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PROFESSOR: OK.

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I guess we'll get started.

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Last time, we were talking
about auditory cortex,

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and the tonotopic fields
in auditory cortex,

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the non-tonotopic fields.

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Any questions about that first
lecture on auditory cortex?

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We're going to continue
on cortex today, and talk

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about some areas of cortex in
a specialized mammal, the bat.

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It's where a lot
of excellent work

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has been done on auditory
cortex that really

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shows-- very nicely--
how neurons respond,

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at least, to the selective
stimuli that are emitted

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and listened to by the bat.

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So we'll be talking
about bat echolocation.

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We'll start out by defining
the different groups of bats,

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and talk about who
discovered bat echolocation.

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The discovery was made
just a few miles from here.

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We'll talk about what the
signals a bat's look like,

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in terms of what they look
like on a spectrogram.

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Then we'll talk about
the specializations

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for processing the emitted
pulse and the return

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00:01:58,300 --> 00:02:01,510
echo in several bat
cortical fields.

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00:02:03,530 --> 00:02:05,520
In the second half
of today's lecture,

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we'll be revisiting
speech sounds.

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We had a little bit of
that at the very beginning

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of my lectures.

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We'll talk about
speech spectrograms.

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And then we'll talk about
cortical processing of speech

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and language, especially
in the human, where

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we have a lot that is known
about processing of language.

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OK.

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00:02:29,280 --> 00:02:31,710
So we'll start out
with bat echolocation.

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These are some pretty
pictures of bats.

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Oh, I also have
some announcements

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now that everybody's here.

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So, on Wednesday's class,
meet at the Massachusetts Eye

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and Ear Infirmary, if
you haven't already

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00:02:46,499 --> 00:02:47,165
gotten an email.

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So, for a lab tour, we meet at
the Massachusetts Eye and Ear

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Infirmary.

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00:02:56,090 --> 00:02:59,370
And there are directions
to get there from here.

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You just get on the Red Line,
going inbound, toward Boston.

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00:03:03,050 --> 00:03:05,670
Get off one stop later,
at the Charles stop.

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00:03:06,730 --> 00:03:10,310
And then you're going to the
Massachusetts Eye and Ear

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Infirmary.

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So a lot of people get
that confused, of course,

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with the big behemoth right
next door , Mass General.

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So Mass.

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Eye and Ear's a
different building.

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It's a different hospital.

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But But it's clearly marked.

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The directions are on the
website, so just follow them.

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So the lab tour will be within
the regular class period,

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so 2:35 to 4:00.

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We're not going to go
beyond that because people

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have commitments after that.

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And we'll-- depending on
how many people show up,

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it's likely we'll divide
into groups and cycle through

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several demonstrations that I
have prepared for you there.

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OK.

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So questions about that?

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So we meet at Mass.

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Eye and Ear on Wednesday.

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At that time, the
assignments are due.

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So we talked a little bit about
the assignment a few weeks ago,

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when we talked about
the Jeffers model.

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00:04:04,160 --> 00:04:07,190
And you can send me the
assignments by email

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or give me a typed
printed version.

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And the idea is that I'll
look them over and then

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hand them back to you
at the review session.

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And we'll talk about
the assignments ,

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and what I consider
the right answers.

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So we did a little switch
for the review sessions.

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So we should put
this on the website,

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if it isn't already there.

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But next week, Monday, we have
two review sessions scheduled.

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The one on Monday will
now be the one on vision.

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And so Doctor Schiller is
going to come and review

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the vision part of
the course on Monday.

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And then I'll be back
a week from Wednesday.

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And we'll do the
audition review.

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00:04:47,880 --> 00:04:50,350
And we'll return your
assignments then, ?

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OK?

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So that's what's
happening next week.

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Any questions on that?

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OK.

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So here are the nice
pictures of bats.

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00:05:00,932 --> 00:05:02,015
They're beautiful animals.

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They have specializations,
of course, for hearing.

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00:05:07,850 --> 00:05:12,110
They have large pinnae, right?

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00:05:12,110 --> 00:05:15,010
Much, much larger
than other animals,

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00:05:15,010 --> 00:05:16,405
especially for their size.

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00:05:18,440 --> 00:05:21,670
They have very small eyes.

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00:05:21,670 --> 00:05:24,365
And their visual systems
are not well developed.

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00:05:26,420 --> 00:05:27,710
They of course have wings.

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So these are flying animals.

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00:05:30,620 --> 00:05:33,310
And many of them
have noseleaves.

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So here's a nose
cartilage that's

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00:05:38,350 --> 00:05:43,540
very well developed because
these animals emit sound.

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00:05:43,540 --> 00:05:45,710
Their echolocation
pulse is emitted.

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00:05:45,710 --> 00:05:47,714
And some of the sound
comes out of the mouth.

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00:05:47,714 --> 00:05:49,255
But some of it comes
out of the nose.

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00:05:50,400 --> 00:05:55,400
And this noseleaf tends
to focus the sound forward

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because that's where the bat
is interested at detecting

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00:05:58,760 --> 00:06:03,290
some kind of a target,
like the insect prey

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00:06:03,290 --> 00:06:04,880
that most of these bats eat.

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00:06:04,880 --> 00:06:09,520
So I should backtrack
and say that we're really

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00:06:09,520 --> 00:06:14,605
talking about three
types of bats.

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We're talking about echolocating
bats, of which there

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are two varieties that I'll
tell you about it in a minute.

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And we're also not going to talk
about non-echolocating bats.

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And sometimes, these
non-echolocating bats

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are called fruit-eating bats.

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They are also flying mammals.

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But they have big eyes.

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00:06:51,990 --> 00:06:54,740
They have relatively
small pinnae.

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00:06:54,740 --> 00:06:58,210
And they navigate around
like birds and other mammals,

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using their visual system.

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So they don't echolocate.

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00:07:03,630 --> 00:07:05,380
So you have
non-echolocating bats

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00:07:05,380 --> 00:07:07,280
that we're not
going to talk about.

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We have echolocating bats
that we will talk about.

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It's starting to get confusing
with all these groups.

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In fact, bats are a very
successful group of mammals.

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Supposedly, there
are more species

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of bats than all other
mammals combined.

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It's and amazingly
successful group of mammals.

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00:07:27,530 --> 00:07:32,010
And mostly because
echolocation has opened up

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a whole new vista for bats.

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Not only can they fly around,
but they can do so at night--

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in total darkness--
and find prey,

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00:07:41,650 --> 00:07:43,910
their targets, their insects.

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So instead of
being fruit eating,

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these echolocating
bats are carnivorous.

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Most of them eat insects
that they catch on the wing.

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So flying insects.

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00:07:57,510 --> 00:08:00,430
But there are
gleaning bats that eat

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00:08:00,430 --> 00:08:01,955
insects on the forest floor.

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00:08:03,200 --> 00:08:08,220
There are vampire bats
that cut little holes

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00:08:08,220 --> 00:08:12,470
in the top of mammals and lap
up the blood that comes out.

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00:08:12,470 --> 00:08:15,790
There are fish eating
bats that eat fish.

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00:08:15,790 --> 00:08:18,615
There are a whole
variety types of bats.

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But most of them eat insects
that they catch on the wing.

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And we'll have a
demonstration of that.

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So these are insect
eating bats here.

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This one I want to
point out its name for.

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This one is called-- in the
middle left, right here--

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megaderma lyra.

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So mega means big.

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Derma means skin, ?

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right?

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00:08:43,620 --> 00:08:45,805
It's so named because
of it's big skin here.

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And lyra refers to
lyrical, or musical,

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or something that sings, OK?

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So these bats are singing.

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Let's look at the types
of singing that they do.

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And this display
shows the two types

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of signals that are
emitted by the two

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00:09:09,250 --> 00:09:12,120
big groups of echolocating bats.

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The first I want to start
with is the simplest.

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00:09:14,950 --> 00:09:16,555
It's called an FM bat.

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00:09:17,790 --> 00:09:22,740
An FM-- you have
an FM radio that

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00:09:22,740 --> 00:09:35,010
stands for frequency
modulated, or Fm.

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00:09:37,310 --> 00:09:37,860
OK?

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00:09:37,860 --> 00:09:47,420
And in this graph of the FM
bat's echolocating signal--

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this graph is called
a spectrogram--

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00:09:50,670 --> 00:09:52,911
and it plots the
frequency on the y-axis

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00:09:52,911 --> 00:09:57,760
and as a function of
time on the x-axis.

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And this echolocating
pulse is the thing

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00:10:01,970 --> 00:10:03,229
that the bat is emitting.

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00:10:03,229 --> 00:10:04,395
It's producing and emitting.

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00:10:05,440 --> 00:10:08,070
And the reason it's
frequency modulated is it

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starts at a high frequency
and modulates down

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00:10:11,420 --> 00:10:12,315
to a lower frequency.

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And here's another one.

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00:10:15,070 --> 00:10:16,730
And here's another one.

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00:10:16,730 --> 00:10:19,340
Now, if there's a
target out there,

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00:10:19,340 --> 00:10:24,640
some distance from the bat,
this pulse that goes out

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00:10:24,640 --> 00:10:26,210
will be reflected
off the target.

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00:10:26,210 --> 00:10:30,250
And then it will come back to
the bat in the form of an echo

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00:10:30,250 --> 00:10:31,310
sometime later.

189
00:10:32,740 --> 00:10:33,240
OK?

190
00:10:33,240 --> 00:10:36,800
So the bat-- in this
case the FM bat--

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00:10:36,800 --> 00:10:39,710
gets information, number
one, if there's an echo,

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00:10:39,710 --> 00:10:41,600
there's a target out there.

193
00:10:41,600 --> 00:10:46,470
And number two, the time
between the pulse and the echo

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00:10:46,470 --> 00:10:49,440
is an indication of the distance
the target is from the bat,

195
00:10:49,440 --> 00:10:49,940
right?

196
00:10:49,940 --> 00:10:54,070
Because the sound has to go
from the bat, to the target,

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00:10:54,070 --> 00:10:56,055
and then from the
target back to the bat.

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00:10:57,290 --> 00:11:01,250
And we know that the
sound velocity in air

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00:11:01,250 --> 00:11:05,060
is about 340 meters per second.

200
00:11:09,590 --> 00:11:12,000
So knowing that
velocity, and knowing

201
00:11:12,000 --> 00:11:16,410
the time between the pulse and
the echo, we-- and the bat--

202
00:11:16,410 --> 00:11:18,600
can get information
of how far away

203
00:11:18,600 --> 00:11:20,305
the target is from the bat.

204
00:11:22,270 --> 00:11:25,550
Now, a couple of things
I want to comment here

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00:11:25,550 --> 00:11:26,460
on this spectrogram.

206
00:11:26,460 --> 00:11:28,920
Number one, the frequency axis.

207
00:11:28,920 --> 00:11:32,130
You might not be able to see
it, but it starts at zero

208
00:11:32,130 --> 00:11:34,550
and then quickly
jumps to 30 kilohertz.

209
00:11:36,090 --> 00:11:38,760
And then there's
60, 90, and 120.

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00:11:38,760 --> 00:11:42,040
So those are very
high sound frequency.

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00:11:42,040 --> 00:11:47,380
And so, in the early days
and to a certain extent

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00:11:47,380 --> 00:11:50,327
still, those frequencies
would be called ultrasonic.

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00:11:57,420 --> 00:11:59,820
And there's no real
good reason for that,

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00:11:59,820 --> 00:12:01,840
except that we're humans.

215
00:12:01,840 --> 00:12:05,810
And everything is important
with respect to humans.

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00:12:05,810 --> 00:12:09,500
And our upper limit of
frequency, as you well

217
00:12:09,500 --> 00:12:12,430
know-- if you're a
very young human--

218
00:12:12,430 --> 00:12:14,640
ends at about 20 kilohertz.

219
00:12:14,640 --> 00:12:18,309
And most of us, who are in
our middle or older ages,

220
00:12:18,309 --> 00:12:20,100
aren't hearing anything
above 10 kilohertz.

