就是你的下一个预测。

What Rich Sutton and Andy Bartow did was said, well, what you really want to do is you want to stick between there, your next prediction.

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所以你需要一系列连续的预测。

So you want successive predictions.

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为什么这对动物来说是一个好的模型?

And why is that a good model for animals?

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因为如果你是动物,在四处觅食时,大多数时候你都找不到任何东西。

Well, because if you're an animal and you're wandering around foraging, mainly you're not finding anything.

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你从一个位置移动到另一个位置,再移动到下一个位置,但你一直在学习。

You're going from position to position to position to position, but you're learning.

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多巴胺编码了这些信号。

And dopamine is encoding those signals.

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我很高兴你提到了‘觅食’这个词,因为我想就觅食在人类决策、学习和行为中的意义展开讨论。

I'm so glad you said the word foraging because I want to hover on the theme of foraging in the context of human decision making and learning and behavior.

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所以,继续你的描述,星期六到了。

So to stay with your description, Saturday rolls around.

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假设那天没下雨。

Let's say it doesn't rain.

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假设这个人不希望下雨。

Let's say the person doesn't want it to rain.

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他不是农民。

They're not a farmer.

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他想在周六去海滩。

They wanna go to the beach on Saturday.

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现在我们可以谈谈奖励预测误差了,对吧?

Now we can talk about reward prediction error, right?

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期望与实际结果之间的差异。

The difference between the expectation and what it actually has.

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好的,我稍微纠正一下。

Okay, interrupt and correct that a bit.

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人们所说的多巴胺所代表的奖励预测误差,是指你在每一步中产生的预测误差,无论你是否获得了奖励。

The reward prediction error that people talk about dopamine representing is the prediction error that you get for every single step whether or not you've received reward.

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在心理学文献中,这种误差被泛化为:你有一个期望,然后你获得了一个奖励。

That's kind of diffused out in the psychology literature as you have an expectation and you have a reward.

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它可能是正的、负的,或者为零。

It may be positive, negative, or zero.

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而你所做的就是在这里产生一个误差。

And what you do is you make an error there.

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这一点在20世纪60年代和70年代就已经被理解了。

That was understood in the '60s and '70s.

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这被称为斯科洛夫-瓦格纳规则,1972年。

It's called the Scorlow Wagner rule, 1972.

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这就是系统应该学习的方式。

That's how the system should learn.

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但事实上,这并不能很好地模拟现实。

The fact is, though, that doesn't model reality very well.

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现实并不会每次都像那样给你反馈。

Reality doesn't give you feedback like that every time.

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现实常常会给你很长一段时间的空白。

Reality often gives you long stretches of nothing.

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萨顿和巴托在他们的算法中的洞见是,一种更好的持续学习算法是采用连续的预测,并将其视为一种学习规则。

The insight, think, of Sutton and Bartow in their algorithm was, well, a better algorithm for learning continuously is to take successive predictions and to say that's a learning rule.

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显然,这是一种在获得结果时的学习规则,当结果不为零时,但它本质上是连续的预测。

Obviously, it's a learning rule with the outcome when you get an outcome, when it's not zero, but it's successive predictions.

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为什么这会是一个如此深刻的想法,对我来说并不清楚。

It's like why that should be such a deep idea is not clear to me.

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从数据来看,我清楚的是,基于这一原理的算法存在于B类大脑、C类蛞蝓大脑,一直到人类大脑中。

What is clear to me from data is an algorithm based on that is installed in B brains, C slug brains, all the way up to human brains.

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这些就是时间差奖励预测误差。

There are these temporal difference reward prediction errors.

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因此,我坐在这里试图回溯它的旧版本,人们通常用通俗的说法说:哦,这是你的期望与奖励之间的差异。

And so I guess I'm sitting here trying to backwash the old version of it, which is people say in a kind of vernacular way, oh, it's the difference between your expectations and reward.

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是的,当这种情况发生时。

Yes, when that happens.

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但大多数时候,这种情况并不会发生,此时,它实际上是你的期望与下一个期望之间的持续差异。

But most of the time, that's not happening, In which case, it's the it's the ongoing difference between your expectation and your next expectation.

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所以,这是你在探索世界过程中期望值的波动。

So it's fluctuations in your expectation as you move through the world.

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伦敦的DeepMind团队击败了世界围棋冠军,开发了AlphaFold,并获得了诺贝尔奖,他们从2015年开始就一路高歌猛进。

The DeepMind guys in London who beat the world Go playing champion and made AlphaFold and won Nobel Prizes, and I mean, they're starting in 2015.

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他们接连取得了令人难以置信的突破。

They just had this unbelievable series of hits.

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他们使用了萨顿和巴托的算法。

They used the Sutton and Bartow algorithm.

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他们训练这些系统时,让计算机玩家在游戏结束前进行数百次棋盘位置的调整,并据此不断更新和学习。

They trained those systems where people would make the players, computer players, would make hundreds of board position changes before you ever got to the end of the game and update and learn based on that.

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他们还加入了许多其他技巧。

They're they threw other tricks into.

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我就不深入技术细节了。

I'm not gonna get technical about it.

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所以这里存在一个差异。

So there's a difference.

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这不仅仅是期望与结果的问题。

It's not just expectation and outcome.

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这是期望、下一个期望、当前结果。

It's expectation, next expectation, current outcome.

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是的。

Mhmm.

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这就是不断延续的东西。

And that is what rolls through.

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而这就是我们在本周即将发表的关于蜜蜂大脑的论文中所看到的,你可以在蜜蜂大脑中观察到类似的学习机制。

And that is what we see installed in we have a paper this week coming out on honeybee brains where you can show the same sorts of learning rules in honeybee brains.

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在蜜蜂大脑中,可能是章胺,而不是多巴胺。

In honeybee brains, it's probably octopamine, not dopamine.

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但关于多巴胺,还有一点要说:它并不仅仅是多巴胺。

But the other thing to say about dopamine is it's not just dopamine.

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很明显,许多类似的神经调质都会随着学习和动机而波动,可能正是整个调质交响乐共同创造了动机状态之类的现象。

It's very clear that lots of neuromodulators like that are fluctuating with learning and motivation and probably the whole symphony of them that creates motivation states and things like that.

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我想短暂休息一下,感谢我们的赞助商大卫。

I'd like to take a quick break to acknowledge one of our sponsors, David.

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大卫生产的蛋白棒与众不同。

David makes protein bars unlike any other.

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他们最新推出的青铜蛋白棒含有20克蛋白质,仅150卡路里,且不含糖。

Their newest bar, the bronze bar has 20 grams of protein, only 150 calories and zero grams of sugar.

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我必须说,这是我吃过最好吃的蛋白棒。

I have to say these are the best tasting protein bars I've ever had.

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多年来我尝试过很多种蛋白棒。

And I've tried a lot of protein bars over the years.

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这些新的大卫蛋白棒以棉花糖为基底,外层覆盖巧克力涂层,简直不可思议。

These new David bars have a marshmallow base and they're covered in chocolate coating and they're absolutely incredible.

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当然,我平时吃的是天然全食物。

I of course eat regular whole foods.

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我吃肉、鸡肉、鱼、鸡蛋、水果、蔬菜等等。

I eat meat, chicken, fish, eggs, fruits, vegetables, etcetera.

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但我每天还会特意吃一两根David蛋白棒当零食,这样很容易就能达到我每磅体重摄入一克蛋白质的目标。

But I also make it a point to eat one or two David bars per day as a snack, which makes it easy to hit my protein goal of one gram of protein per pound of body weight.

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这让我能在不摄入多余热量的情况下,获得所需的蛋白质。

And that allows me to take in the protein I need without consuming excess calories.

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我非常喜欢所有David青铜蛋白棒的口味,包括曲奇面团、焦糖巧克力、双层巧克力和花生酱巧克力。

I love all the David Bronze bar flavors, including cookie dough, caramel chocolate, double chocolate, peanut butter chocolate.

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它们吃起来真的像糖果棒一样。

They all actually taste like candy bars.

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再说一遍,它们非常棒,但关键是不含糖,每根只有150卡路里却含有20克蛋白质。

Again, they're amazing, but again, they have no sugar and they have 20 grams of protein with just 150 calories.

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如果你想尝试David产品,可以访问davidprotein.com/huberman。

If you'd like to try David, you can go to davidprotein.com/huberman.

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目前,他们有一个优惠活动:购买四盒,第五盒免费。

Right now, is offering a deal where if you buy four cartons, you get the fifth carton for free.

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你也可以在亚马逊,或者塔吉特、沃尔玛和克罗格等商店找到David产品。

You can also find David on Amazon or in stores such as Target, Walmart, and Kroger.

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再次提醒,要免费获得第五盒,请访问 davidprotein.com/huberman。

Again, to get the fifth carton for free, go to davidprotein.com/huberman.

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今天的节目还由Juve赞助。

Today's episode is also brought to us by Juve.

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Juve生产医用级红光疗法设备。

Juve makes medical grade red light therapy devices.

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如果非要说我在本播客中一贯强调的一件事,那就是光线对我们生理机能的惊人影响。

Now, if there's one thing that I have consistently emphasized on this podcast, it is the incredible impact that light can have on our biology.

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除了阳光之外,红光和近红外光已被证明能对细胞和器官健康产生积极影响,包括加速肌肉恢复、改善皮肤健康和伤口愈合、改善痤疮、减轻疼痛和炎症,甚至提升线粒体功能和改善视力。

Now, in addition to sunlight, red light and near infrared light sources have been shown to have positive effects on improving numerous aspects of cellular and organ health, including faster muscle recovery, improved skin health and wound healing, improvements in acne, reduced pain and inflammation, even mitochondrial function, and improving vision itself.

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Juve灯光的特别之处,也是我首选红光疗法设备的原因,在于它使用了经过临床验证的波长,即结合特定波长的红光和近红外光,以触发最佳的细胞适应反应。

What sets Juve lights apart, and why they're my preferred red light therapy device, is that they use clinically proven wavelengths, meaning specific wavelengths of red light and near infrared light in combination to trigger the optimal cellular adaptations.

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我个人每周使用Juve全身面板三到四次,并且在家和旅行时都会使用Juve手持设备。

Personally, I use the Juve whole body panel about three to four times a week, and I use the Juve handheld light both at home and when I travel.

