Dr. Lisa Feldman Barrett: How to Understand Emotions

00:00:00.000 | - Welcome to the Huberman Lab Podcast,

00:00:02.280 | where we discuss science and science-based tools

00:00:04.880 | for everyday life.

00:00:05.900 | I'm Andrew Huberman,

00:00:10.320 | and I'm a professor of neurobiology and ophthalmology

00:00:13.360 | at Stanford School of Medicine.

00:00:15.280 | My guest today is Dr. Lisa Feldman Barrett.

00:00:18.200 | Dr. Lisa Feldman Barrett is a distinguished professor

00:00:20.680 | of psychology at Northeastern University.

00:00:23.240 | She also holds appointments at Harvard Medical School

00:00:25.680 | and Massachusetts General Hospital,

00:00:27.840 | where she is the chief scientific officer

00:00:29.920 | of the Center of Law, Brain, and Behavior.

00:00:32.860 | Dr. Barrett is considered one of the top world experts

00:00:35.760 | in the study of emotions,

00:00:37.600 | and her laboratory has studied emotions using approaches

00:00:40.400 | both from the fields of psychology and neuroscience.

00:00:43.800 | Indeed, today you will learn about the neural circuits

00:00:46.320 | and the psychological underpinnings of what we call emotions.

00:00:49.680 | You will learn what emotions truly are

00:00:52.040 | and how to interpret different emotional states.

00:00:54.600 | You will also learn how emotions relate to things

00:00:56.520 | like motivation, consciousness, and affect.

00:01:00.200 | Affect is a term that refers to a more general state

00:01:02.980 | of brain and body that increases or decreases

00:01:05.840 | the probability that you will experience certain emotions.

00:01:08.980 | During today's discussion, Dr. Feldman Barrett

00:01:11.360 | also teaches us how to regulate our emotions effectively,

00:01:14.760 | as well as how to better interpret

00:01:16.220 | the emotional states of others.

00:01:18.120 | You will also learn about the powerful relationship

00:01:20.260 | that exists between our emotional states

00:01:22.800 | and the movement of our body.

00:01:24.840 | In fact, much of today's discussion is both practical

00:01:28.180 | and will be highly informative in terms of the mechanisms

00:01:30.620 | underlying emotions, and it is likely to also be surprising

00:01:34.160 | to you in a number of ways.

00:01:35.640 | It certainly was surprising to me.

00:01:37.040 | I've been a close follower of Dr. Feldman Barrett's work

00:01:39.800 | over many years now, and have always found it

00:01:42.440 | to be tremendously informative.

00:01:44.100 | And when I say her work, I mean both her academic

00:01:46.160 | published papers, as well as her public lectures

00:01:49.080 | that she's given, and her two fabulous books

00:01:51.360 | on emotions and the brain.

00:01:52.480 | The first one entitled "How Emotions Are Made,"

00:01:54.880 | and the second book, which includes information

00:01:57.400 | about emotions, but extends beyond that,

00:01:59.440 | entitled "Seven and a Half Lessons About the Brain."

00:02:02.900 | As you'll see from today's discussion,

00:02:04.520 | Dr. Feldman Barrett is not only extremely informed

00:02:07.860 | about the neuroscience and psychology of emotion,

00:02:09.880 | she's also fabulously good at teaching us that information

00:02:13.520 | in clear terms and in actionable ways.

00:02:16.540 | You'll also notice several times she pushes back

00:02:18.920 | on my questions, in some cases even telling me

00:02:21.720 | that my questions are ill-posed.

00:02:23.440 | And I have to tell you that I was absolutely delighted

00:02:25.760 | that she did that, because you'll see

00:02:27.280 | that every time she did that, it was with the clear purpose

00:02:30.140 | of putting more specificity on the question,

00:02:32.680 | and thereby more specificity and clarity on the answer,

00:02:35.940 | which of course she delivers.

00:02:38.120 | By the end of today's discussion,

00:02:39.780 | you will have both a broad and a deep understanding

00:02:42.600 | of what emotions are, and their origins

00:02:44.920 | in our brain and body.

00:02:46.360 | You will also have many practical tools

00:02:48.780 | with which to better understand

00:02:50.600 | and navigate emotional states.

00:02:52.880 | And moreover, you will have many practical tools

00:02:55.320 | in order to increase your levels of motivation

00:02:57.760 | and better understand your various states of consciousness.

00:03:01.160 | Before we begin, I'd like to emphasize that this podcast

00:03:04.080 | is separate from my teaching and research roles at Stanford.

00:03:06.780 | It is, however, part of my desire and effort

00:03:08.760 | to bring zero cost to consumer information about science

00:03:11.420 | and science-related tools to the general public.

00:03:14.200 | In keeping with that theme,

00:03:15.320 | I'd like to thank the sponsors of today's podcast.

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00:05:42.840 | And now for my discussion with Dr. Lisa Feldman Barrett.

00:05:46.440 | Dr. Lisa Feldman Barrett, welcome.

00:05:49.760 | - Oh, it's my pleasure to be here.

00:05:51.440 | - I've wanted to talk to you for a very long time.

00:05:54.220 | I'd like to talk about emotions.

00:05:57.960 | I think everyone has a sense somehow of what an emotion is,

00:06:02.960 | feeling happy, feeling sad, feeling excited,

00:06:08.720 | feeling curious, perhaps, is even an emotion.

00:06:12.880 | I don't know, you'll tell us.

00:06:14.720 | What are the core components?

00:06:17.000 | What are the sort of macronutrients of an emotion?

00:06:20.720 | Because I know there's a debate about whether or not

00:06:25.040 | we should be talking about emotions versus states,

00:06:28.080 | but what is an emotion?

00:06:30.900 | We all are familiar with what one feels like to us,

00:06:34.440 | but from a scientific perspective,

00:06:36.640 | how do you define an emotion?

00:06:38.640 | - Well, this is a scientist debate about this.

00:06:41.440 | Nobody in the last 150 years has ever been able to agree

00:06:45.880 | on what an emotion is.

00:06:47.820 | And I think from my perspective,

00:06:51.400 | the interesting but tricky bit is that anytime you wanna

00:06:54.840 | talk about what the basic building blocks are of emotion,

00:06:58.320 | none of those basic building blocks

00:06:59.920 | are specific to emotion.

00:07:01.340 | So for example, there are a group of scientists

00:07:04.400 | who will tell you, well, an emotion

00:07:05.960 | is a coordinated response where you have a change

00:07:10.960 | in some physical state, a change in the brain,

00:07:15.080 | a change in the physical state which leads you

00:07:19.480 | to make a particular facial expression.

00:07:22.960 | So you've got physiological changes in the body,

00:07:25.400 | changes in the brain, changes in the face

00:07:27.800 | or in motor movements, okay?

00:07:30.120 | But that describes basically every moment of your life.

00:07:35.040 | Your face is always moving in some way.

00:07:37.720 | If it wasn't, you would look like an avatar basically.

00:07:41.240 | So we're constantly engaged in movements

00:07:43.920 | and those movements have to be coordinated

00:07:46.640 | with the physiological changes in the body

00:07:48.680 | because whether we're in a state

00:07:51.760 | that we would conventionally call emotion or not

00:07:54.600 | because the physiology is supporting those,

00:07:57.800 | it's supporting the glucose and the oxygen

00:08:00.320 | and all the things that you need

00:08:01.480 | to make movements of your body.

00:08:04.040 | And of course, all these movements

00:08:06.080 | are being coordinated by your brain.

00:08:07.560 | So of course, there's a coordinated set of features

00:08:11.760 | that doesn't really describe how emotions are distinct

00:08:15.400 | from any other experience that you have.

00:08:17.880 | But the claim was for a really long time

00:08:22.880 | that there would be diagnostic patterns, okay?

00:08:27.160 | So when something triggered fear,

00:08:29.800 | you would have an increase in heart rate

00:08:32.120 | and you would have a propensity to run away or to freeze

00:08:37.120 | or not just to fall asleep,

00:08:40.680 | although that is something animals do

00:08:42.440 | when they are faced with a predator,

00:08:44.240 | but that's not part of the Western stereotype for fear.

00:08:47.200 | So that wasn't what scientists were looking for.

00:08:50.080 | And also that you would make a particular facial expression,

00:08:53.920 | which was presumed to be the universal expression of fear

00:08:57.800 | where you widen your eyes and you gasp like,

00:09:00.080 | (gasps)

00:09:02.800 | that facial, set of facial movements in other cultures,

00:09:07.480 | like in Melanesian culture, for example,

00:09:09.960 | is a symbol of threat where you are threatening someone,

00:09:14.440 | you are threatening them with aggression basically,

00:09:16.880 | is a war face.

00:09:18.560 | But in Western cultures,

00:09:20.200 | that's the face that Western scientists believed

00:09:23.800 | was the part of that distinctive pattern for fear.

00:09:29.240 | And so the way that scientists defined emotion

00:09:33.640 | for a long time was these kind of states

00:09:37.320 | where you'd see this diagnostic ensemble of signals.

00:09:41.760 | And that would mean that anytime someone showed

00:09:45.480 | one of those signals,

00:09:47.800 | they may move their face in a particular way

00:09:49.560 | or their heart increased at a particular time,

00:09:52.080 | you'd be able to diagnose them as being in a state of fear

00:09:55.480 | as opposed to a state of anger or sadness or whatever.

00:09:58.640 | The empirical evidence just doesn't bear that out.

00:10:03.640 | And so it was kind of a mystery.

00:10:06.000 | The mystery is how is it that you feel angry or sad

00:10:11.000 | or happy or full of gratitude or awe?

00:10:18.240 | How is it that you experience these moments,

00:10:23.720 | but scientists can't find a single set of physical markers

00:10:28.720 | that correspond with each state distinctively, right?

00:10:35.120 | That in a way that you could tell them apart.

00:10:38.400 | That was a really big puzzle for a really long time.

00:10:41.840 | - I have to ask you about this perhaps myth,

00:10:47.440 | perhaps truth about facial expressions and emotions,

00:10:51.440 | because as you were explaining the core components

00:10:55.080 | of emotions, I had to think back

00:10:59.000 | to the classic textbook images of the different faces

00:11:03.280 | associated with fear, with delight, with confusion,

00:11:07.100 | on and on.

00:11:08.140 | We will get to that and your opinions on that,

00:11:11.000 | scientifically informed opinions, of course.

00:11:14.480 | But there is a bit of a myth that the emotion system

00:11:19.980 | and the facial expression system run in both directions.

00:11:24.020 | For instance, people will say, if you smile,

00:11:29.020 | it's harder to feel sad or anxious.

00:11:31.660 | I can't say that's been my experience,

00:11:35.540 | but I very well could be wrong.

00:11:37.700 | So we know that when people's emotional states change,

00:11:42.700 | their facial expressions often will change, right?

00:11:45.440 | If you see someone crying on the street

00:11:48.300 | versus somebody smiling really big,

00:11:50.340 | we can make some assumptions about what might be going on

00:11:53.400 | internally for them.

00:11:54.840 | But put simply, is it true that changing

00:11:58.020 | one's facial expression can direct shifts in the brain

00:12:01.680 | and body, perhaps, that change our emotional states?

00:12:06.760 | - If you'll permit me, what I would say

00:12:09.860 | is that your question is ill-posed.

00:12:14.360 | So first of all, it presumes that there's an emotion system

00:12:18.180 | and that there's a facial expression system.

00:12:21.780 | Now, clearly there's a system for moving facial muscles,

00:12:25.320 | okay, but a movement is not the same as an expression.

00:12:30.320 | A movement is a movement.

00:12:32.900 | An expression is an interpretation

00:12:35.300 | of the meaning of a movement.

00:12:37.420 | Not all movements of the face are expressions.

00:12:42.020 | And this is a problem.

00:12:45.340 | It's a problem in science.

00:12:46.880 | It's often the case, I think, in my experience,

00:12:51.540 | in the science of emotion, but elsewhere too,

00:12:53.860 | that scientists, in their efforts to make their work

00:12:58.860 | meaningful to people, will try to interpret their findings

00:13:05.100 | in ways that the average person would find interesting.

00:13:12.260 | Or the way that a physician would find interesting,

00:13:14.720 | or a teacher, or what have you,

00:13:15.860 | to be able to use this information.

00:13:18.000 | But then they forget that they're actually

00:13:20.620 | making an interpretation and they start to refer

00:13:23.740 | to their observations with the labels of interpretation.

00:13:27.760 | So facial movements are facial movements.

00:13:29.620 | People move their faces and those movements have meaning,

00:13:33.540 | but they're not always to express an internal state.

00:13:37.400 | In fact, one might think that they're very rarely

00:13:40.520 | to express an internal state.

00:13:42.780 | So I don't know that there's

00:13:44.640 | a facial expression system either.

00:13:46.580 | So there's certainly, like I said,

00:13:49.700 | there's circuitry for moving a face,

00:13:52.600 | but what those movements mean is highly variable.

00:13:57.600 | And so that would be my second point,

00:14:02.220 | that where I would say,

00:14:03.820 | when you see someone crying on the street,

00:14:06.040 | you are not looking only at their face.

00:14:08.500 | You might be aware that you're focusing on their face.

00:14:13.500 | That might be the part of the entire sensory ensemble

00:14:17.220 | that you are focusing your attention on.

00:14:19.620 | But your brain is taking in an entire ensemble of signals.

00:14:23.380 | As you know, it's taking in not just the movements

00:14:28.080 | of the face, the tears, or whatever,

00:14:29.940 | it's taking in all of the entire sensory array,

00:14:33.660 | the sounds, the smells,

00:14:35.200 | what's going on inside your own body.

00:14:37.320 | Your brain is being bombarded with signals

00:14:40.740 | from all of those sources.

00:14:42.700 | And when it's making a meaning out of any signal,

00:14:46.560 | it's doing it in an ensemble of signals.

00:14:48.660 | So research shows that babies' cries

00:14:53.180 | aren't acoustically specific

00:14:55.700 | to when they're tired or hungry.

00:14:57.520 | I can show you a video without context

00:15:01.620 | and show you someone crying,

00:15:03.220 | and you might make a judgment.

00:15:06.020 | You might make the stereotypic judgment in the West.

00:15:08.480 | Oh, that person is sad.

00:15:09.720 | And then we pan out and really,

00:15:11.640 | it's a little girl whose dad just came home

00:15:14.360 | from Iraq or something, right?

00:15:15.820 | So brains are always interpreting faces in context.

00:15:19.760 | They're making guesses.

00:15:20.880 | This is something that I've talked about quite a bit,

00:15:23.400 | that we don't read movements in people.

00:15:26.140 | We don't read emotions in facial expressions.

00:15:29.040 | We make inferences about the emotional meaning

00:15:32.680 | of facial movements.

00:15:34.620 | And we do it in an ensemble of other signals,

00:15:37.620 | the context, if you will.

00:15:41.060 | And that's really what's happening.

00:15:43.160 | So do I think that there's feedback

00:15:48.160 | from the face to the brain?

00:15:51.840 | Sure.

00:15:53.000 | I mean, there's feedback from every muscle,

00:15:57.280 | but there's this constant conversation

00:16:00.260 | between the brain and the body.

00:16:03.540 | The brain is sending motor commands.

00:16:05.360 | The body has sensory surfaces,

00:16:08.140 | which are sending signals back to the brain.

00:16:10.060 | So if the face is influencing the brain,

00:16:14.800 | it's doing so in a way that's not special.

00:16:17.760 | It's doing it in a way that works

00:16:22.080 | for all other parts of your body too.

00:16:25.440 | And I guess what I would say,

00:16:28.260 | this is kind of a long-winded answer,

00:16:29.440 | but over time, your brain has learned

00:16:34.440 | that certain patterns of signal over time recur.

00:16:39.180 | And so if you're smiling,

00:16:43.820 | if your brain is telling your facial muscles

00:16:48.480 | to move in a particular way that looks like smiling,

00:16:51.240 | it's happening in a larger ensemble of signals.

00:16:54.260 | And then the brain is predicting what's gonna happen next

00:16:57.240 | because it's learned over time

00:16:59.180 | what happens next so probabilistically.

00:17:02.920 | So if you think about that as cause, then sure.

00:17:07.780 | But it's not this simplistic kind of idea

00:17:11.660 | that an emotion is triggered.

00:17:14.340 | It causes facial muscles to move in a particular way.

00:17:21.900 | And therefore, if you just pose your face

00:17:24.620 | in that particular arrangement,

00:17:28.520 | that will somehow feed back to the emotion system

00:17:31.000 | and change that system.

00:17:32.320 | 'Cause there is no emotion system in your brain.

00:17:37.320 | And the causation just isn't that,

00:17:41.520 | it's not that simplistically mechanistic.

00:17:44.500 | - That makes sense to me.

00:17:45.340 | I frankly never bought the idea

00:17:49.340 | that just smiling would make me feel happy,

00:17:52.640 | especially if my internal state was not one of happiness,

00:17:57.000 | like fighting the internal state.

00:17:58.620 | Also in the early 2000s, I think it was,

00:18:02.000 | there was a lot of discussion

00:18:03.080 | about how positioning the body in certain ways,

00:18:06.320 | taking up more space would allow people

00:18:08.320 | to feel more powerful.

00:18:09.600 | And some of these studies argued

00:18:13.900 | that there were even hormonal shifts associated

00:18:16.080 | with taking up more space

00:18:18.120 | that were associated with feelings of empowerment.

00:18:20.160 | And then when shrinking of oneself

00:18:22.020 | was associated with elevated cortisol states.

00:18:24.520 | And as I say all this, I want to be clear

00:18:27.420 | that I do not take a simplistic view

00:18:31.040 | of the nervous system or endocrine system.

00:18:32.660 | And I don't think that you were implying that either.

00:18:36.400 | Just want to make sure that anyone listening

00:18:37.720 | and watching isn't thinking that,

00:18:39.800 | for instance, that cortisol is bad.

00:18:41.160 | Cortisol is wonderful and essential.

00:18:42.700 | You just need it regulated properly.

00:18:45.000 | Or that the idea that the body and emotional states

00:18:50.000 | are inextricably linked makes a ton of sense to me.

00:18:53.340 | But the idea that you could just, you know,

00:18:55.640 | grab onto one of the nodes in the,

00:18:59.440 | now I have to be careful not to say emotion system,

00:19:01.820 | like position of the body,

00:19:04.000 | like being hunched over makes you depressed.

00:19:06.080 | No, that never made sense to me.

00:19:07.280 | Taking up more space makes you feel more powerful.

00:19:10.400 | That doesn't, it can't be that way.

00:19:12.600 | And yet we were told for about a decade through,

00:19:15.360 | especially through popular press, that this stuff was true.

00:19:19.920 | And so what I love about your work is that it includes

00:19:24.460 | a neuroanatomical, a psychological, a network perspective,

00:19:29.460 | that there isn't one seat of emotions and so on.

00:19:32.680 | So if we could go a little bit further

00:19:35.160 | into the facial expression piece for a moment.

00:19:37.180 | - Sure.

00:19:38.780 | - I was taught in my psychology and neuroscience textbooks,

00:19:41.820 | 'cause it was right there in front of me,

00:19:43.500 | that there were some core categories of facial expression

00:19:48.480 | that were universal across cultures

00:19:50.480 | that conveyed something about the internal state

00:19:53.200 | of the person, that the downward, you know,

00:19:55.760 | lips in the corner and maybe even a furrowing of the brow

00:19:59.300 | was associated with negative valence states,

00:20:02.080 | like sadness, perhaps even depression,

00:20:04.760 | that the opposite of upward turn corners of the mouth

00:20:08.040 | and widening of the eyes was delight and excitement.

00:20:11.580 | Some of that feels pretty true to my experience,

00:20:13.840 | but how do you and other serious scientists of emotions

00:20:18.840 | view that somewhat classic literature now?

00:20:24.180 | - Yeah, so I'll just say that my journey here,

00:20:28.180 | my scientific journey, was not one of attempting

00:20:34.040 | to overturn a century's worth of, are we allowed to swear?

00:20:39.040 | Bullshit, basically.

00:20:42.620 | I mean, it's just, it's like, it's stereotype,

00:20:45.240 | it's basically Western stereotypes

00:20:47.560 | enshrined as scientific fact.

00:20:51.160 | And that sounds like a pretty harsh thing to say,

00:20:54.660 | but I think I pretty much stand by that at this point.

00:20:58.260 | But for me, when I was a graduate student,

00:21:02.480 | when I was an undergraduate in psychology

00:21:06.420 | and in physiology and in anthropology, you know,

00:21:09.160 | I also had read that Darwin said that there were

00:21:13.060 | these distinctive facial expressions

00:21:15.620 | that were coordinated with specific emotional states,

00:21:20.100 | the specific states of the nervous system.

00:21:22.100 | This was Darwin's view.

00:21:24.500 | And I assumed it was correct

00:21:28.140 | until I started to try to use that information in the lab

00:21:34.660 | and everything fell apart, you know?

00:21:39.100 | So when you show someone in a laboratory,

00:21:43.680 | like a student or somebody from the community,

00:21:47.600 | a face, a disembodied face,

00:21:50.400 | where the person's eyes are widened in the face

00:21:53.640 | and they're gasping like a stereotypic fear expression,

00:21:58.000 | most of the time they don't know what it is.

00:22:00.860 | And so I would try to use these faces

00:22:04.180 | and as stimuli and experiments,

00:22:06.620 | and they weren't working the way that they were supposed

00:22:09.540 | to work.

00:22:10.380 | And there were really going all the way back

00:22:14.700 | to the beginning of psychology,

00:22:15.940 | there were always debates about whether or not

00:22:18.100 | this was actually accurate.

00:22:19.620 | And there's a really interesting story

00:22:21.100 | about how Darwin came to this idea,

00:22:24.140 | which I can tell you about,

00:22:26.220 | but it's not because he cared about emotion.

00:22:28.980 | And he was basically taking his own very Western views

00:22:34.080 | about emotion to make some claims about evolution actually.

00:22:39.080 | So I have more to say about that

00:22:43.660 | and about why it's a problem to take anything

00:22:47.740 | that anybody said, even Darwin from 150 or so years ago

00:22:52.740 | or whatever it is and treat it like it's a modern text.