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00:12:21,240 --> 00:12:24,630
So all these frequencies
emitted by the bat,

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00:12:24,630 --> 00:12:27,372
and the echoes coming
back, are beyond the range

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00:12:27,372 --> 00:12:28,080
of human hearing.

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00:12:29,640 --> 00:12:31,810
And in that sense,
they're ultrasonic.

225
00:12:31,810 --> 00:12:34,465
So you can't go out and say, oh.

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00:12:34,465 --> 00:12:37,080
I heard a bat, or
at least in terms

227
00:12:37,080 --> 00:12:41,200
of the echolocating signals
that the bats are emitting.

228
00:12:41,200 --> 00:12:43,600
There are some
sounds that bats emit

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00:12:43,600 --> 00:12:46,160
that are communication sounds.

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00:12:46,160 --> 00:12:47,970
And those are in
the human frequency

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00:12:47,970 --> 00:12:49,410
range to a certain extent.

232
00:12:49,410 --> 00:12:51,570
But almost all the
echolocating signals

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00:12:51,570 --> 00:12:55,610
are well above the upper
limit of our hearing range.

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00:12:56,690 --> 00:12:59,640
Now, another thing that you
can see from this spectrogram

235
00:12:59,640 --> 00:13:03,120
is that there's a big
delay between this pulse

236
00:13:03,120 --> 00:13:05,150
and this echo, OK?

237
00:13:05,150 --> 00:13:06,780
The target is pretty far away.

238
00:13:07,830 --> 00:13:10,810
Generally, bats
head toward targets.

239
00:13:10,810 --> 00:13:12,310
And this has been
shown many times

240
00:13:12,310 --> 00:13:15,290
in behavioral experiments,
especially if they're hungry.

241
00:13:16,110 --> 00:13:16,610
OK?

242
00:13:16,610 --> 00:13:19,260
And as the bat gets closer
and closer to the target,

243
00:13:19,260 --> 00:13:23,824
obviously the time between the
pulse and the returning echo

244
00:13:23,824 --> 00:13:24,365
gets shorter.

245
00:13:26,390 --> 00:13:30,720
And, as you can probably
see from this spectrogram,

246
00:13:30,720 --> 00:13:34,910
there are a lot more
pulses emitted per time

247
00:13:34,910 --> 00:13:38,070
when the bat gets
close to the target

248
00:13:38,070 --> 00:13:40,869
because the bat is interested
in getting a lot of information

249
00:13:40,869 --> 00:13:41,660
when it gets close.

250
00:13:42,850 --> 00:13:46,300
Another reason that the bat
doesn't emit very many pulses

251
00:13:46,300 --> 00:13:47,840
when it's far away
from the target

252
00:13:47,840 --> 00:13:51,750
is, if you emitted a pulse
before the echo returned,

253
00:13:51,750 --> 00:13:55,125
you could get confused
between the outgoing pulse

254
00:13:55,125 --> 00:13:56,340
and the returning echo.

255
00:13:57,410 --> 00:14:00,870
So typically, bats tend to
increase their pulse rate

256
00:14:00,870 --> 00:14:03,740
a lot more as they get
closer to their target.

257
00:14:03,740 --> 00:14:04,240
OK?

258
00:14:04,240 --> 00:14:07,290
And I'm going to show you
a demonstration of that.

259
00:14:07,290 --> 00:14:09,790
I'm sure we'll
convince you of that.

260
00:14:09,790 --> 00:14:14,730
So this is the type of bat
we have here in New England.

261
00:14:14,730 --> 00:14:18,350
Examples of this are a little
brown bat or the big brown bat.

262
00:14:19,630 --> 00:14:23,400
And if anybody has seen
bats-- have you guys seen bats

263
00:14:23,400 --> 00:14:25,011
flying around at night?

264
00:14:25,011 --> 00:14:25,510
Yeah?

265
00:14:25,510 --> 00:14:26,700
Where do you see them?

266
00:14:27,790 --> 00:14:28,610
In your bedroom?

267
00:14:28,610 --> 00:14:33,270
Underneath-- [LAUGHTER] it's
where I've seen some recently,

268
00:14:33,270 --> 00:14:34,270
which is a little scary.

269
00:14:36,600 --> 00:14:39,780
Well, this view graph
says it hunts in open air.

270
00:14:39,780 --> 00:14:40,960
Where has anybody seen them?

271
00:14:40,960 --> 00:14:43,720
I sometimes see them
if I'm out canoeing

272
00:14:43,720 --> 00:14:47,020
on a lake at night,
or in the evening.

273
00:14:47,020 --> 00:14:48,060
Any other places?

274
00:14:48,060 --> 00:14:49,685
On golf courses, for example.

275
00:14:51,170 --> 00:14:54,720
And those are all
sensible, if you will,

276
00:14:54,720 --> 00:14:57,600
places for the bat to hunt
because they're very open

277
00:14:57,600 --> 00:14:58,100
situations.

278
00:14:59,230 --> 00:15:02,460
And there isn't a whole bunch
of clutter, if you will,

279
00:15:02,460 --> 00:15:05,170
that will return
echoes to the bat.

280
00:15:05,170 --> 00:15:07,610
If there's a moth or a
mosquito out there-- it

281
00:15:07,610 --> 00:15:10,520
might be the only
thing out there

282
00:15:10,520 --> 00:15:12,890
above the surface of
the lake, and that's

283
00:15:12,890 --> 00:15:15,690
very interesting to the bat
because it has one target.

284
00:15:15,690 --> 00:15:18,920
It doesn't have a million leaves
of the forest, if you will,

285
00:15:18,920 --> 00:15:20,390
to get confused.

286
00:15:20,390 --> 00:15:22,780
It gets one echo, it knows
there's one target out there.

287
00:15:22,780 --> 00:15:24,710
It goes and swoops out there.

288
00:15:24,710 --> 00:15:28,430
And it possibly eats the
target, if it's an insect.

289
00:15:30,111 --> 00:15:30,610
OK.

290
00:15:35,900 --> 00:15:38,020
Let me give you
some other examples

291
00:15:38,020 --> 00:15:40,060
of some information on FM bats.

292
00:15:40,060 --> 00:15:42,640
First, I want to
point your attention

293
00:15:42,640 --> 00:15:46,490
to who discovered
echolocating bats.

294
00:15:46,490 --> 00:15:47,830
And I have his book here.

295
00:15:48,940 --> 00:15:51,730
This is Donald Griffin's book.

296
00:15:51,730 --> 00:15:53,255
It's called Listening
In the Dark.

297
00:15:54,800 --> 00:15:59,015
And I'll write his
name on the board.

298
00:16:07,500 --> 00:16:10,972
And I'd like to do just a
short reading from his book.

299
00:16:10,972 --> 00:16:12,510
Then I'll pass it around.

300
00:16:14,640 --> 00:16:16,420
So this is the
section where he talks

301
00:16:16,420 --> 00:16:21,520
about this discovery of
bats' ultrasonic sounds.

302
00:16:27,240 --> 00:16:31,280
So he writes, "during my
undergraduate years at Harvard

303
00:16:31,280 --> 00:16:35,520
College, when I was actively
engaged in banding bats

304
00:16:35,520 --> 00:16:38,800
to study their
migration--" So bats here,

305
00:16:38,800 --> 00:16:42,290
about this time of year, start
flying south like birds do.

306
00:16:44,130 --> 00:16:46,970
He says, "I was familiar only
with the generally held view

307
00:16:46,970 --> 00:16:51,860
that bats felt with their wings
the proximity of obstacles."

308
00:16:51,860 --> 00:16:55,110
that was how people thought
they navigated around, by touch.

309
00:17:00,580 --> 00:17:02,580
"Several friends suggested
that I experiment

310
00:17:02,580 --> 00:17:05,720
with the ability of my
bats to avoid obstacles."

311
00:17:05,720 --> 00:17:07,460
Blah, blah, blah.

312
00:17:07,460 --> 00:17:12,140
"I decided that I should contact
a professor in the Harvard

313
00:17:12,140 --> 00:17:13,790
physics department.

314
00:17:13,790 --> 00:17:17,560
That was Professor GW Pierce,
inventor of the Pierce circuit

315
00:17:17,560 --> 00:17:19,930
for the stabilization of
radio frequency oscillator.

316
00:17:22,130 --> 00:17:25,270
Pierce had developed almost
the only apparatus then

317
00:17:25,270 --> 00:17:28,069
in existence that could
detect and generate

318
00:17:28,069 --> 00:17:32,660
a wide range of sounds
lying above the audio range.

319
00:17:32,660 --> 00:17:38,570
That is from 20,000 to almost
100,000 cycles per second.

320
00:17:38,570 --> 00:17:42,800
With some trepidation, I
approached Professor Pierce

321
00:17:42,800 --> 00:17:46,520
in the winter of 1938
with the suggestion

322
00:17:46,520 --> 00:17:48,960
that we use his apparatus
to listen to my bats.

323
00:17:50,470 --> 00:17:52,960
I found him eager to
try the experiment,

324
00:17:52,960 --> 00:17:54,430
particularly since
he was already

325
00:17:54,430 --> 00:17:56,790
engaged in extensive studies
of the high frequency

326
00:17:56,790 --> 00:17:57,880
sounds of insects.

327
00:17:59,970 --> 00:18:03,690
When I first brought
a cage full of bats,

328
00:18:03,690 --> 00:18:07,550
myotis lucifugus--" OK,
that's the little brown bat--

329
00:18:07,550 --> 00:18:10,130
"to Pierce's lab
and held the cage

330
00:18:10,130 --> 00:18:12,340
in front of the
parabolic horn, we

331
00:18:12,340 --> 00:18:16,520
were surprised and delighted to
hear a medley of raucous noises

332
00:18:16,520 --> 00:18:18,270
from the loudspeaker."

333
00:18:18,270 --> 00:18:22,850
So Griffin, as an
undergraduate, discovered

334
00:18:22,850 --> 00:18:27,520
that bats emitted
ultrasonic stimuli, OK?

335
00:18:27,520 --> 00:18:32,745
And he went on to pursue a
lifetime of research on bats.

336
00:18:33,920 --> 00:18:35,910
While he was still
an undergraduate,

337
00:18:35,910 --> 00:18:38,900
he designed some
experiments to see

338
00:18:38,900 --> 00:18:43,110
if the bats could use this
echolocation to avoid objects.

339
00:18:43,110 --> 00:18:46,940
And so he took a room,
turned out all the lights

340
00:18:46,940 --> 00:18:49,740
so the bats could
only use other senses.

341
00:18:49,740 --> 00:18:51,930
And he noticed that
they would fly around.

342
00:18:51,930 --> 00:18:56,210
And he didn't have a very
extensive equipment budget,

343
00:18:56,210 --> 00:19:01,480
so for objects, he went to the
store that sold piano wire.

344
00:19:01,480 --> 00:19:03,700
And he strung piano
wire from the ceiling

345
00:19:03,700 --> 00:19:05,770
to the floor of the room.

346
00:19:05,770 --> 00:19:07,690
And he let the bats fly around.

347
00:19:07,690 --> 00:19:10,730
And he knew that if something
touched the piano wire,

348
00:19:10,730 --> 00:19:15,280
he could hear a little
sound of the wire vibrating.

349
00:19:15,280 --> 00:19:18,480
And he had to go
down in diameter,

350
00:19:18,480 --> 00:19:21,760
to piano wire that was
the thickness of the width

351
00:19:21,760 --> 00:19:25,000
of a human hair,
before the bats finally

352
00:19:25,000 --> 00:19:26,950
started touching the wire.

353
00:19:26,950 --> 00:19:30,900
They could detect objects
even sub-millimeter in size.

354
00:19:30,900 --> 00:19:34,740
So their sense of echolocation
was really well developed,

355
00:19:34,740 --> 00:19:36,090
and very good.

356
00:19:36,090 --> 00:19:37,855
It could detect
very tiny targets.

357
00:19:39,370 --> 00:19:42,665
So that was one of his first,
and foremost, experiments.

358
00:19:44,437 --> 00:19:45,770
Now, I have some demonstrations.