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如果你想尝试Juve,可以访问 juve 拼写为 joovv.com/huberman。

If you'd like to try Juve, you can go to juve spelledjoovv.com/huberman.

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Juve 为所有 Huberman Lab 的听众提供独家折扣,最高可减免 400 美元。

Juve is offering an exclusive discount to all Huberman Lab listeners with up to 400 off Juve products.

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再次提醒,访问 juve 拼写为 joovv.com/huberman,即可享受最高 400 美元优惠。

Again, that's Juve spelledjoovv.com/huberman to get up to $400 off.

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好的。

Okay.

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我想列出几条规则,帮助大家更好地理解这个过程,因为我认为大多数人——包括我自己——都是通过神经科学教材、讲座和论文接触到多巴胺的,我们被灌输了一种过于简化的模型:期待与奖励或缺乏奖励之间的关系。

So I wanna pin up a few rules so that people can move along this, because I think most people, and including me, who learned about dopamine through neuroscience textbooks and lectures and papers and so forth, have been fed this overly simplistic model of expectation versus reward or lack of reward, expectation outcome.

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为了提醒大家,多巴胺的奖励预测误差机制是这样的:多巴胺系统特别喜欢新奇感,尤其是积极的新奇体验,对吧?

So just to remind people, dopamine reward prediction error, if you, the dopamine system loves novelty, especially positive novelty, right?

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比如,你原本以为某家餐厅的餐食会很棒,结果却出乎意料地惊艳;而另一种情况是,你本来预期一家餐厅会非常棒。

You think you're gonna have a great meal someplace that turns out to be spectacular versus you're really expecting a place to be great.

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你的朋友说那里棒极了。

Your friend says it's terrific.

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但你去之后发现,也就一般般。

And then it's okay.

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多巴胺编码了大量期望与奖励之间的关系。

And dopamine codes for a lot of the expectation reward relationship.

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你告诉我们的是,在大多数情况下,情况比这更复杂。

What you're telling us is that in most scenarios, it's more interesting than that.

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在最终结果出来之前,期望会进行更新,而多巴胺正是在编码这一过程。

There's an updating of expectation before the final answer comes in and dopamine is coding for that.

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我想借用‘觅食’这个词,将其应用到人类的现实场景中。

I'd like to take this word foraging and apply it to a real world scenario in humans.

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然后我们可以结合已知的信息,同时你也告诉我哪些是推测,以便以一种直观的方式描绘出这个画面。

And then maybe we can use a combination of what's known and you'll also tell us where it might be conjecture to kind of paint this picture in an intuitive way for people.

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我有个朋友,她现在正在约会市场上。

I have a friend, and she's on the dating market now.

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她偶尔会给我打电话,问我:‘我该怎么解读这条短信或这次互动?’

She will occasionally call me and ask me, you know, like, how do I decode this text message or this interaction?

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我会尽我所能提供支持。

I try and offer my support where I can.

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但对话通常会是这样:我认识了某某人。

But the conversations often go something like this: Met so and so.

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他们看起来真的很棒。

They seem really great.

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他们看起来很忙,约了一个月后见面。

They seem really busy, and they set a plan for like a month from now.

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这很奇怪吗?

Is that weird?

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你知道的,好吧。

You know, like, all right.

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嗯,我会给出我的解读。

Well, you know, and I give my interpretation.

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我会说,他们定了一个具体的计划,这挺好的,你知道的,对方很忙,等等这些情况。

I say, well, you know, it's nice they've set a concrete plan, you know, this and that, like person's busy, you know, this and that.

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我也听到她说,嘿,我认识了一个真的、真的特别棒的人。

I also hear the, Hey, you know, met someone that really, really terrific.

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我说,嘿,听我说,上次你这么说的时候,过了两周,你就开始想怎么才能不再见这个人了?

And I say, Hey, listen, the last time you said this, like two weeks later, it was, how do I get out of seeing this person again?

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所以慢慢来,慢慢收集信息。

So like go slow, like collect data slowly.

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我不能说我一直是对的,但几乎总是三天后或三周后,你会惊呼:天哪,我该怎么脱身?

And I'm not gonna say I'm always right, but almost inevitably it's three days later or three weeks later, it's like, oh my goodness, how do I get out of this thing?

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对吧?

Right?

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所以某种程度上,这和你说的是一回事,对吧?

So in some sense, it's what you're saying, right?

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人生中,人们都在寻找一种健康的伴侣关系。

There's a forging for a healthy thing in life, a mate.

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这种事自古以来就存在,只是以前没有应用程序。

This has happened since the beginning of time, although not with apps.

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这是根据经验和沟通不断调整期望的过程。

There's updating of expectation based on experience and communication.

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我认为这是一个在调整期望背景下非常美好的例证,因为有人可能会问,最终的回报是什么?

And I think this is a really beautiful example of forging in the context of updating expectations because, one and could argue, what is the final reward?

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是婚姻吗?

Is it marriage?

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还是其他什么?

Is it whatever?

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好吧,这很主观。

Okay, that's subjective.

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但我认为我们都能通过经验或观察直观地理解这个例子。

But I think we all can intuitively understand this example, either by experience or by observation.

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所以对于某个人来说,他们刚认识一个人时非常兴奋,见面后越来越兴奋,但未来走向不明,然后随着时间推移发现,哦,对方并不完美。

So for someone, this person, who gets excited about someone they just met, right, then meets them and is increasingly excited, but it's unclear where it's gonna go, then finds out, as life goes, that, oh, they're not perfect.

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这里有个问题。

There's this thing.

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我能接受这个吗?

Can I live with that?

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所以把这看作是他们系统中多巴胺的锯齿状波动。

So thinking of this as like a sawtooth of dopamine going through their system.

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这种说法准确吗?即多巴胺和其他神经调质在编码对成功或失败的预期,而并不真正知道最终的结果是什么。

Is that statement accurate that dopamine and other neuromodulators are encoding the sort of expectation of success or lack of success without actually knowing what the final endpoint It's

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正是如此。

exactly that.

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这就是萨顿和巴托的洞见。

And that's the insight of Sutton and Bartow.

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当我第一次听到这个理论时,是在我做博士后期间从彼得·丹那里学到的,我们当时一起加入了索尔克研究所。

And when I first heard about this, I learned about it from Peter Dan when I was a postdoc, we both arrived at the Salk Institute together.

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它抓住了我,因为突然间,这不再是简单的,好吧。

Something about it captured me because all of a sudden, it's not this, okay.

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你理解预期和结果。

You understand expectation and outcome.

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我的意思是,企业也明白这一点。

I mean, businesses understand that.

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是的

Yeah.

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你感到失望。

You're disappointed.

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你原本期望季度回报是x,但结果却是y。

You expected to have a quarterly return of x, and you had y.

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这更少。

That's less.

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你原本预期它会很低。

You expected it to be low.

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但它更高了。

It was more.

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但这种情况非常罕见。

That's but that's really rare.

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我努力学习了。

I studied hard.

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我想要一个A。

I wanted an a.

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我得到了一个A-。

I got an a minus.

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是的。

Yeah.

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但现实就体现在这个简单而连续的学习更新规则中,它被称为时间差强化学习,即在世界上,这些期望会沿着自己的轨迹发展。

But the reality is embedded in this little simple continuous learning update rule, it's called temporal difference reinforcement learning, is the fact that in the world, these expectations are going through their own trajectory.

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明白吗?

Alright?

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而多巴胺编码的正是这一点。

And that's what dopamine is coding for.

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任何学习规则都应当对出乎意料的结果进行编码。

Any learning rule should code for the surprising outcome.

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嗯。

Mhmm.

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你对某个结果抱有预期,而这个预期要么偏高,要么偏低。

You you you have an expectation for an outcome, and it either high or low of that.

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每一个学习规则都应当如此。

Every learning rule should do that.

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心理学家早在四十年前、五十年前就已经大致弄明白了这一点。

And the psychologist had that kinda figured out forty years ago, fifty years ago.

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但它并不完全奏效,因为它无法解释动物是如何学习的。

But it doesn't quite work because it won't account for the way animals learn.

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它无法让你将事件串联起来。

It won't let you chain events.

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所以,例如,如果我先展示一盏灯,并通过结果进行训练,再使用这种预期-结果学习规则,它就无法回溯到预测灯的事件。

So for example, if I show a light and train on a reward with an outcome, and I use that expectation outcome learning rule, it won't chain back to something that predicts a light.

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假设一个声音预测了灯光,而我们知道灯光预测了结果。

Suppose a sound predicts a light, and we know the light predicted the outcome.

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那么我现在要问,声音会发生什么变化?

Now I ask the question, well, what happens to the sound?

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我们知道人们会学习。

Well, we know people learn.

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他们会把声音和结果联系起来。

They'll they'll associate the sound with the outcome.

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这是巴甫洛夫式的。

It's Pavlovian.

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是的。

Yep.

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但那些学习规则做不到这一点。

But those learning rules won't do that.

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它们学的是错误的东西。

They learn the wrong thing.

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它们就是会这样。

They just do.

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这一点并没有得到充分重视。

It's just not well appreciated.

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现在,当我们试图将这个学习规则与多巴胺联系起来时,我们主要是在理论层面上研究它。

Now, back when we were trying to associate that learning rule with dopamine, there was we were mainly working on it in kind of theoretical way.

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比如,如果你有一个信号,它应该是什么样子的?

Like if you had a signal, what would it need to look like?

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在生物学中,你可能会在哪里找到它?

Where might you find this in biology?

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我记得我们的导师特里·索诺斯基,他上过你的节目,我想他说过类似这样的话:存在一些弥散性的上行系统。

I remember our advisor, Terry Sonosky, who's been on your show, I think he said something like, There are these diffuse ascending systems.

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它们释放这些神经递质。

They deliver these transmitters.

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你们去研究这个吧。

You guys go work on that.

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听起来是的。

Sounds like Yeah.

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他只是在实验室里。

He just laboratory.

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他只是说,这一集获得了异常热烈的反响。

He just This episode was spectacularly received.

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哦,太好了。

Oh, great.

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我的意思是,那是一个非常开放和包容的环境。

Well, mean, it was the most open, inviting environment.

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但当然,所有被布置出来的问题都根本无法解决。

But of course, all the problems given out were impossible to solve.

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我记得当时就在想:什么?

And I remember just thinking, what?