00:22:58.060 | He was writing at a particular time for a particular purpose

00:23:01.580 | and that doesn't necessarily mean that whatever he wrote

00:23:04.960 | is true, but I'll just tell you what the evidence says.

00:23:09.640 | That there has been in psychology a debate,

00:23:17.200 | really vicious debate actually for probably 50 years

00:23:21.640 | about the nature of facial expressions

00:23:23.900 | and whether they're universal

00:23:25.420 | and whether there's this one-to-one correspondence

00:23:27.500 | between a particular face and like a facial configuration

00:23:31.900 | in a particular emotional state,

00:23:33.380 | smiling in happiness, scowling in anger,

00:23:35.540 | wrinkling your nose in disgust.

00:23:37.880 | And so in 2016, I think,

00:23:42.880 | the Association for Psychological Science tasked me

00:23:48.320 | and some other senior scientists

00:23:51.820 | with attempting to write a white paper,

00:23:54.900 | a consensus paper on what the literature actually shows.

00:23:58.380 | So what does the research actually show?

00:23:59.740 | If you read all the research,

00:24:01.280 | can you find a pattern there?

00:24:05.060 | Does it actually reveal anything

00:24:06.740 | about whether or not facial expressions are universal,

00:24:09.080 | particularly for emotion?

00:24:10.380 | And the way they do this,

00:24:13.060 | they have a journal for this purpose

00:24:15.220 | for taking a widely held belief that is highly debated

00:24:19.680 | and bringing together a panel of experts

00:24:21.980 | who disagree with each other at the outset

00:24:24.060 | and they have to work together

00:24:25.780 | to see if they can come to consensus over the data.

00:24:29.160 | And this is something that people have tried in the past.

00:24:35.020 | And I mean, they're really vicious.

00:24:37.980 | People have been vicious with each other over this question.

00:24:41.460 | So when we brought together a group of people,

00:24:46.460 | so several people refused to serve,

00:24:48.660 | senior scientists refused to serve on this panel, but-

00:24:51.300 | - Out of fear of losing their funding or something?

00:24:55.500 | - You know, that's a whole other conversation

00:24:57.260 | about why certain scientists would not want to engage

00:25:02.260 | with people who disagree with them.

00:25:07.620 | That's an interesting conversation to have,

00:25:09.460 | but I don't think it's as simple actually

00:25:12.700 | as just their careerist or they care about their money

00:25:17.220 | or funding or whatever.

00:25:18.820 | That would be an easy answer,

00:25:19.780 | but I don't actually think that's what's going on,

00:25:21.540 | but that's another sort of...

00:25:23.700 | But anyway, so there were five of us who got together,

00:25:26.400 | all senior scientists, all from different fields.

00:25:30.700 | Some of us hadn't met each other before.

00:25:32.460 | We all knew of each other, of course.

00:25:34.740 | And we met over Zoom for two and a half years.

00:25:38.420 | This is pre-COVID 'cause people were all over the world.

00:25:41.860 | And we read over a thousand papers.

00:25:44.900 | So I was the only one in this group of the five of us

00:25:49.900 | who my starting hypothesis was that facial movements

00:25:54.900 | are meaningful, but they're not...

00:25:58.260 | There's no one-to-one correspondence

00:26:00.260 | between a particular facial configuration

00:26:03.520 | like a scowl and anger.

00:26:07.500 | Not just that it would vary across cultures,

00:26:09.660 | but that it varies for you across situations.

00:26:14.780 | I mean, do you scowl every time you're angry?

00:26:17.620 | I don't scowl every time I'm angry.

00:26:19.580 | In fact, and I also scowl at times when I'm not angry.

00:26:22.340 | So, and there are scientific reasons to think

00:26:25.900 | that the collection of facial expressions that people make

00:26:30.900 | when they're angry or when they're sad or whatever

00:26:33.460 | would be highly variable.

00:26:35.140 | So that was my starting position.

00:26:36.740 | And then there were varying four guys.

00:26:40.260 | So there was, I just refer to them as the guys

00:26:42.460 | 'cause it was me and four guys.

00:26:43.980 | And the guys, they all to some extent thought

00:26:47.820 | that facial expressions were universal,

00:26:49.140 | but they had differing reasons for hypothesizing that.

00:26:54.000 | And they also had different commitments,

00:26:57.720 | degrees of commitment to that position.

00:27:01.920 | But we right off the bat sort of agreed

00:27:04.180 | that it didn't matter who was right.

00:27:07.000 | That was just not relevant.

00:27:09.020 | The only thing that mattered was that we could come

00:27:12.620 | to the consensus over the data.

00:27:15.460 | And if we couldn't, we had to really pinpoint why.

00:27:18.980 | Like, so what would be the critical experiments

00:27:21.620 | that would have to be done in order for us

00:27:24.220 | to come to consensus over the data?

00:27:26.260 | And we also agreed that we had all kinds

00:27:30.460 | of contingency set up.

00:27:31.440 | So, you know, you've got five senior people

00:27:34.140 | who are all running big labs and they're investing,

00:27:37.740 | you know, upwards of three years working on a paper.

00:27:40.160 | So if we can't come to consensus, what are we gonna do?

00:27:43.120 | Are we gonna write one paper

00:27:45.200 | and sort of write about the process?

00:27:47.000 | Or are we gonna write separate papers or, you know?

00:27:49.920 | But we had all these contingencies laid out.

00:27:52.920 | But the key here I think is that we agreed

00:27:55.360 | that we were not gonna be adversarial about it

00:27:58.000 | 'cause it didn't matter who was right.

00:28:00.120 | And in fact, if somebody had to admit they were wrong

00:28:02.140 | and someone was gonna have to admit they were wrong,

00:28:04.160 | I mean, it turns out all of us were wrong about something,

00:28:06.180 | but we were gonna be like supportive of each other

00:28:11.180 | and really encourage each other.

00:28:15.140 | Because, you know, being wrong is no one likes to be wrong,

00:28:17.860 | but for scientists to admit they're wrong is hard.

00:28:21.060 | And it's something that we should encourage each other to do

00:28:23.620 | I think more and more publicly.

00:28:25.820 | And I think the people who do that are really brave.

00:28:28.820 | And so that was my position and they all agreed.

00:28:31.460 | And the long story short here is that

00:28:35.960 | two and a half years, a thousand papers later,

00:28:39.540 | we all very reasonably came to consensus

00:28:42.220 | that there was no evidence for facial expressions

00:28:45.060 | of emotion being universal.

00:28:46.800 | And that instead what there's clear evidence of

00:28:50.900 | is that facial expressions,

00:28:54.340 | the way that people move their faces

00:28:57.380 | in moments of expression is highly variable.

00:29:02.700 | Meaning sometimes in anger you scowl meta-analyses,

00:29:07.700 | so statistical summaries of many, many, many studies,

00:29:11.140 | even in the West show that people scowl

00:29:15.680 | about 35% of the time when they're angry,

00:29:19.440 | which is more than chance.

00:29:21.280 | So it gets you a good publication in, you know,

00:29:23.480 | the proceedings of the National Academy.

00:29:26.240 | But that means 65% of the time

00:29:28.460 | people are moving their faces in other meaningful ways.

00:29:31.960 | That's not scowling.

00:29:33.200 | So if you actually used a scowl or even, you know,

00:29:38.760 | a scowl in blood pressure or, you know,

00:29:40.880 | just maybe not one signal, but like a couple of signals,

00:29:43.700 | but you would be wrong more than half the time.

00:29:46.500 | You would miss more than half the cases.

00:29:48.780 | And even more importantly, I think,

00:29:52.420 | that's the reliability question.

00:29:54.060 | So there's low reliability for the correspondence

00:29:58.340 | between a scowl and anger.

00:30:01.220 | It's above chance.

00:30:02.220 | So scowling is one expression of anger,

00:30:06.340 | but it's certainly not the dominant one.

00:30:08.820 | And there is no dominant one.

00:30:10.220 | It's just highly variable,

00:30:11.240 | depending on the situation that you're in.

00:30:13.420 | So sometimes when I'm angry,

00:30:14.900 | I sit quietly and plot the demise of my enemy.

00:30:18.040 | You know, sometimes I smile in anger.

00:30:20.600 | Sometimes I cry in anger.

00:30:22.320 | It really depends on the situation.

00:30:24.320 | But more importantly, half of the scowls that people make

00:30:30.120 | are not related to anger.

00:30:32.380 | That means that the specificity is, again,

00:30:38.120 | higher than chance,

00:30:40.440 | but not that much higher than chance.

00:30:44.320 | So if you see someone scowling,

00:30:46.320 | the chances are that they might not be angry.

00:30:51.020 | They might be concentrating really hard

00:30:53.180 | or they might have gas.

00:30:55.380 | I mean, there are a lot of reasons why people make a scowl.

00:30:59.440 | And we found this for every emotion category

00:31:02.380 | that had ever been studied.

00:31:03.540 | And I want you to notice what I just did there.

00:31:05.740 | I'm no longer referring to an emotion

00:31:07.980 | as if it's an entity or a thing.

00:31:10.260 | So anger isn't one thing.

00:31:12.340 | It's a category of things, a grouping of things.

00:31:15.380 | - And if I'm not mistaken, it includes verbs, right?

00:31:17.860 | Like anger as a set of verb actions in the brain and body.

00:31:22.860 | - Yes. - It's a process.

00:31:24.460 | It's not an event. - It's a process.

00:31:25.620 | Exactly. It's not a noun.

00:31:27.020 | It's a verb and it's a process.

00:31:29.800 | But the point is that it's a highly variable grouping

00:31:34.800 | of instances if you are talking

00:31:38.620 | about all instances of anger.

00:31:40.680 | All instances of anger that you have ever experienced

00:31:43.480 | or witnessed is a highly variable grouping of instances

00:31:48.480 | that vary.

00:31:50.240 | That doesn't mean they're random,

00:31:52.260 | but what the body does in anger

00:31:54.560 | depends on what the physical movements will be in anger.

00:31:57.420 | And that depends on the situation that you're in

00:32:00.060 | and what your goal is.

00:32:02.100 | And there are ways to talk about that in neuroscience terms,

00:32:06.280 | which are a little more precise,

00:32:07.720 | but the important thing to understand here, I think,

00:32:10.600 | is that we're only talking about Western cultures now.

00:32:14.300 | The minute that you go outside of the West

00:32:17.580 | or even to the East,

00:32:20.100 | I mean, so there are other cultures that have been studied

00:32:24.540 | like China and cultures in China and Japan and Korea,

00:32:29.540 | they all have access to knowledge

00:32:33.420 | about Western cultural practices and norms.

00:32:35.780 | So what happens when you go to remote cultures,

00:32:40.340 | which have much less access?

00:32:43.140 | So it's not like they have no access

00:32:44.840 | because we live in a globalized world.

00:32:47.040 | So even hunter gatherers in Tanzania, the Hadza,

00:32:50.120 | have access to Western practices and norms,

00:32:53.020 | but much less, much less.

00:32:55.300 | And we did do that and all bets are off there.

00:33:00.300 | I mean, most of the time they don't even understand

00:33:05.540 | or experience facial movements

00:33:07.260 | as having anything to do with emotion.

00:33:09.500 | - So if they saw an emoji of a smiley face,

00:33:12.180 | would they just assume it was a couple,

00:33:14.580 | they might think it's a face

00:33:16.580 | because as we both know,

00:33:17.980 | there's some fairly hardwired brain circuitry

00:33:20.160 | for the two eyes and a line beneath it

00:33:23.800 | and something in the middle that's pseudo nose,

00:33:26.180 | that organization of just spatial features

00:33:29.440 | cues up face for most primates, including us.

00:33:32.560 | - Although it's really interesting that you say that

00:33:33.760 | because yes, of course that's true,

00:33:34.960 | but it's not there at birth.

00:33:36.320 | What's there at birth is a preference

00:33:39.200 | for that configuration, right?

00:33:41.760 | So it's like there's some,

00:33:44.140 | and we could talk about why that's there,

00:33:45.760 | it's actually very controversial,

00:33:47.200 | but what babies, what newborns orient to,

00:33:51.120 | they orient to that configuration,

00:33:54.520 | but it doesn't have to be a face.

00:33:56.620 | And then very quickly they start learning faces

00:33:59.240 | because they're exposed to face.

00:34:00.960 | I mean, really the first three months of life

00:34:02.760 | is almost like a massive continuous tutorial

00:34:05.900 | on what faces are because they're being fed.

00:34:09.960 | - And everyone's in your face.

00:34:11.080 | I saw a baby last night and you see the baby,

00:34:14.000 | some friends have an unbelievably cute baby,

00:34:16.840 | the big cheeks and there's this desire

00:34:18.960 | to see the baby smile, right?

00:34:20.840 | So you do the things that,

00:34:21.920 | and if the baby shows some sort of facial expression

00:34:24.280 | that makes it seem like it's a little bit resistant

00:34:27.520 | to what you're doing, you stop doing it,

00:34:28.960 | you change up your strategy.

00:34:30.380 | And then when baby cracks a smile,

00:34:33.200 | now I'm going to assume that the baby

00:34:35.100 | may or may not have been happy

00:34:36.400 | inside that little baby head.

00:34:39.500 | But when they do, there's a reciprocity, then we smile.

00:34:43.560 | And so there's a template that's very robust.

00:34:46.120 | - Right, but I want you to notice though that,

00:34:48.160 | so first of all, I'm not saying that recognizing faces,

00:34:52.960 | a face as a face is not hardwired.

00:34:55.240 | It is, but it's hardwired not by genes alone, right?

00:35:00.000 | And in fact, there's a really wonderful book

00:35:01.480 | called "Not by Genes Alone."

00:35:02.960 | Basically, there's cultural inheritance.

00:35:05.880 | We have the kind of nature that requires nurture.

00:35:08.880 | We have the kind of genes that require early learning.

00:35:12.080 | We need wiring instructions from the world

00:35:14.620 | to get the rest of the information

00:35:16.180 | that we need to be competent,

00:35:17.440 | culturally competent in our lives.

00:35:20.480 | And that starts at birth.

00:35:23.140 | It probably starts before birth even.

00:35:27.000 | But in third trimester, there's some evidence of learning,

00:35:30.200 | fetal learning, even in the third trimester.

00:35:32.400 | So the point is not that people aren't hardwired

00:35:37.400 | for viewing faces or recognizing faces,

00:35:40.100 | it's just where does that hard wiring come from?

00:35:41.900 | It's not by genes alone.

00:35:43.120 | Genes aren't the blueprint.

00:35:44.480 | The brain is expecting certain inputs from the world

00:35:46.860 | and it needs that because infant brains

00:35:49.160 | are wiring themselves to their world.

00:35:51.300 | And part of that world is people making faces

00:35:53.300 | and smiling.

00:35:54.220 | And those people happen to also be the ones

00:35:56.180 | who are maintaining that baby's nervous system.

00:35:59.340 | I mean, there is reward learning, right?

00:36:01.980 | Or reinforcement learning right off the bat

00:36:04.220 | because these are the people who keep you comfortable.

00:36:07.400 | They are the ones who feed you.

00:36:09.240 | They're the ones who help you get to sleep

00:36:11.560 | and so on and so forth.

00:36:12.480 | And so you're gonna be very, very sensitive

00:36:14.480 | to changes in the contingencies of their behavior.

00:36:17.660 | Your brain as a pattern learner

00:36:19.720 | is just gonna learn those patterns.

00:36:21.460 | If we know that smiling is a cue for happiness,

00:36:26.460 | it's 'cause we've learned it.

00:36:29.700 | And that doesn't mean that that learning isn't hardwired.

00:36:33.420 | It just means that that information got into your brain

00:36:37.180 | by cultural inheritance,

00:36:39.420 | which is a part of evolutionary theory

00:36:42.760 | in the extended evolutionary synthesis,

00:36:45.640 | not in the original formulation

00:36:49.780 | that some people still kind of stick to.

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00:37:50.660 | - So it's far more nuanced than it was presented to me

00:37:54.840 | in those textbooks,

00:37:55.880 | and it sounds like it was outright wrong on many dimensions.

00:37:58.780 | - Well, can I just mention one thing, though?

00:38:00.300 | - Please.

00:38:01.200 | - This is really serious stuff.

00:38:02.840 | Like, sometimes people think,

00:38:04.880 | "Well, you know, what's the big deal?"

00:38:06.700 | This is such a big deal.

00:38:08.620 | I'll tell you why it's a big deal.

00:38:10.220 | Because in our culture,

00:38:12.300 | people believe that they can read mental states

00:38:16.320 | of other people by their face.

00:38:18.200 | And they believe it so much

00:38:20.480 | that it's enshrined in the legal system.

00:38:23.180 | And there are people who lose their lives

00:38:28.620 | because juries believe

00:38:32.700 | that they can read remorse or the lack of it.

00:38:36.300 | And in fact, there was just a case,

00:38:38.500 | you know, last year, I believe,

00:38:42.380 | where, you know, the Innocence Project got involved

00:38:47.040 | because there was a woman who was on death row.

00:38:48.720 | And what put her on death row

00:38:50.740 | was a police officer's claim

00:38:53.860 | that he could read her emotions

00:38:57.620 | by the comportment of her face and her body.

00:39:01.960 | And, you know,

00:39:05.900 | it was possible to get a stay of execution

00:39:08.960 | so that she could be retried and, you know.

00:39:13.760 | So I'm not saying she was guilty or not guilty.

00:39:15.540 | I'm just saying what put her on death row

00:39:19.900 | was evidence that would not be admissible

00:39:22.300 | in a scientific way now.

00:39:27.140 | And there are lots of cases where judgments are made

00:39:32.140 | that end up impacting people's lives

00:39:35.080 | in pretty serious ways.

00:39:36.800 | So this is a really serious thing.

00:39:40.320 | And it's puzzling to me

00:39:45.200 | why it's so, it's got such traction,

00:39:48.720 | this idea that there are these universal expressions

00:39:52.720 | that we can use to read each other, you know.

00:39:56.720 | It's just not true.

00:39:58.900 | I mean, the science just, it's so overwhelmingly,

00:40:02.060 | I feel like, you know, scientists,

00:40:04.300 | I don't like to use the T word, you know, the F word, fact.

00:40:08.160 | You know, it's a scary word, T word, truth.

00:40:10.880 | But I think in this case, I feel like I can really,

00:40:13.640 | at least with a little T, I can use it.

00:40:16.220 | You probably have particular facial movements

00:40:19.920 | that you make on a regular basis that are tells for you.

00:40:23.200 | I know I do.

00:40:24.320 | You know, my husband can look at my actions

00:40:26.920 | and he can make really decent guesses

00:40:29.040 | about what's going on for me upstairs, right?

00:40:31.620 | But that's because he's known me for 30 years,

00:40:33.860 | actually 30 years today, I should just say that we

00:40:36.680 | met each other 30 years ago today.

00:40:38.400 | But he's, you know, brains are pattern learners.

00:40:40.560 | So I'm not saying that everything is random

00:40:42.620 | and like there's no, it's all noise.

00:40:43.880 | I'm saying that there just aren't these, you know,

00:40:47.740 | universal templates.

00:40:49.140 | They just, it's not like that.

00:40:50.480 | And we really have to stop assuming

00:40:53.840 | that there are.

00:40:55.200 | - Well, I'm so glad that you're getting

00:40:57.840 | that message out there.

00:40:58.680 | And I'm very thankful that you highlighted the seriousness

00:41:02.480 | of these myths that have propagated.

00:41:06.960 | And that's a perfect segue into what I was already

00:41:10.020 | going to ask, which is it's based on something

00:41:13.040 | that I think is in very much agreement

00:41:14.920 | with what you're saying.

00:41:15.940 | A previous guest on this podcast,

00:41:17.920 | I think it was our first guest episode,

00:41:19.640 | Dr. Carl Deisseroth, colleague of mine at Stanford,

00:41:22.660 | incredible bioengineer, really, you know,

00:41:26.440 | 0.01% in his category of science,

00:41:30.060 | as well as a practicing psychiatrist said something

00:41:33.920 | which really stuck with me over the years,

00:41:35.800 | which I once heard him say, you know,

00:41:39.020 | we don't really know how other people feel at all.

00:41:41.720 | In fact, most of the time, we don't even know how we feel.

00:41:45.440 | And that prompted the question for me about how good

00:41:51.200 | or poor are we at gauging our own emotional states,

00:41:55.300 | and in particular, at labeling them,

00:41:57.380 | both to others and for ourselves.

00:41:59.280 | And so here's the direct question.

00:42:01.680 | Is language sufficient to capture

00:42:07.040 | this incredibly complex thing that we're calling emotions?

00:42:11.260 | So for instance, the other day I was in New York

00:42:12.960 | with my sister, then she left, I went out for a bit,

00:42:15.080 | I was having a pretty good day,

00:42:15.980 | and then I returned to the place where I was staying,

00:42:17.960 | and I was hit with this feeling of intense loneliness.

00:42:21.760 | And I don't know why, and then I had a bunch of ideas

00:42:24.080 | about how that related to growing up,

00:42:26.880 | and I was gonna see friends the next day,

00:42:29.080 | and I'm an adult, and so I could use

00:42:30.440 | some top-down regulation and say,

00:42:32.800 | oh, you know, maybe I'm a little tired,

00:42:34.560 | or I didn't, 'cause I hadn't slept as well the night before.

00:42:37.480 | I've been pretty rested recently.

00:42:38.800 | And then I actually wrote in my journal,

00:42:40.500 | I said, you know, maybe most of feeling good

00:42:42.400 | is being pretty well rested and not in any physical pain.

00:42:45.420 | That's a big part of feeling good,

00:42:47.620 | is the absence of fatigue and the absence of physical pain.

00:42:51.320 | And then I thought, wow, that's just so basic.

00:42:55.560 | That's like two building blocks, it's clearly insufficient.

00:42:58.640 | But then I couldn't think of a word

00:43:00.400 | to adequately describe the emotion

00:43:03.060 | that came about an hour later

00:43:04.220 | when I was feeling a little bit better,

00:43:06.460 | but not completely better.

00:43:07.800 | So was I lonely?