359
00:19:47,240 --> 00:19:52,530
And some of them are from
Griffin's original work.

360
00:19:52,530 --> 00:20:00,540
And so, in these
demonstrations, you

361
00:20:00,540 --> 00:20:02,890
have a movie of the bat flying.

362
00:20:03,990 --> 00:20:08,940
And the target, this
time, is a small food item

363
00:20:08,940 --> 00:20:09,775
that's thrown up.

364
00:20:09,775 --> 00:20:10,775
I think it's a mealworm.

365
00:20:11,810 --> 00:20:14,580
So the investigator
throws up the mealworm.

366
00:20:14,580 --> 00:20:16,450
And the bat catches it.

367
00:20:16,450 --> 00:20:20,700
And on the audio
part of the track,

368
00:20:20,700 --> 00:20:23,160
you'll hear some popping.

369
00:20:23,160 --> 00:20:27,970
And I think that's a stroboscope
that's illuminating the image.

370
00:20:27,970 --> 00:20:30,530
You will also hear
a little chirp.

371
00:20:30,530 --> 00:20:32,590
And they're pretty
high frequency.

372
00:20:32,590 --> 00:20:36,010
But that is the bat
echolocating pulse going out.

373
00:20:36,010 --> 00:20:39,560
It's detected by
microphone, and transformed

374
00:20:39,560 --> 00:20:42,470
from the high frequencies
down into lower frequencies

375
00:20:42,470 --> 00:20:45,680
in your audio range,
so you can hear it.

376
00:20:45,680 --> 00:20:46,730
OK?

377
00:20:46,730 --> 00:20:49,950
And notice that,
number one, when

378
00:20:49,950 --> 00:20:53,010
the bat gets close to the
target, the chirps increase

379
00:20:53,010 --> 00:20:54,340
in frequency.

380
00:20:54,340 --> 00:20:56,350
And number two,
when the bat eats

381
00:20:56,350 --> 00:20:58,630
the target, the
chirps stop, right?

382
00:20:58,630 --> 00:21:02,690
Because unlike you or me,
they can't talk and eat

383
00:21:02,690 --> 00:21:03,690
at the same time.

384
00:21:09,010 --> 00:21:13,845
So those chirps are the
bat echolocating pulse.

385
00:21:15,485 --> 00:21:16,110
Here's the bat.

386
00:21:18,540 --> 00:21:20,235
Here's the target coming up.

387
00:21:25,620 --> 00:21:28,530
In that case, as
sometimes happens,

388
00:21:28,530 --> 00:21:30,950
the bat missed the target.

389
00:21:30,950 --> 00:21:32,040
So it's falling away.

390
00:21:43,600 --> 00:21:45,160
Here's the target coming up.

391
00:21:46,760 --> 00:21:50,090
In this case, the bat caught
it in the tip of its wing.

392
00:21:50,090 --> 00:21:52,120
And it brings the wing
in toward its mouth.

393
00:21:52,120 --> 00:21:54,090
And it eats the target.

394
00:21:54,090 --> 00:21:56,870
And it starts pulsing
again after it's

395
00:21:56,870 --> 00:21:57,960
swallowed the target.

396
00:22:08,115 --> 00:22:10,240
And there, I think it caught
it right in its mouth,

397
00:22:10,240 --> 00:22:11,750
without having to use its wings.

398
00:22:20,850 --> 00:22:21,350
OK.

399
00:22:21,350 --> 00:22:27,000
So these are some other films
that I won't go through.

400
00:22:27,000 --> 00:22:28,890
But they were some
experiments that Griffin

401
00:22:28,890 --> 00:22:34,610
did, testing the ability of
bats-- and certain species--

402
00:22:34,610 --> 00:22:36,730
to actually catch fish.

403
00:22:36,730 --> 00:22:40,690
And he was mystified about
this because-- as we've

404
00:22:40,690 --> 00:22:42,400
talked about--
sound and air, when

405
00:22:42,400 --> 00:22:46,510
it comes to a fluid boundary,
mostly reflects off.

406
00:22:46,510 --> 00:22:50,290
So it seemed unimaginable
that the bat echolocating

407
00:22:50,290 --> 00:22:52,770
pulse could go under
the water and would

408
00:22:52,770 --> 00:22:54,190
be reflected of the fish.

409
00:22:54,190 --> 00:22:57,650
So what he figured out
later is that, when

410
00:22:57,650 --> 00:23:00,510
there is a smooth
surface of the water,

411
00:23:00,510 --> 00:23:04,090
the bats did not
seem interested.

412
00:23:04,090 --> 00:23:06,060
But when the fish
came up and rippled

413
00:23:06,060 --> 00:23:09,370
the surface of the water,
that was what the bats we're

414
00:23:09,370 --> 00:23:12,000
actually detecting,
the little ripples

415
00:23:12,000 --> 00:23:14,515
on the surface of the water--
just as you see them visually.

416
00:23:18,120 --> 00:23:22,030
There's some videos of
bats catching fish here.

417
00:23:22,030 --> 00:23:23,250
Bats hanging out.

418
00:23:34,930 --> 00:23:36,960
Bats flying in rooms.

419
00:23:36,960 --> 00:23:37,960
Sorry about that.

420
00:23:41,330 --> 00:23:49,020
Now this last part of the demo
is from more modern experiments

421
00:23:49,020 --> 00:23:53,170
in which the bat
approaches a target.

422
00:23:53,170 --> 00:23:56,040
In this case, the target
is somewhere here.

423
00:23:56,040 --> 00:23:57,250
And it's tethered.

424
00:23:57,250 --> 00:23:58,285
The target is fixed.

425
00:23:59,620 --> 00:24:02,910
This is a spectrogram of
the bat echolocating pulse.

426
00:24:04,020 --> 00:24:08,420
And this is the bat
flying, in slow motion,

427
00:24:08,420 --> 00:24:09,345
to catch the target.

428
00:24:11,670 --> 00:24:13,460
And you can see the
tremendous increase

429
00:24:13,460 --> 00:24:15,450
in pulse repetition rate.

430
00:24:15,450 --> 00:24:17,850
As it eats the target,
it stops vocalizing.

431
00:24:19,190 --> 00:24:22,320
And now it starts again.

432
00:24:22,320 --> 00:24:25,610
And this'll be
repeated at least once.

433
00:24:25,610 --> 00:24:27,050
So here's another run.

434
00:24:27,050 --> 00:24:29,795
Here's the bat
spectrogram down here.

435
00:24:32,220 --> 00:24:33,830
And here's the bat coming in.

436
00:24:33,830 --> 00:24:35,350
Here is the target, right there.

437
00:24:57,820 --> 00:24:59,080
I guess I'd better stop that.

438
00:25:01,901 --> 00:25:02,400
OK.

439
00:25:02,400 --> 00:25:16,260
And so that second demo is
from Doctor Cynthia Moss,

440
00:25:16,260 --> 00:25:17,430
who used to be at Harvard.

441
00:25:17,430 --> 00:25:20,070
And now she's at the
University of Maryland.

442
00:25:20,070 --> 00:25:22,810
And she does extensive
work on bat echolocation.

443
00:25:27,000 --> 00:25:30,460
And so I think it clearly
shows the increase

444
00:25:30,460 --> 00:25:33,510
in pulse repetition rate as the
bat gets close to the target.

445
00:25:35,250 --> 00:25:36,310
Any questions on that?

446
00:25:38,050 --> 00:25:38,550
OK.

447
00:25:38,550 --> 00:25:43,770
So those were all the first
kind of bat I talked about,

448
00:25:43,770 --> 00:25:44,860
the FM bat.

449
00:25:48,170 --> 00:25:51,700
And now, let's get into
the second group of bats.

450
00:25:51,700 --> 00:25:57,491
And this group is
called CFFM bats.

451
00:25:57,491 --> 00:25:57,990
OK.

452
00:26:00,020 --> 00:26:03,390
And these are completely
different species of bats.

453
00:26:03,390 --> 00:26:08,440
They are new world CFFM bats
and old world CFFM bats.

454
00:26:08,440 --> 00:26:10,475
It probably has
evolved several times.

455
00:26:12,180 --> 00:26:17,160
The echolocating pulse and
echo are completely different,

456
00:26:17,160 --> 00:26:19,160
compared to the FM bat.

457
00:26:19,160 --> 00:26:22,100
So in the case of the
mustache bat, which

458
00:26:22,100 --> 00:26:26,110
is an example of CFFM bat,
this is the spectrogram.

459
00:26:26,110 --> 00:26:30,420
Again, frequency on the
y-axis and time on the x-axis.

460
00:26:32,340 --> 00:26:37,250
But in this case, instead of
the pulse sweeping downward,

461
00:26:37,250 --> 00:26:39,900
or a frequency modulated
very downward-- almost

462
00:26:39,900 --> 00:26:45,870
like a chirp-- instead, the
pulse is a constant frequency.

463
00:26:45,870 --> 00:26:49,340
So the CF stands for
constant frequency.

464
00:26:49,340 --> 00:26:51,360
That just means the
frequency is staying

465
00:26:51,360 --> 00:26:53,900
constant as a function of time.

466
00:26:53,900 --> 00:26:55,830
And that's this
flat section here.

467
00:26:58,230 --> 00:27:02,070
In the case of bat sounds,
just like human speech sounds,

468
00:27:02,070 --> 00:27:03,195
there are many harmonics.

469
00:27:04,730 --> 00:27:07,860
There's the first harmonic.

470
00:27:07,860 --> 00:27:09,050
That's called CF1.

471
00:27:10,930 --> 00:27:15,740
There's the second harmonic,
an octave above, CF2.

472
00:27:17,450 --> 00:27:19,340
There's a third harmonic, CF3.

473
00:27:20,750 --> 00:27:23,000
And there's a fourth
harmonic, CF4.

474
00:27:25,490 --> 00:27:30,190
And it's conventional on this
kind of spectrogram display

475
00:27:30,190 --> 00:27:33,150
to illustrate the sounds
that have the most

476
00:27:33,150 --> 00:27:36,840
energy with the
boldest marking here.

477
00:27:36,840 --> 00:27:42,560
So CF2 is the one that has the
highest sound pressure level.

478
00:27:42,560 --> 00:27:44,960
And so that's the darkest here.

479
00:27:44,960 --> 00:27:50,470
These other ones, especially
CF1 and CF4, are lower in level.

480
00:27:50,470 --> 00:27:51,970
They're not as intense.

481
00:27:51,970 --> 00:27:54,750
And so they're not as
black on this display.

482
00:27:54,750 --> 00:27:59,240
And in this display of the FM
bat, the pulse is very intense.

483
00:27:59,240 --> 00:28:02,510
And the echo is, of
course, much reduced.

484
00:28:03,520 --> 00:28:06,340
Echolocating pulses
can be 110 dB,

485
00:28:06,340 --> 00:28:09,920
if you measure them
right at the bat's mouth.

486
00:28:09,920 --> 00:28:11,810
They can be very intense.

487
00:28:11,810 --> 00:28:14,660
And, of course, the bat
contracts its middle ear

488
00:28:14,660 --> 00:28:18,410
muscles to prevent those
kinds of intense stimuli

489
00:28:18,410 --> 00:28:20,870
from damaging its own ears.

490
00:28:20,870 --> 00:28:24,410
And then it relaxes the
muscles when the echo comes by,

491
00:28:24,410 --> 00:28:26,985
and its hearing is fine.

492
00:28:28,070 --> 00:28:28,570
OK.

493
00:28:28,570 --> 00:28:34,890
So at the end of the CF portion,
this echo-locating pulse.

494
00:28:34,890 --> 00:28:37,390
There is a little FM sweep.

495
00:28:37,390 --> 00:28:37,890
OK.

496
00:28:37,890 --> 00:28:39,780
So you can appreciate,
maybe, that there's

497
00:28:39,780 --> 00:28:45,670
an FM1, a little FM2
sweep, a little FM3

498
00:28:45,670 --> 00:28:48,370
sweep, and a little Fm4 sweep.