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但最初的突破在于,我们意识到这与萨顿几年前写下的内容完全吻合。

But the first inroad was realizing that it matched what Sutton had written down not so many years before.

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萨顿获得博士学位,我想是在1984年。

Sutton got his PhD, I think in '84.

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我想他的论文是在1988年发表的。

I think he published the paper in '88.

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我们1990年做这个的时候,遇到了舒尔茨关于多巴胺信号的一组数据。

I was we were doing this in 1990, and we ran into a guy's data on dopamine, signaling both from Schultz.

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我们不认识他。

We didn't know him.

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我们跑过去,能解释他发表的每一篇论文里的每一个图表。

We ran and we could explain every figure in every paper he published.

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我们就想,好吧。

And we just thought, okay.

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这不可能是巧合。

That's not an accident.

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明白了。

Okay.

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快进一下。

Fast forward.

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我们现在已经是第三代了。

We're in generation three.

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现在我们要一路推进到现在。

Now we're gonna come all the way forward.

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人们正在对啮齿类动物进行非常精细、非常详细的实验,可以精确控制多巴胺神经元在何处、何时放电。

People doing very fancy, very detailed experiments in rodents where you can control where dopamine neurons are going to fire, when they're going to fire.

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你可以控制奖励。

You can control reward.

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好吧,你可以控制很多事情。

Okay, you can just control a lot of things.

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所以这显然不仅仅是这些。

And so it's clearly more than that.

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是这些,再加上一些其他的东西,但核心部分就在这里。

It's that and some other stuff, but that central core.

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我看不出有任何充分的理由要抛弃这个简单的解释。

I I I don't see any good reason to throw away that little explanation there.

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早在1990年,人们的意见是:这确实很酷。

Back in 1990, the complaint was, well, that's really cool.

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它与一篇晦涩的《生理学杂志》论文中的轨迹相吻合。

It matches these traces in an arcane Journal of Physiology paper.

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那有什么用呢?

What good is that?

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像这样的强化学习无法学到任何东西。

Reinforcement learning like that can't learn anything.

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当时的问题是,这个说法是正确的。

The problem with that was, at the time, it was right.

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因为那时还没有任何系统取得过惊人的成果。

Like there were no systems that had done anything amazing.

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现在它们已经做到了一切。

Now they've done everything.

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它的表现好得令人难以置信。

And it's insane how good it was.

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你是在说人工智能。

You're talking about the AI.

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我刚刚用手比划的那个算法,和大卫·席尔瓦以及DeepMind团队在开发世界冠军级围棋程序时使用的是同一个,它击败了世界冠军。

That algorithm that I just described with my hands waving is the same thing that David Silver and the DeepMind guys did when they made the world champion go playing program, and it beat the world champion.

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而那个特定的游戏内置了专家建议。

And that particular game had expert advice built into it.

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明白吗?

Okay?

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但他们把所有这些都移除了。

And they removed all that.

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然后从零开始训练它。

And then they trained it from scratch.

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它被称为AlphaGo Zero。

It's called AlphaGo Zero.

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然后那个游戏的表现简直惊人。

And then that game was was amazing.

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这个项目从未被击败过。

This item has never been beaten.

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它基本上超越了围棋的历史。

It basically beats the history of Go.

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因此,举个例子,这太惊人了,是一次突破。

And so the as an example, it's such an amazing that's a breakthrough.

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任何了解这一面的人。

Anybody that knows that side.

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现在这是人工智能的一面。

Now that's the AI side.

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这就是人工智能。

That's the AI.

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但同样的算法也存在于你的大脑中。

But that same algorithm is installed in your head.

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它也存在于鸣禽的大脑中。

It's installed in the head of a songbird.

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现在正在发生的是这种趋同现象。

The interesting thing that's going on now is this kind of convergence.

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对吧?

Right?

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你的脑干里有这些小精灵在运行这个算法。

There are these there are these little gremlins in your brainstem that run that algorithm.

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明白吗?

Okay?

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现在这些算法已经被外部化,放入了计算机程序中,能够完成超越我们的任务。

They've now been externalized and put into a computer program that now does things that supersede us.

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这是一种有点有趣的融合。

It's a little interesting convergence.

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这是我所知道的唯一一种从你大脑中爬出来、进入程序的东西,而现在这个程序正在做我们以前无法想象的事情。

It's the only thing I know of that's sort of crawled out of your mind into a program, and now the program is doing things that we couldn't imagine before.

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而且这与生物学相吻合。

And it matches the biology.

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我的意思是,你可以在像蜜蜂和果蝇这样古老的生物身上看到这一点。

I mean, you can see this in creatures as old as honeybees and Drosophila and whatnot.

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好的。

Okay.

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所以有几件事,一个评论和几个问题。

So a couple of things, one comment and a couple questions.

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首先,我要说一下,这样你就不必觉得非得这么做。

First comment, I'm just going to say so that you don't feel you have to.

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每个人都知道,当里德说多巴胺负责X、Y和Z时,大脑中很可能还有其他化学物质参与其中。

Everyone should know that when Reed says dopamine is responsible for X, Y, and Z, there are many other chemicals in the brain likely involved as well.

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其他化学物质,而且多巴胺有多种功能。

Other chemicals and dopamine has multiple functions.

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是的。

Yeah.

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就像生物学中的任何事物一样。

Want- Like anything in biology.

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是的,应该

Yeah, should

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现在就把这个写在黑板上,这样如果你还想再提到它,可以随时看,但大家不必觉得有压力。

just embed that's up on the chalkboard now so that if you wanna mention it again, you can, but don't feel obligated to people.

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我们在这里讨论多巴胺时视角比较狭窄,但血清素、乙酰胆碱、去甲肾上腺素,甚至我们尚未发现或理解的多肽,也都在发挥作用。

We're talking about dopamine through a narrow cone here, but certainly serotonin, acetylcholine, norepinephrine, peptides we haven't even discovered or understand yet are contributing.

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多巴胺显然是一个主要角色。

Dopamine is clearly a major player.

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我想退一步,举一个人类的例子,一个非人工智能的例子,来理解你刚才说的:人工智能运行的算法,基于的正是我们脑干神经元用来释放多巴胺的相同机制。

I want to step back to a human example, a non AI example, with the understanding of what you just said, which is that the algorithms that AI is running are based on the same algorithms that neurons in our brainstem are using to deploy dopamine.

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我不知道世界上还有其他类似的例子。

Which I don't know of an example like that in the world.

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你有吗?

Do you?

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我没有。

I don't.

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我的意思是——

Mean, I-

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我们已经发现了算法的本质。

Where we've discovered the nature of an algorithm.

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一旦我们将它外部化,编写出代码,就会有少数几个特别的群体突然利用同样的算法取得巨大突破。

Once we externalize it, we write code and then it takes a few very special groups to all of a sudden have giant breakthroughs using that same algorithm.

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而这些突破最终会将信息反馈回我们的大脑。

And those breakthroughs are gonna end up pumping information back into our head.

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因此,我们生活在一个有趣的递归循环中。

And so we live in an it's an interesting recursion there.

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不知道会带来什么结果。

Don't know what will come about.

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是的,我们把生物学习规则赋予了计算机,而计算机竟然能超越我们自身对这些生物学习规则的运用,这确实非常惊人。

Yeah, the fact that we took biological learning rules and gave them to a computer essentially, and the computer then can beat our own use of the biological learning rules is pretty spectacular.

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我觉得这有点可怕,但我想先搁置这个话题,待会儿再说。

And I think it's a little scary, but I want to shelve that for later Okay.

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我想回到约会的例子。

In the I want to return to the dating example.

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你得把这个约会的例子挂在我身上

You're to hang this dating example around my

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脖子上?不,我不这么认为,我们可以把它和另一个例子结合起来。

neck, No, aren't think that, and we can partner it with another example.

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哪个例子比较好?

Which example is good.

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你在与某人互动的过程中不断前行。

You you you you go along in an interaction with somebody.

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你在周四时获得了关于他们的新信息。

You pick up new knowledge about them on Thursday.

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你甚至不一定见到他们。

You don't necessarily even see them.

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这改变了你对他们的预期。

It changes your expectations of them.

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你在周六又获取了一些新的信息。

You pick up some new knowledge on Saturday.

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你碰到了他们的一个同事。

You run into a coworker of theirs.

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他们说:哦,我听说你正在和某某交往。

They say, oh, I hear you're seeing so and so.

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你知道吗, blah, blah, blah, blah, blah?

Did you know blah, blah, blah, blah, blah?

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你获得了新的

You get a new

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改变了你对事物的看法。

Changes view of your view.

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所以我想知道,在不断更新的期望背景下,多巴胺在起什么作用?

So what I want to know is what is dopamine doing in the context of the constantly updated expectations?

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我们知道多巴胺与动机有关。

We know that dopamine is involved in motivation.

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期望的变化是否会影响动机,使人更积极、更悲观、更乐观,或保持中立?

Are the changes in expectation modifying motivation to either move forward, become more pessimistic, more optimistic, or stay neutral?

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这是个很好的问题。

That's a great question.

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所以期望会变化。

So expectations change.

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这些期望的变化由多巴胺的正负波动来编码。

Those changes in expectation encoded by positive and negative fluctuations in dopamine.

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动机从何而来?

Where does motivation come in?

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托德·布雷弗和约翰·科恩对此有个想法,我觉得马特·沃尼克也同意。

Todd Braver and John Cohen had an idea about that, and I think Matt bought Vennick too.

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也就是说,这些预测误差是判断你应该有多大的动机的完美信号。

And that is those prediction errors are perfect signals for deciding how motivated you should be.

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通过衡量这些信号,你该有多想要某样东西?

How much should you want a thing by measuring across those kinds of signals?

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如果你在做实验,试图观察多巴胺,那么根据你观察的时间尺度,你可能会看到它随着期望的波动而产生微小变化。

And if you were doing an experiment, you were trying to look at dopamine, depending on the timescale you looked at, you might see little changes in it that correlated with fluctuating expectations.

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你可能会看到某种类似包络线的东西,一种变化较慢的现象,这正是实验心理学研究中可能采用的实验方式。

You And might see something as a kind of envelope, a slower changing thing, which is the kind of experiment you might do in an experimental psychology setup.

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而这看起来就像是与动机相关联,尽管其下方还伴随着各种细微的波动。

And that would look like it correlated with motivation, with all these little wandering things going on underneath.