00:43:08.640 | Not really, not anymore.

00:43:09.820 | Was I sad?

00:43:10.660 | Not really.

00:43:11.500 | But, you know, as I headed out into the city,

00:43:13.640 | I was thinking, I don't really have a word for how I feel.

00:43:16.800 | I'm sort of okay, not great, not low.

00:43:19.960 | You know, and so I think that we have emotional labels,

00:43:22.480 | I certainly do, for peaks, you know,

00:43:24.540 | these peak emotional states, super happy.

00:43:26.540 | I loved the time with my sister.

00:43:27.860 | We do this every year.

00:43:28.700 | This was a particularly good year for us to do this,

00:43:31.740 | and it went really well.

00:43:33.220 | We were texting back and forth how great it was.

00:43:35.340 | I certainly know what it feels like

00:43:36.460 | to be really down in the pits.

00:43:39.320 | I've got language for that.

00:43:40.820 | But then there's this huge range in between.

00:43:43.040 | And so I guess the simple question is,

00:43:45.300 | should we even trust language as a way

00:43:47.760 | to understand how we're feeling,

00:43:50.600 | or are there additional, if not better, signals

00:43:54.120 | that we should perhaps learn to elaborate

00:43:56.880 | our understanding of emotions with?

00:44:00.060 | - So I'm gonna give you a simple answer,

00:44:04.140 | and then I'm gonna give you a more complicated answer.

00:44:07.820 | So the simple answer is no, language is not sufficient.

00:44:10.580 | Period.

00:44:12.480 | I think the way that you have, well,

00:44:15.680 | I should say one language is not sufficient.

00:44:17.600 | So English is not sufficient,

00:44:20.120 | and probably French on its own is not sufficient,

00:44:22.680 | and probably Swahili on its own is not sufficient.

00:44:25.560 | Although it's very interesting that the states

00:44:30.600 | that we mark with words in each culture,

00:44:35.360 | some of them overlap, but a lot of them don't.

00:44:38.720 | And it's very, very useful to have labels

00:44:42.400 | of emotion concepts from other cultures

00:44:44.640 | that capture configurations or a state

00:44:49.640 | that we don't mark those and sort of distinctively

00:44:54.700 | pull them out as different from other states.

00:44:57.940 | - I'd love to know what some of those are.

00:44:59.360 | - Oh, there are, I should have brought them with me.

00:45:02.580 | I mean, there are some, there's a German word,

00:45:05.680 | which I can't remember the name of the word,

00:45:07.240 | but it's like the experience of someone having a face

00:45:11.600 | that deserves a punch.

00:45:13.680 | - I'm sure someone will tell us in the comments.

00:45:15.360 | Someone who knows German or spend time there,

00:45:17.800 | please put that word in the comments,

00:45:20.080 | but don't punch anybody.

00:45:21.120 | - Another one that's my favorite is ligut,

00:45:25.580 | which is, it's a Polynesian headhunting emotion word,

00:45:33.160 | and it means exuberant aggression in a group like soccer

00:45:38.160 | or headhunting, right, where you're basically,

00:45:46.080 | or I should say also in the military.

00:45:49.320 | So when I was listening to NPR one day,

00:45:51.640 | a couple of years ago, must've been more than that,

00:45:53.580 | 'cause it's in my book,

00:45:54.420 | so it was probably more than seven years ago,

00:45:56.600 | I was listening to these guys talk,

00:45:59.240 | these former military personnel talk about being deployed

00:46:04.240 | in a war where they're with their buddies

00:46:10.080 | and they're basically hunting the enemy

00:46:13.960 | and they feel exuberant, like they're, you know,

00:46:19.480 | and it's not that they're happy, but it's pleasant

00:46:23.380 | and it's very intense, very high arousal, you know,

00:46:27.120 | and in the moment, it seemed right,

00:46:30.880 | and then they come back, you know,

00:46:33.440 | and they ask themselves, like they come back,

00:46:35.380 | and so they're now, you know, their deployment's ended,

00:46:38.240 | now they're back home and they're like,

00:46:39.440 | are my a psychopath?

00:46:40.380 | Like, I enjoy killing people, what is this about?

00:46:42.160 | And I was thinking, no, no, you just experienced ligut,

00:46:45.240 | and if you had a word for it,

00:46:46.600 | you would understand that it's a groupie feeling

00:46:49.520 | where you're all in it together and it's really intense,

00:46:52.960 | and you know, they were experiencing the intensity

00:46:57.960 | of having their life on the line

00:47:00.640 | and being responsible for their brothers, you know,

00:47:04.860 | and sisters in their troop, you know,

00:47:07.520 | so what they would realize is it's perfectly

00:47:12.520 | within the range of normal human variation,

00:47:16.520 | it's just that in English,

00:47:17.640 | we don't have a word for it really,

00:47:19.760 | but there are words that are concepts in other languages,

00:47:22.400 | right, or the other one that I like is called giggle,

00:47:25.520 | which is where when you see a baby who's really cute

00:47:28.320 | and you just wanna like, oh, you don't wanna,

00:47:30.920 | you don't wanna just squeeze. - I had an experience

00:47:31.760 | yesterday evening, the kid was so cute,

00:47:34.200 | there's little cheeks, they're just like jumping at you,

00:47:36.200 | and the parents are delightful people too,

00:47:39.480 | and Dave was just facing out

00:47:40.720 | 'cause they had one of those outward-facing baby things,

00:47:43.520 | and it's just sort of like, yeah.

00:47:45.440 | - And then I think that-- - Giggle, it's called?

00:47:47.560 | - Giggle. - Giggle, oh, giggle

00:47:49.080 | is from the other episode that we did on pelvic health.

00:47:50.760 | - Yeah, well, it also has to do with babies,

00:47:52.220 | but yeah, in a different way.

00:47:54.540 | Or there's one in Japan, I think there's a Japanese word

00:47:56.720 | for the despair that you feel when you got a bad haircut.

00:48:00.600 | - Really? - Yeah, 'cause it's,

00:48:02.680 | I mean, it really is a different kind of feeling than,

00:48:05.600 | you know, 'cause you've gotta like wait for it to grow,

00:48:07.440 | you know, whatever, anyways,

00:48:08.600 | the point being that-- - Amazing.

00:48:10.120 | - Words for us mark particular states,

00:48:13.440 | and they're not always the states

00:48:15.240 | that other people in other cultures care about,

00:48:18.160 | but even, again, the phrasing of your question,

00:48:21.720 | I just want to come back to,

00:48:22.900 | and I'm not trying to pick at you, but--

00:48:25.180 | - Feel free.

00:48:26.020 | What I love is that what you said before,

00:48:27.720 | when you said my question was ill-posed,

00:48:30.460 | in your, in the answer that followed,

00:48:33.240 | it made it very clear why,

00:48:35.360 | and I learned something about how the not emotion system,

00:48:39.920 | but the things, plural, that create emotions work.

00:48:43.920 | So feel free.

00:48:45.280 | I grew up in the same culture that you did.

00:48:47.440 | I'm not Canadian by birth, but in the academic culture,

00:48:50.840 | you know, I mean, the stuff that we take online,

00:48:53.280 | by the way, folks, is nothing compared to the kind of hazing

00:48:56.440 | that I experienced growing up in academic culture

00:49:00.880 | as it was done then.

00:49:02.340 | I don't know if it's still that way now, so feel free.

00:49:04.920 | - Yeah, I think-- - I'm tougher than I look.

00:49:06.120 | - Well, no, but I think my point is

00:49:07.400 | that I'm trying to get at here

00:49:09.040 | is that when we ask questions, any of us, me too,

00:49:11.960 | anybody asks a question,

00:49:13.600 | there are certain assumptions that we're making

00:49:15.460 | in order to allow us to pose the question,

00:49:18.640 | and sometimes what I'm taking issue with

00:49:21.040 | is not the question itself,

00:49:23.320 | but it's the assumptions behind the question, right?

00:49:27.200 | And this is a very classic thing in philosophy of science,

00:49:30.120 | which I know I just said the P word, philosophy,

00:49:32.080 | which scientists, you know,

00:49:33.080 | usually they roll their eyes back in their head

00:49:34.840 | and they'll fall over when you talk about that,

00:49:36.400 | but I think it's really important.

00:49:38.120 | So, you know, can language,

00:49:40.800 | is language sufficient to label or to gauge emotional states?

00:49:46.840 | Kind of sounds like, and this is the assumption

00:49:49.200 | that people make, that there's a state in here

00:49:51.640 | called an emotion, and now I have to label it,

00:49:54.360 | and I have to identify it.

00:49:56.280 | That is not how it works.

00:49:58.080 | Like, that is not what your brain is doing at all,

00:50:01.280 | and in order to explain what I think is happening

00:50:04.040 | and my best available guess, you know,

00:50:06.760 | like based on what I understand,

00:50:08.600 | it's like not even remotely,

00:50:11.240 | that is just not a meaningful question at all.

00:50:15.920 | I do think words are important.

00:50:17.840 | I just don't think that they have to be insufficient

00:50:21.120 | by virtue of what the brain is actually doing,

00:50:23.440 | and the way that I come at this

00:50:25.200 | is just really different from a lot of my colleagues,

00:50:27.920 | so really for 100 years, at least,

00:50:32.680 | I hate when people say things like that,

00:50:34.040 | like for 100 years, but it really is,

00:50:35.520 | like for 100 years, at least,

00:50:37.800 | what psychologists and neuroscientists do or did

00:50:41.760 | and are still doing is they start with a folk experience,

00:50:45.880 | a folk category, a common sense experience,

00:50:47.640 | I feel angry, I'm making a decision,

00:50:50.760 | having a memory, I'm remembering something.

00:50:52.880 | They start with their experience,

00:50:54.960 | and then they go looking for the physical basis

00:50:56.920 | of that experience in the brain or in, you know, in the body.

00:51:01.200 | I think that's really problematic

00:51:04.780 | because not everybody in the world

00:51:06.400 | actually uses those categories or has those experiences.

00:51:09.280 | - Well, a lot of that has to do

00:51:10.200 | with the scientific publication process.

00:51:12.800 | One of the most important statements I ever heard

00:51:14.920 | is from the late Ted Jones,

00:51:16.360 | one of the greatest neuroanatomists

00:51:18.000 | of probably the last 500 years,

00:51:20.640 | which was the following.

00:51:24.280 | He said, "A drug is a substance

00:51:26.760 | "that when injected into an animal or a person

00:51:29.560 | "produces a scientific paper."

00:51:31.660 | And in many ways- - That is wonderful.

00:51:34.000 | - Yeah, yeah, it kind of catches you square in the face

00:51:37.080 | can you go, "Oh, right."

00:51:39.000 | I mean, basically every drug disrupts,

00:51:42.520 | if taken an hour or two before sleep,

00:51:44.960 | changes the amount of REM sleep that you get.

00:51:48.040 | So I could imagine that almost any perturbation

00:51:50.940 | of the language system, the body,

00:51:53.160 | the facial movement system could give you

00:51:56.780 | a quote-unquote effect that you could write a paper about,

00:51:59.600 | but that doesn't mean it has any semblance whatsoever

00:52:02.040 | to what's happening in the world

00:52:03.560 | when we or other people experience emotions.

00:52:05.400 | - And here's the, you know,

00:52:06.880 | there's so much in what you said that I just wanna,

00:52:09.160 | it's very exciting to talk to you.

00:52:10.940 | So the first thing I'll say is that, you know,

00:52:15.120 | we often will identify, we as in the, you know, people,

00:52:20.120 | but also scientists identify biological signals

00:52:25.720 | by what we believe them to mean psychologically.

00:52:32.920 | So serotonin is a happiness chemical.

00:52:35.980 | No, serotonin evolved as a metabolic regulator.

00:52:40.320 | It is a metabolic regulator and whatever it's doing,

00:52:43.880 | it's allowing an animal to spend resources

00:52:47.700 | when the animal's brain isn't sure

00:52:53.640 | there's a reward at the end of that, right?

00:52:55.880 | So you were saying before, you know,

00:52:58.440 | the absence of fatigue, the absence of discomfort,

00:53:01.120 | that's a pleasant feeling, right?

00:53:03.440 | Well, yeah, so maybe serotonin has something to do

00:53:06.480 | with pleasantness because it has something to do

00:53:08.760 | with energetics, right?

00:53:10.360 | Cortisol, cortisol is not a stress hormone.

00:53:13.200 | It's not a stress hormone.

00:53:14.880 | I mean, it's a hormone that is secreted more

00:53:18.880 | when the brain believes that there is

00:53:21.840 | a big metabolic outlay that's required.

00:53:23.960 | That's what stress is basically.

00:53:26.460 | It's the brain believes there's a big metabolic outlay

00:53:28.480 | that's about to be required.

00:53:30.160 | And it matters, these kind of like little semantic tweaks,

00:53:34.880 | like they matter a lot because of how we do,

00:53:38.320 | because of how we do research.

00:53:39.720 | So I would say I don't start with the categories

00:53:43.680 | that derive from English and my own experience.

00:53:46.300 | I start with the nervous system.

00:53:50.020 | I try to learn what is the best available evidence

00:53:55.080 | for how that nervous system evolved,

00:53:58.080 | how it developed, how it's structured, right?

00:54:01.160 | Anatomy to me is very important.

00:54:03.720 | Some of my best hypotheses come from just learning

00:54:08.040 | the anatomy and realizing, oh, no,

00:54:09.640 | there's a connection there.

00:54:10.680 | That's direct, that should mean something.

00:54:13.680 | I mean, I could give you lots of examples

00:54:17.240 | of where we've made discoveries solely

00:54:21.480 | because we noticed a set of anatomical connections

00:54:24.720 | and we're really curious about

00:54:26.600 | what they might be involved with.

00:54:28.960 | But if you start with that premise,

00:54:31.580 | then you think about the brain,

00:54:33.860 | and I think about the brain in a really different way, right?

00:54:36.960 | So I don't think about the brain as a stimulus driven organ.

00:54:40.620 | I think about it more like this,

00:54:44.280 | that the brain is,

00:54:47.920 | first of all, the brain is not running a model

00:54:52.360 | or making inferences about the world.

00:54:55.520 | All the brain knows are signals

00:54:59.520 | from the sensory surfaces of its body.

00:55:02.480 | So your brain is modeling your retina

00:55:04.500 | and it's modeling your cochlea

00:55:06.160 | and it's modeling the sensory surfaces of the skin.

00:55:09.120 | And sure, signals hit those surfaces

00:55:14.980 | and those surfaces transduce those signals

00:55:17.040 | and send them up to the brain,

00:55:18.660 | but the brain only knows the body.

00:55:23.100 | And anything it knows about the world,

00:55:25.300 | it knows about the world through the body,

00:55:27.420 | through the sensory surfaces of the body.

00:55:29.120 | So that's the first, for me, really big important point.

00:55:32.720 | The second important point is that

00:55:34.840 | I think about the brain as being trapped

00:55:36.520 | in a dark silent box called your skull.

00:55:40.320 | And it's so weird saying these things to you.

00:55:43.680 | You're so much, you're like,

00:55:45.960 | you're this really esteemed neuroscientist

00:55:49.880 | and here I am explaining to you

00:55:51.400 | how I think the brain works, it's just very-

00:55:53.960 | - Well, it's important for our audience,

00:55:55.120 | but it's also important for me,

00:55:56.120 | even though, yes, I know these facts,

00:55:59.560 | but I believe it's always informative to go back to.

00:56:04.560 | Go back to the fundamentals because we forget.

00:56:07.960 | Actually, I would say that someone once described,

00:56:10.580 | I'll call him the great,

00:56:12.400 | 'cause he's a great visual neuroscientist,

00:56:14.160 | visual neuroscientist, Tony Movshin,

00:56:15.880 | who founded the Department of Neuroscience at NYU,

00:56:18.440 | once said a real intellectual is somebody

00:56:21.480 | that can appreciate and work with a topic

00:56:24.160 | at multiple levels of granularity, right?

00:56:26.460 | It's not about, and oftentimes the more expertise

00:56:29.780 | is associated with more focus on detail.

00:56:31.680 | So I love returning to the core basics.

00:56:33.620 | So I think it's wonderful, please continue.

00:56:36.180 | - So I think about the brain is being trapped in this box

00:56:38.680 | and it's receiving signals continuously

00:56:42.400 | from the sensory surfaces of the body,

00:56:44.700 | but those signals are the outcomes of some set of changes.

00:56:47.660 | And the brain doesn't know what the changes are.

00:56:49.580 | It doesn't know the causes of those signals,

00:56:51.260 | it just knows the outcomes, it knows the signals.

00:56:53.920 | That's what it's receiving.

00:56:55.460 | And so it has to guess at what the causes

00:56:59.000 | of those signals are in order to stay alive.

00:57:02.560 | And so that's in philosophy called an inverse problem.

00:57:07.560 | So the brain just has a massive continuous inverse problem

00:57:11.740 | that it has to deal with all the time.

00:57:14.000 | - Like it can't have, it doesn't have access

00:57:16.000 | to all the information.

00:57:17.040 | - No.

00:57:17.880 | - It's just a guessing machine.

00:57:18.700 | - It's a guessing machine.

00:57:19.740 | So for example, you know, if you hear a loud bang,

00:57:24.260 | what is that loud bang?

00:57:25.820 | Could be a car door slamming.

00:57:28.040 | It could be thunder.

00:57:30.320 | It could be a car backfiring.

00:57:33.000 | It could be a gunshot.

00:57:34.800 | The brain doesn't know.

00:57:36.440 | It has to guess.

00:57:37.960 | And it's not making a guess like a intellectual guess.

00:57:41.960 | The guess is a motor plan.

00:57:45.480 | It's a plan for changing the internal state of the body

00:57:50.480 | in order to support motor, skeletal motor movements.

00:57:54.680 | Do I need to run?

00:57:55.760 | Do I need to shut the window?

00:57:57.200 | Do I need to get an umbrella?

00:57:58.680 | Do I, you know, do I need to hold my breath

00:58:00.960 | because the car is backfired?

00:58:02.080 | You know, what do I need to do?

00:58:03.800 | So where does that plan come from?

00:58:05.500 | Well, it comes from past experience,

00:58:10.020 | the experience that's been wired into the brain.

00:58:12.880 | But I think that the evidence suggests

00:58:17.000 | that what the brain is doing is basically

00:58:21.400 | reinstating bits and pieces of past experience.

00:58:27.600 | So remembering,

00:58:29.720 | although we don't experience ourselves as remembering,

00:58:31.840 | but basically it's re-implementing ensembles of signals

00:58:35.740 | from the past that are similar to the present in some way.

00:58:41.080 | Now, a bunch of things which are similar to each other

00:58:45.720 | in psychology is a category.

00:58:50.440 | So what the brain is doing is it's creating,

00:58:54.120 | it's constructing a category.

00:58:55.720 | And in fact, we think about the brain

00:58:57.560 | as a continuous category constructor.

00:59:00.280 | It's constructing a category of possible futures,

00:59:04.720 | possible outcomes, possible motor plans,

00:59:08.880 | and how does it know which is the right one?

00:59:12.820 | 'Cause it's not just picking one.

00:59:14.260 | There's gonna be some sample that it's re-implementing,

00:59:18.320 | but how does it know which one?

00:59:20.240 | Which is the right one?

00:59:21.200 | 'Cause there can only be one.

00:59:22.900 | - Well, I feel like in the example of a loud noise,

00:59:25.200 | what I immediately thought of as you were describing that

00:59:27.640 | is that my system would become aware of it.

00:59:31.060 | I would become aware of it.

00:59:31.920 | But then it's a question of, is there another loud noise?

00:59:34.760 | How closely are those loud noises spaced?

00:59:37.200 | Is it getting louder or less loud?

00:59:39.520 | And then, and so a bunch of categories,

00:59:42.160 | it's like a bookshelf with an infinite number of books,

00:59:44.520 | but then with the second loud noise,

00:59:46.620 | now it's just one wing of the library.

00:59:49.820 | And then with the next thing that happens in the context,

00:59:52.360 | it starts narrowing and then pretty soon you get presented

00:59:54.360 | with the book that says the roof is about to cave in.

00:59:57.860 | - And I think your analogy there is pointing out two things.

01:00:02.200 | One is that really what the brain is attempting to do

01:00:07.200 | is to reduce uncertainty.

01:00:09.280 | Because uncertainty is super expensive.

01:00:13.120 | Now, sometimes we like deliberately cultivate uncertainty.

01:00:17.600 | Like we do not, we deliberately try to learn things

01:00:20.400 | we don't, that we don't know.

01:00:22.600 | We put ourselves in novel situations.

01:00:26.160 | We seek novelty and because it's fun and interesting

01:00:28.880 | and whatever, sure.

01:00:30.120 | But imagine every single waking moment of your life

01:00:34.400 | was like that, where you didn't know,

01:00:36.880 | you couldn't narrow things down from the library

01:00:39.440 | to the wing, to the bookshelf,

01:00:41.720 | to the particular shelf on that bookshelf,

01:00:46.320 | to the- - It'd be terrifying.

01:00:47.440 | - Yeah, it would be- - It'd be terrifying.

01:00:48.620 | - Yeah, it would be.

01:00:49.460 | - That's the label I would give it.

01:00:50.840 | It would be terrifying.

01:00:52.040 | 'Cause I couldn't plan anything or do anything

01:00:53.640 | because all possibilities are open.

01:00:55.240 | - Right.

01:00:56.080 | And it's just actually metabolically unsustainable.

01:01:00.120 | And there are some brains that are wired

01:01:03.960 | in a way that they don't predict very well.

01:01:06.080 | They don't create these categories very well.

01:01:09.200 | And so they're dealing with

01:01:11.280 | in really unbelievable amounts of uncertainty.

01:01:16.580 | So that's one thing, is part of what's the goal here,

01:01:21.780 | if you could say there's a goal, is to reduce uncertainty.

01:01:23.900 | And I'm gonna get to why this has anything to do

01:01:25.920 | with emotion in a minute,

01:01:27.000 | but I just need to set up the ground rules

01:01:30.420 | or the assumptions of what I'm working with here.