499
00:28:50,050 --> 00:28:57,030
And it's thought that this
bat uses the FM of the pulse,

500
00:28:57,030 --> 00:28:59,860
and the FM of the
return echo, to get

501
00:28:59,860 --> 00:29:03,290
a measure of the distance that
the target is from the bat.

502
00:29:04,261 --> 00:29:04,760
OK.

503
00:29:04,760 --> 00:29:07,664
It if comes back
in 10 milliseconds,

504
00:29:07,664 --> 00:29:09,080
and you know the
sound of velocity

505
00:29:09,080 --> 00:29:12,450
is 340 meters per second,
you can figure out

506
00:29:12,450 --> 00:29:13,660
how close that is.

507
00:29:15,020 --> 00:29:16,940
And this bat can
do that, as well.

508
00:29:16,940 --> 00:29:19,340
Now, what's going on
with this CF part?

509
00:29:21,200 --> 00:29:25,940
Well, as you can see
on the spectrogram,

510
00:29:25,940 --> 00:29:29,670
the CF of the pulse
is not exactly

511
00:29:29,670 --> 00:29:32,420
the same as the CF of the echo.

512
00:29:33,850 --> 00:29:34,570
OK.

513
00:29:34,570 --> 00:29:38,100
The echo has shifted up to be
a little higher in frequency

514
00:29:38,100 --> 00:29:38,790
in each case.

515
00:29:40,020 --> 00:29:41,520
Now, how can
frequencies be shifted?

516
00:29:42,780 --> 00:29:45,260
Well, it has to do
with the Doppler shift.

517
00:30:12,380 --> 00:30:12,880
OK.

518
00:30:12,880 --> 00:30:17,410
So this is a shift in, in
this case, sound frequency.

519
00:30:24,120 --> 00:30:26,955
But you can have a Doppler
shift for any kind of wave.

520
00:30:28,040 --> 00:30:31,300
For example, you can have a
Doppler shift for light waves.

521
00:30:32,840 --> 00:30:35,010
If you've studied
the Big Bang theory

522
00:30:35,010 --> 00:30:38,370
of the origin of the universe,
there's a big explosion, right?

523
00:30:38,370 --> 00:30:42,620
Everything exploded out and
is moving far away from us.

524
00:30:42,620 --> 00:30:45,230
So you look at the light
coming from a star that's

525
00:30:45,230 --> 00:30:47,400
moving away from you.

526
00:30:47,400 --> 00:30:52,400
It's actually shifted a little
bit to longer wavelengths,

527
00:30:52,400 --> 00:30:55,070
toward the more reddish
hues, because it's

528
00:30:55,070 --> 00:30:56,200
moving away from you.

529
00:30:57,880 --> 00:31:02,260
So Doppler shifts have to
do with wave sources that

530
00:31:02,260 --> 00:31:04,440
are moving relative
to the receiver,

531
00:31:04,440 --> 00:31:07,550
or the receiver moving
relative to the emitter.

532
00:31:09,120 --> 00:31:12,590
Another example of a Doppler
shift, this time for sound,

533
00:31:12,590 --> 00:31:16,770
would be if you were in the
grandstand of a race track,

534
00:31:16,770 --> 00:31:18,970
and the race cars were
going around a big oval.

535
00:31:20,150 --> 00:31:20,650
OK.

536
00:31:20,650 --> 00:31:22,316
And you hear the sound
of their engines.

537
00:31:23,330 --> 00:31:27,930
As the race car comes toward
you, along the straight away,

538
00:31:27,930 --> 00:31:29,620
it sounds like it's
higher in pitch

539
00:31:29,620 --> 00:31:31,340
because it's moving toward you.

540
00:31:32,930 --> 00:31:37,910
As it passes you and then
starts to move away from you,

541
00:31:37,910 --> 00:31:39,710
it sounds like it's
lower in pitch.

542
00:31:39,710 --> 00:31:46,320
So the thing you'd
hear would be [BUZZING]

543
00:31:46,320 --> 00:31:49,660
as each race car went by you.

544
00:31:49,660 --> 00:31:54,630
So, as the race car is here, and
you're the observer listening

545
00:31:54,630 --> 00:31:58,320
here, it emits-- let's
say-- a pulse of sound.

546
00:32:00,461 --> 00:32:00,960
OK.

547
00:32:00,960 --> 00:32:03,210
This might be the peak
of the wave front,

548
00:32:03,210 --> 00:32:08,010
if it were just a
sinusoid, let's say.

549
00:32:09,450 --> 00:32:12,700
Now, by the time a race
car coming toward you

550
00:32:12,700 --> 00:32:16,940
has emitted the next peak,
the race car's actually moved.

551
00:32:18,120 --> 00:32:19,020
OK.

552
00:32:19,020 --> 00:32:20,350
So the peak is here.

553
00:32:20,350 --> 00:32:22,620
And the next peak is emitted.

554
00:32:22,620 --> 00:32:23,950
And it's very close together.

555
00:32:25,060 --> 00:32:27,740
If the race car is
moving away from you,

556
00:32:27,740 --> 00:32:29,960
it emits one peak of sound.

557
00:32:29,960 --> 00:32:32,850
And then by the time it
emits the next peak of sound,

558
00:32:32,850 --> 00:32:35,130
it's moved a little
away from you.

559
00:32:35,130 --> 00:32:37,275
The peaks are farther apart.

560
00:32:38,620 --> 00:32:42,490
And we know the sound source
that has a quick oscillation

561
00:32:42,490 --> 00:32:43,865
sounds like a high frequency.

562
00:32:45,520 --> 00:32:48,700
And the sound source that
has a very slow oscillation

563
00:32:48,700 --> 00:32:49,875
sounds like a low frequency.

564
00:32:52,000 --> 00:32:57,220
So Doppler shifts are
positive, higher frequencies

565
00:32:57,220 --> 00:32:59,950
for objects making
sound moving toward you.

566
00:33:01,160 --> 00:33:05,800
And Doppler shifts are low,
or negative, in frequency.

567
00:33:05,800 --> 00:33:08,080
They make lower
frequencies if the object

568
00:33:08,080 --> 00:33:09,565
is moving away from you.

569
00:33:09,565 --> 00:33:11,500
It's just the physical
characteristics

570
00:33:11,500 --> 00:33:13,460
of sound coupled with movement.

571
00:33:16,450 --> 00:33:17,310
OK.

572
00:33:17,310 --> 00:33:23,090
In the case of these positive
Doppler shifted echoes,

573
00:33:23,090 --> 00:33:26,280
we know either that
the object that

574
00:33:26,280 --> 00:33:31,040
has been reflecting the echo
is moving toward the bat

575
00:33:31,040 --> 00:33:35,210
or, conversely, that
the bat has been flying

576
00:33:35,210 --> 00:33:38,370
toward the object that
is emitting the echo.

577
00:33:39,610 --> 00:33:42,107
So a positive
Doppler shift means

578
00:33:42,107 --> 00:33:43,565
things are getting
closer together.

579
00:33:44,630 --> 00:33:46,320
And a negative
Doppler shift would

580
00:33:46,320 --> 00:33:49,530
be things are going
farther apart.

581
00:33:49,530 --> 00:33:53,080
So not only does the
bat, from its FM sweep,

582
00:33:53,080 --> 00:33:57,140
get an indication of how far
it is away from the target.

583
00:33:57,140 --> 00:34:00,490
But by its Doppler
shifted CF part,

584
00:34:00,490 --> 00:34:05,600
it gets an idea of the
relative motion of the target.

585
00:34:05,600 --> 00:34:07,390
Why is that important?

586
00:34:07,390 --> 00:34:09,840
These types of bats,
instead of hunting

587
00:34:09,840 --> 00:34:12,570
in open air-- like
the FM bats we

588
00:34:12,570 --> 00:34:15,650
have-- these are tropical bats.

589
00:34:15,650 --> 00:34:18,429
And they hunt in
dense vegetation,

590
00:34:18,429 --> 00:34:20,670
like the tropical rain forests.

591
00:34:20,670 --> 00:34:24,020
And there are millions
of objects around.

592
00:34:24,020 --> 00:34:24,900
There are leaves.

593
00:34:24,900 --> 00:34:25,659
There's vines.

594
00:34:26,860 --> 00:34:29,190
There's lots of clutter here.

595
00:34:29,190 --> 00:34:32,099
What the bat is interested
in is not stationary clutter.

596
00:34:33,300 --> 00:34:36,670
Presumably, things that are
Doppler shifted all the same.

597
00:34:36,670 --> 00:34:39,650
But something that is
moving in all this clutter.

598
00:34:39,650 --> 00:34:41,370
It's very interested
in moving objects

599
00:34:41,370 --> 00:34:43,005
because that's a
life form, perhaps.

600
00:34:44,250 --> 00:34:47,389
And just imagine the
kind of a Doppler shift

601
00:34:47,389 --> 00:34:50,670
that would be made
by a moth, first

602
00:34:50,670 --> 00:34:53,909
beating its wing toward
you, if you were the bat.

603
00:34:53,909 --> 00:34:56,980
And then beating its wing
downward, and away, from you.

604
00:34:56,980 --> 00:34:57,480
OK.

605
00:34:57,480 --> 00:35:01,180
That's a very complicated
positive and negative Doppler

606
00:35:01,180 --> 00:35:05,430
shift that the bat would
pick up on its return echo.

607
00:35:05,430 --> 00:35:08,540
And that would be a very
interesting target to the bat.

608
00:35:08,540 --> 00:35:09,050
Yeah.

609
00:35:09,050 --> 00:35:12,026
AUDIENCE: And how do they
tell that the difference is

610
00:35:12,026 --> 00:35:14,436
when they're moving versus
if the object is [INAUDIBLE]?

611
00:35:14,436 --> 00:35:15,560
PROFESSOR: They don't care.

612
00:35:15,560 --> 00:35:19,410
All they care about is that
they might be getting thousands

613
00:35:19,410 --> 00:35:24,010
of Doppler shifted echoes from
the targets in front of them.

614
00:35:24,010 --> 00:35:27,330
Let's say they're flying toward
a whole bunch of tropical rain

615
00:35:27,330 --> 00:35:28,862
forest vegetation.

616
00:35:28,862 --> 00:35:31,320
There are going to be thousands
of positive Doppler shifted

617
00:35:31,320 --> 00:35:32,020
echoes.

618
00:35:32,020 --> 00:35:37,160
And then something is moving
away from them, or toward them,

619
00:35:37,160 --> 00:35:39,340
faster than the background.

620
00:35:39,340 --> 00:35:41,040
All they care is that.

621
00:35:41,040 --> 00:35:44,110
It's Doppler shifted different
relative to the background.

622
00:35:45,680 --> 00:35:47,820
They're just looking
for something special.

623
00:35:47,820 --> 00:35:51,360
That is, something that's moving
relative to the background.

624
00:35:54,550 --> 00:35:55,830
Any other questions on that?

625
00:36:00,310 --> 00:36:07,290
So you can, of course,
design sonar systems.

626
00:36:07,290 --> 00:36:13,100
Submarine sonar systems work by
sending out a pulse of sound,

627
00:36:13,100 --> 00:36:15,220
and listening for the echo.

628
00:36:15,220 --> 00:36:17,730
And most of the kinds
of sonar systems

629
00:36:17,730 --> 00:36:21,480
that we have send out a
ping, which is a frequency

630
00:36:21,480 --> 00:36:24,800
swept signal, and
listen for the echo.

631
00:36:24,800 --> 00:36:28,315
Because it's mostly interested
in the distance from a target,

632
00:36:28,315 --> 00:36:30,620
and whether there's
a target out there.

633
00:36:30,620 --> 00:36:35,180
This is a very unusual type
of echolocation, or sonar,

634
00:36:35,180 --> 00:36:35,680
if you will.

635
00:36:38,540 --> 00:36:39,900
Now why am I bringing this up?

636
00:36:39,900 --> 00:36:42,160
Well, it's very
interesting because the bat

637
00:36:42,160 --> 00:36:45,580
gets two queues
instead of just one.

638
00:36:45,580 --> 00:36:52,230
Also because a lot of work on
bat cortex has used CFFM bats.