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这就是为什么它能够同时发挥这两种功能的原因。

That's the sense in which it could do both functions.

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我们被告知,多巴胺是我们穿越社交媒体环境、约会环境或金融投资环境时所追求的东西。

We are told that dopamine is what we're seeking as we go through a social media environment or we go through a dating environment or we go through a financial environment that we're investing or investing time in.

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但正如你所提到的,多巴胺并不仅仅如此,我们早已知道,它其实是驱动我们前进或促使我们暂停的神经回路算法的一部分。

But as you mentioned, dopamine is not just that, you know, at the finish line, we've known this for a while now, it's part of the neural circuitry algorithm that's driving us forward or causing us to pause.

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但是否可以说,任何系统——无论是社交媒体平台还是其他形式的商业——无论它们是否意识到这一点(它们很可能意识到了),其设计初衷都是不断更新我们的期望,让我们持续参与游戏,保持在‘锻造模式’中?

But is it fair to say that any system, it's a social media platform or it's another form of business, whether they consciously realize it or not, and they probably do, it's built on trying to constantly update our expectations so that we keep playing the game, so that we stay in the forging mode.

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因为如果你仔细想想,这是一次无限滚动。

Because if you think about it, it's an infinite scroll.

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没有最终的结果。

There is no final outcome.

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如果有最终结果,你就不会继续活下去。

If there was a final outcome, you wouldn't keep living.

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你希望这个系统持续运转。

You want that system to keep tracking.

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一旦它到达某个地方,你就希望它还能去另一个地方。

And once it gets to one place, you want it to have another place to which it could go.

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否则,你就不会活下去。

Otherwise, you wouldn't live.

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这或许能解释为什么地球上每个能移动的生物的大脑中都有这种机制。

Probably one insight into why it's in every mobile creature's brain on the planet.

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所以,如果你达成任何目标——无论是吸毒、吃食物、找到伴侣,或其他任何事——如果那一刻就足以让你满足,那你的神经系统恐怕就不会这样运作。

So if any goal that you achieved, whatever it is, taking a drug, eating a food, getting a partner or whatnot, if that was enough for you right then, probably be a hard that's not the way your nervous system works.

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你的神经系统会不断推动你向前。

Your nervous system keeps pushing you forward.

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这正是你所追求的。

That's what you're working for.

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你所追求的就是这种向前推动的动力。

You're working for this push forward drive.

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将这种机制归结为多巴胺的释放并不错误,只是过于粗略。

The mapping that onto dopamine hits is not wrong, it's just blunt.

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这只是一种粗略的说法。

It's just a blunt way to say it.

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这并不错误,但确实很粗略。

It's not wrong, but it is blunt.

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这是一种粗略的表达方式。

It's a blunt way to say it.

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在你获得任何重大意外的刺激之前,你早已带着预期在行动。

You move around with expectations before you get any sort of big unexpected hit.

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这就是我不喜欢‘多巴胺释放’这个说法的原因,因为它暗示着奖励像涓涓细流一样注入你体内。

This is why I don't like the phrase or the words dopamine hits because it implies it's like a reward that gets trickled into you.

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但这是事实。

But it is true.

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你会得到

You get a

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一次刺激。

hit.

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是的。

Mhmm.

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确实存在一种意外的奖励,你的预期序列并没有预料到,而这种奖励会增强你的反应。

It is true that there's this unexpected reward that your expectations, your series of expectations, did not anticipate, and that augments.

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这就是学习规则。

That is the learning rule.

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我们认为多巴胺的波动正是在编码这种机制。

That's what we think the dopamine fluctuations are encoding.

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因此,它同时完成了两项任务。

And so it does both jobs.

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它让你能够更新和学习,同时也编码了你应该具备的动机类型。

It lets you update and learn, and it codes for the kind of motivation you should have.

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当你感到惊讶时,这些就是额外的奖励。

And when you're surprised, those are extra hits.

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所以这么说并不算错。

So it's not wrong to say that.

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只是不够完整。

It's just incomplete.

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我打算

I'm going to

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请你稍微推测一下,但要基于你对多巴胺的了解——你对此了解很多。

ask you to speculate a little bit here, but speculate within the context of what you know about dopamine, which is a lot.

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让我们以我刚才提出的任何一个例子为例。

Let's take any of the different examples that I threw out on the table for us.

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如果我们人为地提高多巴胺水平,不是用像冰毒这样的滥用药物,而是稍微加入一点多巴胺能兴奋剂。

And we artificially ramp up levels of dopamine with, let's not say a drug of abuse, like methamphetamine or something, but, you know, we throw a little bit of a dopaminergic stimulant into the picture.

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这会不会只是提高了锯齿波的高度?

Does that just raise the the kind of the height of the sawtooth?

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这会改变这一切吗?

Does it change any of this?

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比如,这个人在第二次或第三次约会时,去看了一个特别精彩的演出。

For instance, if, this person who goes out on a date on the second or third date, they go to something that, like, maybe a show that's spectacularly good.

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明白吗?

Okay?

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当现在这个人或这个事件与某种体验产生关联时,如果他们经历了多巴胺的激增,这会如何改变其中的动态?

How does that change the dynamics when, you know, it's now there's an association with this person or an event, but let's say that they're flooded with dopamine.

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我们先撇开药物不谈。

Let's take a drug out of the picture.

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这次体验本身产生了更多的多巴胺。

The experience generated more dopamine.

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这会影响他们对这个人的期待和动机吗?

Does it shape their expectation and motivation around that person?

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如果你提高了期待,而这些期待是由多巴胺的变化所编码的,那么这实际上是一个关于持续状态的问题。

If you raise expectations and these are coded by changes in dopamine, then in fact, that's sort of a tonic question.

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这属于一种持续性状态

That's sort of a tonic phase

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你能解释一下什么是持续性吗?

Can you explain tonic?

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大多数人正在经历初始阶段的意志力。

Most people are doing I ginning will.

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所以是缓慢变化的,明白吗?

So slower changing, okay?

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所以我去看了一场演出,让我非常兴奋,我的幸福感容器里多了一点水,明白吗?

So I see a show, it makes me very excited, I have the well fills up with a little more water, Okay?

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它就停在那里。

And it's sitting here.

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所以之后的小刺激都是叠加在这个基础上的。

So now the little hits on are on top of that.

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或者我看到了一些会消耗它的东西。

Or I see something that depletes it.

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我吃了一种药,有些药物会消耗多巴胺。

I take a drug and some drugs deplete dopamine.

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或者他们去看了一场演出,但很糟糕。

Or they went to a play and it sucked.

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是的。

Yeah.

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这让人失望或者感到悲伤。

It's disappointing or it's sad.

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他有

He's got

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糟糕的品味。

bad taste.

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是的。

Yeah.

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这一直在他脑海中挥之不去。

And it just runs in his mind.

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因此,这会降低多巴胺水平,并改变波动对学习的影响方式。

So that can lower the levels, and that changes the way in which the fluctuations have an impact on learning.

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帕金森病是一种疾病,当你带着症状去看医生时,你脑干中70%到75%的多巴胺神经元已经丧失。

Parkinson's disease is a condition where by the time you show up with symptoms in the doctor's office, you've lost 70% to 75% of your dopamine neurons in your brainstem.

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这些是你大脑中仅有的多巴胺来源,除了下丘脑和垂体中的一条微小通路。

Those are only sources of dopamine in your brain, except for a tiny pathway in your hypothalamus and pituitary.

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几个轴线。

A couple of axes.

Speaker 1

视网膜。

Retina.

Speaker 1

呃,抱歉。

Well, there's Sorry.

Speaker 1

我体内有个视网膜生物学家。

Retina biologists in me.

Speaker 1

他们在做完全与此无关的事情。

They're doing things totally unrelated to any of this.

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它们在控制不同光照水平下的适应过程。

They're controlling adaptation at light levels.

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是的,光照水平的适应,特别是在金鱼身上。

Yeah, light level adaptations and certainly in goldfish.

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是的。

Yeah.

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这些其实非常有趣。

Those are actually very interesting.

Speaker 0

我们不谈它们了。

Won't talk about them.

Speaker 0

你之前提到过

You had

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那些在帕金森病中退化的多巴胺能脑干神经元

the dopaminergic brainstem neurons that degenerate in

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当你感到僵硬、开始出现震颤、面部表情呆板、情感淡漠,有人带你去看医生时,你的多巴胺神经元已经损失了70%到75%。

the time you're feeling so stiff, starting to have tremors, all the parts of the flat facey, flat affect, and somebody gets you to a doctor, you're in the 70% to 75% loss.

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好吧?

Okay?

Speaker 0

那这意味着什么?

So what does that mean?

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现在,你脑干中的这些多巴胺神经元,每侧大约有八万个,总共十六万个神经元。

Now all of a sudden, these and dopamine neurons in your brain stem are maybe 80,000 neurons per side, 160,000 neurons.

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这简直微不足道。

That's like nothing.

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它们通过生物性的神经纤维向整个大脑和脊髓发送多巴胺,形成数亿个连接。

They send dopamine delivering wires, biological wires throughout your entire brain and down your spinal cord, making hundreds of millions of connections.

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但你现在把这些神经元数量减少了。

But now you've shrunk those down.

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所以发生的情况是,信号变得非常嘈杂。

And so the one thing that happens is it's very noisy.

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可供传递的神经元数量太少了。

There's not so many neurons to cut for it.

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其中没有平滑的变化。

There's no smooth changes in it.

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相对于你能生成的信号,噪声水平变得非常高。

And the noise floor relative to what you could generate as a signal gets really, really high.

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我们认为多巴胺在信息处理中的作用之一是评估世界,换句话说,计算采取这个行动或那个行动的价值,抓起某物放进嘴里喝水等行为的价值。

Well, one of the things that we think dopamine is involved in, in terms of information processing, is valuing the world, computing, if you will, the value of taking this action or that action, the value of grabbing this and putting it in my mouth and drinking water, etcetera.

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好的。

Okay.

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帕金森病的状态类似于一个平坦的价值函数。

And the Parkinson's state is sort of like a flat value function.

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当你环顾世界时,你无法真正感知事物之间的差异价值,你期望系统能通过波动来告诉你:如果我做这件事或做那件事,如果我注视那个东西等,它会给你提供波动信号,但你现在无法解读这些信号。

You can't really see differential value in things as you look around the world, you expect the system to fluctuate for you to tell you if I were to do this stuff or if I were to do that stuff, if I were to look at that, etcetera, it gives you a fluctuation, but you can't read it.