01:01:34.560 | So the other thing though that you pointed out,

01:01:37.500 | which I think is really important,

01:01:39.000 | is that none of this is static.

01:01:43.040 | It's all evolving over time, right?

01:01:45.480 | The signals are evolving over time.

01:01:47.480 | So both the signals that are constantly hitting

01:01:51.020 | the sensory surfaces of the body

01:01:52.760 | and making their way to the brain,

01:01:54.280 | but also the intrinsic signals in the brain,

01:01:57.040 | it's all changing over time.

01:01:58.680 | So when we talk about context, that's important.

01:02:01.880 | How is the brain making a decision about similarity?

01:02:05.100 | Like what are the features that are similar?

01:02:07.140 | It's not just at a single snapshot in time.

01:02:11.580 | It's always happening dynamically over time, right?

01:02:15.360 | And most of the time though, you don't ask,

01:02:19.100 | you don't wait to hear a second sound.

01:02:21.840 | You're not deliberately attempting

01:02:24.880 | to figure out what the sound is.

01:02:26.740 | Your brain is just sorting it out, right?

01:02:29.660 | And it's sorting it out by narrowing down the possibilities.

01:02:32.800 | And there are some selection mechanisms in the brain

01:02:36.560 | that help it guess better,

01:02:39.940 | but also the signals coming from the world

01:02:45.220 | are also helping to select which possibility is the right one.

01:02:50.220 | - I'd like to take a quick break

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01:03:57.700 | - There's this scene that comes to mind from that movie,

01:04:00.100 | I think it was "Saving Private Ryan,"

01:04:01.540 | where the guys that are about to hit the ground on D-Day

01:04:06.540 | are flinching with every crack of gunfire.

01:04:12.380 | Like they're just, everything's a stimulus to move and to end

01:04:16.180 | and then some of the more seasoned soldiers

01:04:20.100 | are literally having bullets whizzing by their head

01:04:24.580 | and people are dropping dead all around them

01:04:27.440 | and they're moving forward steely-eyed

01:04:29.820 | and stable and upright.

01:04:31.560 | And in part, we look at that and say,

01:04:34.860 | okay, they're courageous, they're seasoned,

01:04:36.900 | maybe they're desensitized in certain ways,

01:04:38.580 | but actually it fits much better with the idea

01:04:42.300 | based on what you're saying,

01:04:43.480 | it fits much better with the idea

01:04:44.900 | that they have intimate knowledge,

01:04:48.020 | both conscious and unconscious knowledge,

01:04:50.880 | that something right next to them is a threat,

01:04:54.360 | but not a threat worth responding to.

01:04:56.060 | - Right, exactly.

01:04:56.900 | - But if it were headed straight for them,

01:04:58.440 | they would quite understand.

01:05:00.100 | - What I would say is that it's not,

01:05:03.540 | you know, I keep referring to things as signals

01:05:06.460 | and really I'm just, that's like my generic word

01:05:09.180 | for a quantity of energy of some sort, you know,

01:05:12.620 | but your brain, my brain, every brain

01:05:14.540 | is constantly making signal, noise, like distinctions.

01:05:18.380 | Do I need to care about this?

01:05:19.400 | Do I not need to care about this, right?

01:05:21.340 | And we have ways of learning

01:05:23.620 | and we also have ways of cueing each other.

01:05:25.380 | So, you know, humans use eye gaze to cue each other

01:05:29.920 | about what is signal and what is noise, right?

01:05:31.820 | So if you and I are sitting,

01:05:33.220 | let's say we were at a coffee shop

01:05:34.900 | and we were in a part of town

01:05:36.260 | that I'd never been to before

01:05:37.660 | and we were sitting having coffee

01:05:39.460 | and, you know, a loud siren went by.

01:05:42.020 | If you turned and looked, I would probably turn and look

01:05:45.300 | because you just cued me

01:05:47.460 | that that was something I need to care about.

01:05:49.120 | If you ignored it, I would probably ignore it

01:05:52.740 | because you just cued me that I didn't need to worry about it

01:05:55.860 | I didn't need to care

01:05:56.740 | and we're constantly doing that with each other

01:05:58.580 | and we also do it with little babies and with kids

01:06:01.100 | and that's how we teach children.

01:06:02.720 | This is signal, this is noise.

01:06:04.140 | This you need to worry about, this you can ignore.

01:06:06.540 | And so, yeah, your description is perfect.

01:06:08.780 | So what does this have to do,

01:06:10.100 | any of this have to do with emotion?

01:06:13.740 | In order to answer that part of the question,

01:06:16.540 | I wanna say, so, okay, you've got these signals.

01:06:20.500 | The brain is like, has these electrical signals going on.

01:06:23.500 | We'll just ignore the hormonal signals for the moment

01:06:26.380 | 'cause that's complicated, you know, one is complicated.

01:06:28.460 | So it's got all these electrical signals going on.

01:06:31.220 | When it's remembering something,

01:06:32.620 | it's just basically reinstating a pattern of signals

01:06:35.660 | and it's got these signals coming in

01:06:37.660 | from the sensory services.

01:06:39.900 | Okay, so what is the brain doing?

01:06:42.660 | It's a signal processor.

01:06:43.940 | So what is it?

01:06:44.780 | I don't mean a computer,

01:06:45.660 | I mean a signal processor in the engineering sense.

01:06:47.780 | So what is it doing?

01:06:50.100 | Without getting into all the dynamics of prediction

01:06:54.260 | and you know, whatever, what the brain is doing

01:06:57.100 | is it's assembling a set of features.

01:07:02.020 | It's some of the features that it's assembling

01:07:04.140 | are very close in detail

01:07:07.340 | to the sensory surfaces of the body.

01:07:10.060 | So in primary visual cortex, there's a retinotopic map.

01:07:14.820 | The details there are very, very low level,

01:07:17.300 | like a line, an edge, you know,

01:07:19.540 | same thing in primary auditory cortex, right?

01:07:21.860 | It's tonotopic, so there are tones.

01:07:24.780 | But it's very, very, very low level details.

01:07:27.860 | And we might, there are many, many, many, many

01:07:30.140 | of these little features.

01:07:31.100 | So we would say it's a high dimensional array,

01:07:34.060 | lots and lots and lots and lots of features.

01:07:37.340 | And then, and let's just talk about one structure,

01:07:40.580 | just the cerebral cortex.

01:07:41.860 | Let's not worry about,

01:07:43.660 | but what I'm about to say is basically true

01:07:45.980 | of really the rest of the brain as well.

01:07:48.500 | If you take the cortex off the surface,

01:07:52.140 | the cortical sheet, off that wavy, you know,

01:07:55.780 | cortical sheet, take it off the rest of the brain,

01:07:58.300 | the subcortical parts,

01:07:59.140 | and you stretch it out like a napkin,

01:08:00.780 | you can see there's a compression gradient there

01:08:02.940 | in the architecture of the neurons.

01:08:05.380 | So at the primary sensory areas,

01:08:07.580 | there are these tiny little pyramidal neurons

01:08:10.660 | that are representing these very low level features.

01:08:13.900 | And they feed into bigger neurons,

01:08:16.020 | which feed into bigger neurons,

01:08:17.380 | which feed into bigger neurons.

01:08:19.420 | So what's happening is you've got this very detailed array

01:08:24.420 | being compressed in its dimensionality

01:08:27.260 | until you get to the middle of the brain at the front,

01:08:30.020 | where there are many fewer neurons,

01:08:32.460 | but they're bigger and they have many more connections.

01:08:35.820 | So it's a dimensionality reduction that's happening.

01:08:38.700 | - So just to make sure I understand correctly

01:08:42.060 | and that the audience understands,

01:08:43.860 | the physical world obviously is transformed

01:08:47.860 | by our sensory apparatus, the retina, the cochlea,

01:08:50.900 | the sensing neurons in our skin.

01:08:54.760 | It's physical things, mechanical pressure,

01:08:57.220 | light, photons, sound waves.

01:08:58.860 | Okay, that's translated into neural code,

01:09:01.800 | which is chemical and electrical.

01:09:04.060 | And those sensory inputs are fairly vast

01:09:08.460 | and they use high dimension, high dimensionality.

01:09:11.980 | So lots of different orientations of lines,

01:09:14.280 | even though it originates

01:09:16.260 | with just three cone photo pigments,

01:09:18.360 | lots of opportunity for encoding different shades of color,

01:09:21.060 | contrast, okay, and all of that.

01:09:23.780 | And so you have lots of little neurons

01:09:25.140 | to represent all the possibilities

01:09:27.380 | of the physical world that are occurring.

01:09:30.380 | But as that information is passed further up along,

01:09:35.040 | excuse me, I have to be careful with the use of hierarchies

01:09:37.340 | 'cause that's controversial nowadays,

01:09:38.840 | not for political reasons, but for accuracy reasons.

01:09:42.700 | As that information is passed along,

01:09:45.240 | there's more convergence

01:09:48.540 | onto a smaller number of larger neurons.

01:09:51.920 | So these are neurons that have access

01:09:53.140 | to a lot of information, but in coarser form.

01:09:55.680 | - Right, so they're low, it's like compressing an MP3,

01:09:59.120 | like how an MP3 compresses information, for example.

01:10:01.860 | So the cortex is representing features.

01:10:05.320 | So, and I represent, I'm just using that in a generic way

01:10:08.720 | because that's also controversial

01:10:10.400 | about exactly how is the brain, okay, but yeah.

01:10:12.700 | - But it works.

01:10:13.540 | - But for now I'm using it just in a generic way.

01:10:16.220 | So you go from lines and edges to a shape,

01:10:20.220 | like a round shape to a face, right?

01:10:23.900 | So you're basically,

01:10:27.900 | you're going, what's happening is there are summaries

01:10:31.340 | of summaries of summaries of summaries.

01:10:34.380 | - I love that.

01:10:35.220 | I hope everyone hears that

01:10:37.120 | 'cause I've been in this field of neuroscience a long time.

01:10:40.180 | As you move along the neuroaxis

01:10:42.700 | from the sensory epithelium,

01:10:44.840 | now it sounds very nomenclature-ish,

01:10:46.760 | but from the surface of the skin inward,

01:10:48.920 | you're getting summaries.

01:10:50.720 | - Yeah.

01:10:51.560 | - Ascent, more and more summaries.

01:10:53.380 | I think that's so important.

01:10:55.520 | That's like a gazillion dollar statement

01:10:59.480 | for understanding of the nervous system.

01:11:02.160 | - But each of those points correspond

01:11:04.840 | to some mental feature, like a line or an edge

01:11:08.180 | or a circle or a square or a face, right?

01:11:12.760 | But now then when you're in the midline at the front,

01:11:17.620 | what are those features?

01:11:19.820 | Well, those features are things like,

01:11:22.080 | they are multimodal summaries,

01:11:24.720 | meaning they are summaries of the sights

01:11:27.100 | and sounds and smells, right?

01:11:28.680 | And they are lower dimensional, meaning they're coarser.

01:11:32.980 | So there are things like threat, reward, pleasure.

01:11:37.980 | I mean, really abstract.

01:11:40.560 | That's what abstract means.

01:11:41.960 | It doesn't mean that those representations

01:11:44.360 | have no sensory or motor meaning.

01:11:48.360 | It means that threat, for example,

01:11:51.120 | a summary can have many different patterns

01:11:55.080 | associated with it.

01:11:56.420 | And the brain is treating them all as equivalent.

01:12:00.760 | - This to me, again, feels so, so important

01:12:05.140 | for people to understand because as I'm hearing this

01:12:08.660 | and this word summaries is just ringing in my mind,

01:12:10.600 | it's so important because one of the core components

01:12:14.880 | of my experience of my emotions,

01:12:17.400 | 'cause that's all I can really say for sure,

01:12:20.200 | my subjective interpretation and labeling of my own emotions

01:12:25.080 | is that they are pretty broad bins,

01:12:28.360 | like I described earlier. - They are pretty broad bins.

01:12:30.200 | And so that's where I was exactly where I was going.

01:12:33.280 | So what about the word anger?

01:12:37.600 | Where is that represented?

01:12:39.720 | Well, that's one of these multimodal abstractions.

01:12:43.000 | In fact, anger is just a couple of phonemes.

01:12:46.060 | It's a couple of sounds, but those sounds,

01:12:49.160 | the sound of anger corresponds over thousands of instances

01:12:54.160 | that you've learned in your life

01:12:57.000 | to very different patterns of sensory motor features.

01:13:01.480 | That's right, because what's going on in your body

01:13:04.120 | during anger can vary.

01:13:07.920 | What way you move your face in anger can vary

01:13:12.160 | depending on the situation.

01:13:13.080 | What you see someone else doing in anger can vary.

01:13:16.760 | And so the word anger or any word

01:13:21.000 | is actually just a multimodal summary

01:13:24.960 | of many, many, many, many instances

01:13:28.760 | which are in their sensory and motor features,

01:13:32.120 | the sensory and motor meaning, very different.

01:13:35.400 | - And it seems to me are highly constrained

01:13:38.360 | by developmental and cultural experience.

01:13:41.020 | - Absolutely. - Because just today

01:13:43.280 | I learned that there's a word in Japan

01:13:45.720 | for the feeling that one has

01:13:48.680 | of having gotten a haircut they don't like.

01:13:50.920 | There's a word in Germany

01:13:54.240 | that pertains to the feeling of wanting to punch someone

01:13:57.560 | specifically because of the look on their face.

01:13:59.880 | - Well, really it's more like to you

01:14:02.280 | it feels like they're asking to be punched in the face.

01:14:04.560 | - Even as you added yet more dimensionality to it.

01:14:07.040 | So upon learning just those things just today,

01:14:09.960 | there is additional dimensionality brought in

01:14:13.360 | such that if I were to ever want to punch somebody

01:14:17.720 | in the face simply because of the look on their face,

01:14:21.200 | that I wouldn't necessarily label that as anger alone.

01:14:26.200 | It now has another dimension to it.

01:14:28.460 | And so I think I'm finally,

01:14:30.560 | I think I'm finally starting to understand

01:14:32.720 | how the developmental and the cultural influences

01:14:36.600 | plus the fact that language is a pretty crude descriptor

01:14:40.680 | for this neural process that you're describing.

01:14:43.040 | - Absolutely, absolutely.

01:14:44.760 | But before you use the word granularity

01:14:48.080 | and so I'm gonna use that word too.

01:14:49.520 | In fact, I've coined that phrase emotional granularity.

01:14:53.400 | This is an aside, I coined that phrase almost 30 years ago

01:15:00.360 | and now people study it like it's a phenomenon

01:15:03.520 | which is cool in a sense.

01:15:05.520 | But also I kind of wanna keep reminding them

01:15:08.400 | like that's a word that refers to a process.

01:15:11.680 | It's not a thing, it's a process.

01:15:13.720 | But the process is,

01:15:14.820 | so when the brain is a category constructor,

01:15:18.640 | how fine grained are the categories?

01:15:22.900 | How precise are the categories, right?

01:15:24.820 | Like if you're using, if your feature of equivalence

01:15:28.640 | that your brain is using is threat,

01:15:31.160 | you're in really big trouble

01:15:33.240 | 'cause there are like a gazillion different

01:15:36.260 | sensory motor patterns that could go with threat.

01:15:39.320 | So your category is gonna be massive.

01:15:42.440 | So how does the brain figure out

01:15:44.600 | which of those massive number of options

01:15:47.620 | is the one to use in this instance?

01:15:52.320 | If on the other hand,

01:15:54.080 | you don't just wanna use sensory motor patterns

01:15:57.520 | as the features of equivalence

01:15:58.920 | or the features that you're using to say,

01:16:01.160 | this instance right now is similar to these past instances.

01:16:04.440 | If I had to search like right now,

01:16:06.760 | what is similar to right now?

01:16:08.080 | It would be me sitting across the table

01:16:10.480 | from somebody who has a beard and is dressed in black.

01:16:14.520 | And there are a lot of details there

01:16:16.760 | that probably don't matter, right?

01:16:18.560 | So you'd be searching for a specific match from the past.

01:16:21.840 | That's not very efficient either.

01:16:23.760 | So you need something in the middle.

01:16:27.640 | And that is to say, you need to have,

01:16:31.340 | your brain has to be able to make categories

01:16:32.900 | that are more fine grained, but not super fine grained,

01:16:36.840 | but they have to be more fine grained than just threat.

01:16:40.160 | - You wanna keep the, in the library analogy

01:16:42.360 | that I made earlier,

01:16:43.240 | you want to keep the rest of the library accessible

01:16:45.920 | at some level.

01:16:46.760 | - Yeah.

01:16:47.580 | - So you're not just staring at that one book.

01:16:49.120 | - But if you use the category bad, this feels bad,

01:16:54.120 | then your brain is basically

01:16:57.440 | going to be partially constructing

01:17:03.100 | an entire wing full of books,

01:17:05.520 | like an entire wing full of options.

01:17:08.040 | If you use the word angry,

01:17:10.220 | then maybe it's a bookcase.

01:17:14.080 | It's constructing a bookcase full of options

01:17:16.840 | and a category that's the size of a bookcase.

01:17:19.000 | And if you were using the word frustrated,

01:17:22.540 | then maybe it's a shelf.

01:17:24.380 | The brain can learn to construct categories

01:17:26.640 | at different scales of generalizability.

01:17:29.960 | So if I'm in an instance and my brain is making a guess,

01:17:34.500 | is it drawing from past instances

01:17:36.820 | that we're associated with the word anger?

01:17:39.820 | We're associated with the word fear.

01:17:42.540 | Maybe it's some combination.

01:17:44.220 | The words are just features, they're just sounds.

01:17:46.580 | There are also all sorts of other features,

01:17:48.300 | like what was my heart doing?

01:17:49.620 | What kind of motor actions did I make?

01:17:52.300 | What did I see next?

01:17:54.740 | So the point being, what I'm trying to bring here is that

01:17:59.160 | it's not like your brain creates an emotional state

01:18:04.020 | and then labels it.

01:18:05.780 | What your brain is doing is creating a category

01:18:09.240 | of possible futures of what it's going to do next.

01:18:13.640 | And that state is largely determined

01:18:17.920 | by what the brain is remembering

01:18:22.680 | and how it's drawing from that huge population,

01:18:25.720 | that huge library of options,

01:18:29.060 | which books is it sampling?

01:18:31.260 | - I love this so much because it explains so much

01:18:34.780 | that frankly has been perplexing to me

01:18:37.620 | and also somewhat troubling to me.

01:18:39.820 | For instance, we hear about emotional intelligence

01:18:43.660 | and sometimes I wonder whether or not

01:18:45.580 | true emotional intelligence would be

01:18:47.940 | what you just described,

01:18:49.520 | the understanding of how this process works

01:18:51.660 | so that you can work with it.

01:18:52.980 | And I definitely want to talk about

01:18:54.560 | how one can work with this knowledge

01:18:56.120 | because I think it's incredibly powerful

01:18:58.340 | in its explanatory power, but also its actionable power.

01:19:03.340 | The other thing is that it's clear to me,

01:19:06.300 | just based on my experience today

01:19:07.780 | of hearing these words from other cultures

01:19:09.460 | that relate to different emotional states,

01:19:11.220 | that this system, unlike a lot of systems in the brain,

01:19:14.820 | I like to think is fairly plastic.

01:19:17.860 | Like the moment that you know

01:19:19.780 | that there are additional dimensions

01:19:22.060 | to sadness, anger, et cetera,

01:19:24.100 | there's something comforting about that.

01:19:26.460 | What's really unsettling is the idea

01:19:28.720 | that we have such broad bins that we would define

01:19:33.340 | a near infinite number of situations as just fear.

01:19:35.940 | That would suck.

01:19:37.340 | That's not a good existence.

01:19:39.220 | And yet I have to ask whether or not you think that

01:19:42.980 | as a species, not as a culture, but our entire species,

01:19:47.500 | whether or not we are taking the exact opposite approach

01:19:51.380 | that we're sort of moving into the emoji-ization,

01:19:54.440 | is that a word?

01:19:55.280 | Make it a word and people can assault me in the comments.

01:19:58.740 | The emoji-ization of this very rich and complex system,

01:20:02.860 | we're starting to get into this mode of like,

01:20:05.360 | I'm going to post an angry face and therefore,

01:20:07.380 | like, this is a bad, I'm angry at you.

01:20:09.240 | This is a bad interaction.

01:20:10.340 | We're going to, it's potentially combative.

01:20:12.900 | Or, and you know, maybe Twitter X or Instagram

01:20:16.420 | or other social media sites are kind of the epitome of this,

01:20:20.060 | where you reduce this high dimensional space in,

01:20:24.380 | you keep the sensory stimulation very high.

01:20:26.680 | It's movie after movie after movie and color and sound

01:20:29.540 | and people doing crazy parkour stuff

01:20:31.720 | and bears eating giraffes or whatever it is,

01:20:34.600 | probably not bears eating giraffes, but you know what I mean?

01:20:36.760 | And you can see stuff that's sexual and violent

01:20:38.980 | and political and emotional and sweet.

01:20:41.120 | And then the cats are kissing the monkey and you're like,

01:20:44.040 | or the monkey's kissing the cat.

01:20:45.340 | And so it's high dimensionality in terms of sensory space.

01:20:48.620 | But then what do we call it?

01:20:49.740 | We're like, oh, this is an emoji.

01:20:52.600 | You assign an emoji, you're hearting something.

01:20:54.820 | You're giving a thumbs up or a thumbs down.

01:20:56.640 | So I almost feel like we're trying to,

01:20:59.460 | we're regressing to a state where we're kind of like

01:21:02.200 | an infant trying to figure out like what the hell

01:21:03.720 | is going on and we're saying, you know what?

01:21:05.240 | You get like six categories of response.

01:21:07.640 | When in reality, we should probably be expanding

01:21:11.540 | the number of different responses that we can have

01:21:14.120 | in order to accurately match the way

01:21:15.780 | that our nervous system actually works.

01:21:18.260 | - Yes, exactly.

01:21:20.120 | There are many different things we could talk about

01:21:22.520 | with respect to the summary that you just gave,

01:21:24.340 | which I think is completely accurate.