639
00:36:52,230 --> 00:36:55,740
And one of the most popular
has been the so-called mustache

640
00:36:55,740 --> 00:37:00,950
bat, I believe because
it has a noseleaf that's

641
00:37:00,950 --> 00:37:03,920
between its upper lip--
it looks like a mustache--

642
00:37:03,920 --> 00:37:04,887
and its nostrils.

643
00:37:04,887 --> 00:37:06,220
So it's called the mustache bat.

644
00:37:07,310 --> 00:37:09,700
And a lot of this
work has been done

645
00:37:09,700 --> 00:37:14,900
by a researcher, who is
still active, at Washington

646
00:37:14,900 --> 00:37:16,480
University in Saint Louis.

647
00:37:16,480 --> 00:37:20,000
And his name is Nobua Suga.

648
00:37:25,770 --> 00:37:29,280
And he was the first,
really, to work successfully

649
00:37:29,280 --> 00:37:30,835
on the bat auditory cortex.

650
00:37:33,100 --> 00:37:39,680
A lot of his work comes from
the 1970s, '80s, and '90s.

651
00:37:39,680 --> 00:37:43,280
And before I explain this
bottom part of this slide,

652
00:37:43,280 --> 00:37:47,030
let me just go on and show
you the kinds of experiments

653
00:37:47,030 --> 00:37:47,835
that Suga did.

654
00:37:47,835 --> 00:37:52,020
And here's one from one of
his publications in the 1980s.

655
00:37:52,020 --> 00:37:57,540
So Suga's work was innovative
because he played around--

656
00:37:57,540 --> 00:38:01,020
well, first he rationalized, OK.

657
00:38:01,020 --> 00:38:04,430
I could try any sound
system I'd like to.

658
00:38:04,430 --> 00:38:05,990
I could try clicks.

659
00:38:05,990 --> 00:38:07,600
I could try pure tones.

660
00:38:07,600 --> 00:38:09,480
I could try noise.

661
00:38:09,480 --> 00:38:10,900
I could try speech.

662
00:38:10,900 --> 00:38:14,650
I could try-- but why don't
I try what the bat listens to

663
00:38:14,650 --> 00:38:16,220
over and over?

664
00:38:16,220 --> 00:38:17,815
It listens to a pulse.

665
00:38:19,170 --> 00:38:21,120
And then a little
bit later, an echo.

666
00:38:22,460 --> 00:38:26,470
And this turned out to be
a very, very wise choice,

667
00:38:26,470 --> 00:38:28,040
as we'll see in a minute.

668
00:38:28,040 --> 00:38:30,710
Secondly, about the
time of the 1970s

669
00:38:30,710 --> 00:38:34,840
and '80s, speech
researchers in human speech

670
00:38:34,840 --> 00:38:37,831
were using synthesized speech.

671
00:38:37,831 --> 00:38:40,080
Of course, we all know what
synthesized speech is now.

672
00:38:40,080 --> 00:38:42,170
But back then, it
was very novel.

673
00:38:42,170 --> 00:38:46,850
And Suga says, well, I'm
going to use synthesized bat

674
00:38:46,850 --> 00:38:48,630
echolocating calls.

675
00:38:48,630 --> 00:38:51,315
And here is an example
of a synthesized pulse.

676
00:38:52,920 --> 00:38:55,310
So this is for the mustache bat.

677
00:38:55,310 --> 00:39:03,010
And this looks like CF1-FM1,
CF2-FM2, and CF3-FM3.

678
00:39:04,560 --> 00:39:07,130
So he's just using
three harmonics.

679
00:39:07,130 --> 00:39:08,950
So one thing about
synthesized calls

680
00:39:08,950 --> 00:39:13,240
is you can do things like
dispense with one harmonic,

681
00:39:13,240 --> 00:39:18,150
if you want to, easily take
it out, and put it an echo.

682
00:39:18,150 --> 00:39:19,830
So here's a pulse.

683
00:39:19,830 --> 00:39:20,870
And here's an echo.

684
00:39:20,870 --> 00:39:22,480
It's a little bit
Doppler shifted.

685
00:39:23,510 --> 00:39:27,720
You can look at the no response
to the pulse, and to the echo.

686
00:39:27,720 --> 00:39:31,440
And this lower
trace is a histogram

687
00:39:31,440 --> 00:39:34,350
from a single neuron
in the auditory cortex

688
00:39:34,350 --> 00:39:37,370
of the echolocating bat to
a pulse, and to an echo.

689
00:39:37,370 --> 00:39:38,510
There's not much response.

690
00:39:40,380 --> 00:39:43,250
Suga found that when
you play a pulse

691
00:39:43,250 --> 00:39:47,800
and, a short time later, an
echo, you get a huge response.

692
00:39:47,800 --> 00:39:49,640
And that's what's
indicated here.

693
00:39:49,640 --> 00:39:52,330
So this is the
pulse-echo combination.

694
00:39:53,410 --> 00:39:55,620
And these are
synthesized stimuli.

695
00:39:57,520 --> 00:40:00,370
And you can read in
the original paper,

696
00:40:00,370 --> 00:40:02,400
it looks like it's
not given here,

697
00:40:02,400 --> 00:40:05,765
exactly what the delay is
between the pulse and the echo.

698
00:40:07,650 --> 00:40:11,590
But Suga tried various
pulse-echo delays.

699
00:40:11,590 --> 00:40:15,310
And he found that cortical
neurons, in many cases,

700
00:40:15,310 --> 00:40:19,550
were very sensitive
to the exact delay

701
00:40:19,550 --> 00:40:21,930
between the pulse and the echo.

702
00:40:21,930 --> 00:40:24,195
So they were, if you
will, delay tuned.

703
00:40:26,310 --> 00:40:30,850
And that's indicated
here, in the first bullet.

704
00:40:33,110 --> 00:40:35,360
"The neuron pictured above
responds little to--" blah,

705
00:40:35,360 --> 00:40:36,990
blah, blah. "--pulse
of an echo alone.

706
00:40:38,290 --> 00:40:41,220
But vigorously to a
pulse followed by an echo

707
00:40:41,220 --> 00:40:41,970
at certain delay.

708
00:40:41,970 --> 00:40:44,710
In this case, 9.3
milliseconds is

709
00:40:44,710 --> 00:40:47,060
the best delay for this neuron."

710
00:40:47,060 --> 00:40:48,650
So this is a delay tuned neuron.

711
00:40:50,900 --> 00:40:56,660
Once Suga did recordings from
different parts of the bat

712
00:40:56,660 --> 00:41:00,600
cortex, he found that the
best delay was actually

713
00:41:00,600 --> 00:41:04,270
mapped along the
surface of the cortex.

714
00:41:04,270 --> 00:41:09,020
So here is some of his
work from the 1990s,

715
00:41:09,020 --> 00:41:13,470
showing you maps of best
delays, and other properties,

716
00:41:13,470 --> 00:41:15,560
in the bat auditory cortex.

717
00:41:15,560 --> 00:41:19,740
So here is a side view
of the bat cortex.

718
00:41:19,740 --> 00:41:21,310
This is looking
at the left side.

719
00:41:21,310 --> 00:41:27,020
This is the front, where
the olfactory areas are.

720
00:41:27,020 --> 00:41:30,410
Way in the back would
be the occipital cortex.

721
00:41:30,410 --> 00:41:32,670
And our old friend,
the auditory cortex,

722
00:41:32,670 --> 00:41:37,750
is in the temporal region,
on the side of the brain,

723
00:41:37,750 --> 00:41:39,030
just like it was in the cat.

724
00:41:39,030 --> 00:41:40,930
And like it is in the human.

725
00:41:40,930 --> 00:41:41,860
And here is A1.

726
00:41:43,080 --> 00:41:47,220
And this rectangle
here is expanded here.

727
00:41:47,220 --> 00:41:49,290
And some of Suga's
maps are shown.

728
00:41:51,360 --> 00:41:54,810
This part right here--
the biggest part--

729
00:41:54,810 --> 00:42:00,290
is cortical field A1, which,
as we've seen in other animals,

730
00:42:00,290 --> 00:42:04,150
is the tonotopically
organized field.

731
00:42:04,150 --> 00:42:06,465
And it's tonotopically
organized in this bat.

732
00:42:07,640 --> 00:42:13,230
And these numbers and lines
are the ISO frequency laminae.

733
00:42:13,230 --> 00:42:14,890
So remember, the
experiment here is

734
00:42:14,890 --> 00:42:20,120
to go in and sample at a
specific place in the cortex,

735
00:42:20,120 --> 00:42:22,250
and find the
characteristic frequency

736
00:42:22,250 --> 00:42:23,670
for neurons in that column.

737
00:42:25,480 --> 00:42:28,220
And then move the
electrode a little bit.

738
00:42:28,220 --> 00:42:28,910
Do the same.

739
00:42:28,910 --> 00:42:29,890
Get the tuning curve.

740
00:42:29,890 --> 00:42:32,090
Get the CF for those neurons.

741
00:42:32,090 --> 00:42:33,140
And so on and so forth.

742
00:42:33,140 --> 00:42:35,470
And build up a map here.

743
00:42:35,470 --> 00:42:39,710
So just like in the
cat, posterior areas

744
00:42:39,710 --> 00:42:41,610
are tuned to low CF.

745
00:42:41,610 --> 00:42:44,240
Low CFs in the bat
are 20 kilohertz.

746
00:42:44,240 --> 00:42:46,305
We're dealing with very,
very high frequencies.

747
00:42:47,410 --> 00:42:51,460
As you go more rostrally, the
CFs get increasingly high.

748
00:42:51,460 --> 00:42:55,920
And at the very rostral end of
A1, the CF is 100 kilohertz.

749
00:42:55,920 --> 00:42:56,770
Extremely high.

750
00:42:58,200 --> 00:43:01,680
And everything looks
exactly like other mammals,

751
00:43:01,680 --> 00:43:06,700
except for this huge area
right in the middle of A1.

752
00:43:08,210 --> 00:43:10,610
And almost all of
the neurons here

753
00:43:10,610 --> 00:43:14,940
are tuned to between
61 and 66 kilohertz.

754
00:43:16,300 --> 00:43:18,260
And you should perk up
your ears a little bit

755
00:43:18,260 --> 00:43:22,740
because that is where
the most intense harmonic

756
00:43:22,740 --> 00:43:26,410
of echolocating pulse is,
right around 61 kilohertz.

757
00:43:28,130 --> 00:43:30,940
And a lot of the Doppler
shifted echoes are just

758
00:43:30,940 --> 00:43:32,560
going to be a little
bit above that.

759
00:43:32,560 --> 00:43:35,500
If the bat is flying
toward the target,

760
00:43:35,500 --> 00:43:38,090
this region goes up
then to 66 kilohertz.

761
00:43:39,380 --> 00:43:46,100
So then there is an expanded
region of the A1 of the bat

762
00:43:46,100 --> 00:43:50,690
that's tuned to a very important
frequency for the echolocating

763
00:43:50,690 --> 00:43:51,190
signal.

764
00:43:52,370 --> 00:43:57,490
And, at first, this was
called an acoustic fovea.

765
00:44:08,850 --> 00:44:13,360
Because if you go down into
lower nuclei of the bat

766
00:44:13,360 --> 00:44:17,110
pathway, and if you actually
go into the cochlea,

767
00:44:17,110 --> 00:44:21,470
you find an expanded region
of the cochlea devoted

768
00:44:21,470 --> 00:44:23,010
to these same frequencies.

769
00:44:23,010 --> 00:44:24,960
That is, you go along
the basilar membrane,

770
00:44:24,960 --> 00:44:28,991
starting at the
most apical regions,

771
00:44:28,991 --> 00:44:29,990
and you march down them.

772
00:44:29,990 --> 00:44:32,330
When you get to the
61 kilohertz place,

773
00:44:32,330 --> 00:44:36,920
there's a lot of cochlea
devoted to processing that area.

774
00:44:36,920 --> 00:44:39,860
And so the fovea,
the eyes, where

775
00:44:39,860 --> 00:44:45,200
you have lots of receptor cells
packed in to a certain part.