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下游信号太嘈杂了。

The downstream It's too noisy.

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太嘈杂了。

It's too noisy.

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你无法解读它。

You can't read it.

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下游系统只能像以前那样继续运作。

The downstream system just has to act as it did before.

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它说,哦,一切都价值相等。

It says, oh, everything's of equal value.

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就待在原地吧。

Just stay put.

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所以我一直认为帕金森病是一种主动的冻结性疾病。

So I've always thought about Parkinson's as an active freezing disease.

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神经系统正在做它本来会做的事情,因为从当前状态切换到下一个动作需要消耗能量。

The nervous system is doing exactly what it would do if because it takes energy to transition from where you are to doing the next thing.

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如果那里并没有更值得追求的东西,为什么要这么做呢?

Why do that if there's nothing more valuable there?

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这又回到了它推动你穿越世界这一观点。

This comes back to the idea of it pushing you through the world.

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它不会适应,因为它必须维持你的行为,否则你会死。

It doesn't habituate because it has to keep your behavior going or else you're gonna die.

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我不认为这是巧合。

I don't think it's a coincidence.

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事实上,我知道多巴胺不仅参与学习、动机、情绪和运动,还承担着其他一些次要功能。

In fact, I know it's not that dopamine is involved in learning, motivation, feelings, and movement among a few other more minor roles.

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所有关于身体运动的方面对我们来说都是直观的。

Everything about physical movement is intuitive to us.

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你向前移动,向后移动,左右移动,保持静止。

You move forward, you move back, you move side to side, you stay put.

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好吧,就像运动一样。

Okay, like movement.

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某一时刻多巴胺的水平,以及你所说的那种持续性的基础水平——我称之为多巴胺的基础水平,而非其上的峰值——能够预测你是否会向前行动、前进时的阻力大小,诸如此类的事情。

The idea that levels of dopamine in a moment and what you're referring to as the tonic kind of baseline, what I call baseline levels of dopamine, as opposed to spikes on top of that, predict whether or not you'll move forward, how much resistance there is to moving forward, these kinds of things.

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但我认为,对很多人来说,将多巴胺放在思维运动的语境下来理解可能会很有帮助,对吧?

But I think for a lot of people, it might be useful to think about dopamine in the context of thought movement, right?

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而动机本质上是一种向前推进的形式。

And motivation is sort of a version of forward movement.

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当我思考自己是否愿意做某事时。

If I think about am I motivated to do something?

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我不再喜欢‘动机’这个词了,我已经决定了。

I no longer like the word motivated, I decided.

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我更喜欢‘紧迫感’这个词。

I like the word a sense of urgency.

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你可以有低、中或高的紧迫感。

You could have a low level of urgency, moderate or high level of urgency.

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我将紧迫感定义为一种持续且坚韧的动机,对吧?

Urgency I define as sort of a persistent, resilient motivation, right?

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我更倾向于用紧迫感代替动机,因为我觉得对大多数人来说,紧迫感更直观。

And the reason I prefer urgency to motivation is that a sense of urgency is more intuitive I think to most people.

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当我们觉得自己必须做某事、非常想做,或者其实并不想做,或者在拖延时,我们大致都能感受到。

We kind of know when we feel we have to do something, We really want to do it or like, we don't really want to do it or we're procrastinating.

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而动机这个词只是一个笼统的术语,用来衡量你有多有动力?

Whereas motivation is this just kind of like catchall term for how motivated are you?

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他们谈论内在动机和外在动机。

They think intrinsic motivation, extrinsic motivation.

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所以当我想到紧迫感时,我想的是那种需要和准备好让身体或思维朝特定方向行动的感觉。

So when I think about a sense of urgency, I think about a sense of a need and readiness to move the body and or move thoughts in a particular direction.

Speaker 1

我们是否认为多巴胺在推动思维和决策朝特定方向进行中起作用?

Do we think that dopamine is involved in moving thoughts and decision making in a particular direction?

Speaker 0

我们正是这么认为的。

We exactly think that.

Speaker 1

好的。

Okay.

Speaker 1

谢谢。

Thank you.

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我并不是在让你验证我这个非理论的理论。

I wasn't asking you to validate my non theory theory.

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我认为,如今多巴胺这个词被滥用得太厉害了,以至于我们甚至都不太明白什么是动机,更不用说多巴胺是如何发挥作用的了——

I think that dopamine is thrown around so much nowadays that we don't even really understand what motivation is, let alone how dopamine would be playing this-

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很明显,多巴胺和其他神经调质参与了大脑状态的稳定和维持。

It's very clear dopamine and the other neuromodulators are involved in stabilizing and sustaining brain states.

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明白吗?

Okay?

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这就是为什么人们认为它们与癫痫有关,对吧?

That's why they're thought to be involved in seizures, right?

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对于大脑状态,你必须稍微牢牢抓住它。

One thing you have to do with the brain state is kind of hold onto it a bit.

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它需要有一定的持续时间。

It's got to have a dwell time.

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我们不妨称之为一个想法。

Let's call that a thought.

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砰。

Boom.

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然后它会向前推进或发生变化,之后可能又会回到那个状态。

And then it goes forward or changes, and then it may come back to that.

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因此,思考以及对你们所谓的思维进行序列化,这些系统显然与之密切相关。

So thinking and sequencing through what you would call thoughts is something that these systems are clearly intimately related to.

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现在有很多优秀的团队正在利用小鼠模型和理论模型探索这一领域。

And there are a lot of great groups now that are exploring this in in mice models and theoretical models as well.

Speaker 0

所以我觉得你把这几个词关联得非常好。

So I think you tie the words together pretty well.

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对于一个必须不断移动才能生存的动物——所有动物都是如此——它必须知道事物的价值有多大,自己应该有多大的动力,以及对某样东西渴望到什么程度。

In an animal that has to keep moving to stay alive, and that's all animals, it has to know how valuable is it, how motivated should I be, how much should I want a thing.

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对吧?

Right?

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我们认为算法影响的大脑计算,正是这些内容。

The calculations that we think the algorithms are affecting in brain are exactly those.

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因此,我们可以用这些心理学词汇来展开讨论,这些词汇有趣且与观察动物行为的方式密切相关。

And so we can have these conversations at the level of these psychology words, which are interesting and pertinent to the way looking an animal behave.

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但现在我们开始从计算层面剖析它:这到底是在计算什么?

But now we're starting to pull it apart at the level of what is this computing?

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它的计算速度有多快?

How fast is it computing it?

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它是如何更新的?

How did it update it?

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现在我们可以基于这些原理构建人工系统。

And now we can build artificial systems based on that.

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我认为2004年大卫·雷迪什发表过一篇论文,将成瘾描述为一种计算机制失常的疾病——当你通过药物持续提供多巴胺,而这种药物阻断了多巴胺的再摄取,系统就无法正确预测了。

And I think there was a paper in 2004 by David Redish talking about addiction as a computational disease gone awry, where you keep feeding the system a level of dopamine by putting a drug in that blocks its reuptake that it can't anticipate right.

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因此它不断追逐这种感觉,却永远无法真正达到。

So it keeps chasing that, and it never gets there.

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当人们患有注意力缺陷多动障碍(ADHD),即使是轻度的,或者他们服用能提高多巴胺水平的药物时,你认为这会让世界上的更多事物变得难以摆脱吗?

When people have ADHD, even low level ADHD, or they take a drug that increases dopamine, do you think that it makes more things in the world sticky?

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我的意思是心理上更难放下,当我们多巴胺水平升高时,会更自然地执着于更多事物。

Meaning mentally sticky, like we we naturally just will latch on to more things when our levels of dopamine are elevated.

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我们会更随机地觅食,还是更狭窄地觅食?

We'll forage more randomly, or do we forage more narrowly?

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因为ADHD的整个概念就是,他们——典型的例子就是‘松鼠’,ADHD患者的多巴胺系统被认为失调了。

Because the whole notion of ADHD is that they, the whole like, oh, squirrel, like that's the kind of generic example is that someone with ADHD, the theory is that their dopaminergic systems are dysregulated.

Speaker 1

这些药物,几乎都是这样,对吧?

These drugs, almost all of them, right?

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无论它是利他林、阿得拉,还是其他药物,都会提高多巴胺和去甲肾上腺素的水平。

Whether or not it's Ritalin or Adderall or these other drugs, they raise levels of dopamine and norepinephrine.

Speaker 0

哦,

Oh,

Speaker 1

是的。

yes.

Speaker 1

它们以某种方式让人进入更狭窄的专注状态,或在选择觅食路径时提供更多的选择性。

And somehow put people into a more narrow trench of focus or give them a little bit more selectivity in terms of what paths they decide to forage.

Speaker 0

是的,我猜测这其实是以一种狭窄且不易偏移的方式稳定了大脑状态和思维序列。

Yeah, I suspect if you made me guess that it's stabilizing brain states and thought sequences in a way that's narrow and it doesn't divert.

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这让你感到惊讶吗,

Does that surprise you that

Speaker 1

不,增加多巴胺会起到这个作用

No, increasing dopamine bees would do

Speaker 0

做到这一点。

do this.

Speaker 0

好吧,所以当你

Okay, so when you're

Speaker 1

是一个觅食者

a forager

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蜜蜂回来后会在蜂巢里跳一段舞,告诉其他觅食者去哪里寻找花蜜来源。

bee, you come back and you do a little dance in the hive and it tells the hive other foragers where to go find the nectar source.

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明白吗?

Okay?

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这是一种完整的语言。

And it's a whole language.

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人们已经弄清楚了。

People have worked that out.

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它告诉你,以太阳为参照,飞多远,还有偏振光的方向。

It tells you fly this far with the sun here and there's a polarization.

Speaker 1

这是一个惊人的现象。

It's an amazing phenomenon.

Speaker 1

是的。

Yeah.

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蜜蜂回去后,真的会跳一种舞,叫做摇摆舞。

The bees go back and they literally, they do this dance, the waggle.

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它们通过触碰蜜蜂的摇摆舞来感知信息。

And they feel the waggle dance on the bee.

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通过感受这种舞蹈,它们就知道该去哪里。

And by feeling it, they know where to go.