01:21:27.260 | So what I would say is that if you look through

01:21:30.400 | even just the last, I don't know, 100 or so years,

01:21:34.320 | like the 19th, 20th centuries, maybe,

01:21:39.100 | you can see that the complexity of people's responses

01:21:44.100 | expands and contracts, right?

01:21:47.880 | So for example, this is something that I've written

01:21:50.520 | really speculatively about, but one of the things

01:21:55.520 | that I found really interesting is that authoritarianism,

01:22:01.080 | authoritarian thinking is the reduction of complexity

01:22:04.560 | to some things that are really, really simple.

01:22:07.360 | Like you're getting rid of all the complexity

01:22:09.680 | to basically these very, very coarse,

01:22:14.680 | low dimensional judgments and things become black and white.

01:22:20.240 | It's the avoidance of complexity

01:22:23.240 | so that there can be simple, single answers to things.

01:22:27.240 | And it happens in human culture at times,

01:22:32.240 | and then there's an expansion of complexity at times too.

01:22:36.880 | So what predicts that?

01:22:40.440 | Like what is it in the human nervous system

01:22:43.000 | or our collective human nervous,

01:22:44.840 | like we're just a bunch of brains attached to bodies

01:22:47.960 | interacting with other brains and bodies, right?

01:22:50.160 | So like, what is it that causes these ripples of,

01:22:55.160 | and I have some thoughts about that

01:22:56.960 | that are really, really, really speculative.

01:22:59.160 | But I think the other thing that's really important

01:23:03.960 | is that we've talked about,

01:23:06.040 | so we'll go back to our cortical sheet that we've,

01:23:08.840 | and by the way, this is just one compression gradient

01:23:11.000 | in the brain, there are others too, right?

01:23:13.680 | There are at least four others that I can think of.

01:23:16.480 | So this is just one.

01:23:18.240 | But all compression gradients work the same way,

01:23:20.720 | which is that, now we've talked about

01:23:22.520 | going from the low level details,

01:23:25.360 | compressing to these multimodal summaries,

01:23:27.560 | these really like simple features that are, right?

01:23:31.720 | But that compression is what engineers would call lossy,

01:23:36.720 | meaning you lose the information, you lose the information.

01:23:44.240 | So when you go from lines and edges to a face,

01:23:47.560 | those neurons, they just know the face.

01:23:49.800 | They don't have, they lose what they've thrown away,

01:23:53.000 | the details they've thrown away,

01:23:54.320 | those details are gone for those neurons

01:23:57.120 | that are representing a face.

01:23:58.320 | - They don't have access to that.

01:23:59.160 | - They don't have access to it.

01:24:00.920 | So we said, well, the brain is making a guess.

01:24:03.320 | It's making a guess about what this big,

01:24:06.560 | very, very high dimensional soup of signals in the world

01:24:11.600 | and in the body, like, what do they mean, right?

01:24:14.480 | When the brain makes a guess,

01:24:16.320 | it starts with the compressed low dimensional signals.

01:24:20.880 | It starts with the features like anger or like threat,

01:24:26.200 | or it starts with these summaries,

01:24:28.800 | and then it has to infer or guess at every synapse,

01:24:33.800 | there's a guess that's being made

01:24:38.200 | about what the details are at the next level,

01:24:42.040 | because what's happening is the guess

01:24:44.880 | is basically the brain going from these really general things

01:24:47.920 | to these very specific sensory motor patterns.

01:24:51.400 | It happens along the cortical sheet.

01:24:53.200 | It happens also down the neuroaxis,

01:24:55.600 | down the nerve, you know, from the cortex to the midbrain,

01:24:59.520 | to the brainstem, to the spinal cord.

01:25:01.360 | You have to go from a representation of, you know,

01:25:05.040 | run to the actual physical movements of muscles,

01:25:10.040 | spindles and, you know, angles of joints

01:25:14.320 | and things like that.

01:25:15.240 | So what you're doing is you're going in the other direction.

01:25:17.960 | You're adding detail, you're particularizing,

01:25:20.560 | and the brain is guessing.

01:25:22.040 | It's guessing, well, if it's using anger

01:25:26.040 | as the general feature, well, which instance of anger is it?

01:25:30.400 | And what are the specifics that are going to happen?

01:25:35.360 | - And what are the, and forgive me,

01:25:38.280 | but what are the adaptive steps

01:25:41.680 | that I might take or not take?

01:25:43.640 | Because, I'm quoting a lot today, so forgive me,

01:25:46.840 | but in the words of the great Sherrington,

01:25:49.840 | Nobel Prize winning physiologist,

01:25:51.360 | the final common pathway is movement.

01:25:53.920 | - Is movement.

01:25:54.920 | - And movement is nuanced, right?

01:25:56.880 | Humans, I suppose, have among the greatest variety

01:25:59.780 | of different speeds and types of movement.

01:26:01.400 | I think about parkour, gymnastics,

01:26:03.600 | think about then what like a cheetah can do.

01:26:06.520 | Cheetahs are impressive.

01:26:07.940 | A gymnast is truly impressive in terms of the range

01:26:10.700 | of movements and speeds, et cetera.

01:26:12.200 | In any event, the ultimate choice

01:26:15.760 | that the nervous system has to make

01:26:16.800 | is whether or not to move, which direction,

01:26:19.760 | how fast, or stay still, move forward, move back.

01:26:22.960 | And I'll just add,

01:26:24.520 | 'cause I'm hoping that you'll expand on this.

01:26:27.760 | It's been said before that ultimately the nervous system

01:26:31.460 | is trying to make decisions about yum, yuck, or meh.

01:26:35.080 | Like, am I going to move towards something?

01:26:37.180 | Am I going to move away from it?

01:26:38.460 | Or am I just going to stay put?

01:26:40.060 | - Well, that's only at the, that's a very,

01:26:43.140 | I would say that those are very low dimensional features.

01:26:45.900 | So those are those compressed features,

01:26:47.380 | but that's not the only thing the brain has to decide.

01:26:50.140 | That's just a misnomer.

01:26:51.920 | - Well, I can get out of this little pickle

01:26:54.160 | that I just put myself in by saying that I didn't say that.

01:26:56.340 | And now I won't quote who did,

01:26:57.880 | 'cause he's a very famous neuroscientist,

01:26:59.600 | but he tried to reduce it all.

01:27:00.880 | He's at Caltech, he's not somebody who studies emotion.

01:27:04.220 | He studies the visual system.

01:27:05.520 | But he said that the neural circuits,

01:27:09.060 | maybe it's 'cause he studies mice,

01:27:10.460 | are essentially binned into yum, yuck, and meh outputs.

01:27:15.260 | And I've always liked it on the one hand,

01:27:17.660 | 'cause threes work and it's simple,

01:27:19.260 | but rarely is the way that we describe things

01:27:21.420 | the way it actually works.

01:27:22.260 | - Yeah, so we would, in studying humans,

01:27:24.760 | we would say, well, that's affect, affect, that's mood.

01:27:28.280 | Or it's just like, is it, should I move towards it?

01:27:31.520 | Is it pleasant?

01:27:32.440 | Should I move away from it?

01:27:33.720 | Is it unpleasant?

01:27:34.760 | Or is it irrelevant, basically?

01:27:36.640 | I don't care.

01:27:37.920 | Okay, think about when you're feeling horrible.

01:27:39.780 | You just feel, you feel bad.

01:27:44.100 | What do you do?

01:27:45.420 | - You don't know it.

01:27:46.260 | - You don't know, because you don't have a plan of action.

01:27:48.600 | And that's ultimately, that is what those compressed

01:27:53.120 | like summary features, those very low course features,

01:27:57.400 | they have to be decompressed into details.

01:28:00.700 | Otherwise, you don't know what to do.

01:28:02.940 | So ultimately, what the brain is doing

01:28:05.920 | is it's sampling from the past based on similarity

01:28:10.920 | to the present to plan an action.

01:28:14.480 | And when I say action,

01:28:15.440 | I don't just mean skeletal motor action, like moving a limb.

01:28:18.780 | The first actions that are planned

01:28:21.720 | are the actions of coordinating the heart and the lungs

01:28:25.000 | and all of the internal actions that are required

01:28:30.000 | to support the motor, the skeletal motor movements.

01:28:32.760 | So your brain is making, is categorizing,

01:28:36.380 | it's creating a category and there are options there.

01:28:40.480 | Those options, the motor plans begin with,

01:28:44.000 | should the heart beat faster?

01:28:46.000 | Should it beat slower?

01:28:47.160 | Does blood pressure need to go up?

01:28:48.760 | Should the blood vessels constrict or should they dilate?

01:28:53.720 | Should the breathing be deeper or more shallow?

01:28:56.860 | I mean, those are the first plans that get made.

01:29:00.500 | And then milliseconds later,

01:29:02.000 | there are the skeletal motor plans.

01:29:04.120 | And then your experience of the world

01:29:07.320 | derives from those motor plans.

01:29:09.880 | Those viscera motor, that is the plans for the viscera,

01:29:13.400 | for the internal organs and the skeletal motor.

01:29:15.760 | So I'm just gonna refer to them as motor.

01:29:18.120 | Those motor plans actually give rise

01:29:20.000 | to your experience of the world.

01:29:21.760 | There's not some state that exists as an emotional state,

01:29:25.320 | which then you apply a label to.

01:29:27.360 | The label is just a set of features that are useful

01:29:32.360 | for generalizing from the past to the present.

01:29:39.280 | And the bin size or the, you know,

01:29:43.480 | of what a word refers to can change.

01:29:48.240 | It can change, it's different for different people

01:29:50.620 | and it can change in your lifetime.

01:29:53.620 | And you can add new bins.

01:29:55.560 | That is, you can, so for example,

01:29:57.240 | there's a concept giskinluk,

01:29:59.600 | which I probably just butchered.

01:30:01.040 | So if you speak Turkish, I'm sorry.

01:30:03.340 | But it's like, it has features of it,

01:30:06.120 | of like loss and like people blocking your goals.

01:30:11.480 | So we would say it's anger and sadness together.

01:30:14.760 | That's giskinluk, when you lose something

01:30:16.600 | and you're pissed off about it.

01:30:18.600 | That's a, but that's a category on its own, right?

01:30:22.880 | It's just a different way of parsing

01:30:24.480 | that really detailed soup.

01:30:27.680 | And the more words you know,

01:30:31.240 | the more, words are just useful for pointing

01:30:36.080 | to a set of features that are similar to each other.

01:30:38.440 | So what I mean by that is, if I say to you, Andrew,

01:30:41.680 | I had pizza last night for dinner.

01:30:43.440 | Pizza, two sounds, two syllables.

01:30:48.840 | That, those two syllables, they stand in

01:30:51.300 | for like 50 different sensory and motor features.

01:30:54.540 | 'Cause I don't have to say to you, I had a food,

01:30:59.040 | I didn't have pizza last night, but let's say I did.

01:31:01.080 | I had a food that was round and flat and had sauce

01:31:05.460 | and also cheese and it had mozzarella cheese

01:31:08.380 | and also a little Parmesan cheese.

01:31:10.260 | And it had mushrooms on it and a little bit of olive.

01:31:14.220 | And that's like really, really detailed and complicated.

01:31:19.220 | But instead I can just say, I had pizza, two features,

01:31:23.140 | two sounds, two syllables, phonemes.

01:31:26.500 | And with those two phonemes,

01:31:28.820 | I have just communicated to you in your brain.

01:31:31.580 | My brain had 50 features it was representing of details.

01:31:34.740 | And now I have just communicated those to you

01:31:38.400 | or some number of them with two sounds, very efficient.

01:31:43.400 | Now, of course, you might think that I was from Chicago

01:31:48.620 | and had deep dish pizza and I'll just resist.

01:31:51.700 | I don't wanna like offend anybody from Chicago.

01:31:54.100 | - It's not pizza, I'll say it. - That's not real pizza.

01:31:56.100 | That's not real pizza.

01:31:57.320 | Right, so you could then ask me, was it,

01:32:02.900 | but you're from Chicago, is that deep dish pizza?

01:32:05.180 | And then I would say, no, no, I'm actually from Toronto,

01:32:07.780 | which is just like New York.

01:32:09.040 | And so no, it was thin crust pizza,

01:32:10.660 | which is really the only kind of pizza there is, just saying.

01:32:14.420 | But my point is that words are just stand in for,

01:32:19.420 | they're just these like low dimensional features,

01:32:23.620 | these sort of gross features that stand in for many,

01:32:26.860 | many, many, many little detailed features.

01:32:28.940 | And that's how we communicate with each other.

01:32:31.220 | - And we are constrained by what we know in our-

01:32:34.660 | - Yes.

01:32:35.500 | - And what we can say and the extent of our vocabulary.

01:32:38.260 | - And I'll just say that little babies, three months old,

01:32:42.780 | they don't speak yet and they don't understand language,

01:32:46.100 | but they can use words to learn abstract categories.

01:32:51.100 | So abstract just means that the word refers

01:32:55.100 | to many different patterns of sensory motor features.

01:32:57.560 | So the word is, or the category,

01:33:01.380 | the things that make the instances similar are a function

01:33:06.380 | or a goal, not like the sensory motor feature.

01:33:09.840 | So you say to a baby, very explicitly,

01:33:13.820 | 'cause we're talking about three,

01:33:14.740 | four month old babies, right?

01:33:16.560 | Babies can also do this implicitly too.

01:33:20.500 | But in experiments, you say to a baby,

01:33:23.020 | look, sweetie, this is a bling.

01:33:27.060 | And you put the bling down and it makes a beeping noise.

01:33:31.420 | And then you say, now this looks different,

01:33:34.900 | feels different, right?

01:33:36.540 | Smells different.

01:33:38.300 | Look, sweetie, this is a bling.

01:33:41.460 | It beeps.

01:33:45.420 | Now you take something else, which also is different.

01:33:50.420 | And you say, look, sweetie, this is a bling.

01:33:53.680 | Now the baby expects this to beep.

01:33:56.960 | - By the way, folks, just listening,

01:33:58.440 | Lisa just gave three examples,

01:34:00.340 | first with a pen, then a coffee mug,

01:34:03.120 | and then her very own watch, three very distinct objects,

01:34:06.700 | but all of which make, that are told,

01:34:09.440 | the baby is told make a bling sound

01:34:12.300 | and they will bin those three visually distinct objects,

01:34:17.220 | functionally distinct objects into one single bin.

01:34:19.860 | - Because they make a,

01:34:21.220 | because they are sharing a function, which is to beep.

01:34:24.540 | - I think this is so important.

01:34:26.620 | And I, and if I may, I want to ask

01:34:31.620 | whether or not we can take this incredible understanding

01:34:37.560 | of emotions, 'cause that's really what we're talking about.

01:34:41.880 | - Well, really talking about how the brain,

01:34:43.680 | my version of how the brain works

01:34:45.140 | and how emotions emerge out of this system, basically.

01:34:49.000 | - And absolutely, you described it far better than I could.

01:34:53.200 | And anchor that to this concept of movement,

01:34:57.580 | that the movement is the final common path,

01:34:59.720 | with the understanding that the movement system,

01:35:03.300 | and forgive me, but that we have systems

01:35:05.060 | in the brain and body that allow us to move,

01:35:06.720 | that's for sure, systems, plural,

01:35:09.720 | that they run in both directions.

01:35:11.580 | In other words, how we feel what we feel our emotions

01:35:16.580 | has some bearing on the movements

01:35:19.720 | that are more or less likely for us in a given context.

01:35:22.820 | And our movements clearly can also influence

01:35:26.500 | the way that we feel internally, right?

01:35:28.500 | - Well, I mean, so if we just look

01:35:31.300 | at how things are happening,

01:35:32.380 | here's what the anatomy tells us,

01:35:35.320 | that when the brain makes a guess,

01:35:37.180 | that guess starts as a motor plan,

01:35:40.540 | starts as a visceral motor plan and a skeletal motor plan.

01:35:43.620 | - So heart rate changes, breathing changes,

01:35:45.900 | blood pressure changes,

01:35:47.500 | and potentially skeletal muscle movement.

01:35:49.500 | - Right, and literal copies,

01:35:52.620 | literal copies, efferent copies of those signals

01:35:56.100 | are sent to, they propagate to the sensory areas,

01:35:59.420 | telling the brain, telling those neurons,

01:36:02.300 | this is the last time we've made this,

01:36:04.480 | in this context, when this other stuff just happened,

01:36:07.920 | like this temporal context, right?

01:36:09.920 | And we made these movements, here's what we saw next,

01:36:14.260 | here's what we felt next, here's what we smelled next, so.

01:36:19.260 | - Yeah, I think of this as the image that pops in my mind,

01:36:21.980 | and we should explain to people what efferents copy is,

01:36:24.820 | in neuroscience and neuroanatomy,

01:36:26.900 | the connection to a structure is called an afferent

01:36:29.900 | with an A, and the connections out from a structure

01:36:32.300 | are called the efferents, but the way I was thinking-

01:36:34.180 | - It doesn't even matter, it's just basically,

01:36:35.860 | the point here is that in our experience,

01:36:38.980 | in the way, your brain conjures an experience, okay?

01:36:42.540 | And that experience is that you feel something first,

01:36:46.800 | you see something, you feel something, you act.

01:36:49.820 | That's not what's happening.

01:36:51.320 | What's happening is your brain is preparing the action first

01:36:55.260 | and the feeling, and your experience,

01:36:58.420 | comes from that action preparation.

01:37:00.840 | So it's a copy, it's like literally you have axons

01:37:04.580 | that are sending motor signals down the brainstem

01:37:09.240 | to the spinal cord, and literal copies of those axons,

01:37:13.180 | like those axons have branches, that collateral branches

01:37:17.040 | that just send axons other places.

01:37:20.240 | The same signal that is being sent to your spinal cord

01:37:25.240 | to move stuff in your body,

01:37:28.660 | that same signal is being sent to other neurons in the brain

01:37:33.060 | as predictions of the sensations that are gonna happen

01:37:36.220 | in a second from now, a moment from now,

01:37:38.020 | probably faster than a second,

01:37:39.580 | but in a couple of milliseconds, if you move.

01:37:44.020 | And so, yes, it is the case

01:37:46.620 | that what you feel is linked to what you do,

01:37:49.160 | and what you do is linked to what you feel,

01:37:50.980 | but not in this simple mechanistic way

01:37:54.060 | that neuroscientists and psychologists

01:37:56.620 | have been using forever.

01:37:59.820 | It's not like you're probed by a stimulus,

01:38:04.820 | you see something, you hear something,

01:38:07.900 | and then you process it and evaluate it,

01:38:10.740 | and then you react to it.

01:38:11.920 | No, that's not what's happening.

01:38:13.380 | What's actually happening under the hood

01:38:15.660 | is that based on how things are right now,

01:38:18.180 | your brain makes a guess, or some guesses,

01:38:20.960 | and those guesses start as motor plans,

01:38:24.160 | and the consequence of those motor plans

01:38:27.900 | are predicted sensations.

01:38:30.240 | And then, of course, sensory signals

01:38:32.940 | are coming from the sensory surfaces,

01:38:34.680 | and here's, to me, really the most mind-boggling thing

01:38:39.340 | about this whole explanation.

01:38:41.720 | If your sensory neurons in your sensory areas are already,

01:38:47.500 | so they're firing, the action potentials,

01:38:50.580 | the spiking has changed

01:38:51.940 | based on these prepared motor movements,

01:38:54.480 | so these are sensory predictions.

01:38:56.720 | And when I give talks, and on my website,

01:38:58.620 | I have some cool examples of how this works,

01:39:01.260 | you can experience it yourself.

01:39:03.280 | You start to experience, you hear things that aren't there,

01:39:07.420 | you feel vibrations in your chest that aren't there,

01:39:09.940 | because your brain is predicting,

01:39:11.140 | it's predicting these sensations.

01:39:12.920 | So let's say the sensations come,

01:39:15.900 | the sensory signals, I should say, let me say,

01:39:17.940 | so the sensory signals from the sensory surfaces of the body

01:39:21.480 | make it to the brain.

01:39:22.520 | If you have, if your neurons are already firing in a way

01:39:28.560 | to anticipate those signals,

01:39:31.180 | those signals just confirm the firing,

01:39:34.140 | and then they're done,

01:39:34.980 | they don't make it any further into the brain.

01:39:37.340 | So when you're predicting well,

01:39:43.720 | your experience is constructed completely by your brain.

01:39:46.980 | The signals from the sensory surfaces

01:39:50.020 | are there just to confirm,

01:39:52.380 | or to change the signals.

01:39:55.780 | So if there's things you didn't anticipate,

01:39:59.360 | then those errors of prediction,

01:40:03.240 | those are the signals that are propagated

01:40:05.060 | and become compressed and stuff,

01:40:06.440 | and we have a special name for that in science,

01:40:10.140 | we call it learning.

01:40:12.080 | You know, Andy Clark is a philosopher

01:40:14.500 | who writes a lot about prediction,

01:40:16.660 | predicting brain and so on,

01:40:18.620 | and he talks about normal everyday experience

01:40:22.100 | as being a controlled hallucination.

01:40:25.840 | - That's true. - Yeah.

01:40:27.720 | - I subscribe to that.

01:40:29.040 | It's a fairly adaptive in most circumstances,

01:40:33.500 | controlled hallucination, but it has its limitations.

01:40:36.300 | And it, I mean, what we were talking about,

01:40:39.260 | if I could be somewhat of a summary neuron,

01:40:41.700 | you can tell me if my summary is too coarse,

01:40:44.260 | is that first of all, that the neural systems

01:40:46.940 | and the brain, let's just call it the nervous system,

01:40:48.940 | 'cause we're talking about brain and body,

01:40:51.360 | are incredibly dynamic.

01:40:52.980 | There's a bunch of inputs.

01:40:55.820 | Those inputs are incredibly elaborate.

01:40:58.040 | They get summarized.

01:40:59.280 | The summary prepares the body for a certain action.

01:41:01.860 | That's a motor commands, a pre-motor commands,

01:41:04.200 | and then some action may or may not be taken,

01:41:06.860 | but already, as soon as an action is taken or not taken,

01:41:11.800 | the whole state of the neural system is different.