776
00:44:45,200 --> 00:44:47,960
And this is where you have a
lot of hair cells packed in,

777
00:44:47,960 --> 00:44:50,615
or expanded region of
the basilar membrane,

778
00:44:50,615 --> 00:44:53,880
where lots of hair
cells processing

779
00:44:53,880 --> 00:44:55,620
this small range of frequencies.

780
00:44:55,620 --> 00:44:59,880
So this is very much
different from other mammals.

781
00:44:59,880 --> 00:45:03,470
And the cochlea of this CFFM
bat is also very different.

782
00:45:05,600 --> 00:45:08,890
Now, we were talking
about delay to neurons.

783
00:45:08,890 --> 00:45:13,220
And Suga found a very
interesting area near A1

784
00:45:13,220 --> 00:45:16,800
in which there is a
mapping for best delay.

785
00:45:16,800 --> 00:45:18,475
And that's indicated here.

786
00:45:19,550 --> 00:45:26,000
And the best delays are marching
from short to longer best

787
00:45:26,000 --> 00:45:28,640
delays, as these
arrows go along here.

788
00:45:29,930 --> 00:45:34,340
Now they're marked
FM1, FM2, FM3.

789
00:45:34,340 --> 00:45:35,740
So what does all that mean?

790
00:45:39,060 --> 00:45:44,840
So Suga found that with his
synthesized pulses and echoes,

791
00:45:44,840 --> 00:45:47,350
he could dissect this
rather complicated

792
00:45:47,350 --> 00:45:52,980
pulse-echo constellation
into smaller parts.

793
00:45:52,980 --> 00:45:55,720
And here's an example of
a stimulus where you have,

794
00:45:55,720 --> 00:46:00,280
it looks like, CF2-FM2, CF3-FM3.

795
00:46:02,390 --> 00:46:06,810
And you have the
echo for CF1-FM1,

796
00:46:06,810 --> 00:46:09,180
and the echo for CF3-FM3.

797
00:46:09,180 --> 00:46:12,850
And that hardly gave any
response to the neurons.

798
00:46:12,850 --> 00:46:18,810
Here's an example where you
have only CF1-FM1 for the pulse,

799
00:46:18,810 --> 00:46:22,220
and only CF2-FM2 for the echo.

800
00:46:22,220 --> 00:46:23,725
And it gave a big response.

801
00:46:25,810 --> 00:46:27,160
And you could do even more.

802
00:46:27,160 --> 00:46:33,630
You can strip off
everything except the FM1

803
00:46:33,630 --> 00:46:35,365
and the echo FM2.

804
00:46:37,030 --> 00:46:39,840
And you get a big
response from the neuron.

805
00:46:39,840 --> 00:46:42,090
So this type of
neuron, then, would

806
00:46:42,090 --> 00:46:48,800
be called an FM1-FM2
best delay neuron.

807
00:46:48,800 --> 00:46:50,180
FM1 is the pulse.

808
00:46:50,180 --> 00:46:51,730
FM2 is the echo.

809
00:46:51,730 --> 00:46:53,680
And with a certain
delay between those two,

810
00:46:53,680 --> 00:46:57,390
you get as big a response as
with the whole constellation

811
00:46:57,390 --> 00:46:58,317
of pulse and echo.

812
00:46:59,630 --> 00:47:04,510
And those neurons were located
in this specific region, called

813
00:47:04,510 --> 00:47:05,010
FM1-FM2.

814
00:47:07,410 --> 00:47:11,150
And their delays were
mapped along this axis,

815
00:47:11,150 --> 00:47:16,606
with delays going from
0.4 to 18 milliseconds.

816
00:47:18,290 --> 00:47:20,170
And knowing the
velocity of sound,

817
00:47:20,170 --> 00:47:23,730
you can convert that
to a target range

818
00:47:23,730 --> 00:47:27,470
of between 7 and
310 centimeters.

819
00:47:27,470 --> 00:47:30,160
That's how far the
target was from the bat

820
00:47:30,160 --> 00:47:32,550
at that specific best delay.

821
00:47:32,550 --> 00:47:36,300
Suga also found some
other best delay regions.

822
00:47:36,300 --> 00:47:41,420
For example, FM2, FM3,
so on and so forth

823
00:47:41,420 --> 00:47:43,460
in other adjacent
parts of cortex.

824
00:47:43,460 --> 00:47:46,130
And this is really
beautiful work,

825
00:47:46,130 --> 00:47:53,300
showing specializations for
cortical neuron response.

826
00:47:53,300 --> 00:47:57,090
And for showing mappings
for those specializations

827
00:47:57,090 --> 00:47:58,880
in the bat cortex.

828
00:47:58,880 --> 00:48:03,270
We don't really have any data
anywhere near as beautiful

829
00:48:03,270 --> 00:48:08,820
on non-echolocating mammalian
cortex that show specialization

830
00:48:08,820 --> 00:48:14,080
for specific features of sound
stimuli as we do like this

831
00:48:14,080 --> 00:48:15,300
in the bat cortex.

832
00:48:15,300 --> 00:48:17,040
And this is really
beautiful work.

833
00:48:17,040 --> 00:48:20,770
This is Nobel Prize
deserving work

834
00:48:20,770 --> 00:48:25,530
because it really shows us
what this bat cortex is doing.

835
00:48:25,530 --> 00:48:27,885
It's responding to specific
features of the pulse.

836
00:48:29,260 --> 00:48:32,340
And the return echo delay
a specific delay later.

837
00:48:32,340 --> 00:48:33,718
So it's very beautiful work.

838
00:48:39,460 --> 00:48:42,210
Let me just mention
one other region here.

839
00:48:42,210 --> 00:48:46,070
Suga showed nearby, a
region where the neurons are

840
00:48:46,070 --> 00:48:49,450
specialized to
certain combinations

841
00:48:49,450 --> 00:48:53,340
of the constant
frequency of the echo.

842
00:48:53,340 --> 00:48:56,590
And then he showed
a Doppler shifted

843
00:48:56,590 --> 00:49:00,250
constant [INAUDIBLE]
pulse and CF of the echo.

844
00:49:00,250 --> 00:49:03,569
So this is the CFCF
region right over here.

845
00:49:13,730 --> 00:49:14,980
Yeah, question.

846
00:49:14,980 --> 00:49:17,537
AUDIENCE: In the last diagram--

847
00:49:17,537 --> 00:49:19,120
PROFESSOR: This one
or the one before?

848
00:49:19,120 --> 00:49:20,050
AUDIENCE: This one right here.

849
00:49:20,050 --> 00:49:20,633
PROFESSOR: OK.

850
00:49:20,633 --> 00:49:22,980
AUDIENCE: The last graph,
like the middle bottom.

851
00:49:22,980 --> 00:49:24,246
PROFESSOR: This guy?

852
00:49:24,246 --> 00:49:28,214
AUDIENCE: Why is that the
neuron is responding, like,

853
00:49:28,214 --> 00:49:33,680
before the onset frequency?

854
00:49:33,680 --> 00:49:35,360
PROFESSOR: I don't
know why that is.

855
00:49:36,380 --> 00:49:42,429
There's some clue to that, as to
why this stimulus starts here.

856
00:49:42,429 --> 00:49:42,970
I don't know.

857
00:49:45,210 --> 00:49:47,196
I don't know the answer to that.

858
00:49:47,196 --> 00:49:50,790
Let's see if it says
anything in the caption.

859
00:49:55,650 --> 00:49:56,290
I don't know.

860
00:49:56,290 --> 00:49:57,790
I don't know why that is.

861
00:49:57,790 --> 00:49:58,470
Sorry.

862
00:49:58,470 --> 00:50:01,720
I'll have to dig out the
paper and figure that out.

863
00:50:03,180 --> 00:50:04,200
Any other questions?

864
00:50:09,720 --> 00:50:13,710
So one thing that's gone
on after Sugo's early work

865
00:50:13,710 --> 00:50:17,480
on these specializations
has asked the question,

866
00:50:17,480 --> 00:50:21,810
is this really happening
in the auditory cortex?

867
00:50:21,810 --> 00:50:25,460
Or is the cortex just
merely a reflection

868
00:50:25,460 --> 00:50:29,770
of some beautiful processing at
a lower level of the pathway?

869
00:50:29,770 --> 00:50:35,140
And to a certain extent,
best delay sensitivity

870
00:50:35,140 --> 00:50:36,640
is found at lower levels.

871
00:50:36,640 --> 00:50:39,800
For example, the
inferior colliculus

872
00:50:39,800 --> 00:50:42,330
has some best
delay tuned neurons

873
00:50:42,330 --> 00:50:43,950
in the echolocating bat.

874
00:50:43,950 --> 00:50:47,760
So it probably has more
in the auditory cortex.

875
00:50:47,760 --> 00:50:50,970
But they can arise at
the inferior colliculus.

876
00:50:57,330 --> 00:50:57,880
OK.

877
00:50:57,880 --> 00:51:03,060
So that's what I wanted to
say about bat echolocation.

878
00:51:03,060 --> 00:51:06,760
And now I'm going to move on and
spend the last part of today's

879
00:51:06,760 --> 00:51:09,000
class talking about
speech sounds.

880
00:51:10,370 --> 00:51:13,940
So we had this particular
slide in an earlier lecture,

881
00:51:13,940 --> 00:51:16,930
I think the very first
lecture that I gave,

882
00:51:16,930 --> 00:51:18,760
talking about what
speech sounds are.

883
00:51:23,110 --> 00:51:28,070
So speech sounds, obviously,
are formed in humans

884
00:51:28,070 --> 00:51:33,600
by the vocal cords,
or vocal folds,

885
00:51:33,600 --> 00:51:38,170
closing and opening during
airflow from the lungs

886
00:51:38,170 --> 00:51:39,590
to the upper vocal tract.

887
00:51:41,180 --> 00:51:46,180
And this closing and
opening of the glottis

888
00:51:46,180 --> 00:51:48,610
gives rise to the
so-called glottal pulses.

889
00:51:49,690 --> 00:51:54,700
When the vocal cords are closed,
there's no airflow coming out.

890
00:51:54,700 --> 00:51:56,825
But when they open,
there's turbulent airflow

891
00:51:56,825 --> 00:51:58,125
and it makes a sound.

892
00:51:59,150 --> 00:52:00,180
So these are pulses.

893
00:52:00,180 --> 00:52:02,550
And they have a whole bunch
of different frequencies.

894
00:52:04,040 --> 00:52:06,930
So this is the wave form
as a function of time.

895
00:52:06,930 --> 00:52:09,450
Sound pressure is
a function of time.

896
00:52:09,450 --> 00:52:14,094
And this is the spectrum showing
the different frequencies

897
00:52:14,094 --> 00:52:14,760
that are formed.

898
00:52:14,760 --> 00:52:17,470
There's a whole bunch
of different frequencies

899
00:52:17,470 --> 00:52:18,575
in your glottal pulses.

900
00:52:18,575 --> 00:52:19,560
It's very complicated.

901
00:52:21,430 --> 00:52:23,320
To form different
speech sounds, you

902
00:52:23,320 --> 00:52:26,285
do things with your
upper vocal tract.

903
00:52:27,460 --> 00:52:31,860
In this case of vowels,
you position the muscles

904
00:52:31,860 --> 00:52:39,270
so that your upper vocal tract
forms filters that enhance

905
00:52:39,270 --> 00:52:43,300
and decrease some of
these frequencies.

906
00:52:43,300 --> 00:52:47,230
And after you apply the filter
function of the vocal tract

907
00:52:47,230 --> 00:52:52,380
to this glottal pulse spectrum,
you get this type of spectrum

908
00:52:52,380 --> 00:52:53,680
where there are certain peaks.

909
00:52:55,210 --> 00:52:58,870
And in the production
of a vowel,

910
00:52:58,870 --> 00:53:01,370
these peaks are at
different frequencies.

911
00:53:01,370 --> 00:53:06,070
So, for this example,
the vowel "eh" in hit,

912
00:53:06,070 --> 00:53:11,660
you have a very low peak, and
a couple of high peaks up here.

