Dr. David Berson: Your Brain's Logic & Function

00:00:00.280 | - 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,

00:00:10.240 | and I'm a professor of neurobiology and ophthalmology

00:00:13.020 | at Stanford School of Medicine.

00:00:14.920 | Today, my guest is Dr. David Berson,

00:00:17.160 | professor of medical science, neurobiology,

00:00:19.480 | and ophthalmology at Brown University.

00:00:22.240 | Dr. Berson's laboratory is credited

00:00:24.020 | with discovering the cells in the eye

00:00:25.960 | that set your circadian rhythms.

00:00:28.180 | These are the so-called intrinsically

00:00:30.080 | photosensitive melanopsin cells,

00:00:32.020 | and while that's a mouthful,

00:00:33.720 | all you need to know for sake of this introduction

00:00:36.140 | is that those are the cells that inform your brain and body

00:00:38.760 | about the time of day.

00:00:40.560 | Dr. Berson's laboratory has also made

00:00:42.480 | a number of other important discoveries

00:00:44.240 | about how we convert our perceptions of the outside world

00:00:47.880 | into motor action.

00:00:50.080 | More personally, Dr. Berson has been my go-to resource

00:00:53.240 | for all things neuroscience for nearly two decades.

00:00:57.160 | I knew of his reputation as a spectacular researcher

00:01:00.180 | for a long period of time,

00:01:01.500 | and then many years ago, I cold called him out of the blue.

00:01:05.080 | I basically corralled him into a long conversation

00:01:08.220 | over the phone after which he invited me out to Brown,

00:01:10.920 | and we've been discussing neuroscience

00:01:13.020 | and how the brain works and the emerging new technologies

00:01:16.700 | and the emerging new concepts in neuroscience

00:01:19.440 | for a very long time now.

00:01:22.020 | You're going to realize today

00:01:23.100 | why Dr. Berson is my go-to source.

00:01:25.600 | He has an exceptionally clear and organized view

00:01:29.260 | of how the nervous system works.

00:01:31.360 | Now, there are many, many parts of the nervous system,

00:01:33.520 | different nuclei and connections and circuits and chemicals

00:01:36.420 | and so forth, but it takes a special kind of person

00:01:39.180 | to be able to organize that information

00:01:41.240 | into a structured and logical framework

00:01:43.860 | that can allow us to make sense of how we function

00:01:46.980 | in terms of what we feel, what we experience,

00:01:49.140 | how we move through the world.

00:01:51.020 | Dr. Berson is truly one of a kind in his ability

00:01:54.040 | to synthesize and organize and communicate that information,

00:01:57.380 | and I give him credit as one of my mentors

00:02:00.100 | and one of the people that I respect most

00:02:02.260 | in the field of science and medical science generally.

00:02:05.220 | Today, Dr. Berson takes us on a journey

00:02:07.580 | from the periphery of the nervous system,

00:02:09.340 | meaning from the outside, deep into the nervous system,

00:02:12.720 | layer by layer, structure by structure, circuit by circuit,

00:02:16.660 | making clear to us how each of these individual circuits

00:02:19.540 | work and how they work together as a whole.

00:02:22.420 | It's a really magnificent description

00:02:24.480 | that you simply cannot get from any textbook,

00:02:27.420 | from any popular book, and frankly, as far as I know,

00:02:30.280 | from any podcast that currently exists out there.

00:02:33.120 | So it's a real gift to have this opportunity

00:02:34.880 | to learn from Dr. Berson.

00:02:36.540 | Again, I consider him my mentor in the field

00:02:39.340 | of learning and teaching neuroscience,

00:02:41.420 | and I'm excited for you to learn from him.

00:02:43.780 | One thing is for certain, by the end of this podcast,

00:02:46.680 | you will know far more about how your nervous system works

00:02:49.560 | than the vast majority of people out there,

00:02:51.620 | including many expert biologists and neuroscientists.

00:02:55.320 | Before we begin, I'd like to emphasize that this podcast

00:02:58.020 | is separate from my teaching and research roles at Stanford.

00:03:00.940 | It is, however, part of my desire and effort

00:03:02.880 | to bring zero cost to consumer information about science

00:03:05.460 | and science-related tools to the general public.

00:03:08.220 | In keeping with that theme,

00:03:09.220 | I'd like to thank the sponsors of today's podcast.

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00:08:01.740 | And now for my discussion with Dr. David Berson.

00:08:05.140 | Welcome.

00:08:06.020 | - Thank you. - Yeah.

00:08:06.940 | - So nice to be here.

00:08:08.120 | - Great to have you.

00:08:09.200 | For more than 20 years,

00:08:11.900 | you've been my go-to source for all things,

00:08:14.260 | nervous system, how it works, how it's structured.

00:08:17.120 | So today I want to ask you some questions about that.

00:08:20.120 | I think people would gain a lot of insight

00:08:22.900 | into this machine that makes them think,

00:08:24.940 | and feel, and see, et cetera.

00:08:27.180 | If you would, could you tell us how we see?

00:08:31.760 | You know, a photon of light enters the eye.

00:08:36.300 | What happens?

00:08:37.480 | - Right.

00:08:38.320 | - I mean, how is it that I look outside,

00:08:40.020 | I see a truck drive by, or I look on the wall,

00:08:42.200 | I see a photo of my dog.

00:08:44.400 | How does that work?

00:08:46.320 | - Right, so this is an old question, obviously.

00:08:49.100 | And clearly in the end,

00:08:50.900 | the reason you have a visual experience

00:08:52.780 | is that your brain has got some pattern of activity

00:08:56.120 | that it associates with the input from the periphery.

00:08:59.100 | But you can have a visual experience

00:09:00.760 | with no input from the periphery as well.

00:09:02.560 | When you're dreaming, you're seeing things

00:09:06.000 | that aren't coming through your eyes.

00:09:07.480 | - Are those memories?

00:09:08.520 | - I would say in a sense,

00:09:10.700 | they may reflect your visual experience.

00:09:13.140 | They're not necessarily specific visual memories,

00:09:15.120 | but of course they can be.

00:09:16.720 | But the point is that the experience of seeing

00:09:18.880 | is actually a brain phenomenon.

00:09:21.400 | But of course, under normal circumstances,

00:09:24.520 | we see the world because we're looking at it,

00:09:26.480 | and we're using our eyes to look at it.

00:09:28.500 | And fundamentally, when we're looking at the exterior world,

00:09:32.240 | it's what the retina is telling the brain that matters.

00:09:35.020 | So there are cells called ganglion cells.

00:09:37.860 | These are neurons that are the key cells

00:09:40.480 | for communicating between eye and brain.

00:09:43.100 | The eye is like the camera.

00:09:44.420 | It's detecting the initial image,

00:09:46.420 | doing some initial processing,

00:09:47.660 | and then that signal gets sent back to the brain proper.

00:09:51.480 | And of course, it's there at the level of the cortex

00:09:54.320 | that we have this conscious visual experience.

00:09:56.200 | There are many other places in the brain

00:09:57.720 | that get visual input as well,

00:09:59.740 | doing other things with that kind of information.

00:10:02.740 | - So I get a lot of questions about color vision.

00:10:05.980 | If you would, could you explain how is it

00:10:09.060 | that we can perceive reds and greens and blues

00:10:12.320 | and things of that sort?

00:10:13.460 | - Right.

00:10:14.300 | So the first thing to understand about light

00:10:16.380 | is that it's just a form of electromagnetic radiation.

00:10:19.900 | It's vibrating, it's oscillating.

00:10:23.400 | But-

00:10:24.240 | - When you say it's vibrating, it's oscillating,

00:10:25.520 | you mean that photons are actually moving?

00:10:28.480 | - Well, in a sense, photons are,

00:10:29.800 | they're certainly moving through space.

00:10:31.840 | We think about photons as particles,

00:10:34.440 | and that's one way of thinking about light,

00:10:36.020 | but we can also think of it as a wave, like a radio wave.

00:10:39.200 | Either way is acceptable.

00:10:40.860 | And the radio waves have frequencies,

00:10:42.540 | like the frequencies on your radio dial.

00:10:45.260 | And certain frequencies in the electromagnetic spectrum

00:10:48.380 | can be detected by neurons in the retina.

00:10:50.960 | Those are the things we see.

00:10:52.940 | But there are still different wavelengths

00:10:54.620 | within the light that can be seen by the eye.

00:10:57.780 | And those different wavelengths are unpacked in a sense,

00:11:00.500 | or decoded by the nervous system

00:11:03.540 | to lead to our experience of color.

00:11:06.400 | Essentially, different wavelengths give us the sensation

00:11:10.480 | of different colors through the auspices

00:11:13.660 | of different neurons that are tuned

00:11:15.880 | to different wavelengths of light.

00:11:17.660 | - So when a photon,

00:11:20.060 | so when a little bit of light hits my eye, goes in,

00:11:23.760 | the photoreceptors convert that into electrical signal.

00:11:26.440 | - Right.

00:11:27.280 | - How is it that a given photon of light

00:11:30.700 | gives me the perception,

00:11:31.920 | eventually leads to the perception

00:11:33.160 | of red versus green versus blue?

00:11:35.200 | - Right.

00:11:36.040 | So if you imagine that in the first layer of the retina

00:11:40.640 | where this transformation occurs

00:11:42.320 | from electromagnetic radiation into neural signals,

00:11:45.200 | that you have different kinds of sensitive cells

00:11:49.740 | that are expressing,

00:11:51.120 | they're making different molecules within themselves

00:11:54.920 | for this express purpose of absorbing photons,

00:11:58.320 | which is the first step in the process of seeing.

00:12:01.320 | Now, it turns out that altogether

00:12:03.880 | there are about five proteins like this

00:12:06.660 | that we need to think about in the typical retina.

00:12:09.660 | But for seeing color, really it's three of them.

00:12:11.840 | So there are three different proteins.

00:12:13.300 | Each absorbs light with a different preferred frequency.

00:12:17.540 | And then the nervous system keeps track of those signals,

00:12:20.600 | compares and contrasts them

00:12:23.980 | to extract some understanding

00:12:25.680 | of the wavelength composition of light.

00:12:28.080 | So you can see just by looking at a landscape,

00:12:30.600 | oh, it must be late in the day

00:12:33.360 | because things are looking golden.

00:12:34.920 | That's all a function of our absorbing

00:12:38.080 | the light that's coming from the world

00:12:39.920 | and interpreting that with our brain

00:12:41.680 | because of the different composition

00:12:43.040 | of the light that's reaching our eyes.

00:12:45.980 | - Is it fair to assume that my perception of red

00:12:48.160 | is the same as your perception of red?

00:12:50.200 | - Well, that's a great question.

00:12:51.360 | - And that mine is better.

00:12:52.560 | - No, I'm just kidding.

00:12:54.220 | It's a great question.

00:12:56.100 | It's a deep philosophical question.

00:12:57.460 | It's a question that really probably

00:12:59.000 | can't even ultimately be answered

00:13:01.140 | by the usual empirical scientific processes

00:13:05.180 | 'cause it's really about an individual's experience.

00:13:08.420 | What we can say is that the biological mechanisms

00:13:14.340 | that we think are important for seeing color, for example,

00:13:17.440 | seem to be very highly similar

00:13:19.520 | from one individual to the next,

00:13:20.980 | whether it be human beings or other animals.

00:13:23.180 | And so we think that the physiological process

00:13:27.500 | looks very similar on the front end,

00:13:29.780 | but once you're at the level of perception

00:13:32.220 | or understanding or experience,

00:13:34.920 | that's something that's a little bit tougher to nail down

00:13:38.480 | with the sorts of scientific approaches

00:13:42.560 | that we approach biological vision with, let's say.

00:13:46.100 | - You mentioned that there are five

00:13:47.880 | different cone types, essentially,

00:13:49.940 | cones being the cells that absorb light

00:13:51.620 | of different wavelengths.

00:13:52.820 | I often wondered when I had my dog what he saw

00:13:58.820 | and how his vision differs from our vision.

00:14:01.940 | And certainly there are animals that can see things

00:14:04.220 | that we can't see.

00:14:05.620 | What are some of the more outrageous examples of that?

00:14:09.140 | - Of seeing things that we can't.

00:14:10.940 | - And in the extreme.

00:14:12.260 | Dogs, I'm guessing, see reds more as oranges.

00:14:16.620 | Is that right?

00:14:17.580 | 'Cause they don't have the same array of neurons

00:14:21.340 | that we have for seeing color.

00:14:22.900 | - Right, so the first thing is it's not really

00:14:25.160 | five types of cones.

00:14:26.980 | There are really three types of cones.

00:14:29.020 | And if you look at the way that color vision

00:14:31.140 | is thought to work, you can sort of see

00:14:32.720 | that it has to be three different signals.

00:14:35.120 | There are a couple of other types of pigments.

00:14:37.300 | One is really mostly for dim light vision.

00:14:40.660 | When you're walking around in a moonless night

00:14:42.780 | and you're seeing things with very low light,

00:14:45.720 | that's the rod cell that uses its own pigment.

00:14:49.220 | And then there's another class of pigments

00:14:51.380 | we'll probably talk about a little bit later,

00:14:52.960 | this melanopsin pigment.

00:14:54.380 | - I thought you were referring to like ultraviolet

00:14:56.240 | and infrared and things of that sort.

00:14:58.500 | - Right, so in the case of a typical,

00:15:01.660 | well, let's put it this way, in human beings,

00:15:04.300 | most of us have three cone types

00:15:06.540 | and we can see colors that stem from that.

00:15:10.860 | In most mammals, including your dog or your cat,

00:15:15.860 | there really are only two cone types.

00:15:18.540 | And that limits the kind of vision that they can have

00:15:21.860 | in the domain of wavelength or color, as you would say.

00:15:25.080 | So really a dog sees the world kind of like

00:15:27.960 | a particular kind of colorblind human might see the world

00:15:31.720 | because instead of having three channels

00:15:33.300 | to compare and contrast, they only have two channels.

00:15:35.760 | And that makes it much more difficult to figure out

00:15:37.480 | exactly which wavelength you're looking at.

00:15:40.140 | - Do colorblind people suffer much

00:15:42.320 | as a consequence of being colorblind?

00:15:44.460 | - Well, it's like so many other disabilities.

00:15:47.420 | We are, the world is built for people

00:15:52.420 | of the most common type.

00:15:54.860 | So in some cases, the expectation can be there

00:15:59.660 | that somebody can see something that they won't be able to

00:16:01.980 | if they're missing one of their cone types, let's say.

00:16:04.460 | So in those moments, that can be a real problem.

00:16:08.740 | If there's a lack of contrast to their visual system,

00:16:12.500 | they will be blind to that.

00:16:14.020 | In general, it's a fairly modest visual limitation

00:16:19.020 | as things go.

00:16:20.640 | For example, if not being able to see acutely

00:16:23.020 | can be much more damaging,

00:16:24.180 | not being able to read fine print, for example.

00:16:26.900 | - Yeah, I suppose if I had to give up

00:16:28.700 | the ability to see certain colors

00:16:31.660 | or give up the ability to see clearly,

00:16:33.380 | I'd certainly trade out color for clarity.

00:16:37.500 | - Right, of course, color is very meaningful to us

00:16:40.020 | as human beings, so we would hate to give it up.

00:16:43.920 | But obviously dogs and cats and all kinds of other mammals

00:16:46.580 | do perfectly well in the world.

00:16:48.100 | - Yeah, because we take care of them.

00:16:49.260 | I spent most of my time taking care of that dog.

00:16:51.660 | He took care of me too.

00:16:54.260 | Let's talk about that odd photopigment.

00:16:59.920 | Photopigment, of course, being the thing that absorbs light

00:17:03.540 | of a particular wavelength.

00:17:05.100 | And let's talk about these specialized ganglion cells

00:17:09.060 | that communicate certain types of information

00:17:12.380 | from eye to the brain that are so important

00:17:15.580 | for so many things.

00:17:16.660 | What I'm referring to here, of course,

00:17:17.960 | is your co-discovery of the so-called

00:17:20.120 | intrinsically photosensitive cells,

00:17:22.260 | the neurons in the eye that do so many of the things

00:17:25.020 | that don't actually have to do with perception,

00:17:27.540 | but have to do with important biological functions.

00:17:30.260 | What I would love for you to do is explain to me

00:17:33.220 | why once I heard you say,

00:17:35.100 | we have a bit of fly eye in our eye.

00:17:38.880 | And you showed this slide of like a giant fly

00:17:42.220 | from a horror movie trying to attack this woman.

00:17:46.260 | And maybe it was an eye also.

00:17:48.600 | So what does it mean that we have a bit of a fly eye

00:17:52.080 | in our eye?

00:17:53.140 | - Yeah, so this last pigment is a really peculiar one.

00:18:01.540 | One can think about it as really the initial

00:18:04.460 | sensitive element in a system that's designed

00:18:07.120 | to tell your brain about how bright things are

00:18:09.640 | in your world.

00:18:10.560 | And the thing that's really peculiar about this pigment

00:18:15.260 | is that it's in the wrong place, in a sense.

00:18:18.460 | When you think about the structure of the retina,

00:18:20.620 | you think about a layer cake, essentially.

00:18:22.560 | You've got this thin membrane at the back of your eye,

00:18:25.340 | but it's actually a stack of thin layers.

00:18:27.820 | And the outermost of those layers

00:18:29.460 | is where these photoreceptors you were talking about earlier

00:18:31.940 | are sitting.