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太神奇了。

Wild.

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嗯,这是一种语言。

Well, it's a language.

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可以解码,我的意思是,它已经被破译了。

Can decode I mean, it's been decoded.

Speaker 0

是的。

Yeah.

Speaker 1

太酷了。

Very cool.

Speaker 0

在某种程度上。

To some degree.

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当你观察蜜蜂时,我知道这一点,因为我过去几年一直在亚利桑那州立大学的蜜蜂专家布莱恩·史密斯那里工作。

When you look at bees, I know this because I've been working with a bee guy, Brian Smith, at Arizona State University for the last few years.

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我整个职业生涯都认识他,但现在我有了一个方法,可以让他在蜜蜂进行气味学习时测量它们体内的多巴胺、血清素和去甲肾上腺素。

I've known him my whole career, but I've now has a methodology that lets him make measurements of dopamine and serotonin and norepinephrine in bees while they do odor learning.

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他让蜜蜂站在一个轴上。

And he has bees on an axis.

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这边是所谓的注意力缺陷蜜蜂,那边则是专注型蜜蜂。

Way over here are the ADD bees, let's call them, and way over here are the concentration bees.

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这与一种与多巴胺相关的化学物质——章胺有关,但关键是章胺与另一种叫酪胺的物质的比例。

And it relates to a chemical that's related to dopamine called octopamine, but it's a ratio of octopamine to it's called tyramine.

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如果你拿灵长类动物来类比,这就像是多巴胺和血清素的关系。

That's like dopamine and serotonin if you were talking about primates.

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注意力缺陷蜜蜂会感受到摇摆舞,然后冲向花蜜,但很快就会分心。

The ADD bees, they feel the waggle dance and they start running for the nectar and then they get distracted.

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它们就像四岁的小孩。

They're the four year old.

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有很多这样的

There are lot

Speaker 1

成年人

of adults like that

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现在,它们因为分心而探索得更多,当然,这正是它们的行为方式。

nowadays And they can't of course, what they do by being distracted is they explore more.

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而这边最远端的那些蜜蜂会直接飞向蜜源。

And then the ones on the far end over here, they fly right to the nectar source.

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所以两者都需要。

So you need both.

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这被称为利用。

That's called exploitation.

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它正在利用蜜源的位置。

This one's exploiting where the nectar source is.

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它会得到蜜源。

It's gonna get it.

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它会把蜜带回蜂巢。

It's gonna bring it back to the hive.

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而那些类似多动症的蜜蜂则是探索者。

And the sort of ADD guys are the explorers.

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它们在寻找新信息、新的蜜源等等。

They're looking for new information, new nectar sources, etcetera.

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你的思维如此直接,你的大脑就会产生这种二元对立。

Well, your mind kind of as blunt as that is, your mind plays this dichotomy.

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在同一个个体身上,你认为我们既有类似多动症的模式,也有更专注的模式。

In the same individual you think that we have this ADHD like mode and a more focused mode.

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你的脑子里有好几只蜜蜂。

You've got multiple bees inside your head.

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其中一只让你成为探索者,这在某些时候非常宝贵。

One of them is making you into the explorer, and that's really, really valuable sometimes.

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公司会留下这样的人。

And companies, they keep these people around.

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他们是善于横向思考的人,你只需要给他们足够的空间。

These are the lateral thinkers and you just have to feed them enough.

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然后还有那些能严格遵循指令、执行最佳行动方案的人。

And then you have the people that can really follow instructions and follow the best course of action and whatnot.

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而你需要所有这些类型的人。

And you need all that.

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你需要所有这些。

You need all that.

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这种能力的分布存在于我们每个人身上,但每个人之间又有所不同。

And this distribution of abilities is built into all of us, but it's different across us.

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你知道的。

You know?

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如果我看着一片橡树叶,告诉你:这个小波纹怎么样?

If I was looking at an oak leaf and I told you, what about this little wiggle?

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这正是我们动机和学习机制中的‘波纹’。

It's the wiggle in our software design for motivation and learning.

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有时候做探索者非常有效,而其他时候,你必须能够遵循这条路径,因为它会带你走向

It's very effective to sometimes be the explorer, And other times, you have to be able to follow the chain of this is gonna lead you to

Speaker 1

你想要的东西。

the thing that you want.

Speaker 1

保持方向。

Stay on course.

Speaker 1

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Speaker 1

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Speaker 1

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Speaker 1

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Speaker 1

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Speaker 1

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Speaker 1

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Speaker 1

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And like I said, it has me sleeping incredibly well, waking up more refreshed than ever.

Speaker 1

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Speaker 1

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Speaker 1

你所描述的,是我们每个人内心都存在的类似注意力缺陷多动障碍的状态,以及高度专注的状态。

What you're describing is a sort of ADHD like mode inside of all of us, as well as a highly focused mode inside all of us.

Speaker 1

我认为你所说的,也指的是有些人非常倾向于注意力缺陷多动障碍模式,而另一些人则非常倾向于高度专注模式。

You're also I think I hear you correctly in thinking that you're also describing the fact that some people are very strongly ADHD mode and other people are very strongly focused.

Speaker 1

他们非常线性。

They're very linear.

Speaker 1

或者以任务为导向。

Or task based.

Speaker 1

以任务为导向。

Task based.

Speaker 0

他们真的能明确一个任务,并在心中保持它,任务会一直存在。

They can really form a task, hold it in mind, a task stays there.

Speaker 0

很多运动员都是这样。

Lots athletes are that way.

Speaker 0

他们设定目标,并且设定多层次的目标。

They set a goal and they set multiple scales of goals.

Speaker 0

他们设定某个目标。

They set some goal.

Speaker 0

你知道,这就是我两年后想要达到的地方。

You know, this is where I wanna be in two years.

Speaker 0

明白吗?

Okay?

Speaker 0

为了实现这个目标,我必须经历种种磨难,才能在两年内抵达。

To get there, I'm gonna have to do you know, I have to crawl through, you know, hell to get there in two years.

Speaker 0

我必须完成这些事情。

And I have to do these things.

Speaker 0

而且我明天早上还会再醒过来,一次又一次,一遍又一遍。

And I'm gonna wake up again tomorrow morning and again and again and again.

Speaker 0

这些目标必须不断重新确立并持续追求。

And these goals have to be reconstituted and pursued.

Speaker 0

如果你,你知道,想打NBA,但六个月后突然决定去打冰球,那就有问题了。

If you, you know, wanted to go play in the NBA and then all of a sudden, six months into that, you decide you wanna go do ice hockey, well, that's the problem.

Speaker 0

这是一个无法集中注意力的人。

That's a person who can't can't focus

Speaker 1

我们都知道这样的人。

We all know these people.

Speaker 1

我有一个问题,我们只能在这里推测:现在有很多说法认为社交媒体,但我说社交媒体时,并不是要贬低它——我本身也在社交媒体上教学和学习。

One question I have, and we can only speculate here is, you know, there's a lot of ideas now that social media but when I say social media, I don't wanna knock on I teach and learn on social media.

Speaker 1

我主要想说的是那些非常短的短视频。

I what I mainly thinking about is short, very short form video.

Speaker 1

有一种说法认为,这种短视频正在给所有人带来注意力缺陷多动障碍。

There's this idea out there that it's quote unquote giving everybody ADHD.

Speaker 1

实际上,我不认为这是真的,但我可以想象,如果我们大脑中存在类似蜜蜂的连续模式,而我们反复接触那种快速切换刺激的环境——比如刷TikTok或YouTube Shorts时,频繁地更新大量不同的情境和信息,这些神经回路可能会变得更强。

Now, I don't actually think that's true, but I could imagine that if we have this continuum of honeybee like modes in our brains, that if we repeatedly engage in a kind of rapid turnover of stimuli, like you get when you scroll a TikTok or YouTube Shorts or something like that, I mean, there's a very frequent updating of lots of different contexts and information that those circuits might get stronger.

Speaker 1

而那些让你能够在节点间移动、根据需要调整路径、理解并整合预期、奖励、失败等所有因素的神经回路。

And that the circuits that allow you to move from node to node and route to a goal, updating as necessary, understanding and integrating expectations and rewards and failures and all the above.

Speaker 1

对吧?

Right?

Speaker 1

运动员的例子、学术的例子,任何生活中的关系导航,所有我们视为构建稳固人生的事情。

The athlete example, the academic example, any life navigating relation, all the stuff that we think of as building a solid life.

Speaker 1

对吧?

Right?

Speaker 1

你可以想象,这种快速更新和探索行为可能会削弱这些神经回路。

You could imagine that some of that rapid updating and foraging could undermine the circuitry.

Speaker 0

是的,你锻炼出了你的注意力缺陷肌肉。

Yeah, you build your ADHD muscle.

Speaker 1

有没有任何证据,或许来自相关或完全不同的实验,表明如果你让人执行需要快速切换的任务,会促使大脑更倾向于追求这种快速反馈,而不是像长期、远期奖励那样的模式?

Is there any evidence maybe from related or other experiments entirely that show that if you give people a task where they have to update very quickly, that you shift the sort of state of the brain toward seeking that more and and doing that more easily than you do kind of like long long haul, distant reward type stuff?

Speaker 0

我不知道人在这种情况下答案是什么,但我了解如何训练人工系统来实现这一点。

I don't know the answer to that in people, but I do know about training artificial systems to do it.

Speaker 0

你必须非常小心地控制混合比例,以免系统在其中一种可能性上过度训练。

And you have to be very careful to control the mix so that it doesn't overtrain on some on one of these two possibilities.

Speaker 0

如果我们把这两种可能性分开,一种是追逐目标,另一种是追逐所有飞过的东西。

If we're gonna divide these two possibilities, chase a goal, chase everything that flies along.

Speaker 0

对吧?

Right?

Speaker 0

你不想只做其中任何一件事。

And you don't want to do either one of those things.

Speaker 0

你需要平衡这两者。

You have to balance that.

Speaker 0

有时你必须施加约束,才能让人工网络实现这种平衡。

And sometimes you have to impose constraints to make that happen in an artificial network.

Speaker 0

在人类身上,这个问题要复杂得多。

It's a more complicated problem in people.

Speaker 0

我的意思是,我能想象在很多情况下,患有多动症是绝对必要的。

I mean, I can imagine I know lots of settings for being ADD is absolute requirement.