913
00:53:11,660 --> 00:53:13,036
These pacer called formants.

914
00:53:14,280 --> 00:53:16,410
And they're labeled by Fs.

915
00:53:16,410 --> 00:53:17,830
So we went over this before.

916
00:53:17,830 --> 00:53:20,670
So there's F1 here,
F2, and F3 here.

917
00:53:21,680 --> 00:53:25,800
And certain cochlear implant
processors, of course.

918
00:53:25,800 --> 00:53:27,790
Try to look at the
acoustic spectrum,

919
00:53:27,790 --> 00:53:30,965
and pick off these formants.

920
00:53:32,860 --> 00:53:36,310
And they present a lot
of electrical stimuli

921
00:53:36,310 --> 00:53:39,140
to electrodes that correspond
to them in the cochlea.

922
00:53:40,950 --> 00:53:43,120
This one we have a
lot of stimulation

923
00:53:43,120 --> 00:53:44,940
at these low
frequency electrodes,

924
00:53:44,940 --> 00:53:46,960
which would be apical
in the cochlear implant.

925
00:53:48,130 --> 00:53:50,580
And then in the
intermediate electrodes,

926
00:53:50,580 --> 00:53:54,440
they completely shut them
down, even if there's

927
00:53:54,440 --> 00:53:56,490
a little bit of
background noise.

928
00:53:56,490 --> 00:53:58,990
And then they would present a
lot of stimuli at the position

929
00:53:58,990 --> 00:54:00,660
corresponding to F2 and F3.

930
00:54:02,330 --> 00:54:07,010
And that's an effort to
decrease background noise, which

931
00:54:07,010 --> 00:54:09,260
is always a big
problem in listening

932
00:54:09,260 --> 00:54:10,900
to any kind of
acoustic wave form.

933
00:54:10,900 --> 00:54:12,830
But especially if you
have a cochlear implant.

934
00:54:14,750 --> 00:54:18,200
So this vowel, "ah,"
in the word "call"

935
00:54:18,200 --> 00:54:20,740
has two formants very
low in frequency.

936
00:54:20,740 --> 00:54:22,310
And one in the middle frequency.

937
00:54:22,310 --> 00:54:24,920
It sounds very
different, of course.

938
00:54:24,920 --> 00:54:27,100
And your vocal tract
position is very different.

939
00:54:28,440 --> 00:54:33,190
And this volume, which is
"oo," as in the word cool,

940
00:54:33,190 --> 00:54:37,030
has three fairly evenly
spaced formants here.

941
00:54:37,030 --> 00:54:40,440
Your vocal tract is yet
in a different position.

942
00:54:40,440 --> 00:54:43,020
And you interpret this
as yet a different vowel.

943
00:54:44,180 --> 00:54:50,590
Now that's a display that's
not very conventional.

944
00:54:50,590 --> 00:54:54,510
Much more conventional is to
look at a speech spectrogram.

945
00:54:54,510 --> 00:54:57,100
So this is very similar
to what we've just

946
00:54:57,100 --> 00:55:00,570
looked at for bat
echolocating pulses.

947
00:55:00,570 --> 00:55:05,560
This spectrogram is a graph
on the y-axis of frequencies.

948
00:55:05,560 --> 00:55:09,460
And now these are more
normal sonic, if you will,

949
00:55:09,460 --> 00:55:10,690
frequencies.

950
00:55:10,690 --> 00:55:13,820
These are well within the
human range, of course,

951
00:55:13,820 --> 00:55:17,265
going from 0 to 7
kilohertz on this axis.

952
00:55:18,740 --> 00:55:20,460
This is a time axis here.

953
00:55:21,730 --> 00:55:26,640
And again, the higher
in level, the darker the

954
00:55:26,640 --> 00:55:28,280
display in the spectrogram.

955
00:55:28,280 --> 00:55:31,050
So there's some really
dark bands here.

956
00:55:31,050 --> 00:55:34,300
And there's some very light
stuff here, and here, and here.

957
00:55:36,200 --> 00:55:44,515
And this is the utterance-- "Joe
took father's shoe bench out."

958
00:55:44,515 --> 00:55:46,420
OK, and that's what
the sound looks

959
00:55:46,420 --> 00:55:49,920
like when you make
that utterance.

960
00:55:49,920 --> 00:55:53,230
So the spectrogram plots the
frequencies of speech sounds

961
00:55:53,230 --> 00:55:53,790
over time.

962
00:55:55,290 --> 00:55:57,620
What we've talked
about-- up until now--

963
00:55:57,620 --> 00:56:01,731
are voiced segments,
which are mostly vowels.

964
00:56:01,731 --> 00:56:03,980
So in this utterance, you
have a bunch of vowels here.

965
00:56:03,980 --> 00:56:08,110
Here's a nice one, "ah"
in the word father's.

966
00:56:09,770 --> 00:56:13,750
And you can quite clearly
see there's a nice band here

967
00:56:13,750 --> 00:56:14,760
that would be F1.

968
00:56:16,700 --> 00:56:19,550
That would be about
at 500 kilohertz.

969
00:56:19,550 --> 00:56:23,206
And F2 is about at 1 kilohertz.

970
00:56:25,620 --> 00:56:28,580
F3 would be about
at 2 kilohertz.

971
00:56:29,910 --> 00:56:36,500
And there's a fourth
formant about 3 kilohertz.

972
00:56:36,500 --> 00:56:39,275
And that's the very beautiful
vowel, "ah" as in father.

973
00:56:41,520 --> 00:56:42,580
Here's another one.

974
00:56:47,190 --> 00:56:48,100
"Joe."

975
00:56:48,100 --> 00:56:53,430
So "oh." "Oh" is a vowel
where, in this case,

976
00:56:53,430 --> 00:56:56,050
there's a beautiful
stable formant here.

977
00:56:56,050 --> 00:56:59,070
But here is a formant
that's transitioning

978
00:56:59,070 --> 00:57:02,720
from higher frequency,
maybe about 1.5 kilohertz,

979
00:57:02,720 --> 00:57:05,520
down to below 1 kilohertz.

980
00:57:05,520 --> 00:57:06,195
So it's Joe.

981
00:57:07,800 --> 00:57:10,430
And there's a
higher formant here.

982
00:57:10,430 --> 00:57:11,280
OK.

983
00:57:11,280 --> 00:57:15,702
So those are the vowels, or
the so-called voiced segments.

984
00:57:15,702 --> 00:57:17,160
And voicing just
means that there's

985
00:57:17,160 --> 00:57:23,860
a constant outflow of sound
coming through the vocal tract.

986
00:57:23,860 --> 00:57:25,574
And you can make
these sounds forever.

987
00:57:25,574 --> 00:57:26,490
You can say, ahhhhhhh.

988
00:57:27,846 --> 00:57:30,770
And you can just keep
going if you want to.

989
00:57:30,770 --> 00:57:32,990
Of course, you don't
in normal speech.

990
00:57:32,990 --> 00:57:37,530
Now for consonants,
there are several types.

991
00:57:40,070 --> 00:57:42,890
And these are generally
called unvoiced segments.

992
00:57:42,890 --> 00:57:44,960
Mostly consonants are
intervals containing

993
00:57:44,960 --> 00:57:47,730
bands of frequencies,
swept frequencies,

994
00:57:47,730 --> 00:57:49,060
and silent intervals.

995
00:57:50,170 --> 00:57:52,900
So for example, one
of the consonants

996
00:57:52,900 --> 00:57:55,760
here is F in the word fathers.

997
00:57:57,060 --> 00:58:00,380
And right before, at the
beginning of the sound F,

998
00:58:00,380 --> 00:58:03,520
you go, which is
no sound, right?

999
00:58:03,520 --> 00:58:04,700
You close your lips.

1000
00:58:04,700 --> 00:58:07,270
You keep sound from coming out.

1001
00:58:07,270 --> 00:58:09,816
And you finally
go, father, right?

1002
00:58:09,816 --> 00:58:11,440
And that's what's
happening right here.

1003
00:58:12,710 --> 00:58:14,400
So that's a stop consonant.

1004
00:58:14,400 --> 00:58:18,450
You stop the vocal tract
before you let it go.

1005
00:58:19,530 --> 00:58:25,020
And the vowel T, as in took,
is another stop consonant.

1006
00:58:25,020 --> 00:58:28,390
So you're not doing
anything at the beginning.

1007
00:58:28,390 --> 00:58:30,710
And finally, you go, took.

1008
00:58:30,710 --> 00:58:31,880
Right?

1009
00:58:31,880 --> 00:58:38,630
When you let go, and
emit the sound of took,

1010
00:58:38,630 --> 00:58:41,095
you have a very
complex frequency band.

1011
00:58:42,230 --> 00:58:44,490
That's generally
high frequencies.

1012
00:58:44,490 --> 00:58:47,520
2 kilohertz in this case,
up beyond 7 kilohertz.

1013
00:58:48,780 --> 00:58:50,520
There's that explosion
of sound right

1014
00:58:50,520 --> 00:58:55,500
at the beginning of the
consonant T, as and took.

1015
00:58:55,500 --> 00:58:56,500
OK.

1016
00:58:56,500 --> 00:59:00,870
Now there been a lot of
course studies on speech

1017
00:59:00,870 --> 00:59:03,610
coding in the auditory nerve
and the cochlear nucleus.

1018
00:59:05,750 --> 00:59:08,980
And one of the findings
shouldn't be too surprising

1019
00:59:08,980 --> 00:59:09,480
at all.

1020
00:59:09,480 --> 00:59:14,985
You have auditory nerve fibers
that have tuning curves, right?

1021
00:59:14,985 --> 00:59:17,335
We've been over tuning
curves many times before.

1022
00:59:28,200 --> 00:59:33,430
So tuning curve is a
graph of sound pressure

1023
00:59:33,430 --> 00:59:34,390
level for a response.

1024
00:59:35,535 --> 00:59:37,220
There's a sound frequency here.

1025
00:59:42,070 --> 00:59:47,776
And then a 1 kilohertz CF.

1026
00:59:47,776 --> 00:59:50,570
The CF for this tuning
curve would be 1 kilohertz,

1027
00:59:50,570 --> 00:59:51,160
let's say.

1028
00:59:58,530 --> 01:00:03,700
And a 10 kilohertz CF
might look like that.

1029
01:00:05,456 --> 01:00:06,420
OK.

1030
01:00:06,420 --> 01:00:10,550
So you can explore the responses
of 1 kilohertz auditory nerve

1031
01:00:10,550 --> 01:00:14,270
fibers and 10 kilohertz
auditory nerve fibers

1032
01:00:14,270 --> 01:00:15,725
to this type of stimulus.

1033
01:00:17,810 --> 01:00:21,040
And obviously, the
1 kilohertz fibers

1034
01:00:21,040 --> 01:00:22,255
are going to be very active.

1035
01:00:24,390 --> 01:00:26,090
During portions
of this utterance,

1036
01:00:26,090 --> 01:00:29,420
for example, there's
a lot of 1 kilohertz

1037
01:00:29,420 --> 01:00:32,480
in this "oh" second
formant here.

1038
01:00:32,480 --> 01:00:35,610
So the 1 kilohertz fiber's going
to respond like crazy there.

1039
01:00:36,960 --> 01:00:41,260
In the vowel "ah," there's a
big 1 kilohertz band there.

1040
01:00:41,260 --> 01:00:44,210
The 1 kilohertz fiber is
going to respond a lot there.

1041
01:00:44,210 --> 01:00:48,060
It's not going to
respond here or here.

1042
01:00:48,060 --> 01:00:52,790
But it's going to respond a lot
at the end of the "out" sound.

1043
01:00:52,790 --> 01:00:54,090
OK.

1044
01:00:54,090 --> 01:00:57,980
The 10 kilohertz fiber is
kind of out of luck, right?

1045
01:00:57,980 --> 01:00:58,780
Its way up here.

1046
01:00:58,780 --> 01:00:59,745
It's off the axis.

1047
01:01:01,940 --> 01:01:08,655
But notice the tail of
this 10 kilohertz fiber.