00:18:32.780 | That's where the film of your camera is, essentially.

00:18:35.420 | That's where the photons do their magic

00:18:37.020 | with the photopigments and turn it into a neural signal.

00:18:39.140 | - I like that.

00:18:39.980 | I've never really thought of the photoreceptors

00:18:41.020 | as the film of the camera, but that makes sense.

00:18:42.780 | - Yeah, or like the sensitive chip,

00:18:44.820 | CCD chip in your cell phone.

00:18:47.220 | It's the surface on which the light pattern

00:18:49.420 | is imaged by the optics of the eye.

00:18:52.240 | And now you've got an array of sensors

00:18:54.180 | that's capturing that information

00:18:56.260 | and creating a bitmap, essentially.

00:18:59.100 | But now it's in neural signals distributed

00:19:01.060 | across the surface of the retina.

00:19:03.260 | So all of that was known to be going on 150 years ago.

00:19:07.040 | A couple of types of photoreceptors, cones and rods.

00:19:10.740 | If you look a little bit more closely, three types of cones.

00:19:13.820 | That's where the transformation

00:19:15.580 | from electromagnetic radiation to neural signals

00:19:20.480 | was thought to take place.

00:19:22.520 | But it turns out that this last photopigment

00:19:24.680 | is in the other end of the retina,

00:19:27.060 | the innermost part of the retina.

00:19:28.500 | That's where the so-called ganglion cells are.

00:19:30.540 | Those are the cells that talk to the brain,

00:19:32.140 | the ones that actually can communicate directly

00:19:34.860 | what information comes to them from the photoreceptors.

00:19:38.220 | And here you've got a case

00:19:39.900 | where actually some of the output neurons

00:19:43.100 | that we didn't think had any business

00:19:44.780 | being directly sensitive to light

00:19:46.980 | were actually making this photopigment,

00:19:50.060 | absorbing light and converting that to neural signals

00:19:53.420 | and sending it to the brain.

00:19:54.900 | So that made it pretty surprising and unexpected,

00:19:58.640 | but there are many surprising things about these cells.

00:20:01.800 | So, and what is the relationship to the fly eye?

00:20:05.140 | Right, so the link there is that if you ask

00:20:08.180 | how the photopigment now communicates downstream

00:20:13.180 | from the initial absorption event

00:20:15.960 | to get to the electrical signal,

00:20:17.560 | that's a complex cellular process,

00:20:19.500 | involves many chemical steps.

00:20:22.260 | And if you look at how photoreceptors in our eyes work,

00:20:26.640 | you can see what that cascade is, how that chain works.

00:20:30.340 | If you look in the eyes of flies

00:20:33.400 | or other insects or other invertebrates,

00:20:36.660 | there's a very similar kind of chain,

00:20:38.740 | but the specifics of how the signals get

00:20:41.460 | from the absorption event by the pigment

00:20:43.600 | to the electrical response

00:20:44.860 | that the nervous system can understand

00:20:47.040 | are characteristically different

00:20:48.900 | between fuzzy furry creatures like us

00:20:53.740 | and insects, for example, like the fly.

00:20:56.500 | I see.

00:20:57.340 | So these funny extra photoreceptors

00:21:00.640 | that are in the wrong layer

00:21:01.740 | doing something completely different

00:21:03.060 | are actually using a chemical cascade

00:21:06.740 | that looks much more like what you would see

00:21:08.300 | in a fly photoreceptor

00:21:10.100 | than what you would see in a human photoreceptor,

00:21:12.900 | a rod or a cone, for example.

00:21:14.580 | So it sounds like it's a very primitive aspect

00:21:18.700 | of biology that we maintain.

00:21:20.380 | - Exactly right.

00:21:22.100 | - And despite the fact

00:21:22.940 | that dogs can't see as many colors as we can

00:21:25.060 | and cats can't see as many colors as we can,

00:21:26.860 | we have all this extravagant stuff for seeing color.

00:21:29.760 | And then you've got this other pigment

00:21:31.560 | sitting in the wrong, not wrong,

00:21:33.700 | but in a different part of the eye,

00:21:36.980 | sending, processing light very differently

00:21:40.300 | and sending that information into the brain.

00:21:42.460 | So what do these cells do?

00:21:45.580 | I mean, presumably they're there for a reason.

00:21:47.820 | - They are.

00:21:48.740 | And the interesting thing is that one cell type like this,

00:21:53.740 | carrying one kind of signal,

00:21:56.300 | which I would call a brightness signal, essentially,

00:22:00.220 | can do many things in the brain.

00:22:02.120 | - When you say brightness signal,

00:22:03.180 | you mean that it, like right now, I have these cells.

00:22:05.940 | Do I have these cells?

00:22:06.780 | Of course not. - You do.

00:22:07.620 | - I'm joking, I hope I have these cells in my eye.

00:22:09.760 | And they're paying attention to how bright it is overall,

00:22:12.760 | but they're not paying attention, for instance,

00:22:14.060 | to the edge of your ear

00:22:15.140 | or what else is going on in the room.

00:22:16.740 | - Right, so it's the difference between

00:22:19.140 | knowing what the objects are on the table

00:22:21.740 | and knowing whether it's bright enough

00:22:23.180 | to be daylight right now.

00:22:25.820 | So why does your nervous system need to know

00:22:28.960 | whether it's daylight right now?

00:22:30.700 | Well, one thing that needs to know,

00:22:31.980 | that is your circadian clock.

00:22:33.980 | You know, if you travel across time zones to Europe,

00:22:37.420 | now your internal clock thinks it's California time,

00:22:41.940 | but the rotation of the earth is, you know,

00:22:44.880 | for a different part of the planet.

00:22:46.420 | You know, the rising and setting of the sun

00:22:47.860 | is not at all what your body is anticipating.

00:22:50.280 | So you've got an internal representation

00:22:52.100 | of the rotation of the earth in your own brain.

00:22:54.640 | That's your circadian system.

00:22:56.180 | It's keeping time.

00:22:58.660 | But now you've played a trick on your nervous system.

00:23:00.900 | You put yourself in a different place

00:23:02.360 | where the sun is rising at the, quote, wrong time.

00:23:05.660 | Well, that's not good for you, right?

00:23:07.620 | So you gotta get back on track.

00:23:08.980 | One of the things this system does is sends a,

00:23:12.020 | oh, it's daylight now signal to the brain,

00:23:14.980 | which compares with its internal clock.

00:23:16.860 | And if that's not right,

00:23:18.420 | it tweaks the clock gradually

00:23:20.460 | until you get over your jet lag

00:23:21.840 | and you feel back on track again.

00:23:24.100 | So the jet lag case makes a lot of sense to me,

00:23:26.980 | but presumably these elements didn't evolve for jet lag.

00:23:31.380 | Right.

00:23:32.220 | So what are they doing on a day-to-day basis?

00:23:35.900 | Right, well, one way to think about this

00:23:37.460 | is that the clock that you have in not just your brain,

00:23:42.980 | in all the cells, or almost all of the cells of your body,

00:23:45.660 | they're all oscillating, they're all, you know.

00:23:49.020 | They got little clocks in them.

00:23:49.860 | They got little clocks in them themselves.

00:23:51.660 | They're all clocks.

00:23:52.780 | You know, they need to be synchronized appropriately.

00:23:58.820 | And the whole thing has to be built in biological machinery.

00:24:04.620 | This is actually a beautiful story

00:24:07.380 | about how gene expression can control gene expression.

00:24:10.940 | And if you set it up right,

00:24:12.060 | you can set up a little thing

00:24:13.420 | that just sort of hums along at a particular frequency.

00:24:16.940 | In our case, it's humming along at 24 hours,

00:24:19.340 | 'cause that's how our earth rotates,

00:24:21.060 | and it's all built into our biology.

00:24:23.460 | So this is great,

00:24:24.840 | but the reality is that the clock can only be so good.

00:24:28.060 | I mean, we're talking about biology here.

00:24:29.620 | It's not precision engineering,

00:24:32.380 | and so it can be a little bit off.

00:24:34.140 | Well, also it doesn't, it's in our brain,

00:24:35.900 | so it doesn't have access to any regular unerring signal.

00:24:39.620 | Well, if in the absence of the rising and setting

00:24:42.460 | of the sun, it doesn't.

00:24:43.460 | If you put someone in a cave,

00:24:45.560 | their biological clock will keep time

00:24:47.820 | to within a handful of minutes of 24 hours.

00:24:51.860 | That's no problem for one day.

00:24:55.020 | But if this went on without any correction,

00:24:57.280 | eventually you'd be out of phase.

00:24:59.220 | And this is actually one of the things

00:25:00.500 | that blind patients often complain about.

00:25:03.540 | If they've got retinal blindness, is insomnia.

00:25:08.540 | Or sleep and history in the middle of the night.

00:25:10.140 | Exactly, they're not synchronized.

00:25:11.740 | Their clock is there, but they're drifting out of phase

00:25:14.740 | because their clock's only good to 24.2 hours

00:25:19.700 | or 23.8 hours.

00:25:21.900 | Little by little, they're drifting.

00:25:24.140 | So you need a synchronization signal.

00:25:26.020 | So even if you never across time,

00:25:27.580 | as I was saying, of course, we didn't back on the savanna.

00:25:29.680 | We stayed within walking distance of where we were.

00:25:32.620 | You still need a synchronizer

00:25:35.620 | 'cause otherwise you have nothing to actually confirm

00:25:39.140 | when the rising and the setting of the sun is.

00:25:41.580 | That's what you're trying to synchronize yourself to.

00:25:44.340 | I'm fascinated by the circadian clock

00:25:47.100 | and the fact that all the cells of our body

00:25:50.100 | have essentially a 24 hour-ish clock in them.

00:25:53.340 | Right.

00:25:54.460 | We hear a lot about these circadian rhythms

00:25:56.180 | and circadian clocks, the fact that we need light input

00:25:59.180 | from these special neurons in order to set the clock.

00:26:02.300 | But I've never really heard it describe

00:26:04.300 | how the clock itself works

00:26:06.460 | and how the clock signals to all the rest of the body

00:26:10.180 | when the liver should be doing one thing

00:26:12.860 | and when the stomach should be doing another.

00:26:15.580 | I know you've done some work on the clock.

00:26:18.180 | So if you would just maybe briefly describe

00:26:21.580 | where the clock is, what it does,

00:26:24.500 | and some of the top contour

00:26:26.860 | of how it tells the cells of the body what to do.

00:26:29.780 | Right.

00:26:30.600 | So the first thing to say is that, as you said,

00:26:32.860 | the clock is all over the place.

00:26:34.660 | Most of the tissues in your body have clocks.

00:26:37.980 | We probably have, what, millions of clocks in our body.

00:26:40.260 | I would say that's probably fair.

00:26:42.020 | If you have millions of cell types,

00:26:43.340 | you probably may have millions of clocks.

00:26:46.100 | The role of the central pacemaker for the circadian system

00:26:50.260 | is to coordinate all of these.

00:26:52.760 | And there's a little nucleus,

00:26:55.900 | a little collection of nerve cells in your brain.

00:26:59.540 | It's called the suprachiasmatic nucleus, the SCN.

00:27:03.620 | And it is sitting in a funny place

00:27:05.760 | for the rest of the structures in the nervous system

00:27:07.660 | that get direct retinal input.

00:27:09.600 | It's sitting in the hypothalamus,

00:27:11.980 | which you can think about as sort of the great coordinator

00:27:15.500 | of drives and-

00:27:18.460 | The source of all our pleasures and all our problems.

00:27:20.740 | Right. Or most our problems.

00:27:22.100 | Yes, it really is.

00:27:23.980 | But it's sort of deep in your brain,

00:27:26.220 | things that drive you to do things.

00:27:28.020 | If you're freezing cold, you put on a coat, you shivery.

00:27:31.460 | All these things are coordinated by the hypothalamus.

00:27:34.140 | So this pathway that we're talking about from the retina

00:27:37.580 | and from these peculiar cells

00:27:39.660 | that are encoding light intensity

00:27:41.820 | are sending signals directly into a center

00:27:45.420 | that's surrounded by all of these centers

00:27:47.940 | that control autonomic nervous system

00:27:51.060 | and your hormonal systems.

00:27:54.160 | So this is a part of your visual system

00:27:57.220 | that doesn't really reach the level of consciousness.

00:27:59.500 | It's not something you think about.

00:28:01.900 | It's happening under the radar kind of all the time.

00:28:05.900 | And the signal is working its way

00:28:07.540 | into this central clock coordinating center.

00:28:12.380 | Now, what happens then is not that well understood,

00:28:17.400 | but it's clear that this is a neural center

00:28:20.020 | that has the same ability to communicate

00:28:21.740 | with other parts of your brain as any other neural center.

00:28:25.580 | And clearly there are circuits

00:28:28.780 | that involve connections between neurons

00:28:31.220 | that are conventional.

00:28:34.060 | But in addition, it's quite clear

00:28:35.340 | that there are also sort of humoral effects

00:28:37.480 | that things are oozing out of the cells in the center

00:28:42.020 | and maybe into the circulation

00:28:43.580 | or just diffusing through the brain to some extent

00:28:47.620 | that can also affect neurons all swear.

00:28:50.660 | But the hypothalamus uses everything

00:28:52.760 | to control the rest of the bodies.

00:28:54.240 | And that's true of the suprachiasmatic nucleus,

00:28:56.640 | this circadian center as well.

00:28:59.020 | It can get its fingers into the autonomic nervous system,

00:29:03.400 | the humoral system,

00:29:04.740 | and of course up to the centers of the brain

00:29:07.160 | that organize coordinated rational behavior.

00:29:12.160 | So if I understand correctly,

00:29:14.300 | we have this group of cells, the suprachiasmatic nucleus,

00:29:16.620 | it's got a 24 hour rhythm.

00:29:18.520 | That rhythm is more or less matched

00:29:21.620 | to what's going on in our external world

00:29:23.840 | by the specialized set of neurons in our eye.

00:29:26.420 | But then the master clock itself, the SCN,

00:29:30.460 | releases things in the blood, humoral signals

00:29:33.020 | that go out various places in the body.

00:29:37.820 | And then you said to the autonomic system,

00:29:39.360 | which is regulating more or less how alert or calm we are,

00:29:42.100 | as well as our thinking and our cognition.

00:29:44.240 | So I'd love to talk to you about the autonomic part.

00:29:48.380 | Presumably that's through melatonin,

00:29:52.220 | it's through adrenaline.

00:29:55.660 | How is it that this clock is impacting

00:29:58.380 | how the autonomic system, how alert or calm we feel?

00:30:02.060 | - Right, so there are pathways

00:30:05.140 | by which the suprachiasmatic nucleus can access

00:30:09.300 | both the parasympathetic and sympathetic nervous system.

00:30:12.260 | - Just so people know, the sympathetic nervous system

00:30:14.400 | is the one that tends to make us more alert,

00:30:16.180 | and the parasympathetic nervous system

00:30:18.100 | is the portion of the autonomic nervous system

00:30:20.880 | makes us feel more calm, in broad context.

00:30:24.120 | - To first approximation, right.

00:30:25.780 | So this is, both of these systems are within the grasp

00:30:30.780 | of the circadian system through hypothalamic circuits.

00:30:35.020 | One of the circuits that will be, I think,

00:30:37.700 | of particular interest to some of your listeners

00:30:40.040 | is a pathway that involves this sympathetic branch

00:30:44.100 | of the autonomic nervous system, the fight or flight system,

00:30:47.740 | that is actually, through a very circuitous route,

00:30:50.900 | innervating the pineal gland,

00:30:52.780 | which is sitting in the middle of your brain.

00:30:55.380 | - The so-called third eye.

00:30:56.980 | - Right, so this is the-

00:30:58.380 | - We'll have to get back to why it's called the third eye,

00:31:00.600 | because, yeah. - That's an interesting history.

00:31:02.260 | - You can't call something the third eye and not,

00:31:04.060 | and just, you know.

00:31:05.240 | - Just leave it there. - Just leave it there.

00:31:06.780 | - Right. - Right.

00:31:08.440 | - Anyway, this is the major source of melatonin in your body.

00:31:11.500 | - So light comes into my eye. - Yes.

00:31:15.200 | - Passed off to the suprachiasmatic nucleus, essentially,

00:31:18.020 | not the light itself,

00:31:18.880 | but the signal representing the light.

00:31:21.220 | - Sure.

00:31:22.060 | - Then the SCN, the suprachiasmatic nucleus,

00:31:24.300 | can impact the melatonin system via the pineal.

00:31:28.880 | - Right, the way this is seen is that

00:31:30.600 | if you were to measure your melatonin level

00:31:33.880 | over the course of the day,

00:31:35.600 | if you could do this, you know, hour by hour,

00:31:38.160 | you'd see that it's really low during the day,

00:31:40.480 | very high at night.

00:31:42.160 | But if you get up in the middle of the night

00:31:44.100 | and go to the bathroom and turn on

00:31:45.300 | the bright fluorescent light,

00:31:47.120 | your melatonin level is slammed to the floor.

00:31:49.480 | Light is directly impacting your hormonal levels

00:31:53.360 | through this mechanism that we just described.

00:31:57.180 | So this is one of the routes by which light can act

00:32:00.560 | on your hormonal status through pathways

00:32:04.440 | that are completely beyond

00:32:06.440 | what you normally would think about, right?

00:32:08.440 | You're thinking about the things in the bathroom.