01:41:14.100 | It's changed as a consequence of what just happened.

01:41:16.900 | Now, of course, when people hear that,

01:41:18.740 | and when I hear that, indeed, I feel like,

01:41:21.020 | wow, it's a tough system to study,

01:41:22.700 | because these are dynamical neural systems,

01:41:24.860 | and we have the technology to put people

01:41:28.080 | in functional scanners and look at what lights up,

01:41:32.160 | so to speak.

01:41:33.000 | We have the capacity to ask people

01:41:35.420 | how they feel based on questionnaires,

01:41:36.940 | but you can imagine that's incredibly crude,

01:41:39.320 | so then you give them Likert scales of rate from one to 10,

01:41:42.300 | how happy or sad you are,

01:41:44.020 | and so you're adding some depth and dimensionality to it,

01:41:47.620 | but it's incredibly crude.

01:41:48.860 | It's nothing like real experience,

01:41:51.180 | and if somebody is more verbal, less verbal,

01:41:54.500 | maybe they somaticize more or less.

01:41:56.700 | The example comes to mind that occasionally

01:41:59.780 | you learn from social media,

01:42:01.580 | which often I learned from social media,

01:42:03.340 | when someone once said, "I don't think in thoughts.

01:42:05.580 | I think in feels," and I thought, okay, great.

01:42:08.220 | You're probably also from Northern California,

01:42:09.980 | and then I said, "Wait, Andrew, stop being so judgmental.

01:42:12.360 | What do you mean?"

01:42:13.200 | And I asked, and they said,

01:42:14.020 | "I experience emotions in their mind

01:42:17.340 | first as a bodily state.

01:42:19.940 | Then the label comes much later."

01:42:22.740 | That's not how it works for me.

01:42:24.160 | It feels fairly more integrated, brain and body for me,

01:42:27.940 | but other people started chiming in,

01:42:30.280 | "No, I think of emotion.

01:42:32.060 | I experience emotions clearly as a verbal label.

01:42:35.060 | It's all in their head."

01:42:36.780 | And so you start to realize

01:42:37.880 | that we might all be encoding the world

01:42:40.220 | slightly differently or very differently,

01:42:42.820 | and it's changing in time.

01:42:44.020 | So then the question becomes what are the anchor points

01:42:48.000 | in terms of our understanding of emotions

01:42:50.320 | that we can work with?

01:42:52.100 | And the following questions come to mind.

01:42:55.160 | Neither you nor I are clinicians as far as I know.

01:42:58.940 | I'm certainly not.

01:42:59.780 | - I was actually trained as a clinician.

01:43:01.060 | - Oh, there you go.

01:43:01.880 | You're wrong again.

01:43:03.000 | - No, no, no.

01:43:03.840 | But I haven't practiced in like really gazillions of years.

01:43:07.860 | - Well, you're more than qualified

01:43:10.040 | to answer the question I'm about to ask,

01:43:11.440 | which is to me, there is a great conflict of information

01:43:16.440 | in the psychology, psychiatry,

01:43:20.260 | and let's just call it wellness and mental health space,

01:43:22.940 | which is when we are feeling lousy, like not good,

01:43:27.140 | let's put valence on it, just lousy.

01:43:28.720 | I don't want, in a state that we were having an emotion

01:43:31.500 | that we don't want to have,

01:43:32.860 | there's an entire category of information that says,

01:43:36.980 | you need to feel your feelings.

01:43:39.340 | You need to feel your feelings.

01:43:40.300 | You need to acknowledge that they're there.

01:43:41.900 | You need to go into the feeling, maybe even full catharsis.

01:43:45.480 | You need to amplify the feelings

01:43:47.220 | until they quote unquote leave your body.

01:43:49.740 | After all, Steve Jobs was into scream therapy

01:43:52.200 | and he helped him expunge his anger.

01:43:54.700 | Who knows?

01:43:55.540 | You get these examples.

01:43:56.860 | He's probably the worst example

01:43:58.180 | 'cause it seemed like he was angry a lot from what I hear.

01:44:00.580 | But then there's another category of thought,

01:44:03.400 | which is, no, you need to use your ability

01:44:06.940 | to top down control inhibition of the cortex

01:44:10.820 | on lower structures.

01:44:11.860 | Again, I'm deliberately using crude language here

01:44:14.620 | to say, wait, this is an emotion.

01:44:17.240 | Emotions pass.

01:44:19.100 | This is not real.

01:44:20.500 | This is just a limited set of high dimensionality stuff

01:44:23.760 | that's been summarized.

01:44:24.720 | And you know what?

01:44:25.560 | Like, I don't need to feel this way.

01:44:28.000 | I can make myself feel differently.

01:44:30.020 | Maybe I'll go for a run.

01:44:31.060 | In fact, I always feel better after I go for a run.

01:44:33.300 | So even this question as simple as

01:44:35.860 | should we feel our feelings

01:44:37.800 | or should we not feel our feelings?

01:44:41.540 | And of course, you would hope

01:44:42.740 | that this would be answered appropriately

01:44:45.380 | such that people don't go harm other people or themselves.

01:44:48.460 | But assuming that they're not gonna harm other people

01:44:50.300 | or themselves verbally or physically,

01:44:52.300 | then you really get yourself into a bit of a pickle.

01:44:55.540 | We don't understand what to do with emotions,

01:44:59.260 | ours or other people's,

01:45:00.580 | because clearly we don't understand emotions per se.

01:45:05.580 | - So I would say I'm gonna answer your question

01:45:10.100 | and then I wanna also pick at the word,

01:45:14.340 | I wanna pick at an assumption

01:45:15.980 | because it's come up actually a couple of times

01:45:19.040 | and there's something super important in your descriptions

01:45:22.600 | that I just wanna pull out for the listeners

01:45:26.060 | 'cause this thing is really important

01:45:27.300 | and you're doing it very naturally,

01:45:28.940 | but I think some people, it just bears commenting on.

01:45:32.480 | So let me just deal with the question of

01:45:34.560 | should we feel our feelings or use our words?

01:45:37.500 | We say to little kids, use your words,

01:45:38.980 | don't throw a tantrum.

01:45:40.740 | But then there was also this other feeling,

01:45:42.540 | oh, just feel, it's important to feel

01:45:44.140 | and you don't wanna get it, have it be pent up.

01:45:45.940 | - Or use your body and hit a pillow.

01:45:48.900 | I mean, there's scream therapy, bite the pillow,

01:45:50.700 | scream the pillow, tear the pillow.

01:45:52.820 | You can pay $5,000 for a week of doing this

01:45:55.660 | and they'll tell you you're gonna feel better at the end.

01:45:57.380 | So the answer there is it's the wrong question.

01:46:00.980 | Like flexibility is important for everything always, right?

01:46:05.980 | So first of all, you don't have emotions in your body.

01:46:11.860 | Your body doesn't keep the score, you know?

01:46:14.500 | - Yeah, great book title because it's super catchy,

01:46:17.060 | but with all due respect to I think

01:46:19.100 | the important work of van der Kolk,

01:46:22.500 | I think it oversimplified and led people to believe

01:46:26.420 | that their back pain was trauma

01:46:28.500 | and that all trauma is somaticized and it's not.

01:46:32.620 | - No, it's not.

01:46:33.460 | But I would go further and say like,

01:46:35.380 | first of all, your body does keep the score,

01:46:37.540 | your brain keeps the score, your body is the scorecard.

01:46:41.140 | That's super important.

01:46:44.020 | And he has done really important work,

01:46:46.700 | but his explanations for why things work

01:46:49.860 | is scientifically incorrect.

01:46:52.700 | It just is because we don't feel things in our bodies.

01:46:57.380 | Everything we feel, we feel in our brains.

01:47:00.060 | We don't see in our eyes, we see in our brains.

01:47:03.020 | Of course, we need our eyes, but we don't see in our eyes.

01:47:06.780 | Just like if you pinch your hand,

01:47:10.900 | take skin and pinch between two fingers,

01:47:14.460 | the skin, you don't feel that actually in your hand,

01:47:17.100 | you feel it in your brain.

01:47:19.180 | That's the magic of the brain in a sense.

01:47:22.100 | So what I would say is it depends on the situation

01:47:27.100 | and what your goal is.

01:47:31.740 | Sometimes it is useful to use your words

01:47:35.780 | and sometimes it is useful to go for a run.

01:47:38.120 | It just depends on what your goal is.

01:47:42.100 | - Well, both those cases that you gave,

01:47:45.260 | both those examples, excuse me,

01:47:47.400 | it's a way of shifting off the emotion.

01:47:50.100 | I guess what I'm asking is-

01:47:51.900 | - Well, sometimes you don't want to shift off the emotion.

01:47:53.940 | Sometimes the wisest thing to do is live in the emotion.

01:47:58.800 | That is, sometimes discomfort,

01:48:02.880 | sometimes when something feels bad,

01:48:04.660 | it doesn't mean something is wrong.

01:48:06.000 | It just might mean that you're doing something hard.

01:48:08.300 | - Well, earlier I wrote,

01:48:09.140 | when you're talking about the broad categorization

01:48:11.340 | of emotions, I wrote down,

01:48:12.860 | simple is good when it feels good.

01:48:15.060 | I just feel really great.

01:48:16.540 | But then when things feel lousy,

01:48:18.300 | that's where nuance could be beneficial.

01:48:19.780 | - Yeah, absolutely, because emotions are recipes for action.

01:48:24.700 | When you go from feeling bad to feeling angry or sad,

01:48:29.620 | it's a recipe for action.

01:48:31.740 | And I would also say, and this is an analogy,

01:48:34.580 | but I sort of, I stand by it.

01:48:37.140 | I had major back surgery a couple of years ago

01:48:43.700 | and I know something about chronic pain.

01:48:46.500 | It's not my area of study,

01:48:47.980 | but I know something about it because I've reanalyzed

01:48:51.100 | some data sets and I've read a lot.

01:48:53.260 | So I'm not an expert, but I have ideas.

01:48:56.340 | And I thought to myself,

01:48:57.180 | well, I don't want to end up with chronic back pain.

01:49:00.860 | So what I did was I made sure,

01:49:02.860 | after I got through the first couple of weeks

01:49:05.260 | where I really needed oxycodone so that I could walk,

01:49:08.180 | I was up and walking the same day I had surgery,

01:49:10.900 | if you could call it walking as sort of a euphemism

01:49:12.940 | for like hobbling around with a walker.

01:49:15.140 | But I made sure that I felt the pain.

01:49:18.340 | That is, I dosed myself with discomfort quite deliberately

01:49:24.380 | because I wanted to make sure that,

01:49:28.260 | I'm sorry for using, you know, Cartesian language.

01:49:30.740 | I don't know how else to say this.

01:49:32.180 | I wanted my brain to be taking in the prediction error.

01:49:35.960 | I wanted my brain to feel,

01:49:40.620 | I wanted to focus attention on the changing discomfort

01:49:45.620 | over time because it meant that my body was healing

01:49:52.120 | as the discomfort got less,

01:49:53.480 | but my brain would never feel that discomfort changing

01:49:56.820 | if I took painkillers.

01:50:00.380 | And because the prediction error,

01:50:05.380 | the things that the brain doesn't predict

01:50:07.660 | are teaching signals.

01:50:09.860 | And I think it's true also in your life.

01:50:12.060 | Like sometimes you wanna feel it

01:50:13.940 | because you wanna feel the discomfort

01:50:16.820 | because it's instructive about something.

01:50:18.660 | And sometimes it's not.

01:50:20.300 | And that's, maybe that's not really an answer,

01:50:22.300 | but the only way that you can figure that out for yourself

01:50:25.020 | is to do it sometimes.

01:50:26.220 | If you're always getting rid of discomfort,

01:50:28.740 | you never know when it's useful.

01:50:30.540 | And it is useful sometimes.

01:50:32.780 | But now I wanna get to this point that I was making before.

01:50:35.780 | Like we are talking about feeling and emotion

01:50:38.380 | like they're interchangeable and they're not, right?

01:50:42.340 | So here's how I would say it.

01:50:44.980 | Your brain is always regulating your body 24/7.

01:50:49.980 | And your body is always sending sensory signals

01:50:53.840 | back to the brain about the sensory state of the body.

01:50:57.320 | And our nervous systems aren't wired for us to experience

01:51:02.060 | those sensory changes that are happening in the body

01:51:07.340 | in any degree of detail.

01:51:09.040 | We're just not.

01:51:12.300 | And it's a good thing.

01:51:13.500 | Like right now, as we talk here, our hearts are beating

01:51:17.820 | and our pancreas is squishing stuff out,

01:51:22.180 | liver is filtering and like oxygen concentrations

01:51:28.020 | are changing.

01:51:29.740 | Like, oh, there's a whole drama going on inside each of us

01:51:32.980 | and our listeners.

01:51:34.060 | And we're largely, we're not aware.

01:51:35.920 | And I hope our listeners aren't aware

01:51:37.580 | because if they were, they would not be listening

01:51:39.020 | to anything we were saying.

01:51:40.180 | They'd be completely enraptured or in discomfort

01:51:45.180 | at what's going on inside them.

01:51:47.260 | Instead, the brain creates a low dimensional summary,

01:51:52.400 | this gross kind of like barometer,

01:51:55.320 | which is feeling, affective feeling.

01:51:58.040 | We call it, or you could call it mood,

01:51:59.440 | but scientists call it affect with an A.

01:52:01.740 | Feeling pleasant, feeling unpleasant, feeling worked up,

01:52:04.220 | feeling calm, feeling comfortable, feeling uncomfortable.

01:52:07.360 | It's kind of a general barometer of the state of the body.

01:52:12.360 | And it's not emotion.

01:52:14.800 | That, those feelings, those features of feeling

01:52:18.220 | are features of consciousness

01:52:20.300 | because your brain is always regulating your body.

01:52:22.620 | Your body's always sending signals back to the brain.

01:52:24.940 | The brain is always representing them

01:52:26.940 | in this low dimensional way.

01:52:28.680 | Whether you're paying attention or not,

01:52:30.320 | like whether the brain is focusing,

01:52:32.220 | it's applying attention to those neurons or not.

01:52:36.300 | Those signals are there.

01:52:37.680 | And even when we're not emotional.

01:52:40.840 | You know, like if you're driving on the highway

01:52:44.300 | and somebody cuts you off and you think, what an asshole.

01:52:47.940 | The assholeness of that person,

01:52:49.920 | that intensity of that negative affect is,

01:52:53.300 | you experience it as a property of that person,

01:52:57.020 | but really it's coming from you.

01:52:59.060 | It's not a property of that person.

01:53:01.340 | It's, that's a feature of your experience in that moment.

01:53:06.220 | And affect is always there.

01:53:09.500 | Sometimes it's in the foreground,

01:53:10.780 | sometimes it's in the background, but it's always there.

01:53:13.380 | And it's a summary of physical things,

01:53:15.820 | which is why it helps to,

01:53:18.060 | if you take ibuprofen or Tylenol, it will reduce,

01:53:22.160 | I mean, studies show it reduces negative feeling.

01:53:25.300 | If you go for a run, if you go for a walk,

01:53:27.620 | if you shift your attention to the outside world,

01:53:31.460 | then the features that of experience

01:53:34.260 | that are derived from the inside world diminish.

01:53:38.820 | That's why going for a run helps or going for a walk helps

01:53:41.860 | or, you know, getting sleep helps, right?

01:53:45.660 | These are all things where you're changing

01:53:47.860 | the state of your body.

01:53:49.740 | And so the sensory state of your body is changing

01:53:52.180 | and so your affect changes.

01:53:54.460 | But emotions are the story that the brain tells

01:53:58.420 | about what caused the sensory signals

01:54:02.900 | that affect derives from.

01:54:04.460 | So what caused those changes?

01:54:06.640 | What do I need to do about those changes?

01:54:09.060 | That's, it's a much bigger event

01:54:12.900 | than just these features of experience,

01:54:15.380 | which are all features of consciousness,

01:54:16.900 | which are always there.

01:54:18.640 | They're always there.

01:54:19.460 | And in fact, in our culture,

01:54:24.400 | we pathologize people when they just experience

01:54:29.400 | their bodies as physical sensations and not as emotions.

01:54:34.540 | Like we say, oh, that person is somaticizing or somatizing.

01:54:38.080 | They're not, they should be experiencing an emotion,

01:54:41.840 | but really they're, you know,

01:54:43.120 | just experiencing a stomach ache and that's bad.

01:54:45.800 | But that's actually a judgment call

01:54:47.800 | that is probably sometimes wrong.

01:54:50.000 | Sometimes it's probably better to experience a stomach ache.

01:54:53.260 | Sometimes it's more productive.

01:54:55.060 | Part of being emotionally intelligent

01:54:56.340 | is knowing when not to construct an emotion, you know?

01:55:00.460 | Like right before the COVID pandemic

01:55:03.640 | was announced officially,

01:55:05.540 | I was in New Zealand giving talks.

01:55:10.540 | And my daughter, who was in college at that time,

01:55:16.380 | was flying literally like I think less than a week

01:55:21.820 | before the pandemic was announced.

01:55:23.820 | She got on a plane and she flew to New Zealand to meet me

01:55:26.520 | because it was spring break

01:55:27.480 | and I always would bring her with me on spring break.

01:55:30.620 | And in that, and I remember really vividly,

01:55:34.180 | I was in New Zealand, there was only one case,

01:55:37.660 | one case of COVID in New Zealand at that point.

01:55:41.200 | And I got on the phone to my husband and I said,

01:55:44.660 | I'm experiencing a very high level of arousal

01:55:49.460 | and it's very, very unpleasant.

01:55:52.160 | Now, my husband knows me very well.

01:55:57.500 | And he said, yeah, there's a lot of uncertainty.

01:56:00.720 | And I said, I know.

01:56:02.460 | Now, he didn't say to me, well, you're anxious

01:56:04.420 | and you just don't really know it.

01:56:06.060 | 'Cause I wasn't anxious.

01:56:07.380 | I was feeling uncertain.

01:56:10.360 | And as you know, or maybe people know

01:56:15.360 | that when there's a lot of uncertainty,

01:56:17.000 | there's also a lot of arousal

01:56:18.580 | because the brain is attempting to learn

01:56:22.060 | and the neuromodulators that are important

01:56:24.080 | for learning new things happen

01:56:26.420 | to also cause a subjective sense of arousal.

01:56:30.800 | And they actually also modulate your autonomic nervous system

01:56:33.920 | so your heart can beat faster and whatever.

01:56:35.360 | And our go-to explanation for what that is

01:56:38.840 | is to experience that arousal as anxiety.

01:56:42.160 | But I was uncertain.

01:56:43.960 | And remember that how your brain,

01:56:46.440 | the story it's telling itself,

01:56:47.860 | the category it's making is a plan for action.

01:56:50.960 | Well, what do you do in anxiety and fear?

01:56:53.980 | You freeze or you run away.

01:56:55.820 | What do you do in uncertainty?

01:56:57.940 | You forage for information.

01:57:00.620 | You tolerate the discomfort and you forage for information,

01:57:04.460 | which is what I was doing when I called and said,

01:57:07.020 | what should we do?

01:57:07.860 | Should I meet her at the airport

01:57:09.060 | and turn around and come back?

01:57:10.020 | Or should we have a vacation?

01:57:11.100 | Like, I don't really know.

01:57:12.400 | And you know, what I ended up doing

01:57:15.180 | was foraging for information for another couple of days

01:57:18.400 | and then made a split second decision in the air

01:57:22.160 | when we were flying from one island to the other

01:57:24.140 | and just rerouted us and we went home.

01:57:26.320 | And then the borders closed like two days later, you know?

01:57:30.060 | But my point is that this is not just, you know,

01:57:34.640 | psychological mumbo jumbo.

01:57:40.300 | You can train yourself to experience

01:57:44.460 | your heart pounding in your chest as determination.

01:57:49.460 | When my daughter, this is all in how emotions are made,

01:57:52.620 | these examples, but they're true.

01:57:54.460 | I mean, my daughter, this book I wrote a couple of years ago,

01:57:58.340 | when my daughter was 12 years old,

01:57:59.620 | she was testing for a black belt in karate.

01:58:01.940 | She was five feet tall, not even.

01:58:04.700 | And she was testing against these like massively large

01:58:07.860 | adolescent boys, okay, who were like a foot taller than her.

01:58:12.860 | And her sensei, who was a 10th degree black belt,

01:58:17.420 | didn't say to her, "Don't be afraid."

01:58:20.380 | He said, "Get your butterflies flying in formation."

01:58:23.720 | And I was like, in rapture, I was like,

01:58:26.900 | "Oh my God, this guy is totally brilliant."

01:58:29.260 | That is the best, you know, meaning to give to arousal

01:58:34.260 | that changes the meaning of it.

01:58:40.940 | What you do when you create an emotion

01:58:43.280 | is you're giving meaning to those affective feelings.

01:58:48.280 | And you have more control than you might think

01:58:53.460 | in how you do that.

01:58:54.980 | You can do it by changing the physical state

01:58:57.560 | that gives rise to those feelings,

01:58:59.320 | but you can also change it by learning more,

01:59:02.280 | how to make more categories

01:59:03.540 | and how to make them more fluidly

01:59:06.260 | so that you do something different.

01:59:08.960 | And it's not that things will necessarily feel

01:59:13.340 | any more unpleasant or any less or any more pleasant.

01:59:18.100 | It's that the feeling becomes a source of wisdom.

01:59:23.100 | It's a cue to do something different.

01:59:26.840 | - There's a case where I absolutely believe

01:59:30.940 | that knowledge about how emotions and affect

01:59:37.380 | and states of the brain and body work,

01:59:39.360 | which is what you're beautifully describing

01:59:41.040 | for people today, is extremely useful in and of itself.

01:59:46.040 | And I think, frankly, it's a refreshing

01:59:50.820 | and welcome departure from a lot of the conversations

01:59:53.740 | that we normally have on this podcast,

01:59:55.260 | where, you know, we talk a lot about protocols,

01:59:57.660 | we talk about tools, things that people can do,

01:59:59.940 | ways they can implement the knowledge.