Speaker 1

你能给我举几个例子吗?

Can you give me a few examples?

Speaker 0

战斗。

Combat.

Speaker 0

战斗。

Combat.

Speaker 0

快速决策。

Rapid decision making.

Speaker 0

就像战斗机飞行员那样。

Kind of the fighter pilot.

Speaker 0

情境认知。

Situational knowledge.

Speaker 0

那么他们是如何为这种情况做准备的呢?

Now what do they do to prepare for that?

Speaker 0

顺便说一下,我爸爸是海军上尉。

By the way, my dad was a captain in the Navy.

Speaker 0

我脑子里有很多实战的例子。

Have lots of combat examples in my head.

Speaker 0

嗯,他们进行训练。

Well, they practice.

Speaker 0

他们进行训练。

They practice.

Speaker 0

他们练习应对突如其来的状况。

They practice being surprised.

Speaker 0

他们练习在饥饿状态下承受压力,所有这些训练都是为了当情况发生时,他们不需要逐个考虑所有可能性,而是能高效应对,但这需要训练。

They practice being hungry and then they put themselves under stress and all so that when that happens, they don't have to run through every possibility and they're very effective, but that requires training.

Speaker 0

这需要大量的心理训练。

That requires an enormous amount of mental training.

Speaker 0

这完全是心理层面的较量。

It's all about the mental game.

Speaker 1

这是个很好的例子。

That's a good example.

Speaker 1

我们请过几位注意力缺陷多动障碍(ADHD)专家,他们都一致认为,无论是轻度还是重度的儿童和成人ADHD患者,都能在他们真正喜欢和感兴趣的事情上高度集中注意力。

We've had a couple of experts in ADHD on here and all of them have agreed that children and adults with ADHD, mild or severe, can focus very intensely on things they really enjoy and are interested in.

Speaker 1

这不是缺乏专注能力的问题。

It's not a lack of ability to focus.

Speaker 1

而是要进入那种高度专注的状态,需要穿越很多崎岖的地形,除非是他们热爱的事情。

It's that there's a lot of choppy terrain to get into that narrow mode of focus, unless it's something they love.

Speaker 1

你给一个ADHD孩子一款他们喜欢的电子游戏,他们立刻就能沉浸其中,就像你见过的他们最专注的样子。

You give a kid with ADHD a video game they love, they'll drop right in as if it was, you know, the most focused you've ever seen them.

Speaker 0

每当需要快速做出一系列决策时,我认为你都希望找一个至少能训练到这种水平的人。

Anytime you have to do rapid fire decision making, I think you would want somebody who is able to at least train up to that level there.

Speaker 1

你是否担心过度接触频繁的媒体内容?

Do you worry about the overexposure to, you know, frequent media.

Speaker 1

是的,这些短平快的媒体。

Yeah, these short media.

Speaker 0

我有很多孩子。

I have a lot of kids.

Speaker 0

所以像所有父母一样,我最大的敌人是屏幕时间。

And so like every parent, my main nemesis is screen time.

Speaker 0

明白吗?

Okay?

Speaker 0

我正在想办法监控、衡量、限制屏幕时间,而且你知道,我的孩子比我聪明。

I'm trying to figure out how to monitor it, measure it, restrict it, and, you know, and basically, my kids are smarter than me.

Speaker 0

他们更灵活,行动更快,我根本斗不过他们。

And they're they're more nimble, they they move faster than I mean, so it's a battle I'm losing.

Speaker 0

所以我决定,唯一能对抗的方法就是输,但要输得更聪明一点,偏向我这一方。

So I've decided that the only way I can combat it is to lose it, but lose it a little more effectively toward my side.

Speaker 0

但我得承认,当我看到YouTube短视频,那些小片段,比如,看这个人。

So but I have to admit, when I see YouTube shorts, these little, you know, like, oh, look at this person.

Speaker 0

他用果冻建了一栋房子,现在快倒了。

He built a house out of Jell O and it's falling over now.

Speaker 0

好的。

Okay.

Speaker 0

看看这个人。

Look at this other person.

Speaker 0

有一只鹦鹉在玩刺绣,我的天,这让我觉得麻木。

There's a parakeet poke I mean, it it's mind numbing to me.

Speaker 0

对吧?

Right?

Speaker 1

嗯,这种内容很难带来长期的学习效果。

Well, there isn't a lot of long term learning.

Speaker 1

你知道,我衡量学习是否有效的一个标准是:我是否在之后的某个时间点又回想起并反思过它?

I you know, one of the things that I define learning by as useful learning is did I reflect on it again at a point later in time?

Speaker 1

前几天我在社交媒体上看到一个视频,是我一个朋友的播客节目,斯蒂芬·巴特利特正在采访一位嘉宾,这位嘉宾直接切入了这个话题的核心。

The other day I was on social media and I actually saw a clip, it was on a friend of mine who has a podcast, Stephen Bartlett, and he was interviewing a guest and the speak gets right to the heart of this conversation.

Speaker 1

很多内容一闪而过,各种智慧型建议,比如健康建议,全都不断轰炸着你。

A lot of stuff flies by, lot of wisdom type advice, you know, health advice, all the, you know, it's constant barrage.

Speaker 1

但这一句让我印象深刻。

But this one stuck with me.

Speaker 1

这很有趣。

It's interesting.

Speaker 1

他问那个人:生命的意义是什么?

He asked the guy, What's the meaning of life?

Speaker 1

人们在播客里常问这个问题。

People ask this on podcasts.

Speaker 1

今天我不会问你这个问题。

I won't ask you that today.

Speaker 1

这是莱克斯·弗里德曼才会问的问题。

That's a Lex Friedman question.

Speaker 1

当你上莱克斯的播客时,你可以回答他,但我不会问你。

When you go on Lex's podcast, you can answer it to him, but I won't ask you that.

Speaker 1

但史蒂文问了那个人——我忘了他是谁,抱歉啊,你觉得生命的意义是什么?

But Steven asked this guy, I forget who it was, so forgive me, you know, what do you think the point of life is?

Speaker 1

那个人说,人生的意义在于学会享受时光的流逝。

And the guy said, it's to learn to enjoy the passage of time.

Speaker 1

我觉得,这真是太棒了。

And I thought, that's pretty awesome.

Speaker 1

我会在此基础上补充一点:也要从事那些能为你赢得更多时间的行为,比如确保你不会破坏时间这一核心部分。

I would add to it and also engage in behaviors that buy you more time, you know, as I make sure you don't undermine your the time piece of it.

Speaker 1

但这件事只是在社交媒体上一闪而过,却深深印在了我心里。

But, you know, it was something that flew by on social media, but stuck with me.

Speaker 1

很少有短视频能带给我真正持久的娱乐或信息,让我事后反复回味。

It is exceedingly rare that a short clip provides entertainment or information that really stays with me, that I reflect on it later.

Speaker 1

但当我读一本书时,几乎每章都会划出五到十个重点,之后总会回头再看。

Whereas when I read a book, it's exceedingly rare that I don't have five or 10 things underlined per chapter that I go back to later.

Speaker 0

读书需要花不少时间。

It takes a while to read a book.

Speaker 0

这就是关键所在。

That's the thing.

Speaker 0

阅读一本书需要一系列深思熟虑且有意识的行动。

It takes a deliberative set of intentional actions to read a book.

Speaker 0

这就是媒介之间的差异。

That's the difference in the modality.

Speaker 0

因此,这引出了我一直以来的一个疑问:

So one thing that this speaks to then is I've wondered whether

Speaker 1

那些需要付出努力的活动——无论是否包含回报,但确实包含努力,而且通常比较缓慢,努力和缓慢往往相伴而行——这是否正是强化神经回路的机制之一?

activities that require effort that may or may not include reward, but that include effort and that are a little bit slower, and effort and slower tend to go hand in hand, not always whether or not that is part of the mechanism that strengthens a circuit.

Speaker 1

努力能增强算法吗?

Does effort strengthen an algorithm?

Speaker 1

换句话说,如果我刷社交媒体,很容易不停地滑动、滑动、滑动,观看短视频内容。

In other words, if I get on social media, it's very easy to scroll, scroll, scroll, scroll, scroll short form video content.

Speaker 1

这根本不需要什么努力。

Doesn't take any effort.

Speaker 1

事实上,这其中也没有任何学习发生。

So and in fact, there's no learning involved.

Speaker 1

你只需要动一下拇指,但其实并没有任何学习发生。

All you have to do is move your thumb, but there's really no learning involved.

Speaker 1

而如果我必须做点什么,比如解一个谜题,或者解决某个问题、思考某件事、应对某个挑战,那才是学习发生的地方。

Whereas if I have to do something, if I have to puzzle into do a puzzle to get in, or if I have to solve something or think about something or grapple with something, that is where the learning occurs.

Speaker 1

如果我们知道的话,努力和多巴胺之间有什么关系?

What's the relationship between, if we know, between effort and dopamine?

Speaker 0

现在有很多研究关注动物完成一项任务所需付出的努力程度。

There is a good bit of work now where people look at the amount of effort an animal has to do to accomplish a task.

Speaker 0

让我回到你刚才说的一点,这很有趣。

Let me just go back to something you just said, which was interesting.

Speaker 0

当你需要付出努力时,更容易学到东西,因为它让你放慢了节奏。

When you have to do effort, it's easier to learn something because it slows you down.

Speaker 0

我不确定努力本身是不是原因,还是说努力之所以有效,是因为它让过程变慢了,嗯。

I don't know whether effort is itself the cause or whether the fact that effort is slow Mhmm.

Speaker 0

所以它让过程变慢了。

And so it slows it down.

Speaker 1

所以也许我们可以设计一个实验来放慢这个过程。

So maybe we could design an experiment to set a slowing it down.

Speaker 1

它可能

It may

Speaker 0

立刻让我有了这个想法。

immediately give me this idea.

Speaker 0

在针对啮齿动物的简单实验中确实如此,但你知道,啮齿动物并不太会阅读。

So that's true in simple experiments with rodents, but, you know, rodents can't read very well.

Speaker 0

我从未见过哪只啮齿动物能很好地操作手机。

I've never seen a rodent that I admired that could manage a cell phone very well.

Speaker 0

你知道,即使那些能识字的啮齿动物,情感表现也相当平淡。

You know, even the rodents that can read are kind of flat affectively and all.