00:32:10.540 | Oh, there's the toothbrush.

00:32:12.080 | You know, there's the tube of toothpaste.

00:32:13.820 | But meanwhile, this other system is just counting photons

00:32:17.680 | and saying, oh, wow, there's a lot of photons right now.

00:32:20.120 | Let's shut down the melatonin release.

00:32:22.640 | - This is one of the main reasons why

00:32:24.400 | I've encouraged people to avoid bright light exposure

00:32:27.280 | in the middle of the night.

00:32:28.320 | Not just blue light, but bright light of any wavelength.

00:32:32.120 | Because there's this myth out there that blue light,

00:32:34.800 | because it's the optimal signal for activating this pathway

00:32:37.720 | and shutting down melatonin,

00:32:39.520 | is the only wavelength of light that can shut it down.

00:32:43.420 | But am I correct in thinking that

00:32:45.360 | if a light is bright enough,

00:32:47.200 | it doesn't matter if it's blue light, green light,

00:32:49.320 | purple light, even red light,

00:32:51.720 | you're going to slam melatonin down to the ground,

00:32:54.720 | which is not a good thing to happen

00:32:57.000 | in the middle of the night, correct?

00:32:58.400 | - Right, yeah.

00:32:59.320 | I mean, any light will affect the system to some extent.

00:33:03.480 | The blue light is somewhat more effective,

00:33:06.440 | but don't fool yourself into thinking

00:33:09.000 | that if you use red light,

00:33:09.920 | that means you're avoiding the effect.

00:33:12.640 | It's certainly still there.

00:33:14.460 | And certainly if it's very bright,

00:33:15.660 | it'll be more effective in driving the system

00:33:18.440 | than dim blue light would be.

00:33:20.060 | - Interesting.

00:33:20.900 | A lot of people wear blue blockers.

00:33:22.520 | And in a kind of odd twist of misinformation out there,

00:33:28.480 | a lot of people wear blue blockers

00:33:29.720 | during the middle of the day,

00:33:31.200 | which basically makes no sense

00:33:32.920 | because during the middle of the day

00:33:34.060 | is when you want to get a lot of bright light

00:33:36.880 | and including blue light into your eyes, correct?

00:33:39.420 | - Absolutely.

00:33:40.260 | Not just for the reasons we've been talking about

00:33:42.700 | in terms of circadian effects.

00:33:44.540 | There are major effects of light on mood

00:33:47.060 | and seasonal affective disorder

00:33:51.060 | apparently is essentially a reflection

00:33:53.660 | of this same system in reverse.

00:33:55.820 | If you're living in the Northern climes

00:33:58.700 | and you're not getting that much light

00:34:00.620 | during the middle of the winter in Stockholm,

00:34:03.600 | you might be prone to depression

00:34:06.580 | and phototherapy might be just the ticket for you.

00:34:09.420 | And that's because there's a direct effect of light on mood.

00:34:13.620 | There's an example where if you don't have enough light,

00:34:16.460 | it's a problem.

00:34:17.660 | So I think you're exactly right.

00:34:18.700 | It's not about is light good or bad for you?

00:34:20.380 | It's about what kind of light and when

00:34:22.780 | that makes the difference.

00:34:25.440 | - Yeah, the general rule of thumb that I've been living by

00:34:27.260 | is to get as much bright light in my eyes,

00:34:29.100 | ideally from sunlight,

00:34:31.220 | anytime I want to be alert

00:34:32.900 | and doing exactly the opposite when I want to be asleep

00:34:36.260 | or getting drowsy.

00:34:37.100 | - And there are aspects of this that spin out

00:34:40.820 | way beyond the conversation we're having now

00:34:42.620 | to things like this.

00:34:44.320 | It turns out that the incidence of myopia-

00:34:47.540 | - Nearsightedness.

00:34:48.640 | - Nearsightedness, right,

00:34:50.780 | is strongly related to the amount of time

00:34:53.560 | that kids spend outdoors.

00:34:56.140 | - In what direction of effect?

00:34:57.740 | - The more they spend time outdoors,

00:34:59.800 | the less nearsightedness they have.

00:35:02.120 | So this is all about-

00:35:02.960 | - And is that because they're viewing things at a distance

00:35:04.460 | or because they're getting a lot of blue light,

00:35:06.540 | less sunlight?

00:35:07.360 | - It's a great question.

00:35:08.300 | It is not fully resolved what the epidemiological,

00:35:11.620 | what the basis of that epidemiological finding is.

00:35:14.380 | One possibility is the amount of light,

00:35:16.180 | which would make me think about this

00:35:17.660 | melanopsin system again,

00:35:19.960 | but it might very well be a question of accommodation

00:35:22.700 | that is the process by which you focus on

00:35:24.380 | near or far things.

00:35:25.960 | If you're never outdoors, everything is nearby.

00:35:28.360 | If you're outdoors, you're focusing far.

00:35:30.340 | - Unless you're on your phone.

00:35:31.580 | - Right, exactly.

00:35:32.900 | - There's a tremendous amount of interest these days

00:35:36.060 | in watches and things that count steps.

00:35:39.580 | I'm beginning to realize that we should probably

00:35:41.740 | have a device that can count photons during the day

00:35:45.920 | and can also count photons at night

00:35:47.620 | and tell us, hey, you're getting too many photons.

00:35:49.420 | You're going to shut down your melatonin at night,

00:35:51.040 | or you're not getting enough photons.

00:35:52.360 | Today, you didn't get enough bright light,

00:35:53.900 | whether or not it's from artificial light or from sunlight.

00:35:56.740 | I guess the, where would you put it?

00:35:58.020 | I guess you put it on the top of your head,

00:35:59.180 | or you'd probably want it someplace outward facing.

00:36:02.620 | - Right, probably what you need is as many photons

00:36:05.580 | over as much of the retina as possible

00:36:07.260 | to recruit as much of this system as possible.

00:36:11.380 | - In thinking about other effects

00:36:12.620 | of this non-image forming pathway

00:36:15.180 | that involves these special cells in the eye and the SCN,

00:36:19.800 | you had a paper a few years ago

00:36:21.580 | looking at retinal input to an area of the brain,

00:36:26.580 | which has a fancy name, the perihabenula,

00:36:30.780 | but names don't necessarily matter,

00:36:33.020 | that had some important effects on mood

00:36:36.380 | and other aspects of light.

00:36:39.440 | Maybe you could tell us a little bit about

00:36:40.740 | what is the perihabenula?

00:36:42.780 | - Oh, wow, so that's a fancy term,

00:36:45.100 | but I think the way to think about this

00:36:47.040 | is as a chunk of the brain that is sitting

00:36:51.260 | as part of a bigger chunk that's really the linker

00:36:55.420 | between peripheral sensory input of all kinds,

00:36:58.220 | virtually all kinds, whether it's auditory input

00:37:02.780 | or tactile input or visual input

00:37:07.060 | to the region of your brain, the cortex,

00:37:09.220 | that allows you to think about these things

00:37:11.080 | and make plans around them and to integrate them

00:37:13.740 | and that kind of thing.

00:37:15.000 | So we've known about a pathway that gets from the retina

00:37:21.900 | through this sort of linker center,

00:37:27.900 | it's called the thalamus, and then on up to the cortex.

00:37:31.460 | - Exactly, but you want to arrive at the destination, right?

00:37:34.460 | Now you're at grand central and now you can do your thing

00:37:36.740 | 'cause you're up at the cortex.

00:37:38.340 | So this is the standard pattern.

00:37:40.100 | You have the sensory input coming from the periphery,

00:37:41.860 | you've got these peripheral elements

00:37:43.380 | that are doing the initial stages of-

00:37:45.980 | - The eye, the ear, the nose.

00:37:47.520 | - The eye, the skin of your fingertips, right?

00:37:49.820 | No, the taste buds on your tongue,

00:37:51.520 | they're taking this raw information in

00:37:53.480 | and they're doing some pre-processing maybe

00:37:56.860 | or the early circuits are,

00:37:58.900 | but eventually most of these signals

00:38:00.420 | have to pass through the gateway to the cortex,

00:38:02.660 | which is the thalamus.

00:38:04.660 | And we've known for years, for decades, many decades,

00:38:09.160 | what the major throughput pathway

00:38:11.100 | from the retina to the cortex is and where it ends up.

00:38:14.500 | It ends up in the visual cortex.

00:38:15.820 | You pat the back of your head,

00:38:17.300 | that's where the receiving center is

00:38:20.820 | for the main pathway from retina to cortex.

00:38:23.840 | But wait a minute, there's more.

00:38:25.700 | There's this little side pathway

00:38:27.540 | that goes through a different part of that linking

00:38:30.340 | thalamus center, the gateway to the cortex.

00:38:32.660 | - It's like a local train from Grand Central to-

00:38:34.900 | - It's in a weird part of the neighborhood, right?

00:38:37.580 | It's a completely different,

00:38:38.700 | it's like a little trunk line that branches off

00:38:41.580 | and goes out into the hinterlands

00:38:43.620 | and it's going to the part of this linker center

00:38:46.460 | that's talking to a completely different part of cortex,

00:38:48.820 | way up front, frontal lobe,

00:38:51.300 | which is much more involved in things like planning

00:38:54.140 | or self-image or-

00:38:57.660 | - Self-image, literally how one thinks about oneself.

00:39:01.020 | - Do you feel good about yourself?

00:39:02.920 | Or what's your plan for next Thursday?

00:39:06.480 | It's a very high level center

00:39:11.020 | in the highest level of your nervous system.

00:39:13.580 | And this is the region that is getting input

00:39:16.060 | from this pathway, which is mostly worked out

00:39:18.980 | in this function by Samer Hatara's lab.

00:39:21.340 | I know you had him on the podcast.

00:39:23.220 | - We didn't talk about this pathway.

00:39:24.220 | - This pathway at all, right.

00:39:25.660 | So, Diego Fernandez and Samer and the folks

00:39:30.660 | that work with them were able to show

00:39:33.100 | that this pathway doesn't just exist

00:39:35.020 | and get you to a weird place.

00:39:37.140 | But if you activate it at kind of the wrong time of day,

00:39:41.940 | animals can become depressed.

00:39:45.360 | And if you silence it under the right circumstances,

00:39:48.740 | then weird lighting cycles that would normally

00:39:52.000 | make them act sort of depressed,

00:39:55.560 | no longer have that effect.

00:39:57.520 | - So, it sounds to me like there's this pathway

00:39:59.240 | from I to this unusual train route

00:40:03.740 | through the structure we call the thalamus,

00:40:06.740 | then up to the front of the brain that relates

00:40:08.780 | to things of self-perception, kind of higher level functions.

00:40:13.360 | I find that really interesting because most

00:40:14.980 | of what I think about when I think about these fancy,

00:40:17.740 | well, or these primitive, rather, neurons

00:40:20.860 | that don't pay attention to the shapes of things,

00:40:22.840 | but instead to brightness, I think of,

00:40:24.800 | well, it regulates melatonin, circadian clock, mood, hunger,

00:40:28.780 | the really kind of vegetative stuff, if you will.

00:40:32.540 | And this is interesting because I think a lot

00:40:35.480 | of people experience depression, not just people

00:40:38.480 | that live in Scandinavia in the middle of winter.

00:40:42.120 | And we are very much divorced

00:40:45.080 | from our normal interactions with light.

00:40:47.800 | It also makes me realize

00:40:49.780 | that these intrinsically photosensitive cells

00:40:52.220 | that set the clock, et cetera, are involved

00:40:55.400 | in a lot of things.

00:40:56.620 | I mean, they seem to regulate a dozen

00:40:59.760 | or more different basic functions.

00:41:01.500 | I want to ask you about a different aspect

00:41:05.200 | of the visual system now, which is the one

00:41:08.300 | that relates to our sense of balance.

00:41:10.880 | So, I love boats, but I hate being on them.

00:41:13.700 | I love the ocean from shore because I get incredibly seasick.

00:41:18.280 | I'll just, it's awful.

00:41:19.540 | I think I'm gonna get seasick if I think about it too much.

00:41:22.060 | And once I went on a boat trip, I came back

00:41:23.920 | and I actually got, I got motion sick

00:41:27.380 | or wasn't seasick 'cause I went rafting.

00:41:30.260 | So, there's a system that somehow gets messed up.

00:41:33.520 | They always tell us if you're feeling sick

00:41:34.720 | to look at the horizon, et cetera, et cetera.

00:41:37.320 | So, what is the link between our visual system

00:41:39.480 | and our balance system?

00:41:40.700 | And why does it make us nauseous sometimes

00:41:43.320 | when the world is moving in a way

00:41:45.640 | that we're not accustomed to?

00:41:47.360 | I realize this is a big question

00:41:48.880 | because it involves eye movement, et cetera.

00:41:51.600 | But let's maybe just walk in at the simplest layers

00:41:56.320 | of vision, vestibular, so-called balance system,

00:42:01.320 | and then maybe we can piece the system together for people

00:42:04.320 | so that they can understand.

00:42:05.160 | And then also we should give them some tools

00:42:06.880 | for adjusting their nausea

00:42:08.640 | when their vestibular system is out of whack.

00:42:12.000 | - Cool, so, I mean, the first thing to think about

00:42:14.460 | is that the vestibular system is designed to allow you

00:42:20.460 | to see how your, or detect, sense how you're moving

00:42:25.460 | in the world, through the world.

00:42:29.020 | It's a funny one because it's about your movement

00:42:34.360 | in relationship to the world in a sense,

00:42:36.300 | and yet it's sort of interoceptive in the sense

00:42:39.460 | that it is really in the end sensing the movement

00:42:44.460 | of your own body.

00:42:46.180 | - Okay, so, interoception we should probably delineate

00:42:48.120 | for people is when you're focusing on your internal state

00:42:50.660 | as opposed to something outside you.

00:42:52.140 | - Right.

00:42:52.980 | - But it's a gravity sensing system.

00:42:55.280 | - Well, it's partly a gravity sensing system

00:42:57.540 | in the sense that gravity is a force that's acting on you

00:43:02.540 | as if you were moving through the world

00:43:05.380 | in the opposite direction.

00:43:06.860 | - All right, now you gotta explain that one to me.

00:43:10.440 | - Okay, so basically the idea is that

00:43:12.920 | if we leave gravity aside,

00:43:16.840 | we're just sitting in a car in the passenger seat

00:43:21.820 | and the driver hits the accelerator

00:43:24.500 | and you start moving forward, you sense that.

00:43:26.740 | If your eyes were closed, you'd sense it.

00:43:28.420 | If your ears were plugged and your eyes were closed,

00:43:30.580 | you'd still know it.

00:43:31.740 | - Yeah, many people take off on the plane like this,

00:43:33.900 | they're dreading the flight

00:43:35.100 | and they know when the plane is taking off.

00:43:36.900 | - Sure, that's your vestibular system talking

00:43:38.920 | because anything that jostles you

00:43:40.900 | out of the current position you're in right now

00:43:43.100 | will be detected by the vestibular system, pretty much.

00:43:46.640 | So this is a complicated system,

00:43:49.600 | but it's basically in your inner ear,

00:43:52.840 | very close to where you're hearing.

00:43:54.240 | - Right, they put it there.

00:43:55.580 | And I don't know who they is.

00:43:57.880 | - I don't really know, they're starting to ride.

00:44:00.280 | - I'm just kidding.

00:44:01.400 | To steal our friend Russ Van Gelder's explanation,

00:44:03.960 | we weren't consulted the design phase and no one-

00:44:06.560 | - That's a great line, that's a great line.

00:44:08.760 | - But it's interesting, it's in the ear.

00:44:11.880 | - Yeah, yeah, it's deep in there

00:44:14.660 | and it's served by the same nerve actually

00:44:18.520 | that serves the hearing system.

00:44:20.620 | One way to think about it is both the hearing system

00:44:23.420 | and the vestibular self-motion sensing system

00:44:26.880 | are really detecting the signal in the same way.

00:44:29.320 | They're hairy cells and they're excited.

00:44:32.400 | - Really hairy?

00:44:33.240 | - Yeah, sort of, they got little cilia sticking up

00:44:35.320 | off the surfaces.

00:44:36.820 | And depending on which way you bend those,

00:44:38.720 | the cells will either be inhibited or excited.

00:44:41.100 | They're not even neurons, but then they talk to neurons

00:44:44.080 | with a neuron-like process and off you go.

00:44:46.140 | Now you've got an auditory signal

00:44:47.560 | if you're sensing things bouncing around in your cochlea,

00:44:51.480 | which is-

00:44:52.320 | - Sound waves.

00:44:53.160 | - Sympathetically the bouncing of your eardrum,

00:44:55.760 | which is sympathetically the sound waves in the world.

00:44:58.800 | But in the case of the vestibular apparatus,

00:45:01.280 | evolution has built a system that detects the motion

00:45:04.500 | of say fluid going by those hairs.

00:45:07.880 | And if you put a sensor like that in a tube

00:45:11.300 | that's fluid-filled, now you've got a sensor

00:45:14.040 | that will be activated when you rotate that tube

00:45:17.940 | around the axis that passes through the middle of it.

00:45:20.020 | Those who were just listening won't be able to visualize.

00:45:22.420 | - No, I think that makes sense.

00:45:23.380 | I was thinking of it as three hula hoops.

00:45:25.420 | - Right, three hula hoops.

00:45:26.260 | - One standing up, one lying down on the ground.