02:00:01.980 | And here, this is certainly one of those cases as well,

02:00:05.480 | but it's a beautiful one and a very important one

02:00:10.480 | where the knowledge itself,

02:00:14.800 | just the knowledge of additional words for different states.

02:00:18.360 | I love the example of putting butterflies into formation

02:00:21.520 | because inherent to that is that you're not trying

02:00:25.060 | to get rid of the butterflies, quite the opposite.

02:00:28.260 | You're deploying them in certain ways.

02:00:30.100 | And there's an action step and a psychological step there,

02:00:32.520 | of course that's required, but that it isn't, you know,

02:00:35.980 | view morning sunlight for an average of 10 minutes

02:00:37.880 | to set your circadian rhythm,

02:00:39.000 | which is something that I say over and over again,

02:00:41.300 | I'll go into the grave saying that,

02:00:42.540 | they'll probably put a window over my grave

02:00:43.860 | so sunlight can get in at this point,

02:00:45.620 | but which would be fine with me.

02:00:47.060 | But in any case, knowledge is power,

02:00:51.340 | is something that we hear, but it's not always true.

02:00:54.300 | Often it's knowledge is power,

02:00:56.260 | but you need to do X, Y, and Z in a certain order.

02:00:59.200 | But here, what you've provided

02:01:00.800 | and you're continuing to provide is knowledge

02:01:04.120 | that people can use that real estate within their brain.

02:01:09.120 | I'm deliberately not giving it a name

02:01:11.740 | because it's distributed real estate

02:01:13.660 | that allows them to take an unpleasant feeling

02:01:16.900 | and work with it, that it has more dimensionality

02:01:20.700 | than we probably realize.

02:01:22.360 | That's becoming clear to me that rarely,

02:01:25.940 | if ever is there less dimensionality.

02:01:29.200 | You can always give it more dimensionality

02:01:31.100 | by just shifting your attention.

02:01:32.740 | And you can practice this really.

02:01:34.580 | There's a story that I tell about when I,

02:01:37.580 | the brief moment when I tried to learn how to paint.

02:01:40.740 | And so there's an object like a cup

02:01:43.860 | and you have this three-dimensional object

02:01:45.540 | and you want to render it on a two-dimensional canvas.

02:01:48.300 | So you could just try to draw the cup

02:01:51.140 | and then what you get is a pretty shitty looking cup.

02:01:57.580 | But what a realist painter will teach you to do

02:02:00.940 | is to take the cup and to break it apart

02:02:03.580 | into pieces of light.

02:02:05.760 | And then what you try to paint are the pieces of light.

02:02:08.520 | So you're transferring, your first what you're doing

02:02:10.520 | is you're taking this very low dimensional course object

02:02:15.460 | called a cup and you're breaking it

02:02:17.080 | into tiny little pieces of light.

02:02:19.260 | - Which is what the visual system does.

02:02:20.460 | - Which is what the visual system does.

02:02:21.820 | And so what you're doing

02:02:22.700 | is you're categorizing it differently

02:02:25.220 | in order to emphasize the features

02:02:27.940 | that are more high dimensional,

02:02:29.700 | that are in there, right?

02:02:31.380 | They're in there, in the brain.

02:02:33.780 | But you can, but what you're doing essentially

02:02:36.140 | is you're having the brain,

02:02:38.380 | your brain is applying attention

02:02:40.260 | to basically focus more on those details.

02:02:43.940 | And then you transfer the details

02:02:46.540 | on to the two-dimensional canvas.

02:02:49.400 | And what you get is a pretty decent looking

02:02:53.180 | three-dimensional cup on a two-dimensional canvas,

02:02:57.380 | unless you're me and then it still looks shitty.

02:03:00.180 | And so maybe I'll take it up again sometime in the future.

02:03:05.400 | But my point is that you can do that

02:03:06.820 | with your own sensory condition of your body.

02:03:09.640 | In emotion, you can deliberately focus on

02:03:13.240 | what your heart is doing to the best of your ability

02:03:16.560 | that you can sense it, right?

02:03:17.660 | Or you can deliberately focus on your breathing

02:03:19.760 | or you could deliberately focus on what your muscles

02:03:21.780 | or how tense they feel.

02:03:23.940 | You can change the dimensionality of your experience

02:03:27.800 | by the shifting of your attention.

02:03:29.800 | - Love it.

02:03:31.620 | And forgive me for giving another example,

02:03:33.980 | but I think it's one that will resonate with both of us

02:03:35.820 | and hopefully with our listeners as well,

02:03:37.340 | which is the great Oliver Sacks, neurologist and author,

02:03:41.220 | talked about and wrote about,

02:03:45.480 | he'd worked with these patients

02:03:46.940 | that either had locked-in syndrome or severe autism

02:03:51.460 | or severe Tourette's or Parkinson's.

02:03:53.900 | And, you know, most people would,

02:03:55.980 | even clinicians who specialize in those areas

02:03:59.180 | would look at those people

02:04:00.020 | and say that they're living in a diminished world.

02:04:02.580 | It's, they lack capacities that other people have

02:04:05.820 | and it's all about the absence of certain abilities.

02:04:10.460 | And then what he did eventually was incredible.

02:04:14.100 | He loved animals.

02:04:15.480 | So he would spend time thinking about

02:04:18.540 | what it would be like, for instance, to be a bat,

02:04:21.780 | hanging in the corner of a room and experience the room,

02:04:24.980 | not through vision, but mainly through echolocation.

02:04:28.260 | And he would spend a lot of time thinking about that.

02:04:31.220 | He also did a lot of drugs at one point in his career

02:04:33.260 | and then stopped because they were very destructive drugs,

02:04:36.020 | not just psychedelics, but also methamphetamines.

02:04:38.580 | So yes, he has that.

02:04:39.420 | But he eventually changed his practice

02:04:41.600 | to trying to experience human emotion,

02:04:45.280 | but first think about animal sensory experience.

02:04:48.720 | And he would do that for lots of different types of animals,

02:04:50.840 | octopuses and bats and all these different things.

02:04:53.040 | And then it allowed him, in his words,

02:04:56.040 | it allowed him to then interact with patients

02:04:59.420 | in a way where he could feel,

02:05:01.460 | maybe even empathize a little bit

02:05:03.400 | with how they experienced life.

02:05:05.080 | And then he would write books about it in a way,

02:05:07.640 | and here I'm borrowing someone else's words,

02:05:09.240 | that storied these people into almost greater,

02:05:14.280 | larger than life characters.

02:05:16.480 | And now, of course, he wasn't trying to detract

02:05:18.440 | from their suffering,

02:05:19.700 | but he was trying to give people an understanding

02:05:21.600 | of what that suffering was like

02:05:23.680 | through their actual experience.

02:05:26.160 | And he did, in my opinion and the opinion of many other

02:05:29.140 | people, a masterful job in doing that.

02:05:32.120 | But it came through much in the same way

02:05:33.600 | that your art teacher said,

02:05:35.000 | pay attention to the way the changes in light

02:05:38.480 | across the object as opposed to trying

02:05:40.640 | to draw the object themselves.

02:05:43.080 | So the takeaway here that I think we're arriving at

02:05:46.280 | is that, that you've provided,

02:05:48.320 | is that if we add dimensionality to our description of

02:05:53.320 | or experience of the sensory inputs,

02:05:57.500 | and there's a ton of it to reach to,

02:06:00.540 | and we maybe even come up with some new internal labels

02:06:03.760 | or language-based labels,

02:06:05.880 | that we can experience the world in much richer

02:06:08.960 | and much more adaptive ways.

02:06:10.560 | - Absolutely.

02:06:11.560 | And I love your stories,

02:06:14.040 | and I love this story in particular about Oliver Sacks,

02:06:16.880 | because it resonates with my experience

02:06:19.960 | when I was reading Ed Yong's new book.

02:06:23.000 | - Oh, at first he wrote, "We Contain Multitudes,"

02:06:26.760 | which I think won a Pulitzer.

02:06:28.420 | And then what is the recent one?

02:06:31.200 | - Right, with the animals.

02:06:32.040 | - "An Immense World."

02:06:32.860 | - "An Immense World."

02:06:33.700 | And what I was thinking was,

02:06:35.120 | first of all, it's a masterful, masterful, masterful book.

02:06:40.880 | I wish I had written that book.

02:06:42.360 | I wrote him a fan letter.

02:06:43.600 | I was like, "This is such an amazing book."

02:06:45.200 | - It's an amazing book.

02:06:46.720 | - But because he helps you experience,

02:06:50.600 | so what I wanna say is this,

02:06:54.780 | that there are all these animals

02:06:56.560 | that have different sensory surfaces than we do,

02:06:58.940 | and they can detect signals in the world

02:07:01.120 | that are not relevant to us

02:07:03.480 | because we don't have sensory surfaces for them.

02:07:06.780 | And it reminds you, first of all,

02:07:09.680 | that what you experience as reality

02:07:13.000 | is really not in the world alone,

02:07:15.720 | and it's not in your head alone.

02:07:17.700 | It is in the transaction between the two.

02:07:20.380 | The neurons in your brain and in your nervous system

02:07:24.240 | are also part of the reality.

02:07:26.160 | And so reality is the transaction.

02:07:29.040 | Reality are the features that are the transaction

02:07:31.720 | between signals in the world and signals in your brain.

02:07:35.640 | And the parts of the world that some other animals experience

02:07:40.640 | that we will never experience,

02:07:42.960 | they're not really part of our reality

02:07:44.480 | because they don't interact with anything that we have.

02:07:48.860 | But for those animals, it's part of their niche.

02:07:51.360 | It's part of their, you know, niche is just the word

02:07:53.420 | for the parts of the world that matter to you, basically.

02:07:56.440 | And I was thinking that if people read this book,

02:07:59.080 | and maybe it will help them have empathy

02:08:03.740 | for other people who don't have minds like theirs

02:08:07.160 | and who don't experience the world in the way that they do.

02:08:11.060 | Your description of what Oliver Sacks,

02:08:14.240 | what his actions were and his goals,

02:08:19.240 | it did occur to me that this book by Ed Yong

02:08:21.760 | would be a great tool for helping people to understand

02:08:26.600 | that the way that they experience the world,

02:08:29.560 | it might be different

02:08:30.520 | than how other people experience the world.

02:08:32.560 | And even a little bit of a window on that,

02:08:35.140 | it would be a good thing.

02:08:36.640 | - So I'd like to ask you more about this word affect.

02:08:39.300 | And then I'd like to discuss how things that we do

02:08:44.680 | or don't do might be useful for putting us

02:08:48.480 | in broad categories of affect

02:08:51.120 | so that we might experience particular arrays of emotions.

02:08:56.120 | So this is my attempt to understand affect

02:09:00.080 | in an effort to think about some actionable items.

02:09:03.440 | - Absolutely.

02:09:05.080 | - I love the word affect the way you described it

02:09:07.980 | as setting up a potential or a series of potentialities

02:09:12.300 | for different emotions to occur.

02:09:15.040 | I make it a point to get sunlight in my eyes in the morning

02:09:19.560 | to try and wake up my brain and body

02:09:21.200 | because indeed it does that.

02:09:22.600 | Broadly speaking, I make an effort to get good sleep at night

02:09:26.460 | because that makes everything better.

02:09:28.880 | - Absolutely.

02:09:29.700 | - When I'm not sleeping well or enough,

02:09:33.240 | it makes everything worse.

02:09:35.280 | This is non-clinical, non-nuanced language.

02:09:38.780 | But I think most people when they hear affect

02:09:42.460 | and they think about the examples I just gave,

02:09:46.140 | kind of understand like, yeah, like when a kid is tired

02:09:48.840 | or at least I'm a kid, they get cranky.

02:09:51.080 | When we're sleep deprived, we get cranky.

02:09:53.060 | Indeed, there are times when I'm sleep deprived

02:09:55.160 | and little things great on me.

02:09:58.040 | They're like a splinter just feels super annoying

02:10:01.140 | and maybe even painful.

02:10:03.260 | But when I'm well rested, things are going better.

02:10:05.880 | It's not that bad.

02:10:07.680 | So tell us more about affect

02:10:09.800 | because I think it's a really important anchor point

02:10:13.040 | for us to understand emotions in ourselves

02:10:15.540 | and other people.

02:10:16.520 | - Neuroscientists think about

02:10:20.600 | the sensory systems for touch and proprioception,

02:10:25.980 | which we call somatic sensation,

02:10:28.340 | as being in the service of motor movement,

02:10:32.380 | skeletal motor movements.

02:10:33.780 | Really, our sense of touch and even vision actually

02:10:38.140 | also works this way.

02:10:39.820 | And actually, audition does too.

02:10:42.080 | These senses actually serve the brain's ability

02:10:46.560 | to control the movements of the body.

02:10:50.120 | And the same thing is true

02:10:53.740 | for regulating the systems of the body.

02:10:58.640 | So brains, one of their fundamental jobs

02:11:01.880 | are to coordinate and regulate the systems inside your body,

02:11:06.880 | your heart, your lungs, your gut, all the moving parts.

02:11:12.120 | And the information, the sensory signals

02:11:16.400 | that those organs and tissues and so on

02:11:20.880 | send back to the brain, as I said before,

02:11:24.060 | those sensory signals are important

02:11:30.380 | to the brain's ability to regulate the body,

02:11:33.300 | but we don't feel them directly.

02:11:35.860 | We usually experience them as affective feelings,

02:11:39.480 | these very simple physical sorts of feelings.

02:11:43.040 | And then we elaborate them in various ways.

02:11:45.160 | When they get very intense, those are the moments

02:11:48.020 | when the brain creates emotion out of them.

02:11:51.400 | So the brain's regulation of the body,

02:11:57.500 | the predictive regulation of the body,

02:12:00.380 | the technical term is allostasis.

02:12:02.620 | But when I'm explaining this to the public,

02:12:04.920 | I use a metaphor.

02:12:06.500 | And all metaphors are wrong,

02:12:09.100 | but some metaphors are less wrong and useful.

02:12:14.100 | So the metaphor that I use is,

02:12:17.320 | your brain is running a budget for your body.

02:12:19.900 | And it's not budgeting money,

02:12:21.860 | it's budgeting glucose and salt and oxygen and water

02:12:24.700 | and all the nutrients that you need to stay alive and well.

02:12:28.240 | And so you can think about withdrawals from that budget,

02:12:32.120 | like burning glucose or using up oxygen.

02:12:36.540 | You can think about deposits, like sleeping and eating.

02:12:42.980 | You can think about savings.

02:12:47.180 | So when you're with a friend who you trust

02:12:49.560 | and everything you do actually

02:12:51.540 | is just slightly less metabolically expensive, right?

02:12:54.420 | And you can also think about taxes.

02:12:57.100 | Like if you are stressed, socially stressed,

02:12:59.880 | within two hours of eating a meal,

02:13:02.480 | that same meal will cost you

02:13:06.120 | the equivalent of 104 more calories in the inefficiency

02:13:12.520 | that you will metabolize it because of that stress.

02:13:16.340 | Meaning you'll burn more energy.

02:13:18.180 | - You'll be more inefficient in metabolizing the food.

02:13:23.180 | So it's as if you had eaten 104 more calories.

02:13:28.700 | - Oh, so I had it exactly backwards.

02:13:30.040 | - And so over the course of a year, that's 11 pounds.

02:13:33.740 | - So when we say that people are taxing on us.

02:13:36.460 | - Yeah, like it's literally true.

02:13:38.060 | - Their language works, their language works.

02:13:40.300 | - So the way I describe it is that

02:13:41.940 | you can think about affect as a quick and dirty summary

02:13:46.700 | of the state of your body budget.

02:13:48.540 | If things are going reasonably well,

02:13:54.700 | then you'll feel okay.

02:13:57.740 | You might even feel pleasant.

02:13:59.140 | If you're running a deficit in your body budget,

02:14:04.820 | then you're gonna feel fatigued or distressed.

02:14:08.900 | And that doesn't mean something is necessarily wrong.

02:14:11.520 | Like for example, when you exercise,

02:14:13.240 | you get to a certain point

02:14:14.320 | where you've reached your ventilatory load.

02:14:16.620 | Usually it's like 20 minutes in or 10 minutes in

02:14:19.880 | or whatever, depending on how hard you're working.

02:14:22.280 | And you start to feel unpleasant and fatigued.

02:14:25.060 | But that doesn't mean that something's wrong.

02:14:26.620 | That just means that you're working really hard

02:14:28.480 | and you have to push through it.

02:14:29.560 | And then when you drink water and you eat afterwards

02:14:33.340 | and replenish, and then you're fine, right?

02:14:34.980 | In fact, you're better.

02:14:35.960 | It's a way of building a better, stronger future you.

02:14:41.560 | So affect is basically when things,

02:14:45.780 | when you're feeling really worked up,

02:14:46.940 | it probably means that something's uncertain somewhere.

02:14:49.720 | So I just think about these as like quick and dirty ways

02:14:53.500 | of thinking about what your affect means.

02:14:58.500 | And then oftentimes, as we've said before,

02:15:03.360 | emotion regulation that is controlling emotion

02:15:05.720 | really actually is not so much about

02:15:07.620 | changing the meaning of affect.

02:15:09.220 | It's changing the affect.

02:15:10.800 | And so it's useful to understand that affect is tied

02:15:17.540 | to the state of your body.

02:15:21.380 | Or actually what it's tied to is your brain's beliefs

02:15:24.220 | about the state of your body.

02:15:25.920 | Your brain is modeling the state of the body.

02:15:28.460 | And that's interoception, that's the technical word.

02:15:31.820 | Interoception is not your awareness of your body.

02:15:35.580 | It's your brain's modeling of your body,

02:15:37.200 | what your brain believes to be true

02:15:38.580 | about the metabolic state of your body.

02:15:40.880 | And that's how I think about affect.

02:15:43.900 | That's how I think about my own affect.

02:15:45.740 | And my daughter actually who was depressed for,

02:15:50.540 | so I should say depression is like a bankrupt body budget.

02:15:54.020 | Like you just can't move.

02:15:56.060 | You feel fatigued, so fatigued that you can't move

02:15:59.500 | and you're very distressed.

02:16:01.700 | It's like bankruptcy.

02:16:02.900 | And actually, if you, I mean,

02:16:06.020 | depression is a metabolic illness.

02:16:09.020 | And if you look at the symptoms of depression,

02:16:11.380 | they really are about metabolic,

02:16:14.240 | having metabolic deficits, basically.

02:16:20.020 | - And it's interesting that one of the hallmark features

02:16:22.320 | of depression, subjectively speaking,

02:16:24.140 | is lack of positive anticipation about the future,

02:16:27.440 | which makes perfect sense from the perspective

02:16:30.540 | of a depleted brain body budget.

02:16:32.620 | - Yes, exactly.

02:16:33.660 | And you're basically, think about the fact

02:16:36.220 | that prediction error, right?

02:16:38.660 | So if you're feeling unpleasant,

02:16:40.100 | you're not gonna be anticipating pleasant things.

02:16:42.300 | And even if those things that are in the world

02:16:44.500 | could give you pleasure, you won't notice them

02:16:47.140 | because learning from prediction error,

02:16:49.500 | things that you didn't predict, is expensive.

02:16:51.820 | And if you don't have the resources,

02:16:53.860 | you're not gonna, right?

02:16:54.700 | So it's, but anyways, my daughter came up with this

02:16:58.500 | after we had this very interesting thing

02:17:02.020 | that happened to us on another trip.

02:17:04.180 | We were in Sweden because I was giving a keynote

02:17:07.140 | at the Karolinska Institute and we went,

02:17:09.460 | I took her to Sweden and this is when she was recovering

02:17:12.340 | from depression and like, you know,

02:17:14.700 | she is just one of the millions of young adults who,

02:17:19.340 | you know, adolescents and young adults

02:17:21.500 | who were experiencing depression.

02:17:23.900 | And we got to Sweden and she was very, very jet lagged.

02:17:31.780 | We both were, it was like one of these, like, you know,

02:17:34.380 | we had to like, you know, planes, trains and automobiles,

02:17:38.300 | like it was just, you know, getting there.

02:17:40.420 | And she woke up the next morning and she looked horrible.

02:17:44.580 | She felt horrible.

02:17:45.420 | It actually seemed to me like she was about to enter

02:17:47.660 | another depressive episode.

02:17:49.060 | And I said to her, I basically got her out of bed.

02:17:53.900 | I fed her a meal.

02:17:55.300 | I gave her four ibuprofen and I put her back to sleep.

02:17:58.900 | And she got up five hours later and she was absolutely fine.

02:18:01.380 | Her mood was fine.

02:18:03.140 | Now I'm not telling you that ibuprofen is the,

02:18:05.980 | an antidepressant that you should take if you're depressed.

02:18:08.740 | But what I'm telling you is that, you know,

02:18:10.460 | you said something, Andrew, that was so interesting.

02:18:12.340 | In the beginning, you said, am I fatigued?

02:18:14.820 | Does my body, do I have pain somewhere?

02:18:16.660 | Is my body hurt?

02:18:17.700 | You know, these are, well, right.

02:18:19.420 | When basically what she was having was she was fatigued

02:18:23.860 | and she was having what I would call,

02:18:25.860 | it's called, the technical word is visceral nociception,

02:18:30.500 | which means her stomach hurt, you know, everything hurt.

02:18:34.020 | And sure, you know, her muscles probably hurt too,

02:18:36.020 | but it was really her innards.

02:18:37.620 | Really, she just was distressed.

02:18:39.820 | And the ibuprofen helped her get back to sleep

02:18:44.220 | and then she slept and she got up

02:18:45.460 | and she was completely fine.

02:18:46.860 | And then we walked around Stockholm for the rest of the day

02:18:49.180 | talking about this experience,

02:18:50.620 | which for her was like flipping on a light switch.

02:18:53.220 | You know, "How Emotions Are Made,"

02:18:54.700 | this book that I referred to, I wrote that book for her.

02:18:58.540 | I wrote that book for her, but also for me,

02:19:00.460 | because it was a way of putting down on paper

02:19:03.700 | all the things that I wanted her to know.

02:19:06.420 | And then I thought other people

02:19:08.060 | should know about their kids, you know,

02:19:09.780 | and maybe even their kids could read it.