Speaker 0

我的意思是,啮齿动物根本不是研究这个的好模型。

I mean, rodent is a terrible model for this, really.

Speaker 0

我甚至都不会在啮齿动物身上做这个实验。

I I I wouldn't even do the experiment on a rodent.

Speaker 0

我在人类身上做实验,只需几句话,就能让人进入某种状态,比如让他们感到饥饿,或者通过让他们思考X、Y、Z来引导他们进入某种心理状态,并设置各种对照来加以控制。

I do the experiment in a human where you can, with a few words, set a human in a certain state and go out or you can make them hungry or you can put a human into a mental state by just asking them to think about X, Y, and Z and have various controls to account for that.

Speaker 0

我得承认,当我关注我们这一代人时,我刚读完一本书,叫《焦虑的一代》。

I have to admit that when I look at the generation we're concerned about I've just read this book, The Anxious Generation.

Speaker 1

哦,是的。

Oh, yeah.

Speaker 1

乔纳森上过这个播客。

Jonathan was on this podcast.

Speaker 0

我和他曾经一起参与过麦克阿瑟网络项目,研究神经科学与法律。

And I was on a MacArthur Network, Neuroscience and Law with him for a while.

Speaker 0

他真是个头脑极其清晰的人。

And he he's just an extremely clear headed person, really.

Speaker 0

他总能让我对各种事情产生新的思考。

Always made me think about things.

Speaker 0

另一方面,我不确定,除了与他人比较,以及社交媒体让你如此迅速地进行这种比较之外。

On the other hand, I don't know, other than the comparison to others and the speed at which social media lets you do that.

Speaker 0

我有四个女儿和一个儿子。

And I have, you know, I have girls mainly, four girls and one boy.

Speaker 0

我不确定这具体对他们造成了什么影响。

I don't know what it's doing to them exactly.

Speaker 0

我们都还好。

We we all okay.

Speaker 0

我觉得没人真的知道。

I I don't think anybody does.

Speaker 0

我觉得我们都怀疑其中有些方面并不好。

I think we all suspect there's features of it that aren't good.

Speaker 0

但这就像是在试图阻挡海啸。

And yet it's like we're trying to hold back the tsunami.

Speaker 0

我的意思是,水已经从我们身边涌过去了。

I mean, it's just the water is going past us.

Speaker 0

所以我认为应对它的唯一方式就是靠飞行控制系统。

And so I think the only way to deal with it is kind of fly by wire.

Speaker 0

你知道吗,当这边刚冒出一点小火苗,有人就说这真的会导致抑郁和情绪问题,是这些特性造成的,那时我们才能去做出反应。

You know, when a little fire starts over here and somebody says, oh, this really causes a depression and mood, and it's these features of it, then we can go react to that and all.

Speaker 0

但要预知它在全球范围内的影响却非常困难。

But it's very hard to know what it's gonna do globally.

Speaker 0

它正在以自己的方式不断演变。

It's it's it's evolving with its own.

Speaker 0

它感觉起来像是独立于我们所做的任何事情之外。

It feels like it's independent of anything we do.

Speaker 0

所以我认为,我们必须采取一种提前介入的应对方式。

And so I I think it's gonna have to be a a of a get in front of it reaction.

Speaker 0

比如,我孩子刚得到了一部手机。

You can't for example, my kid just got a cell phone.

Speaker 0

她13岁。

She's 13.

Speaker 0

据她说,她是班上最后一个得到手机的,她是班上最后一个上七年级就拥有手机的学生。

She was the last according to her, and she's the reporter here, she's the last seventh grader in her school to get a cell phone.

Speaker 0

但事实是,她被排除在所有讨论之外了。

And but the the raw fact was, she I'm being left out of all the discussions and whatnot.

Speaker 0

答案确实是这样。

And the the answer was that that is true.

Speaker 0

她确实被排除在外了。

She is being left out.

Speaker 0

他们现在最喜欢用的是 Snapchat。

Their their mode of choice is Snapchat now.

Speaker 0

Snapchat 有很多弊端。

Well, there's a lot of downside to Snapchat.

Speaker 0

现在,我的神经系统和生理状态已经被她不断发来的手机消息所牵动。

And so now I'm the I, my nervous system, and my physiology is now hooked to her blizzard of time request on my phone.

Speaker 0

你知道吗?我进来之前就把手机关了。

It did you know, I turned it off before I came in here.

Speaker 0

在飞机横跨全国的时候,我一直在拒绝这些请求,只给十五分钟时间之类的。

On the plane flying over the country, I'm denying things and giving fifteen minutes and whatnot.

Speaker 0

所以乔纳森对如何解决这个问题有切实的建议。

So Jonathan has real prescriptions for how to fix that.

Speaker 0

他对如何解决这个问题提出了很好的建议。

He has good suggestions for how to fix that.

Speaker 0

但集体行动这件事你知道,集体行动很难,因为它们是由人类组成的,你根本没法让所有人都同时做同一件事。

But the collective action thing is you know, collective actions are hard because, you know, they're collections of humans, and you just can't get people to all do something at once.

Speaker 0

总会有个叛逃者。

There's always a defector.

Speaker 1

但我觉得,只要我们也在培养那种更缓慢、更费力的知识整合方式。

Well, I think as long as we're also training the other more slow, effortful type integration of knowledge.

Speaker 1

我的意思是,如果社交媒体能有设置选项,让我点击‘娱乐’就好了。

I mean, it'd be wonderful if social media had settings where I could click entertainment.

Speaker 1

那样我就能只看到娱乐内容。

I would just get entertainment stuff.

Speaker 1

然后我就知道我花了多少时间在娱乐上,而不是在学习上,因为我确实从社交媒体中学到了很多。

And then I knew how long I was doing that versus educate me because I do learn a lot from social media.

Speaker 1

我确实努力在社交媒体上学习。

And I certainly try and learn on social media.

Speaker 1

前几天有句话听起来可能微不足道,但关于学会享受时间流逝,它在我心中留下了深刻的印象。

And this, what may sound like kind of a trivial statement the other day and learned to enjoy the passage of time was what sat with me in some way that felt important to me at that moment.

Speaker 1

我一直在用几种不同的视角反思这件事。

And I've been reflecting on it through a couple of different lenses.

Speaker 1

我们显然无法解决这个问题。

We're obviously not going to solve this problem.

Speaker 1

我对觅食时速度与努力之间的关系感到好奇。

I am curious about speed versus effort when foraging.

Speaker 1

让我们回到约会的例子。

Let's take it back to the dating example.

Speaker 1

这个人知道后可能会生气,嗯,我不会透露她是谁,但我说过,注意到了这个长期存在的模式。

This person's gonna kill me for, yeah, I'm not gonna reveal who she is, but you know, I said, listen, I noticed this pattern over time.

Speaker 1

你过早地贬低别人,或者过度兴奋,但最终总是回到同样的地方,心里想:唉,我为什么要这么做?

You discount people early or you get very excited and then it always kind of ends up in the same place where you're like, Ugh, why did I do that?

Speaker 1

我当时就想,好吧,我们不妨试试不同的算法,也许可以更缓慢地收集数据,或者干脆每周多见几次,持续两周后再做决定。

And I was like, Well, let's, you know, so maybe run a different algorithm, maybe start to collect data a little bit more slowly, or maybe, you know, see them more frequently for like two weeks and then make a decision.

Speaker 1

这样你就不会浪费那么多时间了。

So it's not, you didn't waste so much time.

Speaker 1

虽然更频繁意味着花更多时间,但不是在长时间跨度上,你懂吧?

Still more frequently means more time, but not over time, you know?

Speaker 1

所以我们可以改变自己的探索方式。

So we can change our mode of foraging.

Speaker 1

我本人把社交媒体移到了一部旧手机上,然后把它锁在一个超级监狱式的保险箱里,每天有22个小时都无法解锁。

I personally put social media on an old phone and it goes in a supermax prison lockbox that you can't code out of for twenty two hours a day.

Speaker 0

你对自己这么狠?

You do that to yourself?

Speaker 0

是的,我会这么做。

I do.

Speaker 0

你就像那种无法抗拒吃巧克力的人?不,你是直接堵死它。

Not You're like a person that can't avoid eating chocolate, can't No, you block

Speaker 1

巧克力并不是那个原因。

it the chocolate wasn't that.

Speaker 1

我最近读了一篇论文,说即使你的手机正面朝下放在桌子上或包里,只要在同一个房间里,就会降低你的认知表现,即使你并没有意识到手机的存在。

I just, I'd read this paper that was published recently that said that if your phone is upside down on a table or in your bag in the same room, it lowers cognitive performance even if you're not aware of the phone.

Speaker 1

这是在消耗认知资源。

It's Calls to pulling resources.

Speaker 1

是的,资源。

Yeah, resources.

Speaker 1

当手机在另一个房间时,你的认知表现似乎会恢复到之前的较高水平。

It's pulling it's in another room, it seems that your cognitive performance returns to its previously higher levels.

Speaker 1

所以我觉得这很不错。

So I thought that's pretty good.

Speaker 1

于是我开始把手机放在另一个房间,然后我想,我还能把这个做法推进到什么地步?

So I started keeping my phone in the other room and I thought, how much further can I take this?

Speaker 1

所以我认为,对像我这样的人而言,与这些事物保持物理距离是不可妥协的,这感觉非常好。

So I think that the physical distance from things that's non negotiable feels really good to somebody like me.

Speaker 1

眼不见,心不烦

Out of sight, out

Speaker 0

是的

Yeah.

Speaker 0

Of

Speaker 1

也许吧

Maybe.

Speaker 1

不过我想把话题拉回到多巴胺上。

Although I wanna bring this back to dopamine.

Speaker 1

你知道吗,多巴胺系统能否学会通过抵制某些事物来获得动力和愉悦感?

You know, can the dopamine system learn to get motivation states and pleasure from resisting things.

Speaker 1

我认为这种病态的版本可能是这样的:我们做过一期关于厌食症的节目,对大多数人来说食物是令人愉悦的,但真正患有厌食症的人,其奖励系统似乎进入了一种状态——抵制食物反而成了奖励。

I think of a pathologic version of this might be, we did an episode on anorexia where food is rewarding for most people, but for people who have true anorexia, the reward system seems to enter a state where resisting food becomes the reward.

Speaker 0

掌控感很好。

Control feels good.

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