00:45:28.300 | - Right, one in the other direction, three directions.

00:45:31.680 | The people who fly will talk about roll, pitch, and yaw,

00:45:35.080 | that kind of thing.

00:45:35.920 | So the three axes of encoding,

00:45:39.260 | just like in the cones of the retina.

00:45:40.080 | - Sort of the yes, the no, and then I always say it's,

00:45:43.220 | and then the puppy head tilt.

00:45:44.380 | - Yeah, the puppy head tilt, that's the other one.

00:45:46.700 | So the point is that your brain is eventually going to be

00:45:50.320 | able to unpack what these sensors are telling you

00:45:54.620 | about how you just rotated your head

00:45:57.100 | in very much the way that the three types of cones

00:45:59.460 | we were talking about before are reading the incoming photons

00:46:04.860 | in the wavelength domain differently.

00:46:06.840 | And if you can compare and trust, you get red, green, blue.

00:46:09.940 | So it's the same basic idea.

00:46:11.680 | If you have three sensors and you array them properly,

00:46:14.600 | now you can tell if you're rotating your head

00:46:16.680 | left or right, up or down.

00:46:18.460 | That's the sensory signal coming back into your brain,

00:46:22.440 | confirming that you've just made a movement that you will.

00:46:26.560 | - But what about on the plane?

00:46:27.700 | Because when I'm on the plane, I'm completely stationary.

00:46:29.720 | The plane's moving, but my head hasn't moved.

00:46:32.440 | So I'm just moving forward, gravity is constant.

00:46:35.420 | - Exactly.

00:46:36.260 | - How do I know I'm accelerating?

00:46:37.880 | - So what's happening now is your brain

00:46:39.640 | is sensing the motion and the brain is smart enough also

00:46:44.640 | to ask itself, did I will that movement

00:46:48.580 | or did that come from the outside?

00:46:50.560 | So now in terms of sort of understanding

00:46:52.520 | what the distributor signal means,

00:46:54.680 | it's gotta be embedded in the context

00:46:56.300 | of what you tried to do or what your other sensory systems

00:47:01.160 | are telling you about what's happening right now.

00:47:02.680 | - I see, so it's very interesting, but it's not conscious.

00:47:06.600 | Or at least if it's conscious, it's not conscious,

00:47:09.400 | it's definitely very fast, right?

00:47:11.520 | The moment that plane starts moving,

00:47:12.840 | I know that I didn't get up out of my chair

00:47:14.480 | and run forward.

00:47:15.320 | - Right.

00:47:16.160 | - But I'm not really thinking about

00:47:17.280 | getting up out of my chair.

00:47:18.580 | I just know.

00:47:19.420 | - I guess the way I think about it

00:47:20.440 | is that the nervous system is "aware" at many levels.

00:47:25.440 | When it gets all the way up to the cortex

00:47:29.000 | and we're thinking about it,

00:47:30.420 | you're talking about it, that's cortical.

00:47:34.140 | But the lower levels of the brain

00:47:37.380 | that don't require you to actually actively think about it,

00:47:40.400 | they're just doing their thing,

00:47:42.320 | are also made aware, right?

00:47:44.040 | A lot of this is happening under the surface

00:47:45.880 | of what you're thinking.

00:47:47.080 | These are reflexes.

00:47:48.760 | - Okay, so we've got this gravity sensing system.

00:47:52.440 | - Right.

00:47:53.280 | - I'm nodding for those that are listening

00:47:57.100 | for a yes movement of the head,

00:47:59.180 | a no movement of the head

00:48:00.360 | or the tilting of the head from side to side.

00:48:02.720 | - Right.

00:48:03.560 | - And then you said that knowledge about

00:48:04.840 | whether or not activation of that system

00:48:07.400 | comes from my own movements

00:48:08.960 | or something acting upon me, like the plane moving,

00:48:12.520 | has to be combined with other signals.

00:48:15.640 | And so how is the visual information

00:48:19.600 | or information about the visual world

00:48:21.040 | combined with balance information?

00:48:22.880 | - Right.

00:48:23.720 | So, yeah, I mean, I guess maybe the best way

00:48:26.560 | to think about how these two systems work together

00:48:29.940 | is to think about what happens

00:48:31.060 | when you suddenly rotate your head to the left.

00:48:34.020 | When you suddenly rotate your head to the left,

00:48:36.620 | your eyes are actually rotating to the right automatically.

00:48:40.820 | You do this in complete darkness.

00:48:43.260 | If you had an infrared camera and watched yourself

00:48:48.100 | in complete darkness, you can't see anything.

00:48:49.780 | Rotating your head to the left,

00:48:50.780 | your eyes would rotate to the right.

00:48:52.460 | That's your vestibular system saying,

00:48:56.340 | I'm gonna try to compensate for the head rotation

00:49:00.960 | so my eyes are still looking in the same place.

00:49:04.160 | Why is that useful?

00:49:05.240 | Well, if it's always doing that,

00:49:08.400 | then the image of the world on your retina

00:49:10.240 | will be pretty stable most of the time.

00:49:12.800 | And that actually helps vision.

00:49:14.800 | - Have they built this into cameras for image stabilization?

00:49:18.280 | 'Cause when I move, when I take a picture with my phone,

00:49:20.400 | it's blurry, it's not clear.

00:49:22.460 | - Well, actually, you might wanna get a better phone

00:49:25.600 | because now what they have is software in the better apps

00:49:29.680 | that will do a kind of image stabilization post hoc

00:49:32.640 | by doing a registration of the images

00:49:34.480 | that are bouncing around.

00:49:35.760 | They say the edge of the house was here,

00:49:38.240 | so let's get that aligned at each of your images.

00:49:40.580 | So you may not be aware if you're using a good new phone

00:49:44.760 | that if you walk around a landscape and hold your phone,

00:49:49.760 | that there's all this image stabilization going on.

00:49:52.980 | But it's built into standard cinematic technology now

00:49:57.980 | because if you tried to do a handheld camera,

00:50:00.200 | things would be bouncing around, things would be unwatchable.

00:50:02.800 | You wouldn't be able to really understand

00:50:04.160 | what's going on in the scene.

00:50:05.560 | So the brain works really hard

00:50:08.720 | to mostly stabilize the image of the world on your retina.

00:50:12.200 | Of course, you're moving through the world,

00:50:13.500 | so you can't stabilize everything.

00:50:14.880 | But the more you can stabilize most of the time,

00:50:17.740 | the better you can see.

00:50:19.060 | And that's why when we're scanning a scene,

00:50:22.840 | looking around at things,

00:50:24.600 | we're making very rapid eye movements

00:50:26.840 | for very short periods of time, and then we just rest.

00:50:30.440 | But we're not the only ones that do that.

00:50:31.940 | If you ever watch a hummingbird,

00:50:33.120 | it does exactly the same thing at a feeder, right?

00:50:35.540 | But it's with its body.

00:50:37.040 | It's gonna make a quick movement,

00:50:38.680 | and then it's gonna be stable.

00:50:41.460 | And when you watch a pigeon walking on the sidewalk,

00:50:44.520 | it does this funny head bobbing thing.

00:50:46.160 | But what it's really doing is racking its head back

00:50:48.820 | on its neck while its body goes forward

00:50:51.260 | so that the image of the visual world stays static.

00:50:54.380 | Is that why they're doing it?

00:50:55.860 | Yes.

00:50:56.820 | And you've seen the funny chicken videos on YouTube, right?

00:50:59.540 | You take a chicken, move it up and down,

00:51:01.060 | the head stays in one place.

00:51:02.140 | It's all the same thing.

00:51:03.700 | All of these animals are trying hard

00:51:06.200 | to keep the image of the world stable on their retina

00:51:08.820 | as much of the time as they possibly can.

00:51:10.880 | And then when they've got to move, make it fast,

00:51:13.340 | make it quick, and then stabilize again.

00:51:15.460 | That's why the pigeons have their head back?

00:51:16.900 | It is, yeah.

00:51:18.060 | Wow.

00:51:19.340 | Yeah.

00:51:20.180 | I just need to pause there for a second and digest that.

00:51:23.200 | Amazing.

00:51:24.040 | In case people aren't, well,

00:51:28.440 | there's no reason why people would know

00:51:30.060 | what we're doing here,

00:51:30.900 | but essentially what we're doing is we're building up

00:51:32.740 | from sensory, you know, light onto the eye, color,

00:51:36.780 | to what the brain does with that,

00:51:39.060 | the integration of that, you know,

00:51:40.520 | circadian clock, melatonin, et cetera.

00:51:42.100 | And now what we're doing is we're talking about

00:51:43.460 | multi-sensory or multimodal,

00:51:45.800 | combining one sense vision with another sense balance.

00:51:50.560 | And it turns out that pigeons know more about this

00:51:53.600 | than I do because pigeons know to keep their head back

00:51:56.240 | as they walk forward.

00:51:57.960 | All right, so that gets us to this issue of motion sickness.

00:52:02.520 | And you don't have to go out on a boat.

00:52:05.680 | Anytime I go to New York,

00:52:06.900 | I sit in an Uber or in a cab in the back.

00:52:09.440 | And if I'm looking at my phone while the car is driving,

00:52:13.220 | I feel nauseous by time I arrive at my destination.

00:52:17.020 | I always try and look out the front of the windshield

00:52:19.380 | because I'm told that helps,

00:52:20.620 | but it's a little tiny window.

00:52:22.800 | And I end up feeling slightly less sick if I do that.

00:52:26.960 | So what's going on with the vision and the balance system

00:52:31.960 | that causes a kind of a nausea?

00:52:34.300 | And actually, if I keep talking about this,

00:52:35.820 | I probably will get sick.

00:52:37.220 | I don't throw up easily,

00:52:38.300 | but for some reason, motion sickness is a real thing for me.

00:52:42.620 | It's a problem for a lot of people.

00:52:44.340 | I mean, I think the fundamental problem typically

00:52:47.120 | when you get motion sick

00:52:48.240 | is what they call visual vestibular conflict.

00:52:52.760 | That is, you have two sensory systems

00:52:55.360 | that are talking to your brain

00:52:56.480 | about how you're moving through the world.

00:52:58.520 | And as long as they agree, you're fine.

00:53:02.440 | So if you're driving,

00:53:04.320 | your body senses that you're moving forward.

00:53:07.160 | Your vestibular systems

00:53:08.800 | is picking up this acceleration of the car.

00:53:12.480 | And your visual system is seeing the consequences

00:53:14.900 | of forward motion in the sweeping of the scene past you.

00:53:19.360 | Everything is honky-dory, right?

00:53:20.860 | No problem.

00:53:22.140 | But when you are headed forward,

00:53:25.580 | but you're looking at your cell phone,

00:53:26.880 | what is your retina seeing?

00:53:28.000 | Your retina is seeing the stable image of the screen.

00:53:30.280 | There's absolutely no motion in that screen.

00:53:33.560 | Or the motion is, or some other motion,

00:53:35.740 | like a movie or, yeah. Or it's a motion

00:53:36.580 | you're watching if you're playing a game,

00:53:37.940 | or you're watching a video, a football game.

00:53:40.400 | The motion is uncoupled with what's actually happening

00:53:43.360 | to your body.

00:53:44.300 | Your brain doesn't like that.

00:53:45.560 | Your brain likes everything to be aligned.

00:53:48.280 | And if it's not, it's going to complain to you.

00:53:50.580 | By making me feel nauseous.

00:53:51.420 | By making you feel nauseous,

00:53:52.420 | and maybe you'll change your behavior.

00:53:53.880 | So you're getting-

00:53:54.760 | I'm getting punished.

00:53:55.840 | Yeah, for setting it up

00:53:57.980 | so your signal's not going to flick, right.

00:53:59.740 | By the vestibular-

00:54:01.120 | You'll learn.

00:54:01.940 | Visuals.

00:54:02.780 | In time. I love it.

00:54:06.400 | I love the idea of reward signals.

00:54:08.560 | And we've done a lot of discussion

00:54:10.280 | about this on this podcast of things like dopamine reward

00:54:12.840 | and things, but also punishment signals.

00:54:14.560 | And I love this example.

00:54:17.120 | Well, maybe marching a little bit further

00:54:20.440 | along this pathway, visual input is combined

00:54:24.240 | with balance input.

00:54:25.900 | Where does that occur?

00:54:28.320 | And maybe, 'cause I have some hint of where it occurs,

00:54:32.160 | you could tell us a little bit about this

00:54:34.200 | kind of mysterious little mini brain

00:54:37.560 | that they call the cerebellum.

00:54:38.600 | Cerebellum, yeah.

00:54:40.100 | So, you know, the way I tried to describe the cerebellum

00:54:43.760 | to my students is that it serves sort of like

00:54:48.760 | the air traffic control system functions in air travel.

00:54:53.320 | So that it's a system that's very complicated

00:54:57.560 | and it's really dependent on great information.

00:55:01.060 | So it's taking in the information

00:55:02.620 | about everything that's happening everywhere,

00:55:04.620 | not only through your sensory systems,

00:55:07.640 | but it's listening in to all the little centers elsewhere

00:55:10.520 | in your brain that are computing

00:55:11.680 | what you're gonna be doing next and so forth.

00:55:13.580 | So it's just ravenous for that kind of information.

00:55:15.780 | So it really is like a little mini brain.

00:55:17.700 | It is, it's got access to all those signals.

00:55:21.820 | And it really has an important role

00:55:25.460 | in coordinating and shaping movements.

00:55:29.880 | But, you know, if you suddenly eliminated

00:55:33.680 | the air traffic control system,

00:55:36.460 | planes could still take off and land,

00:55:38.940 | but you might have some unhappy accidents in the process.

00:55:43.940 | So the cerebellum is kind of like that.

00:55:45.860 | It's not that you would be paralyzed

00:55:48.160 | if your cerebellum was gone

00:55:49.900 | because you still have motor neurons.

00:55:51.360 | You still have ways to talk to your muscles.

00:55:54.100 | You still have reflex centers.

00:55:56.420 | And it's not like you would have any sensory loss

00:55:59.800 | because you still have your cortex

00:56:01.480 | getting all of those beautiful signals

00:56:03.020 | that you can think about.

00:56:04.980 | But you wouldn't be coordinating things so well anymore.

00:56:09.380 | The timing between input and output might be off.

00:56:12.860 | Or if you were trying to practice a new athletic move,

00:56:16.660 | like an overhead serve in tennis,

00:56:19.260 | you'd be just terrible at learning.

00:56:21.380 | But all of the sequences of muscle movements

00:56:25.220 | and the feedback from your sensory apparatus

00:56:27.320 | that would let you really hit that ball

00:56:29.360 | exactly where you wanted to after the nth rep, right?

00:56:32.700 | You know, the thousandth rep or something,

00:56:34.940 | you get much better at it.

00:56:36.100 | So the cerebellum's all involved in things like

00:56:38.500 | motor learning and refining the precisions of movement

00:56:44.380 | so that they get you where you want to go.

00:56:47.220 | If you reach for a glass of champagne

00:56:49.940 | that you don't knock it over or stop short.

00:56:52.200 | You know, that's what it's good at.

00:56:54.580 | People who have selective damage to the cerebellum.

00:56:57.320 | Absolutely.

00:56:58.160 | And what I come familiar with, well, Korsakoff's

00:57:03.160 | is different, right?

00:57:04.440 | Isn't that a B vitamin deficiency in chronic alcoholics?

00:57:07.560 | Right.

00:57:08.400 | And they have a, they tend to walk kind of bow-legged

00:57:10.120 | and they can't coordinate their movements.

00:57:11.860 | Is that, that has some, that-

00:57:13.480 | Not sure about the cerebellar-

00:57:15.300 | But also cerebellum.

00:57:16.440 | I'm not sure about the cerebellar involvement there,

00:57:19.060 | but you know, the typical thing would be

00:57:22.000 | a patient who has a cerebellar stroke or a tumor,

00:57:26.680 | for example, might be not that steady on their feet.

00:57:31.680 | You know, if the, you know, dynamics of the situation

00:57:37.340 | is standing on a street car with no pole to hold onto,

00:57:40.840 | they might not be as good at adjusting

00:57:43.000 | all of the little movements of the car.

00:57:45.360 | You know, there's a kind of tremor that can occur

00:57:49.340 | as they're reaching for things

00:57:50.940 | because they reach a little too far

00:57:53.560 | and then they over-correct and come back.

00:57:56.260 | Things like that.

00:57:57.500 | So it's very common neurological phenomenon, actually.

00:58:02.500 | Cerebellar ataxia is what the neurologists call it.

00:58:07.260 | And it can happen not just with cerebellar damage,

00:58:09.140 | but damage to the tracts that feed the information

00:58:11.420 | into the cerebellum.

00:58:12.260 | Right, just deprive the structure.

00:58:13.340 | Exactly, or output from the cerebellum.

00:58:15.500 | And so the cerebellum is where a lot of visual

00:58:17.860 | and balance information is combined.

00:58:19.900 | In a very key place in the cerebellum,

00:58:21.960 | which is, it's really one of the oldest parts

00:58:26.320 | in terms of evolution.

00:58:27.160 | Talking about the flocculus.

00:58:27.980 | The flocculus, right.

00:58:28.820 | This is a, it's a critical place in the cerebellum

00:58:32.200 | where visual and vestibular information comes together

00:58:35.160 | for according just the kinds of movements

00:58:37.300 | we were talking about.

00:58:38.320 | This image stabilizing network, it's all happening there.