02:19:12.300 | But what she did with that was she came up

02:19:14.980 | with a new concept called the emotional flu.

02:19:19.100 | And the emotional flu is when you're having

02:19:23.300 | a bad body budgeting day and you're just like,

02:19:27.060 | you didn't get enough sleep maybe,

02:19:28.580 | or there's some stress at work or at school

02:19:33.060 | that you can't get rid of otherwise.

02:19:35.020 | My husband likes to say,

02:19:36.100 | "Well, other people's opinions of you

02:19:40.020 | are just electrical activity in somebody's head,"

02:19:42.820 | which I love.

02:19:43.900 | Like that's just another way of categorizing it.

02:19:45.620 | It's sort of like taking apart the cup

02:19:48.380 | into pieces of light, right?

02:19:49.900 | And so whatever, there are just these moments

02:19:52.500 | where you feel depleted and you could use that.

02:19:55.660 | I mean, we usually, we often use affect

02:19:59.500 | as a indicator of how the world is.

02:20:03.180 | You know, if I feel bad,

02:20:04.180 | something must be wrong in the world,

02:20:06.700 | but you have to resist that sometimes

02:20:09.220 | because sometimes there's nothing wrong in the world.

02:20:11.260 | It's just that you didn't get enough sleep

02:20:12.660 | or you need to have a little bit more protein,

02:20:16.300 | or maybe you haven't gone for a walk

02:20:18.060 | and you're stiff or whatever.

02:20:19.420 | You need to do some stretching.

02:20:20.820 | - Are those, sorry to interrupt,

02:20:22.020 | but I think people are going to want to anchor

02:20:23.660 | to a few of these positive steps that they can take

02:20:27.660 | to, I don't want to say replenish,

02:20:29.620 | but to shift affect in positive directions,

02:20:32.980 | sleep, movement, nutrition.

02:20:36.100 | And I've heard you say before

02:20:37.740 | that we are essentially amino acid foraging machines.

02:20:41.260 | So I noticed you said protein.

02:20:42.660 | You didn't say you need a bagel.

02:20:44.540 | You said protein.

02:20:46.740 | We could go down that rabbit hole.

02:20:48.020 | Maybe we do, maybe we don't.

02:20:49.900 | But I want to use this also just as a quick opportunity

02:20:53.140 | to say, as you're saying all this,

02:20:55.460 | one can immediately understand why alcohol

02:20:59.460 | and drugs of abuse are both so compelling, right?

02:21:03.020 | You're not feeling well.

02:21:04.420 | So you're feeling tired.

02:21:06.340 | Take a stimulant that releases dopamine and epinephrine,

02:21:08.740 | but you're taxing your already taxed body budget

02:21:12.660 | in a way that then puts you in a more depleted state later.

02:21:16.000 | Or alcohol, like you feel lousy.

02:21:18.340 | Alcohol never did this for me,

02:21:19.540 | but friends I have who are recovered alcoholics

02:21:21.900 | will tell me that it was like a magic elixir.

02:21:23.820 | It made them feel right.

02:21:25.900 | That's their language.

02:21:27.140 | But then of course there's a price to pay later

02:21:29.020 | because then it drops your baseline

02:21:30.460 | below where it was initially.

02:21:31.540 | - Absolutely, 110%.

02:21:34.700 | But I just also want to say that so is serotonin.

02:21:39.600 | Like so are SSRIs maybe.

02:21:42.900 | And when I say maybe, what I mean by that is

02:21:47.000 | if you really have a metabolic problem,

02:21:49.300 | like say something's wrong with your mitochondria

02:21:51.320 | or you're recovering from an illness

02:21:53.220 | and you know, or there's just some metabolic problem

02:21:56.340 | in your body, that metabolic problem is real.

02:21:59.940 | If you start to feel unpleasant, you will,

02:22:04.660 | I mean, feel unpleasant, it will feel,

02:22:06.580 | your mood will be negative.

02:22:08.300 | If you start taking serotonin,

02:22:11.180 | if you start taking SSRIs which will leave more serotonin

02:22:15.320 | in the synapses of your neurons before it's taken up again,

02:22:21.080 | that will juice the system.

02:22:23.340 | You will be able to spend, you'll be able to move,

02:22:26.300 | you'll feel like you have more energy for a while.

02:22:30.500 | But your nervous system is a complex system

02:22:34.020 | and so it's gonna make adjustments elsewhere

02:22:36.380 | to try to deal with that budgeting problem.

02:22:40.100 | So exactly what happens when you take drugs of abuse

02:22:44.300 | and what happens on the short term

02:22:46.500 | can happen for some people with SSRIs

02:22:48.940 | on the longer term where at first it starts to work

02:22:51.800 | and then it stops working and you start to gain weight

02:22:55.120 | and you know, because your metabolism is slowing

02:22:58.200 | because your brain is attempting to deal

02:22:59.600 | with that budgeting problem.

02:23:02.200 | So it really matters what the, you know, what the source is.

02:23:05.640 | It could be that your brain believes

02:23:07.400 | you have a budgeting problem, but there really isn't one.

02:23:10.160 | It could be that there really is one.

02:23:12.280 | These things matter to how you treat it.

02:23:15.000 | - One thing to just mention about SSRIs

02:23:19.220 | and I unfortunately, for reasons of confidentiality,

02:23:21.800 | I can't cite the source on this,

02:23:23.440 | but let me just say that somebody who's highly informed

02:23:25.840 | in the landscape of pharmaceutical treatments

02:23:29.320 | for psychiatric challenges has told me

02:23:33.500 | that there's an emerging theory among psychiatrists,

02:23:36.420 | it's kind of a collective emerging theory

02:23:38.100 | that one of the reasons why nowadays you hear

02:23:42.220 | about so-called treatment resistant depression,

02:23:44.660 | but you did not hear about so-called treatment

02:23:47.860 | resistant depression prior to the advent of SSRIs

02:23:51.520 | is that there's a growing body of thought

02:23:53.600 | in the psychiatric community that SSRIs may over time,

02:23:57.120 | as you're pointing out, deplete the very neural systems

02:24:00.660 | that subserve enhanced mood.

02:24:02.600 | So it's different than a drug of abuse

02:24:04.980 | that gives you a very acute effect

02:24:06.360 | like methamphetamine or cocaine or alcohol,

02:24:09.320 | but that over time you may actually be pulling

02:24:12.800 | the very neural circuits and neurochemicals

02:24:15.720 | that would allow for positive affect

02:24:18.160 | deeper and deeper into the trenches, so to speak.

02:24:21.940 | And so there's a growing number of people

02:24:23.700 | who simply don't respond to the drugs any longer

02:24:26.460 | or other treatments.

02:24:27.380 | - Right, so I wasn't trying to say the mechanism is the same,

02:24:29.760 | I was basically saying the theme is the same.

02:24:31.960 | - And I'm agreeing with you.

02:24:33.180 | - What happens over the short term with drugs of abuse

02:24:35.600 | happens over the longer term with, for some people,

02:24:38.020 | with SSRIs because it hasn't been recognized yet

02:24:40.880 | that at the basis, depression is a metabolic problem.

02:24:45.880 | And when you have a metabolic problem like diabetes

02:24:49.840 | or obesity or heart disease,

02:24:53.860 | it's not that that causes depression,

02:24:56.240 | it's that there's a common problem,

02:24:59.080 | which is that somewhere in this very complex system

02:25:02.360 | of your metabolism, there's a drag

02:25:05.600 | and it produces negative mood.

02:25:08.320 | And that's how you experience it.

02:25:10.160 | Sometimes it's good not to turn,

02:25:12.080 | it's productive not to turn that negative affect

02:25:16.680 | into an emotion.

02:25:18.720 | Sometimes, you know, sometimes a cigar is just a cigar.

02:25:22.040 | Sometimes you just need to deal with the affective problem

02:25:25.440 | by dealing with your physical state.

02:25:28.200 | And that's the tricky bit,

02:25:29.960 | is knowing when is affect telling you

02:25:32.880 | something is wrong with the world?

02:25:34.440 | And when is it telling you that there's something wrong

02:25:36.680 | with your physical state that you need to attend to?

02:25:39.040 | - I think everything to me at least

02:25:41.240 | starts with a good night's sleep on a consistent basis.

02:25:45.440 | And every psychiatric challenge and indeed suicide itself

02:25:50.440 | seems to be associated with and often preceded

02:25:53.600 | by challenges in sleeping, changes in circadian rhythm.

02:25:58.460 | So I think that's why to me,

02:26:00.440 | sleep is the foundation of mental health and physical health.

02:26:02.680 | - Yep, absolutely.

02:26:03.640 | And so when I tell people, when they say,

02:26:05.240 | "Well, what can I do?"

02:26:06.080 | It's like, well, if there's only one thing that you could pick

02:26:09.360 | I would say get a good night's sleep on a regular basis.

02:26:12.460 | If you could pick two more, I would say eat healthfully,

02:26:14.940 | like stop eating pseudo food.

02:26:17.020 | Don't get me wrong, like I love French fries.

02:26:18.880 | I love French fries.

02:26:19.880 | They're like, that's like God's most perfect food.

02:26:21.840 | I mean, really.

02:26:22.920 | But eat healthfully, like eat real food and get exercise.

02:26:27.920 | And if you do those three things,

02:26:30.920 | I know I sound like a mother

02:26:32.840 | and so feel free to roll your eyes at me,

02:26:35.480 | but as a neuroscientist, those are the actually,

02:26:38.720 | before you start with all the, you know,

02:26:40.640 | mentalizing Jedi tricks, you could just start with this

02:26:43.720 | and that would actually take you pretty far.

02:26:45.960 | - And that will resonate very well with our audience.

02:26:50.580 | The basics of sleep, exercise, food, sunlight

02:26:55.080 | and social connection are the ones that we just anchor.

02:26:57.560 | Those five are the ones that we just keep returning to

02:27:01.120 | over and over again.

02:27:02.120 | And I think people will say, oh, it's just simple motherly

02:27:05.520 | advice, but I think that those five things,

02:27:08.960 | even just the one thing around sleep,

02:27:11.160 | there's some work that's required to get that done.

02:27:13.560 | So it's not as simple, the categories are simple,

02:27:16.320 | but the work that's required to get great sleep

02:27:20.320 | as often as one can on a consistent basis,

02:27:22.660 | if you're raising kids, have a career, live in the world,

02:27:26.220 | there's a lot there.

02:27:27.160 | And so that's where I think there's an elaboration

02:27:29.840 | of things and one needs to learn to be flexible,

02:27:32.480 | like when you're traveling, how do you do that?

02:27:34.160 | When, you know, friends are visiting, how do you do that?

02:27:37.000 | When weather's off and so on.

02:27:39.560 | The relationship piece is something-

02:27:41.240 | - I was just going to say, I'm so glad you mentioned that.

02:27:43.640 | I'm so glad you mentioned that.

02:27:44.480 | - Because you've said before,

02:27:45.800 | and this was another one of those moments,

02:27:47.660 | I listened to you, I've listened to as many of your podcasts

02:27:50.300 | as I possibly can, but I think it was the first

02:27:52.660 | or the second one with Lex Friedman, where you said,

02:27:55.640 | you know, we are regulating each other's nervous systems.

02:27:59.040 | And I will never forget that.

02:28:00.760 | And, you know, I imagine that you married your husband

02:28:04.820 | for a number of different reasons,

02:28:06.000 | but when people pair up with romantic partners,

02:28:11.000 | with friends, with coworkers,

02:28:13.360 | the ideal situation is one in which we are not taxed,

02:28:17.520 | where maybe even people, and just being around them

02:28:21.920 | or just knowing that they are in our lives

02:28:24.640 | provides a sort of deposit to-

02:28:26.920 | - Yeah, it's a savings.

02:28:27.880 | It provides a savings. - It's a savings.

02:28:28.880 | - For sure.

02:28:29.720 | - And then I think that's a lot of what emotional resonance,

02:28:32.200 | to put kind of pop language on it, is all about.

02:28:35.920 | Who feels good to be around,

02:28:36.980 | who doesn't feel good to be around.

02:28:37.820 | - Yeah, I would say the best thing

02:28:40.340 | for a human nervous system is another human.

02:28:44.640 | And the worst thing for a human nervous system

02:28:47.380 | is also another human.

02:28:49.320 | And so you really want to be around the people

02:28:51.840 | who make you the best version of yourself that you could be.

02:28:55.640 | And that doesn't mean that you always get a savings.

02:28:58.740 | Like sometimes you're taking care of that person.

02:29:02.480 | And so you're absorbing some of their burden, right?

02:29:07.160 | And vice versa.

02:29:08.940 | But I would say the research on social isolation

02:29:13.940 | and loneliness and so on shows us that,

02:29:17.560 | well, along with research on synchrony,

02:29:19.400 | and there's just a whole bunch of research to suggest

02:29:22.120 | that we are the caretakers of each other's nervous systems.

02:29:26.040 | And it doesn't matter what your opinion is.

02:29:28.320 | Like it doesn't, you know, it just,

02:29:29.620 | but we just, that's how we evolved as a species.

02:29:32.280 | And so you get to decide

02:29:33.980 | what kind of a person are you going to be?

02:29:37.320 | You know, are you going to be a savings

02:29:42.260 | or are you going to be a tax?

02:29:43.620 | - And in general, it seems that people who decide

02:29:45.480 | that they're going to be a savings tend to,

02:29:49.280 | because people gravitate towards that and want more of that.

02:29:52.540 | And hopefully would provide that also.

02:29:54.640 | I mean, I think the reciprocity piece here

02:29:56.400 | feels really, really strong.

02:29:58.280 | - Well, that's a really interesting thing

02:30:00.520 | about the synchrony work, right?

02:30:02.280 | So there's work that if you research,

02:30:04.360 | that if you put people together

02:30:05.360 | who don't even know each other,

02:30:06.360 | but if they like each other and they have a sense of trust,

02:30:09.440 | even after a couple of minutes,

02:30:10.760 | they start to synchronize their physical signals.

02:30:12.820 | Their heart rate starts to synchronize,

02:30:15.280 | their movements start to synchronize,

02:30:16.840 | their heart rate probably synchronizes

02:30:18.160 | 'cause their breathing starts to synchronize, right?

02:30:21.000 | And it's really interesting to see what you typically see

02:30:23.620 | is that who is pacing and who is leading.

02:30:26.320 | Like one person is the leader

02:30:27.820 | and then the other person is the pacer.

02:30:29.960 | And I got that language from when I learned hypnosis,

02:30:33.160 | by the way.

02:30:34.000 | But it switches back and forth, like who's the leader.

02:30:37.620 | Like in a good, what we say good,

02:30:40.480 | like in an interaction that looks productive,

02:30:43.720 | it's switching all the time who is pacing

02:30:47.040 | and who is leading.

02:30:48.200 | It's not that always one person is in charge,

02:30:53.200 | so to speak, physiologically speaking.

02:30:55.360 | We did a series recently on mental health with Paul Conte,

02:30:57.840 | who's a psychiatrist and the word narcissism

02:31:01.320 | came up a few times

02:31:02.280 | because people have a lot of questions about that.

02:31:04.240 | And he emphasized that narcissists are not confident.

02:31:07.920 | They operate from a place of a deficit of pleasure.

02:31:11.120 | It's never enough and an intense envy,

02:31:13.280 | although that's not how they present

02:31:14.640 | and they're often usually not aware of it themselves,

02:31:19.080 | but it's what leads healthy people to feel

02:31:21.540 | as if the interactions with those people,

02:31:23.460 | narcissists often can be very compelling in the moment,

02:31:26.880 | but they feel very taxed afterwards

02:31:28.680 | and kind of confused by what happened.

02:31:31.040 | And it sounds like it ties back to this lack of synchrony.

02:31:34.980 | On the positive side of things,

02:31:37.600 | it's also clear from what you just said

02:31:41.160 | that when people regulate each other's nervous systems

02:31:45.420 | in a way where people are making little deposits

02:31:47.680 | and providing savings for each other,

02:31:49.560 | or maybe things are just neutral,

02:31:51.440 | that those nervous systems are then in a position

02:31:54.660 | to pay attention to other things too

02:31:56.780 | and not just try and work out the dynamics.

02:31:59.340 | - Oh, for sure.

02:32:00.260 | Oh, and that's very true at work.

02:32:02.040 | So there's research showing that,

02:32:04.140 | especially in the creativity sector,

02:32:07.080 | innovation sector of the economy,

02:32:09.580 | the best predictor of performance on the job

02:32:12.860 | is the extent to which people feel,

02:32:15.240 | I mean, after you account for sleep

02:32:16.900 | and watering and sleeping and feeding, right?

02:32:19.860 | Like the best predictor is the amount of trust

02:32:23.760 | that you have in your team and in your managers.

02:32:28.100 | Because if the world is predictable,

02:32:29.760 | it could still be, things could be hard.

02:32:31.560 | But even when things are unpredictable,

02:32:33.360 | you have people who have your back.

02:32:35.620 | And so basically what you're doing is you're,

02:32:39.260 | they're making deposits or savings,

02:32:44.300 | they're causing savings in each other's body budgets

02:32:46.460 | so their resources can be spent on the harder things,

02:32:49.780 | which is failing and having to pick yourself back up

02:32:54.140 | and try again, which is partly what you do

02:32:56.460 | when you're an innovator.

02:32:58.020 | So I think that there's also research to show

02:33:01.020 | that in your personal life,

02:33:02.920 | when you do random acts of kindness for people

02:33:06.580 | or when you're kind, in general,

02:33:08.820 | you derive also a body budgeting benefit from that.

02:33:13.380 | So for a while, I had a friend

02:33:17.020 | who we would meet each other for lunch once a month

02:33:21.020 | and we would take turns paying.

02:33:23.660 | I mean, we could both pay for ourselves,

02:33:26.320 | but we kind of got a double hit.

02:33:28.820 | He paid for me one month

02:33:30.140 | and then I would pay for him one month.

02:33:32.340 | So we get the double hit of being kind to someone else

02:33:37.340 | and also they got the benefit of someone being kind to them.

02:33:44.140 | And I'll just say, I think kindness is a,

02:33:47.380 | I don't know that we have so many conversations

02:33:50.380 | about that in our culture right now,

02:33:51.980 | but I think kindness is very, very underrated

02:33:56.340 | and should be, you know, like when I feel like shit,

02:34:00.380 | I bake bread for my neighbor who's in his 70s,

02:34:05.380 | him and his wife.

02:34:07.260 | That's what I do when I'm not feeling good.

02:34:10.920 | And you know, I mean, after I've taken care of the physical,

02:34:14.460 | the possible physical causes.

02:34:17.080 | And then I feel great because he's always so,

02:34:19.660 | he's always so grateful

02:34:23.600 | and then I felt like I made his day better.

02:34:26.400 | And then also he helps me in other ways,

02:34:28.160 | like with my garden and stuff,

02:34:29.880 | 'cause he's just like a master gardener.

02:34:31.460 | And so I feel like we have this relationship

02:34:34.040 | where we help each other.

02:34:36.060 | And I know it sounds really sappy,

02:34:38.720 | but, and even though all the research backs up

02:34:43.720 | what I'm saying, it doesn't quite describe the feeling

02:34:47.580 | of when someone is just really happy

02:34:50.360 | because you just gave them a little surprise

02:34:52.460 | and they're, you know, like that's,

02:34:54.260 | there's just some juice in that, I think.

02:34:56.340 | - On some culture out there, there's a word for that.

02:34:59.360 | - I'm sure there is. - And someone will tell us.

02:35:00.540 | - I'm sure there is, I'm sure there is.

02:35:02.340 | - Well, I have to say,

02:35:06.360 | I've thoroughly enjoyed this conversation.

02:35:09.380 | - Oh, me too.

02:35:10.220 | - I've been looking forward to it for a long time.

02:35:12.600 | And you've provided us with a really broad arc,

02:35:16.960 | but also a deep dive into not just how emotions are made,

02:35:21.040 | not just about affect, but as you mentioned earlier,

02:35:24.960 | you know, really how the nervous system works.

02:35:26.980 | And I am certain in fact that our audience is taking this in

02:35:31.980 | and realizing that that knowledge is incredibly powerful.

02:35:35.160 | The addition of nuance,

02:35:36.960 | both to language and to sort of self-reflection states

02:35:41.640 | as extremely valuable.

02:35:44.800 | Oftentimes when one gets into a conversation

02:35:47.100 | that has some level of reductionism

02:35:49.240 | and you get into nomenclature and things like that,

02:35:51.700 | it can really pull away

02:35:53.320 | from the real life experience of something.

02:35:55.200 | But this is exactly the opposite.

02:35:56.700 | What you've done for us today

02:35:58.500 | is you've provided such a rich array of information

02:36:01.480 | that adds richness and depth to the real life experience.

02:36:05.680 | And that is really invaluable.

02:36:08.720 | So on behalf of myself and all the listeners

02:36:12.440 | and the people watching this,

02:36:14.080 | I want to say thank you for today's discussion.

02:36:17.120 | Thank you for the books you've written,

02:36:18.940 | which we've provided links to in the show note captions.

02:36:22.040 | Thanks for showing up on social media

02:36:24.160 | despite the challenges that exist there.

02:36:28.080 | Sometimes you always handle yourself so well there

02:36:30.980 | and we will refer people

02:36:32.040 | to your excellent social media accounts as well.

02:36:34.920 | And just for all the work that you're doing

02:36:36.400 | and that your laboratory

02:36:37.440 | and you're now director of various things

02:36:39.640 | and relate to AI and more,

02:36:41.740 | and we'll talk about this hopefully in future episodes,

02:36:43.720 | but just a really enormous thank you.

02:36:48.720 | - Thank you.

02:36:49.600 | - Thank you for joining me for today's discussion

02:36:52.460 | about the psychology and neuroscience of emotions

02:36:54.880 | with Dr. Lisa Feldman Barrett.

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02:37:30.680 | of the Huberman Lab Podcast, we discuss supplements.

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02:38:50.360 | Thank you once again for joining me for today's discussion

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02:38:58.920 | [upbeat music]

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Dr. Lisa Feldman Barrett: How to Understand Emotions | Huberman Lab Podcast

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