00:58:41.920 | And there's learning happening there as well.

00:58:43.660 | So that if your vestibular apparatus

00:58:45.960 | is a little bit damaged somehow,

00:58:48.880 | your visual system is actually talking to your cerebellum

00:58:52.820 | saying there's a problem here, there's an error.

00:58:55.860 | And your cerebellum is learning to do better

00:58:58.840 | by increasing the output of the vestibular system

00:59:01.260 | to compensate for whatever that loss was.

00:59:03.680 | So it's a little error correction system.

00:59:05.340 | That's sort of typical of a cerebellar function.

00:59:08.400 | And it can happen in many, many different domains.

00:59:10.180 | This is just one of the domains

00:59:11.900 | of sensory motor integration that takes place there.

00:59:15.300 | So I should stay off my phone in the Ubers.

00:59:18.700 | If I'm on a boat, I should essentially look

00:59:22.300 | and as much as possible act as if I'm driving the machine.

00:59:25.760 | - Right.

00:59:26.600 | - That'd be weird if I was in the passenger seat

00:59:28.180 | pretending I was driving the machine,

00:59:29.480 | but I do always feel better

00:59:30.660 | if I'm sitting in the front seat passenger.

00:59:32.700 | - Right, the more of the visual world that you can see

00:59:35.780 | as if you were actually the one doing the motion,

00:59:38.380 | I would think.

00:59:39.420 | - Let's stay in the inner ear for a minute

00:59:41.020 | as we continue to march around the nervous system.

00:59:44.400 | When you take off in the plane or when you land

00:59:48.500 | or sometimes in the middle of the air,

00:59:50.060 | your ears get clogged, or at least my ears get clogged.

00:59:53.260 | That's because of pressure buildup

00:59:56.300 | in the various tubes of the inner ear, et cetera.

00:59:59.340 | We'll get into this.

01:00:00.220 | But years ago, our good friend, Harvey Carton,

01:00:05.100 | who's another world-class neuroanatomist,

01:00:08.220 | gave a lecture and it talked about

01:00:12.140 | how plugging your nose and blowing out

01:00:14.420 | versus plugging your nose and sucking in

01:00:17.420 | can, should be done at different times

01:00:20.100 | depending on whether or not you're taking off or landing.

01:00:23.600 | And I always see people try to un-pop their ears.

01:00:26.920 | And when you do scuba diving,

01:00:28.340 | you learn how to do this without necessarily,

01:00:30.300 | I can do it by just kind of moving my jaw now

01:00:32.860 | 'cause I've done a little bit of diving.

01:00:35.480 | But what's the story there?

01:00:37.700 | We don't have to get into all the differences

01:00:39.740 | in atmospheric pressure, et cetera.

01:00:41.140 | But if I'm taking off and my ears are plugged,

01:00:44.260 | or I've recently ascended, plane took off,

01:00:46.460 | my ears are plugged, do I plug my nose and blow out

01:00:48.540 | or do I plug my nose and suck in?

01:00:49.940 | - Right, so the basic idea is that if your ears feel bad

01:00:54.940 | because you're going into an area of higher pressure,

01:00:58.620 | so if they pressurize the cabin more than the pressure

01:01:01.960 | that you have on the surface of the planet,

01:01:03.760 | your eardrums will be bending in and they don't like that.

01:01:07.020 | If you push them more, they'll hurt even more.

01:01:08.640 | - That's a good description that the pressure goes up,

01:01:11.620 | then they're gonna bend in.

01:01:12.580 | - Bend in, and then the reverse would be true

01:01:14.660 | if you go into an area of low pressure.

01:01:16.620 | So if you started to drive up the mountainside,

01:01:20.140 | the pressure is getting lower and lower outside.

01:01:22.140 | Now the air behind your eardrum is blooming out, right?

01:01:26.860 | So it's just a question of are you trying to get

01:01:28.680 | more pressure or less pressure behind the eardrum?

01:01:31.460 | And there's a little tube that does that

01:01:32.780 | and comes down into the back of your throat there.

01:01:35.540 | And if you force pressure up that tube,

01:01:37.580 | you're gonna be putting more air pressure

01:01:39.500 | into the compartment.

01:01:41.100 | - To counter it.

01:01:42.260 | - If it's not enough, and if you're sucking,

01:01:45.500 | you're going the other way.

01:01:46.460 | In reality, I think as long as you open the passageway,

01:01:49.080 | I think the pressure differential

01:01:50.780 | is gonna solve your problem.

01:01:52.220 | So I think you could actually blow in

01:01:54.220 | when you're not, quote, supposed to.

01:01:55.960 | - Okay, so you could just hold your nose and blow air out

01:02:00.180 | or hold your nose and suck in the effect.

01:02:04.100 | Either way is fine.

01:02:05.020 | - I think so.

01:02:05.860 | - Excellent, I just won $100 from Harvey Carton.

01:02:09.100 | Thank you very much.

01:02:10.500 | Harvey and I used to teach in our anatomy together,

01:02:12.820 | and I'll say, I don't think it matters,

01:02:14.180 | but thank you, I'll split that with you.

01:02:16.820 | This is important stuff, but it's true.

01:02:21.940 | You hear this, so it doesn't matter either way.

01:02:25.420 | - I'm no expert in this area.

01:02:27.300 | Don't quote me.

01:02:28.140 | - He's not gonna, well, I'm going to quote you.

01:02:30.260 | Okay, so we've talked about the inner ear

01:02:32.140 | and we've talked about the cerebellum.

01:02:33.960 | I want to talk about an area of the brain

01:02:35.740 | that is rarely discussed, which is the midbrain.

01:02:40.160 | And for those that don't know,

01:02:42.820 | the midbrain is an area beneath the cortex.

01:02:45.640 | I guess we never really defined cortex.

01:02:47.180 | It was just kind of the outer layers

01:02:48.500 | or are the outer layers of the,

01:02:51.800 | at least mammalian brain or human brain.

01:02:54.500 | But the midbrain is super interesting

01:02:57.140 | because it controls a lot of unconscious stuff,

01:03:02.140 | reflexes, et cetera.

01:03:03.860 | And then there's this phenomenon even called blindsight.

01:03:07.900 | So could you please tell us about the midbrain,

01:03:11.320 | about what it does and what in the world is blindsight?

01:03:15.660 | - Yeah, so this is a, there's a lot of pieces there.

01:03:19.520 | I think the first thing to say is

01:03:20.920 | if you imagine the nervous system in your mind's eye,

01:03:25.280 | you see this big honking brain

01:03:27.080 | and then there's this little wand that dangles down

01:03:32.080 | into your vertebral column, the spinal cord,

01:03:34.540 | and that's kind of your visual impression.

01:03:37.760 | What you have to imagine is starting in the spinal cord

01:03:40.080 | and working your way up into this big, magnificent brain.

01:03:42.700 | And what you would do as you enter the skull

01:03:46.400 | is get into a little place

01:03:47.920 | where the spinal cord kind of thickens out.

01:03:50.160 | It still has that sort of long, skinny, trunk-like feeling.

01:03:54.800 | - Sort of like a paddle or a spoon shape.

01:03:56.660 | - Right, it starts to spread out a little bit,

01:03:58.520 | and that's 'cause your evolution has packed

01:04:00.480 | more interesting goodies in there

01:04:02.040 | for processing information and generating movement.

01:04:05.300 | So beyond that is this tween brain

01:04:09.740 | we were talking about, this linker brain.

01:04:12.180 | Diencephalon really means the between brain.

01:04:14.820 | - Oh, I thought you said tween.

01:04:16.020 | - Well, it is, yes.

01:04:16.860 | - No, no, between, between, I'm sorry, I thought you said tween.

01:04:19.740 | - Yeah, it's the between,

01:04:20.820 | it's the between brain is what the name means.

01:04:24.280 | It's the linker from the spinal cord in the periphery

01:04:27.740 | up to these grand centers of the cortex.

01:04:30.380 | But this midbrain you're talking about

01:04:33.300 | is the last bit of this enlarged sort of spinal cordy thing

01:04:37.240 | in your skull, which is really the brainstem

01:04:39.500 | is what we call it.

01:04:40.940 | The last bit of that before you get to this relay

01:04:43.860 | up to the cortex is the midbrain.

01:04:46.940 | And there's a really important visual center there.

01:04:49.560 | It's called the superior colliculus.

01:04:51.480 | There's a similar center in the brains

01:04:54.540 | of other vertebrate animals, a frog, for example,

01:04:57.440 | or a lizard would have this.

01:04:59.020 | It's called the optic tectum there.

01:05:01.380 | But it's a center that in these non-mammalian vertebrates

01:05:06.380 | is really the main visual center.

01:05:10.420 | They don't really have what we would call a visual cortex,

01:05:13.900 | although there's something sort of like that.

01:05:16.040 | But this is where most of the action is

01:05:17.540 | in terms of interpreting visual input

01:05:19.560 | and organizing behavior around that.

01:05:22.480 | You can sort of think about this region of the brainstem

01:05:27.420 | as a reflex center that can reorient the animal's gaze

01:05:32.420 | or body, or maybe even attention to particular regions

01:05:37.740 | of space out there around the animal.

01:05:41.580 | And that could be for all kinds of reasons.

01:05:43.540 | I mean, it might be a predator just showed up

01:05:45.780 | in one corner of the forest and you pick that up

01:05:48.520 | and you're trying to avoid it.

01:05:50.000 | Or just any movement.

01:05:51.020 | Many movement, right?

01:05:52.420 | It might be that suddenly something splats on the page

01:05:57.300 | when you're reading a novel

01:05:58.540 | and your eye reflexly looks at it.

01:06:02.020 | You don't have to think about that.

01:06:03.180 | That's a reflex.

01:06:04.140 | - What if you throw me a ball, but I'm not expecting it,

01:06:07.260 | and I just reach up and try and grab it, catch it or not?

01:06:10.700 | Is that handled by the midbrain?

01:06:12.260 | - Well, that's probably not the midbrain,

01:06:14.920 | although, I mean, by itself,

01:06:17.080 | because it's going to involve all these limb movements,

01:06:19.660 | this movement of your arm and body.

01:06:21.480 | - What about ducking if something's suddenly

01:06:24.780 | thrown at my head?

01:06:25.620 | - Yeah, sure, right.

01:06:26.460 | Brains like that will certainly have a brainstem component,

01:06:29.020 | a midbrain component.

01:06:30.460 | You know, something looms and you duck.

01:06:32.420 | It may not be the superior colliculus we're talking about.

01:06:36.840 | Now, it might be another part of the visual midbrain,

01:06:39.140 | but these are centers that emerged early

01:06:41.700 | in the evolution of brains like ours

01:06:43.900 | to handle complicated visual events

01:06:46.740 | that have significance for the animal.

01:06:48.900 | In terms of space, where is it in space?

01:06:51.620 | And in fact, this same center actually gets input

01:06:54.340 | from all kinds of other sensory systems

01:06:56.200 | that take information from the external world,

01:06:58.900 | from particular locations,

01:07:00.580 | and where you might want to either avoid or approach things

01:07:03.540 | according to their significance to you.

01:07:05.660 | So you get input from the touch system.

01:07:08.700 | You get input from the auditory system.

01:07:11.540 | I worked for a while in rattlesnakes.

01:07:13.500 | They get input from a part of their warm sensors

01:07:17.740 | on their face.

01:07:18.580 | They're in these little pits on the face.

01:07:20.580 | - They used to work on baby rattlesnakes, right?

01:07:22.220 | - Well, they were adults, actually.

01:07:23.980 | - Oh, I wasn't trying to diminish the danger.

01:07:25.660 | I thought for some reason they were little ones.

01:07:27.660 | Why in the world would you work on rattlesnakes?

01:07:30.280 | - Well, because they have a version

01:07:33.780 | of an extra receptive sensory system.

01:07:35.940 | That is, they're looking out into the world

01:07:39.020 | using a completely different set of sensors.

01:07:41.100 | They're using the same sensors

01:07:42.300 | that would feel the warmth on your face

01:07:44.000 | if you stood in front of a bonfire,

01:07:45.880 | except evolution has given them

01:07:48.420 | this very nice specialized system

01:07:49.960 | that lets them image where the heat's coming from.

01:07:52.220 | You can sort of do that anyway, right?

01:07:53.900 | If you walk around the fire,

01:07:56.220 | you can feel where the fire is

01:07:57.900 | from the heat hitting your face.

01:08:00.460 | - Is that the primary way in which they detect prey?

01:08:04.300 | - It's one of the major ways.

01:08:06.660 | And in fact, they use vision as well.

01:08:09.100 | And they bring these two systems together

01:08:11.100 | in the same place, in this tectum region,

01:08:13.620 | this brain stem, midbrain region.

01:08:15.460 | - What's all the tongue jutting about when the snakes?

01:08:17.580 | - That I don't know.

01:08:19.080 | That may be olfactory.

01:08:20.380 | There may be-

01:08:21.220 | - They're sniffing the air with their tongue.

01:08:22.220 | - Yeah, there may be a-

01:08:23.900 | - Earlier in our drive,

01:08:24.780 | you told me that flies actually

01:08:26.300 | taste things with their feet.

01:08:27.700 | - They do, yeah.

01:08:28.540 | - That's so weird.

01:08:29.380 | - Yeah, they have taste receptors

01:08:31.060 | in lots of funny places.

01:08:32.540 | - I want to pause here just for one second

01:08:34.920 | before we get back into the midbrain.

01:08:36.500 | I think what's so interesting in all seriousness

01:08:40.120 | about taste receptors on feet, heat sensors,

01:08:45.040 | tongues jutting out of snakes,

01:08:47.660 | and vision and all this integration

01:08:49.360 | is that it really speaks to the fact

01:08:51.980 | that all these sensory neurons

01:08:55.020 | are trying to gather information

01:08:57.820 | and stuff it into a system

01:08:59.720 | that can make meaningful decisions and actions.

01:09:03.260 | And that it really doesn't matter

01:09:04.620 | whether or not it's coming from eyes or ears or nose

01:09:06.680 | or bottoms of feet,

01:09:08.520 | because in the end, it's just electricity flowing in.

01:09:11.460 | And so it sounds like it's placed on each animal.

01:09:14.860 | It always feels weird to call fly an animal,

01:09:17.300 | but they are creatures, they are animals.

01:09:21.380 | It's placed in different locations on different animals,

01:09:23.740 | depending on the particular needs of that animal.

01:09:26.620 | - Right, but how much more powerful

01:09:29.140 | if the nervous systems can also cross-correlate

01:09:32.820 | across sensory systems?

01:09:34.920 | So if you've got a weak signal from one sensory system,

01:09:38.100 | you're not quite sure there's something there,

01:09:40.320 | and a weak signal from another sensory system

01:09:42.980 | that's telling you the same locations

01:09:44.780 | is a little bit interesting.

01:09:46.320 | There might be something there.

01:09:47.740 | If you've got those two together, you've got corroboration.

01:09:50.500 | Your brain now says it's much more likely

01:09:53.100 | that that's gonna be something worth paying attention to.

01:09:56.860 | - Right, so maybe I'm feeling some heat

01:09:59.540 | on one side of my face,

01:10:01.200 | and I also smell something baking in the oven.

01:10:05.820 | So now neither is particularly strong,

01:10:08.180 | but as you said, there's some corroboration,

01:10:10.380 | and that corroboration is occurring in the midbrain.

01:10:12.460 | - Right, and then if you throw things into conflict,

01:10:15.960 | now the brain is confused,

01:10:17.300 | and that may be where your emotion sickness comes from.

01:10:20.000 | So it's great to have, as a brain,

01:10:22.980 | it's great to have as many sources of information

01:10:24.740 | as you can have, just like if you're a spy or a journalist.

01:10:29.400 | You don't want as much information

01:10:30.580 | as you can get about what's out there,

01:10:33.040 | but if things conflict, that's problematic, right?

01:10:35.640 | Your sources are giving you different information

01:10:37.300 | about what's going on.

01:10:38.480 | Now you've got a problem on your hands.

01:10:39.820 | What do you publish?

01:10:40.820 | - The midbrain is so fascinating.

01:10:43.520 | I don't wanna eject us from the midbrain

01:10:46.300 | and go back to the vestibular system,

01:10:47.820 | but I do have a question that I forgot to ask

01:10:49.640 | about the vestibular system,

01:10:50.740 | which is why is it that for many people, including me,

01:10:53.780 | there's, despite my motion sickness in cabs,

01:10:56.420 | that there's a sense of pleasure in moving through space

01:11:00.820 | and getting tilted relative to the gravitational pull

01:11:03.380 | of the earth?

01:11:04.220 | For me growing up, it was skateboarding,

01:11:05.680 | but people like to corner in cars, corner on bikes.

01:11:08.800 | It may be, for some people, it's done running or dance,

01:11:13.340 | but what is it about moving through space

01:11:16.300 | and getting tilted, a lot of surfers around here,

01:11:19.680 | getting tilted that can tap

01:11:23.220 | into some of the pleasure centers?

01:11:25.320 | Do we have any idea why that would feel good?

01:11:26.940 | - I have no clue.

01:11:28.620 | - Is there dopaminergic input to this system?

01:11:31.460 | - Well, the dopaminergic system gets a lot of places.

01:11:36.220 | It's pretty much, to some extent,

01:11:40.300 | everywhere in the cortex,

01:11:41.340 | a lot more in the frontal lobe, of course,

01:11:43.500 | but that's just for starters.

01:11:45.880 | I mean, there's basically dopaminergic innervation

01:11:47.880 | most places in the central nervous system,

01:11:50.280 | so there's the potential for dopaminergic involvement,

01:11:52.700 | but I really have no clue about the tilting phenomenon.

01:11:55.200 | I mean-

01:11:56.040 | - People pay money to go on roller coasters.

01:11:58.000 | - Right.

01:11:58.840 | Well, I think that may be as much about the thrill

01:12:00.640 | as anything else. - Sure.

01:12:01.480 | And falling is, the falling reflex is very robust

01:12:04.360 | in all of us.

01:12:05.200 | When the visual world's going up very fast,

01:12:07.160 | it usually means that we're falling.

01:12:08.420 | - Right, right.

01:12:09.260 | - But in some people like that, some people don't.

01:12:10.740 | - Right, and kids tolerate a lot more

01:12:14.640 | sort of vestibular craziness spinning around

01:12:16.720 | until they've dropped.

01:12:18.460 | - Well, I've friends, it always, you know,

01:12:21.420 | worries me a little bit that they throw their kids.

01:12:23.600 | I'm not recommending anyone do this.

01:12:25.000 | When they're little kids, you know,

01:12:25.860 | like throwing the kids really far back and forth.

01:12:29.000 | Some kids seem to love it.

01:12:30.420 | - Yeah.

01:12:31.260 | Yeah, our son loved being shaken up and down

01:12:33.920 | very, very vigorously.

01:12:37.200 | That's the only thing that would calm him down sometimes.

01:12:39.280 | - Interesting.

01:12:40.280 | Yeah, so I'm guessing.

01:12:41.360 | We can guess that maybe there's some activation

01:12:46.360 | of the reward systems from moving through space.

01:12:50.200 | - Well, I mean, if you think about, you know,

01:12:51.860 | how rewarding it is to be able to move through space

01:12:54.820 | and how unhappy people are who are used to that,

01:12:57.920 | who suddenly aren't able to do that,

01:12:59.680 | there is a sense of agency, right?

01:13:01.740 | If you can choose to move through the world and to tilt,

01:13:05.240 | that's not only you're moving through the world,

01:13:06.800 | but you're doing it with a certain amount of finesse.

01:13:08.440 | Maybe that's what it is.

01:13:09.360 | You can feel like you're the master of your own movement

01:13:13.240 | in a way that you wouldn't if you were going straight.

01:13:15.120 | I'm just blowing smoke here, right?

01:13:17.160 | - Yeah, well, we can speculate.

01:13:18.420 | That's fine.

01:13:19.260 | I couldn't help but ask the question.

01:13:21.400 | Okay, so if we move ourselves, pun intended,

01:13:25.000 | back into the midbrain.

01:13:27.220 | The midbrain's combining all these different signals

01:13:29.080 | for reflexive action.

01:13:31.120 | At what point does this become deliberate action?

01:13:34.880 | Because if I look at something I want

01:13:36.740 | and I want to pursue it,

01:13:37.580 | I'm going to go toward it, and many times,

01:13:41.060 | that's a deliberate decision.

01:13:42.320 | - Right, so this gets very slippery, I think,

01:13:46.660 | because what you have to try to imagine

01:13:49.260 | is all these different parts of the brain

01:13:51.000 | working on the problem of staying alive

01:13:53.940 | and surviving in the world.

01:13:58.980 | They're working on the problem simultaneously,

01:14:01.080 | and there's not one right answer to how to do that.

01:14:06.260 | But one way to think about it is that

01:14:09.880 | you have high levels of your nervous system

01:14:11.760 | that are very well designed to override

01:14:16.100 | an otherwise automatic movement if it's inappropriate.

01:14:19.580 | So if you've imagined you've been invited to tea

01:14:22.320 | with the queen, and she hands you

01:14:25.120 | a very fancy wedge wood tea cup, very thin.

01:14:29.760 | - Wedge wood tea cup?

01:14:30.840 | - Yes, with very hot tea in it,

01:14:33.040 | and you're burning your hand,

01:14:34.100 | you probably will try to find a way to put that back down

01:14:36.960 | on the saucer rather than just dropping it on the floor

01:14:40.140 | because you're with the queen.

01:14:42.380 | You're trying to be appropriate to that.

01:14:45.520 | So you have ways of reining in automatic behaviors

01:14:49.380 | if they're going to be maladaptive,

01:14:51.160 | but you also want the reflex to work quickly

01:14:54.580 | if it's the only thing that's going to save you,

01:14:56.060 | the looming object coming at your head.

01:14:58.340 | You don't have time to think about that.

01:15:00.300 | So this is the interplay in these hierarchically

01:15:04.300 | organized centers of the nervous system.

01:15:06.100 | At the lowest level, you've got the automatic sensors

01:15:09.500 | and centers and reflex arcs that will keep you safe

01:15:14.500 | even if you don't have time to think about it.

01:15:16.740 | And then you've got the higher center saying,

01:15:18.740 | well, maybe we could do this as well,

01:15:20.640 | or maybe we shouldn't do that at all, right?

01:15:23.500 | So you have all of these different levels

01:15:25.700 | operating simultaneously,

01:15:27.540 | and you need bi-directional communication

01:15:30.620 | between high level cognitive centers,

01:15:34.620 | decision-making on the one hand,

01:15:37.740 | and these low level, very helpful reflexive centers,

01:15:40.300 | but they're a little bit rigid, a little hardwired,

01:15:43.460 | so they need some nuance.

01:15:44.540 | So both of these things are operating in tandem

01:15:47.380 | in real time, all the time in our brains.

01:15:49.860 | And sometimes we listen more to one than the other.

01:15:51.780 | You've heard people in sports talking about

01:15:55.060 | messing up at the plate 'cause they overthought it,

01:15:57.540 | thinking too hard about it.

01:15:59.020 | That's partly, you've already trained your cerebellum

01:16:01.900 | how to hit a fastball right down the middle.

01:16:04.980 | Right, and if you start looking for something new

01:16:08.100 | or different, you're gonna mess up your reflexive swing.

01:16:11.140 | Right, if you're trying to think about the physics

01:16:12.960 | of the ball as it's coming at you,

01:16:15.020 | you've already missed, right?

01:16:16.380 | 'Cause you're not using your,

01:16:18.780 | all those reps have built a kind of knowledge

01:16:22.260 | is what you wanna rely on when you don't have enough time

01:16:25.380 | to contemplate.

01:16:27.100 | - This is important and a great segue

01:16:30.300 | for what I'd like to discuss next,

01:16:32.960 | which is the basal ganglia,

01:16:35.900 | this really interesting area of the brain

01:16:38.220 | that's involved in GO-type commands and behaviors,

01:16:43.220 | instructing us to do things, and NO-GO,

01:16:46.460 | preventing us from doing things.

01:16:47.760 | Because so much of motor learning and skill execution

01:16:50.720 | and not saying the wrong thing,

01:16:53.520 | or sitting still in class when,

01:16:55.640 | or as you used with the "Tea with the Queen" example,

01:16:59.480 | feeling discomfort involves suppressing behavior,

01:17:03.900 | and sometimes it's activating behavior.

01:17:05.820 | A tremendous amount of online attention is devoted

01:17:07.880 | to trying to get people motivated.

01:17:11.360 | This isn't the main focus of our podcast.

01:17:13.320 | We touch on some of the underlying neural circuits

01:17:15.080 | of motivation, dopamine, and so forth.

01:17:17.400 | But so much of what people struggle with out there

01:17:20.840 | are elements around failure to pay attention,

01:17:25.840 | or challenges in paying attention,

01:17:28.300 | which is essentially like putting the blinders on,

01:17:30.660 | getting a soda straw view of the world

01:17:32.660 | and maintaining that for a bout of work

01:17:34.700 | or something of that sort,

01:17:35.940 | and trying to get into action.

01:17:38.900 | So of course, this is carried out by many neural circuits,

01:17:42.420 | not just the basal ganglia,

01:17:43.580 | but what are the basal ganglia

01:17:45.840 | and what are their primary roles

01:17:47.900 | in controlling go-type behavior and no-go-type behavior?

01:17:51.920 | - Yeah, so I mean, the basal ganglia are sitting deep

01:17:55.440 | in what you would call the forebrain,

01:17:57.920 | so the highest levels of the brain.

01:18:00.520 | They are sort of cousins to the cerebral cortex,

01:18:05.480 | which we talked about as sort of the highest level

01:18:07.440 | of your brain, the thing you're thinking with.

01:18:09.920 | - Cerebral cortex being the refined cousins,

01:18:11.880 | and then you've got the- - Right.

01:18:13.480 | - The brutes. - Yeah.

01:18:15.320 | - I mean, that's probably totally unfair, but the point-

01:18:18.600 | - I like the basal ganglia.

01:18:19.560 | I can relate to the brutish parts of the brain.

01:18:22.700 | Little bit of hypothalamus, little bit of basal ganglia, sure.

01:18:25.600 | - We need it all, we need it all.

01:18:27.820 | And this area of the brain has gotten a lot bigger

01:18:32.820 | as the cortex has gotten bigger,

01:18:35.280 | and it's deeply intertwined with cortical function.

01:18:39.320 | The cortex can't really do what it needs to do

01:18:41.520 | without the help of the basal ganglia and vice versa,

01:18:43.680 | so they're really intertwined.

01:18:46.560 | And in a way, you can think about this logically

01:18:51.600 | as saying if you have the ability to withhold behavior

01:18:55.440 | or to execute it, how do you decide which to do?

01:18:58.880 | Well, the cortex is gonna have to do that thinking for you.

01:19:01.720 | You have to be looking at all the contingencies

01:19:04.340 | of your situation to decide, is this a crazy move

01:19:07.680 | or is this a really smart investment right now or what?

01:19:11.480 | - I don't wanna go out for a run in the morning,

01:19:13.120 | I'm gonna make myself go out for a run,

01:19:15.280 | or I'm having a great time out on a run

01:19:17.840 | and I know I need to get back,

01:19:19.040 | but I kind of wanna go another mile.

01:19:20.720 | - I mean, another great example is that the marshmallow test

01:19:23.640 | for the little kids, they can get two marshmallows

01:19:25.860 | if they hold off just 30 seconds initially.

01:19:30.860 | They can have one right away,

01:19:32.560 | but if they can wait 30 seconds, they got two.

01:19:34.280 | So that's the no-go because their cortex is saying,

01:19:37.400 | I really like to have two more than having one,

01:19:41.000 | but they're not gonna get the two unless they can

01:19:43.920 | not reach for the one.

01:19:45.680 | So they've got to hold off the action

01:19:48.780 | and that has to result from a cognitive process.

01:19:53.360 | So the cortex is involved in this in a major way.

01:19:56.660 | - Yeah, as I recall in that experiment,

01:19:59.000 | the kids used a variety of tools to,

01:20:01.000 | some would distract themselves.

01:20:03.000 | I particularly related to the kid that would just

01:20:04.880 | put himself right next to the marshmallows

01:20:07.320 | and then some of the kids covered their eyes,

01:20:09.960 | some of them would count or sing.

01:20:11.840 | Yeah, so that's all very cortical, right?

01:20:13.280 | Coming up with a novel strategy,

01:20:15.080 | simple example that we're using here.

01:20:16.560 | But of course, this is at play anytime someone decides

01:20:19.520 | they wanna go watch a motivational speech or something,

01:20:21.880 | just, you know, a Steve Jobs commencement speech

01:20:24.260 | just to get motivated to engage in their day.

01:20:26.560 | - Should I take this new job?

01:20:28.360 | You know, it's got great benefits,

01:20:30.000 | but it's in a lousy part of the country.

01:20:32.080 | - Why do you think that some people have a harder time

01:20:36.080 | running these go no-go circuits

01:20:38.120 | and other people seem to have very low activation energy,

01:20:42.180 | we would say.

01:20:43.020 | They can just, you know, they have a task,

01:20:44.720 | they just lean into the task.

01:20:46.040 | Whereas some people getting into task completion

01:20:49.040 | or things of that sort is very challenging for them.

01:20:52.440 | - Yeah, I mean, I think it's really just another,

01:20:54.920 | it's a special case of a very general phenomenon,

01:20:57.280 | which is brains are complicated

01:21:00.280 | and brains we have are the result of genetics and experience

01:21:07.000 | and my genes are different from your genes

01:21:08.820 | and my experiences are different from your experiences.

01:21:11.000 | So the things that will be easy or hard for us

01:21:13.600 | won't necessarily be aligned.

01:21:15.040 | They might just happen to be just because they are.

01:21:18.640 | But the point is that, you know,

01:21:20.560 | you're dealt a certain set of cards,

01:21:23.940 | you have a certain set of genes, you are handed a brain.

01:21:27.640 | You don't choose your brain, it's handed to you.

01:21:30.280 | But then there's all this stuff you can do with it.

01:21:32.300 | You know, you can learn.

01:21:36.320 | You know, to have new skills or to act differently

01:21:39.880 | or to show more restraint,

01:21:41.240 | which is kind of relevant to what we're talking about here,

01:21:43.820 | or maybe show less restraint if your problem is

01:21:47.200 | you're so buttoned down, you never have any fun in life

01:21:49.200 | and you should loosen up a little bit.

01:21:50.840 | - Thank you, I appreciate the insult.

01:21:52.680 | Yeah.

01:21:53.520 | David's always encouraged me to have a little more fun.

01:21:58.120 | So basal ganglia are, they're kind of the disciplinarian

01:22:04.080 | or they're sort of the instructor conductor of sorts, right?

01:22:07.960 | Go, no go, you know, you be quiet, you start now.

01:22:11.440 | - I wish I knew more about the basal ganglia than I do.

01:22:14.920 | My sense is that it, you know, this system is key

01:22:19.320 | for implementing the plans that get cooked up in the cortex,

01:22:23.500 | but they also influence the plans

01:22:27.640 | that the cortex is dishing out

01:22:30.540 | because this is a major source of information

01:22:33.700 | to the cortex.

01:22:34.540 | So it becomes almost impossible to figure out

01:22:36.900 | where the computation begins and where it ends

01:22:40.640 | and who's doing what,

01:22:41.780 | because these things are all interacting

01:22:44.200 | in a complex network.

01:22:45.780 | And it's all of it, it's the whole network.

01:22:47.600 | It's not, you know, one is the leader

01:22:49.380 | and the other is the follower.

01:22:50.500 | - Right, of course.

01:22:51.340 | Yeah, these are, all the structures that we're discussing

01:22:53.320 | are working in parallel.

01:22:55.400 | - Right.

01:22:56.240 | - And there's a lot of changing crosstalk.

01:22:59.140 | I have this somewhat sick habit, David,

01:23:03.260 | every day I try and do 21 no-goes.

01:23:06.200 | So if I want to reach for my phone,

01:23:08.160 | I try and not do it just to see if I can prevent myself

01:23:12.080 | from engaging in that behavior, if it was reflexive.

01:23:15.520 | If it's something I want to do, deliberate choice,

01:23:18.520 | then I certainly allow myself to do it.

01:23:20.560 | I don't tend to have too much trouble with motivation,

01:23:22.880 | with go type functions, mostly because I'm so busy

01:23:25.880 | that I wish I had more time for more goes,

01:23:29.160 | but so to speak.

01:23:31.100 | But do you think these circuits have genuine plasticity

01:23:34.880 | in them?

01:23:35.720 | - Absolutely.

01:23:36.540 | I mean, everybody knows how they've learned over time

01:23:39.580 | to wait for the two marshmallows, right?

01:23:41.600 | You know, you don't have to have instant gratification

01:23:44.000 | all the time.

01:23:44.840 | You know, you're willing to do a job sometimes

01:23:48.380 | that isn't your favorite job

01:23:49.480 | because it comes with the territory

01:23:50.840 | and you want the salary that comes at the end of the week

01:23:52.800 | or the end of the month, right?

01:23:54.200 | So we can defer gratification.

01:23:57.240 | You know, we can choose not to say the thing

01:23:59.900 | that we know is going to inflame our partner

01:24:01.880 | and create a meltdown for the next week.

01:24:04.960 | You know, we learn this control,

01:24:07.920 | but I think these are skills like any other.

01:24:10.120 | You can get better at them if you practice them.

01:24:13.080 | So I think you're choosing to do that spontaneously

01:24:15.720 | as kind of a, you know, it's a mental practice.

01:24:18.020 | It's a discipline.

01:24:18.860 | It's a way of building a skill that you want to have.

01:24:21.760 | - Yeah, I find it to be something that when I engage

01:24:25.360 | in a no-go type situation,

01:24:29.860 | then the next time and the next time

01:24:32.040 | that I find myself about to move reflexively,

01:24:34.640 | there's a little gap in consciousness

01:24:36.320 | that I can make a decision

01:24:38.240 | whether or not this is really the best use of my time.

01:24:40.820 | Because I sometimes wonder

01:24:42.760 | whether or not all this business around attention,

01:24:45.440 | certainly there's the case of ADHD

01:24:46.960 | and clinical diagnosed ADHD,

01:24:48.680 | but all these, the issue around focus and attention

01:24:51.200 | is really that people just have not really learned

01:24:53.440 | how to short circuit a reflex.

01:24:56.260 | And so much of what makes us different than rattlesnakes

01:24:59.140 | or, well, actually they could be deliberate,

01:25:01.120 | but from the other animals

01:25:03.240 | and is our ability to suppress reflex.

01:25:06.400 | - Yeah, well, that's the cortex.

01:25:08.280 | I mean, or let's say the forebrain.

01:25:10.040 | Cortex and basal ganglia working together,

01:25:12.580 | sitting on top of this lizard brain

01:25:15.600 | that's giving you all these great adaptive reflexes

01:25:17.920 | that help you survive.

01:25:19.440 | You just hope you don't get the surprising case

01:25:22.400 | where the thing that your reflex is telling you

01:25:24.640 | is actually exactly the wrong thing

01:25:26.160 | and you make a mistake, right?

01:25:28.280 | - Right, so that's what the cortex is for.

01:25:29.900 | It's adding nuance and context and experience,

01:25:33.780 | past association, and in human beings,

01:25:36.740 | obviously learning from others through communication.

01:25:41.360 | - Well, I was, you went right to it

01:25:43.660 | and it was where I was gonna go.

01:25:45.700 | So let's talk about the cortex.

01:25:47.100 | We've worked our way up the so-called neuroaxis

01:25:49.420 | as the aficionados will know.

01:25:52.640 | So we're in the cortex.

01:25:54.120 | This is the seat of our higher consciousness,

01:25:55.860 | self-image, planning and action.

01:25:58.220 | But as you mentioned, the cortex isn't just about that.

01:26:00.500 | It's got other regions that are involved in other things.

01:26:02.960 | So maybe we should, staying with vision,

01:26:05.620 | let's talk a little bit about visual cortex.

01:26:07.880 | You told me a story, an amazing story about visual cortex.

01:26:11.800 | And it was a somewhat of a sad story, unfortunately,

01:26:13.840 | about someone who had a stroke to visual cortex.

01:26:17.020 | Maybe if you would share that story,

01:26:20.280 | because I think it illustrates many important principles

01:26:23.240 | about what the cortex does.

01:26:25.080 | - Right, so the visual cortex is,

01:26:29.680 | you could say the projection screen,

01:26:31.600 | the first place where this information streaming

01:26:35.720 | from the retina through this thalamus connecting linker

01:26:40.720 | gets played out for the highest level of your brain to see.

01:26:46.780 | I mean, it's a representation.

01:26:48.800 | It's a map of things going on in the visual world

01:26:52.560 | that's in your brain, and when we describe a scene

01:26:57.560 | to a friend, we're using this chunk of our brain

01:27:03.320 | to be able to put words, which are coming

01:27:04.960 | from a different part of our cortex,

01:27:07.260 | to the objects and movements and colors

01:27:10.220 | that we see in the world.

01:27:11.620 | So that's a key part of your visual experience.

01:27:17.740 | When you can describe the things you're seeing,

01:27:20.280 | you're looking at your visual cortex, and this is-

01:27:23.560 | - Could I just ask a quick question?

01:27:24.640 | So right now, because I'm looking at your face,

01:27:27.780 | as we're talking, there are neurons in my brain,

01:27:31.060 | more or less in the configuration of your face

01:27:34.720 | that are active as you move about.

01:27:37.840 | And what if I were to close my eyes and just imagine,

01:27:42.840 | I do this all the time, by the way, David,

01:27:44.960 | I close my eyes and I imagine David Berson's face.

01:27:48.920 | I don't tend to do that as often, maybe I should,

01:27:51.080 | but you get the point.

01:27:52.360 | I'm now using visualization of what you look like

01:27:55.760 | by way of memory.

01:27:57.200 | If we were to image the neurons in my brain,

01:27:59.960 | would the activity of neurons resemble the activity

01:28:04.440 | of neurons that's present when I open my eyes

01:28:08.600 | and look at your actual face?

01:28:09.640 | - This is a deep question.

01:28:11.040 | We don't really have a full accounting yet.

01:28:14.960 | Yes, except you're talking about looking in detail

01:28:18.760 | at the activity of neurons in a human brain

01:28:22.600 | and that's not as easy to do as it would be

01:28:25.120 | in some kind of animal model.

01:28:27.420 | But the bottom line is that you have a spatial representation

01:28:32.420 | of the visual world, laid as a map of the visual world,

01:28:36.740 | laid out on the surface of your cortex.

01:28:38.880 | The thing that's surprising is that it's not one map.

01:28:42.560 | It's actually dozens of maps.

01:28:44.840 | - What do each of those maps do?

01:28:46.360 | - Well, we don't really have a full accounting there either,

01:28:48.720 | but it looks a little bit like the diversification

01:28:52.200 | of the output neurons of the retina,

01:28:54.960 | the ganglion cells we were talking about before.

01:28:56.920 | There are different types of ganglion cells

01:28:58.760 | that are encoding different kinds of information

01:29:00.920 | about the visual world.

01:29:01.920 | We talk about the ones that were encoding the brightness,

01:29:05.020 | but other ones are encoding motion or color,

01:29:07.720 | these kinds of things.

01:29:08.800 | The same kinds of specializations

01:29:10.560 | in different representations of the visual world

01:29:12.960 | in the cortex seem to be true.

01:29:15.980 | It's a complex story.

01:29:17.200 | We don't have the whole picture yet,

01:29:19.900 | but it does look as if some parts of the brain

01:29:21.760 | are much more important for things like reaching for things

01:29:26.160 | in the space around you.

01:29:28.160 | And other parts of the cortex are really important

01:29:30.040 | for making associations between particular visual things

01:29:32.800 | you're looking at now and their significance.

01:29:35.840 | What is that object?

01:29:37.600 | What can it do for me?

01:29:38.440 | How can I use it?

01:29:39.640 | - What about the really specialized areas of cortex,

01:29:42.360 | like neurons that respond to particular faces,

01:29:46.460 | or neurons that, I don't know,

01:29:49.600 | can help me understand where I am

01:29:52.320 | relative to some other specific object?

01:29:54.680 | - Right, so these are properties of neurons

01:29:58.960 | that are extracted from, detected by,

01:30:03.960 | recording the activity of single neurons

01:30:07.500 | in some experimental system.

01:30:09.500 | What's going on when you actually perceive

01:30:11.880 | your grandmother's face is a much more complicated question.

01:30:15.440 | It clearly involves hundreds and thousands

01:30:17.560 | and probably millions of neurons

01:30:19.680 | acting in a cooperative way.

01:30:21.480 | So you can pick out any one little element

01:30:23.900 | in this very complicated system

01:30:26.060 | and see that it's responding differentially

01:30:28.160 | to certain kinds of visual patterns.

01:30:29.940 | And you think you're seeing a glimpse

01:30:31.620 | of some part of the process

01:30:33.040 | by which you recognize your grandmother's face.

01:30:36.140 | But that's a long way from a complete description.

01:30:38.940 | And it certainly isn't gonna be at the level

01:30:40.940 | of a magic single neuron that has the special stuff

01:30:44.160 | to recognize your grandmother.

01:30:45.320 | It's gonna be in some pattern of activity

01:30:47.640 | across many, many cells resonating

01:30:50.980 | in some kind of special way

01:30:52.900 | that will represent the internal memory of your mother.

01:30:57.580 | - Which is really incredible.

01:30:59.120 | - Yeah.

01:30:59.960 | - I mean, every time we do this deep dive,

01:31:01.620 | which we do from time to time,

01:31:02.840 | you and I, we kind of like march into the nervous system

01:31:05.240 | and explore how different aspects

01:31:08.640 | of our life experiences is handled there

01:31:12.520 | and how it's organized.

01:31:15.040 | It, after so many decades of doing this,

01:31:17.620 | it still boggles my mind that the collection of neurons,

01:31:22.620 | one through seven, active in a particular sequence

01:31:26.400 | gives the memory of a particular face

01:31:28.940 | and run backwards seven through to one.

01:31:32.600 | It gives you a complete, you know,

01:31:33.640 | could be, you know, rattlesnake, pit viper,

01:31:37.260 | heat sensing organs, as we were talking about earlier.

01:31:39.920 | So it sounds, is it true that there's a lot

01:31:43.240 | of multi-purposing of the circuitry?

01:31:45.520 | Like we can't say one area of the brain does A

01:31:49.280 | and another area of the brain does B.

01:31:50.960 | So, you know, areas can multitask

01:31:54.120 | or have multiple jobs, they can moonlight.

01:31:56.440 | - Right, but I think in my career,

01:32:01.120 | the hard problem has been to square that

01:32:05.160 | with the fact that, you know, things are specialized,

01:32:10.880 | that there are specific genes expressed in specific neurons

01:32:14.840 | that make them make synaptic connections

01:32:17.160 | with only certain other neurons.

01:32:19.240 | And that particular synaptic arrangement actually results

01:32:22.880 | in the processing of information that's useful

01:32:26.180 | to the animal to survive, right?

01:32:28.400 | So it's not as if it's either a big undifferentiated network

01:32:33.400 | of cells and looking at any one

01:32:35.840 | is never gonna tell you anything,

01:32:37.060 | that's too extreme on the one hand,

01:32:39.280 | nor is it the case that everything is hardwired

01:32:41.040 | and every neuron has one function

01:32:42.600 | and this all happens in one place in the brain.

01:32:45.760 | It's way more complicated and interactive

01:32:47.960 | and interconnected than that.

01:32:49.560 | - So we're not hardwired or softwired.

01:32:52.160 | We're sort of, I don't know what the analogy should be.

01:32:54.920 | What substance would work best, David?

01:32:57.120 | - No idea there, but you know,

01:32:58.920 | the idea is that it's always network activity.

01:33:03.420 | There's always many, many neurons involved

01:33:06.040 | and yet there's tremendous specificity

01:33:08.680 | in the neurons that might or might not be participating

01:33:10.940 | in any distributed function like that, right?

01:33:13.860 | So you have to get your mind around the fact

01:33:15.400 | that it's both very specific

01:33:17.300 | and very nonspecific at the same time.

01:33:19.360 | It's a little tricky to do,

01:33:20.600 | but I think that's kind of where the truth lies.

01:33:23.080 | - Yeah, and so this example that you mentioned

01:33:27.180 | to me once before about a woman who had a stroke

01:33:29.760 | in visual cortex, I think it speaks to some of this.

01:33:32.120 | - Right.

01:33:33.340 | - Could you share with us that story?

01:33:34.760 | - Sure, so the point is that you all,

01:33:38.480 | those of us who see, have representations

01:33:42.280 | of the visual world and our visual cortex.

01:33:44.680 | What happens to somebody when they become blind

01:33:49.680 | because of problems in the eye, the retina, perhaps?

01:33:53.460 | You have a big chunk of the cortex,

01:33:56.440 | this really valuable real estate for neural processing

01:33:59.520 | that has come to expect input from the visual system

01:34:05.040 | and there isn't any anymore.

01:34:06.480 | So you might think about that as fallow land, right?

01:34:08.960 | It's unused by the nervous system.

01:34:13.080 | And that would be a pity,

01:34:13.920 | but it turns out that it is in fact used.

01:34:16.640 | And the case that you're talking about

01:34:20.840 | is of a woman who was blind from very early in her life

01:34:25.840 | and who had risen through the ranks

01:34:30.400 | to a very high level executive secretarial position

01:34:33.720 | in a major corporation.

01:34:36.200 | And she was extremely good at braille reading

01:34:38.640 | and she had a braille typewriter

01:34:39.760 | and that's how everything was done.

01:34:41.960 | And apparently she had a stroke

01:34:44.980 | and was discovered at work, collapsed,

01:34:46.600 | and they brought her to the hospital.

01:34:48.460 | And apparently the neurologist who saw her

01:34:51.980 | when she finally came to said,

01:34:54.500 | I've got good news and bad news.

01:34:56.200 | Bad news is you've had a stroke.

01:34:57.960 | The good news is that it was in an area of your brain

01:35:00.260 | you're not even using, it's your visual cortex.

01:35:03.040 | And I know you're blind from birth,

01:35:04.580 | so there shouldn't be any issue here.

01:35:06.560 | The problem was she lost her ability to read braille.

01:35:10.000 | So what appears to have been the case,

01:35:13.500 | and this has been confirmed in other ways

01:35:16.380 | by imaging experiments in humans,

01:35:18.700 | is that in people who are blind from very early in birth,

01:35:22.020 | the visual cortex gets repurposed

01:35:25.260 | as a center for processing tactile information.

01:35:28.780 | And especially if you drain to be a good braille reader,

01:35:31.560 | you're actually reallocating somehow

01:35:34.320 | that real estate to your fingertips,

01:35:37.300 | you know, a part of the cortex

01:35:38.380 | that should be listening to the eyes.

01:35:40.260 | So that's an extreme level of plasticity,

01:35:42.440 | but what it shows is the visual cortex

01:35:45.740 | is kind of a general purpose processing machine.

01:35:48.760 | It's good at spatial information

01:35:51.620 | and the skin of your fingers is just another spatial sense

01:35:55.060 | and deprived of any other input.

01:35:57.360 | The brain seems smart enough,

01:35:59.620 | if you want to put it that way,

01:36:01.100 | to rewire itself, to use that real estate for something

01:36:05.160 | useful, in this case, reading braille.

01:36:07.120 | - Incredible.

01:36:08.840 | Somewhat tragic, but incredible.

01:36:10.340 | At least in that case, tragic.

01:36:12.280 | - Very informative.

01:36:13.120 | - Very informative.

01:36:14.080 | And of course it can go the other way too,

01:36:16.080 | where people can gain function in particular modalities

01:36:20.160 | like improved hearing or tactile function

01:36:22.640 | in the absence of vision.

01:36:23.960 | - Right.

01:36:24.800 | - Tell us about connectomes.

01:36:29.360 | We hear about genomes, proteomes, microbiomes,

01:36:33.040 | ohms, ohms, ohms these days.

01:36:35.580 | What's a connectome and why is it valuable?

01:36:39.360 | - Yeah, so connectome actually now has two meanings.

01:36:42.720 | So I only refer to the one that is my passion right now,

01:36:47.680 | and that is really trying to understand the structure

01:36:50.100 | of nervous tissue at a scale that's very, very fine.

01:36:55.100 | - Smaller than a millimeter.

01:36:59.160 | - Way smaller than a millimeter, a nanometer or less.

01:37:02.680 | As that's a thousand times smaller,

01:37:04.580 | or it's actually a million times smaller.

01:37:11.080 | So really, really tiny on the scale of individual synapses

01:37:16.080 | between individual neurons or even smaller,

01:37:18.140 | like the individual synaptic vesicles

01:37:20.440 | containing little packets of neurotransmitter

01:37:22.240 | that are gonna get released

01:37:23.800 | to allow one neuron to communicate to the next.

01:37:26.360 | So very, very fine.

01:37:28.300 | But the notion here is that you're doing this

01:37:33.300 | section after section at very fine scale.

01:37:39.300 | So in theory, what you have is a complete description

01:37:41.900 | of a chunk of nervous tissue that is so complete

01:37:46.300 | that if you took enough time to identify

01:37:48.080 | where the boundaries of all the cells are,

01:37:49.860 | you could come up with a complete description

01:37:52.380 | of the synaptic wiring of that chunk of nervous tissue

01:37:55.780 | because you have a complete description

01:37:56.860 | where all the cells are and where all the synapses

01:37:58.980 | between where all the cells are.

01:38:00.380 | So now you essentially have a wiring diagram

01:38:02.700 | of this complicated piece of tissue.

01:38:04.660 | So the omics part is the exhaustiveness of it.

01:38:08.540 | Rather than looking at a couple of synapses

01:38:10.620 | that are interesting to you from two different cell types,

01:38:13.860 | you're looking at all the synapses of all of the cell types,

01:38:17.980 | which of course is this massive avalanche of data, right?

01:38:22.680 | - So in genetics, you have genetics and then you have genomics

01:38:25.340 | which is the idea of getting the whole genome.

01:38:27.060 | - All of it.

01:38:27.900 | - And we don't really have an analogous word for genetics,

01:38:30.900 | but it would be connectivity and canomics.

01:38:33.180 | - Right, connectivity. - Excuse me, connectomics.

01:38:35.540 | - Connectomics, sure, sure.

01:38:36.980 | - Connectivity and connectomics.

01:38:38.020 | - Right, so it's wanting it all.

01:38:40.340 | And of course it's crazy ambitious,

01:38:42.700 | but that's where it gets fun.

01:38:45.240 | Really it's a use of electron microscopy,

01:38:48.540 | a very high resolution microscopic imaging system

01:38:53.480 | on a new scale with way more payoff

01:38:56.900 | in terms of understanding the connectivity

01:38:58.700 | of the nervous system.

01:38:59.540 | And it's just emerging,

01:39:01.520 | but I really think it's gonna revolutionize the field

01:39:04.300 | because we're gonna be able to query these circuits.

01:39:07.240 | How did they actually do it?

01:39:08.540 | Look at the hardware

01:39:09.900 | in a way that's never been possible before.

01:39:12.420 | - The way that I describe this to people is

01:39:15.100 | if you were to take a chunk of kind of cooked

01:39:18.300 | but cold spaghetti and slice it up very thin,

01:39:21.760 | and you're trying to connect up each image of each slice

01:39:25.940 | of the edge of the spaghetti

01:39:28.100 | as figure out which ropes of spaghetti belong to which.

01:39:30.820 | - And have a complete description

01:39:32.220 | of where this piece of spaghetti touches

01:39:33.820 | that piece of spaghetti,

01:39:34.660 | and is there something special there?

01:39:36.340 | - Where the meat sauce is and all the other cell types

01:39:38.680 | and the pesto, where it all is around the spaghetti,

01:39:43.680 | because those are the other cells,

01:39:44.740 | the blood vessels and the glial cells.

01:39:47.520 | So what's it good for?

01:39:49.820 | I mean, maps are great.

01:39:51.780 | I always think of connectomics and genomics and proteomics,

01:39:57.440 | et cetera, as necessary but not sufficient.

01:40:00.080 | - Right, right.

01:40:01.360 | So I mean, in many cases,

01:40:02.520 | what you do is you go out and probe the function,

01:40:05.860 | and you understand how the brain does the function

01:40:08.000 | by finding neurons that seem to be firing

01:40:10.920 | in association with this function that you're observing.

01:40:14.100 | And little by little, you work your way in,

01:40:15.700 | and now you wanna know what the connectivity is.

01:40:17.300 | Maybe the anatomy could help you.

01:40:19.720 | But this connectomics approach,

01:40:21.540 | or at least the serial electron microscopy

01:40:23.660 | reconstruction of neurons approach,

01:40:27.220 | really is allowing us to frame questions

01:40:29.960 | starting from the anatomy and saying,

01:40:33.460 | I see a synaptic circuit here.

01:40:35.120 | My prediction would be that these cell types

01:40:37.200 | would interact in a particular way.

01:40:38.860 | Is that right?

01:40:40.160 | And then you can go and probe the physiology,

01:40:42.180 | and you might be right or you might be wrong.

01:40:43.760 | But more often than not,

01:40:45.380 | it looks like the structure is pointing us

01:40:47.460 | in the right direction.

01:40:48.780 | So in my case, I'm using this to try to understand a circuit

01:40:53.500 | that is involved in this image stabilization network

01:40:56.160 | we're talking about, keeping things stable on the retina.

01:41:00.260 | And this thing will only respond

01:41:02.540 | at certain speeds of motion.

01:41:04.740 | These cells in the circuit, like slow motion,

01:41:07.300 | they won't respond to fast motion.

01:41:09.180 | How does that come about?

01:41:10.340 | Well, I was able to probe the circuitry.

01:41:14.060 | I knew what my cells looked like.

01:41:15.500 | I could see which other cells were talking to it.

01:41:17.460 | I could categorize all the cells

01:41:19.060 | that might be the players here

01:41:20.580 | that are involved in this mechanism

01:41:22.240 | of tuning the thing for slow speeds.

01:41:25.520 | And then we said, it looks like it's that cell type.

01:41:27.860 | And we went and looked and the data bore that up.

01:41:31.120 | But the anatomy drove the search for the particular cell type

01:41:34.500 | because we could see it connected in the right place

01:41:36.880 | to the right cells.

01:41:38.020 | So that creates the hypothesis

01:41:40.100 | that lets you go query the physiology,

01:41:42.620 | but it can go the other way as well.

01:41:44.020 | So it's always the synergy between these functional

01:41:46.100 | and structural approaches that gives you the most lift.

01:41:51.100 | But in many cases,

01:41:53.660 | the anatomy has been a little bit the weak sister in this,

01:41:56.660 | the structure, trying to work out the diagram

01:41:59.120 | because we haven't had the methods.

01:42:00.900 | Now the methods exist.

01:42:02.660 | And this whole field is expanding very quickly

01:42:05.740 | because people want these circuit diagrams

01:42:08.240 | for the particular part of the nervous system

01:42:10.900 | that they're working on.

01:42:12.400 | If you don't know the cell types and the connections,

01:42:14.300 | how do you really understand how the machine works?

01:42:17.380 | - Yeah, what I love about is

01:42:18.820 | we don't know what we don't know.

01:42:20.580 | And as scientists, we don't ask questions.

01:42:22.700 | We pose hypotheses.

01:42:23.860 | Hypotheses being, of course,

01:42:25.460 | some prediction that you wager your time on, basically.

01:42:29.260 | And it either turns out to be true or not true.

01:42:32.300 | But if you don't know that a particular cell type is there,

01:42:37.580 | you could never in any configuration of life

01:42:42.540 | or a career or exploration of a nervous system

01:42:46.540 | wager a hypothesis because you didn't know it was there.

01:42:49.300 | So this allows you to say,

01:42:50.140 | "Ah, there's this little interesting little connection

01:42:52.900 | between this cell that I know is interesting

01:42:54.980 | and another cell that's a little mysterious,

01:42:56.660 | but interesting.

01:42:57.600 | I'm going to hypothesize that it's doing blank,

01:43:00.020 | blank, and blank and go test that."

01:43:01.280 | And in the absence of these connectomes,

01:43:03.400 | you would never know that that cell

01:43:04.540 | was lurking there in the shadows.

01:43:06.540 | - Right, right.

01:43:07.980 | Yeah, and if you're just trying to understand

01:43:09.500 | how information flows through this biological machine,

01:43:14.240 | you want to know where things are.

01:43:16.380 | Neuro-transmitters are dumped out of the terminals

01:43:18.640 | of one cell and they diffuse across the space

01:43:21.880 | between the two cells, which is kind of a liquidy space,

01:43:24.600 | and they hit some receptors on the postsynaptic cell

01:43:26.700 | and they have some impact.

01:43:28.920 | Sometimes that's not through a regular synapse.

01:43:31.400 | Sometimes it's through a neuromodulator,

01:43:33.080 | like you often talk about on your podcast,

01:43:35.840 | that are sort of oozing-

01:43:36.680 | - Dopamine or something. - Dopamine, exactly.

01:43:38.220 | Oozing into the space between the cells,

01:43:40.540 | and it may be acting at some distance

01:43:42.700 | far from where it was released, right?

01:43:45.020 | But if you don't know where the release is happening

01:43:47.200 | and where other things are that might respond

01:43:49.200 | to that release, you're groping around in the dark.

01:43:52.500 | - Well, I love that you are doing this,

01:43:54.100 | and I have to share with the listeners

01:43:57.800 | that the first time I ever met David,

01:44:00.460 | and every time I've ever met with him in person,

01:44:03.220 | at least at his laboratory at Brown,

01:44:06.220 | he was in his office, door closed,

01:44:08.740 | drawing neurons and their connections.

01:44:11.740 | And this is somewhat unusual for somebody

01:44:13.700 | who's a, you know, endowed full professor,

01:44:16.500 | chairman of the department, et cetera, for many years,

01:44:19.240 | to be doing the hands-on work.

01:44:20.900 | Typically that's the stuff that's done by technicians

01:44:22.780 | or graduate students or postdocs.

01:44:24.180 | But I think it's fair to say that you really love

01:44:28.080 | looking at nervous systems and drawing

01:44:31.460 | the accurate renditions of how those nervous systems

01:44:34.940 | are organized and thinking about how they work.

01:44:37.340 | - Yeah, it's pure joy for me.

01:44:38.820 | I mean, I'm a very visual person.

01:44:40.440 | My wife is an artist.

01:44:41.560 | We look at a lot of art together.

01:44:43.540 | Just the forms of things are gorgeous in their own right.

01:44:47.580 | But to know that the form is, in a sense, the function,

01:44:51.280 | that the architecture of the connectivity

01:44:55.560 | is how the computation happens in the brain at some level,

01:44:59.460 | even though we don't fully understand that in most contexts,

01:45:02.840 | gives me great joy, 'cause I'm working on something

01:45:05.400 | that's both visually beautiful, but also deeply beautiful

01:45:09.880 | and sort of a higher sort of knowledge context.

01:45:14.880 | You know, what is it all about?

01:45:17.600 | - Love it.

01:45:18.440 | Well, as a final question, I get asked very often

01:45:21.560 | about how people should learn about neuroscience

01:45:24.080 | or how they should go about pursuing maybe an education

01:45:28.160 | in neuroscience if they're at that stage of their life

01:45:30.320 | or that's appropriate for their current trajectory.

01:45:34.040 | Do you have any advice to young people, old people,

01:45:37.080 | and anything in between about how to learn

01:45:39.720 | about the nervous system, maybe in a more formal way?

01:45:42.480 | I mean, obviously we have our podcast.

01:45:43.880 | There are other sources of neuroscience information

01:45:46.800 | out there, but for the young person who thinks

01:45:49.340 | they want to understand the brain,

01:45:51.600 | they want to learn about the brain,

01:45:53.800 | what should we tell them?

01:45:55.080 | - Well, that's a great question.

01:45:56.360 | And there's so many sources out there.

01:45:57.840 | It's almost a question of how do you deal with this avalanche

01:46:01.080 | of information out there?

01:46:02.840 | I mean, I think our podcast is a great way for people

01:46:05.320 | to learn more about the nervous system in an accessible way,

01:46:08.240 | but there's so much stuff out there.

01:46:09.760 | And it's not just that.

01:46:10.960 | I mean, the resources are becoming more and more available

01:46:13.920 | for average folks to participate in neuroscience research

01:46:18.580 | on some level.

01:46:19.420 | There's this famous eye wire project of Sebastian Sommer.

01:46:21.360 | - Oh yeah, maybe tell us about eye wire.

01:46:23.240 | - Yeah, so that's connectomics.

01:46:24.560 | And that's a situation where a very clever scientist

01:46:28.200 | realized that the physical work

01:46:31.600 | of doing all this reconstruction of neurons

01:46:34.720 | from these electron micrographs,

01:46:37.240 | there's a lot of time involved.

01:46:39.920 | Many, many person hours have to go into that

01:46:42.400 | to come up with the map that you want

01:46:44.760 | of where the cells are.

01:46:46.340 | And he was very clever about setting up a context

01:46:49.240 | in which he could crowdsource this.

01:46:51.360 | And people who were interested

01:46:52.200 | in getting a little experience, looking at nervous tissue

01:46:54.760 | and participating in a research project

01:46:57.440 | could learn how to do this and do a little bit.

01:46:59.600 | - From their living room.

01:47:00.440 | - From their living room, their laptop.

01:47:01.800 | - We'll put a link to eye wire.

01:47:03.040 | That's a, it also is a great bridge

01:47:04.600 | between what we were just talking about connectomics

01:47:06.480 | and actually participating in research.

01:47:08.520 | - Right.

01:47:09.360 | - And you don't need a graduate mentor

01:47:10.680 | or anything like that.

01:47:12.120 | - Right, so more of this is coming

01:47:14.640 | and I'm actually interested in building more of this

01:47:17.360 | so that people who are interested,

01:47:20.160 | want to participate at some level,

01:47:21.560 | don't necessarily have the time or resources

01:47:24.520 | to get involved in laboratory research

01:47:27.160 | can get exposed to it and participate

01:47:29.920 | and actually contribute.

01:47:31.120 | So I think that's one thing.

01:47:34.640 | I mean, just asking questions of the people around you

01:47:38.240 | who know a little bit more

01:47:39.400 | and have them point you in the right direction.

01:47:41.200 | Here's a book you might like to read.

01:47:42.600 | There's lots of great popular books out there

01:47:45.840 | that are accessible that will give you some more sense

01:47:48.760 | of the full range of what's out there in the neurosciences

01:47:51.720 | and how-

01:47:52.560 | - We can put some links to a few of those

01:47:53.640 | that we like on basic neuroscience.

01:47:56.280 | Our good friend, Dick Maslin, the late Richard,

01:47:59.560 | people will call him Dick, Dick Maslin had a good book.

01:48:02.360 | I forget the title at the moment.

01:48:05.360 | It's sitting behind me somewhere over there on the shelf,

01:48:07.320 | but about vision and how nervous systems work.

01:48:10.440 | A pretty accessible book for the general public.

01:48:12.600 | - Right, right.

01:48:13.480 | So that, and there's so many sources out there.

01:48:16.580 | I mean, Wikipedia is a great way.

01:48:18.120 | If you had a particular question about visual function,

01:48:20.160 | I would say by all means head to Wikipedia

01:48:23.040 | and get the first look and follow the references from there

01:48:27.560 | or go to your library or, you know,

01:48:30.320 | there's so many ways to get into it.

01:48:32.000 | It's such an exciting field now.

01:48:33.960 | There's so many, I mean,

01:48:35.080 | any particular realm that's special to you,

01:48:37.520 | your experience, your, you know, your strengths,

01:48:40.000 | your passions, there's a field of neuroscience

01:48:44.000 | devoted to that.

01:48:44.840 | You know, if you've got,

01:48:45.680 | if you know somebody who's got a neurological problem

01:48:47.920 | or a psychiatric problem,

01:48:50.480 | there's a branch of neuroscience

01:48:51.880 | that is devoted to trying to understand that

01:48:54.640 | and to solve these kinds of problems down the line.

01:48:57.480 | So feel the, feel the buzz.

01:49:00.960 | It's an exciting time to get involved.

01:49:03.380 | - Great, those are great resources

01:49:04.720 | that people can access from anywhere,

01:49:06.520 | zero cost as you need an internet connection.

01:49:08.780 | But aside from that, we'll put the links to some,

01:49:11.320 | and I'm remembering Dick's book is called

01:49:13.820 | "We Know It When We See It."

01:49:15.960 | - One of my heroes.

01:49:16.960 | - Yeah, a wonderful colleague,

01:49:18.480 | who unfortunately we lost a few years ago,

01:49:20.080 | but listen, David, this has been wonderful.

01:49:24.120 | - It's been a blast.

01:49:24.960 | - We really appreciate you taking the time to do this.

01:49:26.820 | As people probably realize by now,

01:49:29.320 | you're an incredible wealth of knowledge

01:49:31.040 | about the entire nervous system.

01:49:32.960 | Today, we just hit this top contour

01:49:35.240 | of a number of different areas

01:49:36.360 | to give a flavor of the different ways

01:49:38.340 | that the nervous system works and is organized

01:49:41.020 | and how that's put together,

01:49:43.360 | how these areas are talking to one another.

01:49:45.220 | What I love about you

01:49:46.060 | is that you're such an incredible educator

01:49:48.320 | and I've taught so many students over the years,

01:49:50.460 | but also for me personally as friends,

01:49:54.200 | but also anytime that I want to touch into the beauty

01:49:57.840 | of the nervous system, I rarely lose touch with it,

01:50:00.740 | but anytime I want to touch into it

01:50:02.160 | and start thinking about new problems

01:50:03.920 | and ways that the nervous system is doing things

01:50:06.480 | that I hadn't thought about, I call you.

01:50:08.360 | So please forgive me for the calls past, present,

01:50:12.040 | and future, unless you change your number.

01:50:13.880 | And even if you do, I'll be calling.

01:50:15.960 | It's been such a blast, Andy.

01:50:18.540 | This has been a great session

01:50:20.980 | and it's always fun talking to you.

01:50:22.700 | It always gets my brain racing.

01:50:24.960 | So thank you.

01:50:27.860 | - Thank you.

01:50:28.780 | Thank you for joining me today

01:50:29.880 | for my discussion with Dr. David Berson.

01:50:32.280 | By now, you should have a much clearer understanding

01:50:35.180 | of how the brain is organized

01:50:37.100 | and how it works to do all the incredible things

01:50:39.580 | that it does.

01:50:40.780 | If you're enjoying and/or learning from this podcast,

01:50:43.200 | please subscribe to our YouTube channel.

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01:51:18.560 | While today's discussion did not focus on supplements,

01:51:21.580 | many previous podcast episodes include discussions

01:51:24.220 | about supplements.

01:51:25.220 | And while supplements aren't necessary for everybody,

01:51:28.220 | many people derive benefit from them

01:51:30.100 | for things like sleep or focus or anxiety relief and so on.

01:51:33.940 | One issue with the supplement industry, however,

01:51:36.140 | is that oftentimes the quality

01:51:38.060 | will really vary across brands.

01:51:40.580 | That's why we partnered with Thorne, T-H-O-R-I-N-E,

01:51:43.060 | because Thorne supplements

01:51:44.540 | are of the absolute highest standards

01:51:46.260 | in terms of the quality of the ingredients they include

01:51:48.520 | and the precision of the amounts

01:51:50.020 | of the ingredients they include.

01:51:51.420 | In other words, what's listed on the bottle

01:51:53.140 | is what's actually found in the bottle,

01:51:54.900 | which is not true of many supplements out there

01:51:57.080 | that have been tested.

01:51:58.280 | If you'd like to see the supplements that I take,

01:52:00.120 | you can go to thorne.com/u/huberman.

01:52:04.980 | And there, you can see the supplements that I take

01:52:06.980 | and you can get 20% off any of those supplements.

01:52:09.600 | And if you navigate deeper into the Thorne site

01:52:11.660 | through that portal, thorne.com/u/huberman,

01:52:15.640 | you can also get 20% off any of the other supplements

01:52:18.560 | that Thorne happens to make.

01:52:20.040 | If you're not already following Huberman Lab

01:52:21.780 | on Instagram and Twitter, feel free to do so.

01:52:24.720 | Both places I regularly post short video posts

01:52:27.860 | or text posts that give tools related to health

01:52:31.200 | and neuroscience and so forth.

01:52:32.780 | And most of the time, that information is non-overlapping

01:52:35.740 | with the information on the podcast.

01:52:37.140 | Again, it's just Huberman Lab on Instagram and Twitter.

01:52:39.680 | And last but not least,

01:52:41.240 | thank you for your interest in science.

01:52:43.120 | [upbeat music]

01:52:45.700 | you

Dr. David Berson: Your Brain's Logic & Function | Huberman Lab Podcast #50

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