1048
01:01:09,880 --> 01:01:12,020
If I had drawn it a
little bit further

1049
01:01:12,020 --> 01:01:15,700
it would be extending
past 1 kilohertz.

1050
01:01:15,700 --> 01:01:18,720
So it's certainly going to
respond, right, in here,

1051
01:01:18,720 --> 01:01:21,135
as long as the sound
level is high enough.

1052
01:01:22,600 --> 01:01:26,440
If you keep the sound level
of this utterance low,

1053
01:01:26,440 --> 01:01:30,435
down here, then the frequency
is obviously down here.

1054
01:01:32,080 --> 01:01:34,870
That 10 kilohertz fiber
is not going to respond.

1055
01:01:34,870 --> 01:01:38,070
But if you boost the
sound level, such

1056
01:01:38,070 --> 01:01:41,080
that you're in the tail
of the tuning curve,

1057
01:01:41,080 --> 01:01:45,150
this 10 kilohertz CF fiber
is going to start to respond.

1058
01:01:45,150 --> 01:01:51,410
For example, response to these
frequencies here, this 4, 5,

1059
01:01:51,410 --> 01:01:52,460
and 6 kilohertz.

1060
01:01:52,460 --> 01:01:54,730
Maybe the 7
kilohertz can respond

1061
01:01:54,730 --> 01:01:59,520
to things like the consonants,
if the sound level is high

1062
01:01:59,520 --> 01:02:02,785
enough so that it's
within its response areas.

1063
01:02:04,370 --> 01:02:11,970
So there's clear CF processing
of this type of speech signal

1064
01:02:11,970 --> 01:02:14,710
at the auditory nerve and
in the cochlear nucleus.

1065
01:02:14,710 --> 01:02:16,830
There's also phase locking.

1066
01:02:16,830 --> 01:02:20,430
For example, these
lower frequencies

1067
01:02:20,430 --> 01:02:23,590
are within the frequency
range where there's really

1068
01:02:23,590 --> 01:02:26,090
good phase locking for
the auditory nerve.

1069
01:02:27,120 --> 01:02:30,340
Remember, phase locking
falls off above 1 kilohertz.

1070
01:02:30,340 --> 01:02:31,850
And by about 3
kilohertz, there's

1071
01:02:31,850 --> 01:02:34,070
not much phase locking at all.

1072
01:02:34,070 --> 01:02:37,374
But many of these voiced,
or vowel, segments

1073
01:02:37,374 --> 01:02:38,790
are going to have
low frequencies.

1074
01:02:38,790 --> 01:02:41,060
And they're going to
be good phase locking

1075
01:02:41,060 --> 01:02:43,010
in the auditory nerve
or cochlear nucleus.

1076
01:02:44,320 --> 01:02:45,880
So that's just sort of a review.

1077
01:02:45,880 --> 01:02:49,530
Think about the auditory
nerve response to these speech

1078
01:02:49,530 --> 01:02:52,730
signals because clearly,
the auditory nerve

1079
01:02:52,730 --> 01:02:55,700
is going to respond
very nicely, in terms

1080
01:02:55,700 --> 01:02:59,180
of what its CFs tell it to.

1081
01:02:59,180 --> 01:03:01,610
Now, there's been a lot
of interesting work.

1082
01:03:01,610 --> 01:03:05,566
Of course, I don't have time to
get into much speech processing

1083
01:03:05,566 --> 01:03:08,390
and language representation.

1084
01:03:08,390 --> 01:03:10,650
But I just wanted to
show you some things that

1085
01:03:10,650 --> 01:03:13,985
relate quite nicely to what
we've just gone through

1086
01:03:13,985 --> 01:03:14,693
for echolocation.

1087
01:03:16,320 --> 01:03:19,650
Here are some synthesized
speech stimuli.

1088
01:03:21,240 --> 01:03:21,740
OK.

1089
01:03:21,740 --> 01:03:24,010
And you can do this very
nicely on your computer.

1090
01:03:24,010 --> 01:03:27,440
This is a spectrogram of
the synthesized sound.

1091
01:03:27,440 --> 01:03:30,560
Frequency is on the
y-axis and time,

1092
01:03:30,560 --> 01:03:34,880
in this case in milliseconds,
the very quick stimulus

1093
01:03:34,880 --> 01:03:35,810
is on the x-axis.

1094
01:03:36,860 --> 01:03:39,300
And there are several
harmonics, very much

1095
01:03:39,300 --> 01:03:43,200
like we had for the CF
echolocating bat sound.

1096
01:03:43,200 --> 01:03:45,320
And there's some regions
of constant frequency.

1097
01:03:46,850 --> 01:03:48,530
And there are
clearly some regions

1098
01:03:48,530 --> 01:03:53,340
of frequency modulation, very
much like the bat echolocating

1099
01:03:53,340 --> 01:03:54,780
signal that we just went over.

1100
01:03:54,780 --> 01:03:58,960
Except that now the
modulated part of the signal

1101
01:03:58,960 --> 01:04:02,450
is in the front
instead of at the back

1102
01:04:02,450 --> 01:04:03,550
like it was for the bat.

1103
01:04:05,290 --> 01:04:09,230
And so right here,
on the third formant,

1104
01:04:09,230 --> 01:04:12,430
is a very interesting transition
that's not shown in black.

1105
01:04:12,430 --> 01:04:13,305
It's shown in white.

1106
01:04:14,740 --> 01:04:20,910
Because in the work of Liberman
and Mattingly from the 1980s,

1107
01:04:20,910 --> 01:04:25,400
they studied this so-called
formant transition.

1108
01:04:25,400 --> 01:04:29,930
So the format here
is the vowel "ah."

1109
01:04:29,930 --> 01:04:33,530
And you have these three
formants, 1, 2, and 3.

1110
01:04:34,660 --> 01:04:38,030
And the transition
leading up into that

1111
01:04:38,030 --> 01:04:43,110
is either the consonant
D or the consonant G.

1112
01:04:44,950 --> 01:04:46,535
It's when it's coming down.

1113
01:04:49,070 --> 01:04:54,310
It's the combination "da."
but when this third formant

1114
01:04:54,310 --> 01:04:59,890
transition is instead going
up, it's the consonant "gah."

1115
01:04:59,890 --> 01:05:03,300
completely different speech
sound, "da" versus "gah."

1116
01:05:03,300 --> 01:05:04,640
No one would ever mistake them.

1117
01:05:06,020 --> 01:05:06,520
Right.

1118
01:05:06,520 --> 01:05:10,500
And so what Liberman and
Mattingly did was they

1119
01:05:10,500 --> 01:05:15,290
varied this transition
into the third formant.

1120
01:05:15,290 --> 01:05:24,390
Instead of just having one
like that, or one like this,

1121
01:05:24,390 --> 01:05:26,885
they sloped it any
number of degrees.

1122
01:05:29,740 --> 01:05:30,240
All right.

1123
01:05:30,240 --> 01:05:39,170
And when it goes, I think
when it's falling, it's "da."

1124
01:05:39,170 --> 01:05:42,680
And when it's rising, it's
"gah" if I'm not mistaken.

1125
01:05:44,110 --> 01:05:47,480
So what would you expect if
it was right in the middle?

1126
01:05:49,840 --> 01:05:51,400
Well, you could expect anything.

1127
01:05:51,400 --> 01:05:54,660
But actually, the
observation is,

1128
01:05:54,660 --> 01:05:58,710
as you move this
formant transition over,

1129
01:05:58,710 --> 01:06:00,740
subjects do not report
something that's

1130
01:06:00,740 --> 01:06:03,670
in between "gah" and "da."

1131
01:06:03,670 --> 01:06:06,000
Instead, all of a
sudden, they quickly

1132
01:06:06,000 --> 01:06:09,780
shift from "gah" to "da."

1133
01:06:09,780 --> 01:06:10,500
All of a sudden.

1134
01:06:10,500 --> 01:06:13,700
And there's a very sharp
boundary in the shift.

1135
01:06:13,700 --> 01:06:17,353
And the subjects never report
something that's intermediate.

1136
01:06:19,730 --> 01:06:24,130
So this is an example of
putting the speech sound, which

1137
01:06:24,130 --> 01:06:29,900
can be modulating continuously,
into two sharply defined

1138
01:06:29,900 --> 01:06:31,350
perceptual categories.

1139
01:06:31,350 --> 01:06:34,720
Either "gah" or either "da."

1140
01:06:34,720 --> 01:06:36,210
But nothing in between.

1141
01:06:36,210 --> 01:06:38,580
No gradual slope in between.

1142
01:06:38,580 --> 01:06:40,350
It's just one or the other.

1143
01:06:40,350 --> 01:06:45,165
This gave rise to the idea
of categorical perception

1144
01:06:45,165 --> 01:06:46,570
of speech sounds.

1145
01:06:50,250 --> 01:06:53,280
The other thing they could
do is do things like this.

1146
01:06:54,480 --> 01:07:01,430
Present the black stimuli to
one ear and the white stimuli

1147
01:07:01,430 --> 01:07:02,290
to the other ear.

1148
01:07:03,440 --> 01:07:06,760
And you get the perception,
then, of a speech sound.

1149
01:07:06,760 --> 01:07:14,600
If you don't present any
formant transition at all,

1150
01:07:14,600 --> 01:07:16,590
what would you expect to happen?

1151
01:07:16,590 --> 01:07:19,780
Well, what actually happens is
you do hear something ambiguous

1152
01:07:19,780 --> 01:07:22,480
if there's actually no
formant transition at all.

1153
01:07:24,200 --> 01:07:26,780
If there's a formant
transition, in one ear

1154
01:07:26,780 --> 01:07:29,200
and the rest of the
sound to the other ear,

1155
01:07:29,200 --> 01:07:31,120
you hear the complete
speech sound.

1156
01:07:31,120 --> 01:07:35,320
If you just present this formant
transition and nothing else,

1157
01:07:35,320 --> 01:07:37,910
you just hear a little
chirp, a little speech sound.

1158
01:07:37,910 --> 01:07:40,470
But you add that to
the rest, and you

1159
01:07:40,470 --> 01:07:46,120
get an unambiguous or
categorical "da" or "gah."

1160
01:07:46,120 --> 01:07:46,620
OK.

1161
01:07:46,620 --> 01:07:50,160
These are beautiful
series of experiments

1162
01:07:50,160 --> 01:07:56,690
by Alvin Liberman in the 1980s.

1163
01:07:56,690 --> 01:08:01,360
Now, in cortex, the
interesting question,

1164
01:08:01,360 --> 01:08:06,210
then, if you pull an
analogy between bat signals

1165
01:08:06,210 --> 01:08:08,740
and human signals,
we've had spectrograms

1166
01:08:08,740 --> 01:08:10,800
from the two which are
not that much different.

1167
01:08:11,960 --> 01:08:15,240
The question is, do we
have specialized neurons

1168
01:08:15,240 --> 01:08:22,029
in our cortices that are
sensitive to specific features

1169
01:08:22,029 --> 01:08:22,979
of those signals?

1170
01:08:22,979 --> 01:08:27,250
For example, features are things
like whether these two formants

1171
01:08:27,250 --> 01:08:30,100
are close together,
whether there's

1172
01:08:30,100 --> 01:08:33,954
a formant sweep going
down or going up.

1173
01:08:33,954 --> 01:08:36,890
Do we have specific,
if you will,

1174
01:08:36,890 --> 01:08:40,220
feature detectors
in the human cortex?

1175
01:08:40,220 --> 01:08:42,000
We don't know that.

1176
01:08:42,000 --> 01:08:44,090
What we do know
clearly is that there

1177
01:08:44,090 --> 01:08:48,080
are areas that are very
selective for language

1178
01:08:48,080 --> 01:08:51,019
and speech stimuli in
the cortex of humans.

1179
01:08:52,200 --> 01:08:53,700
So in the cortex
of humans, we've

1180
01:08:53,700 --> 01:08:56,420
talked about there
being a primary auditory

1181
01:08:56,420 --> 01:08:59,220
cortex in the
temporal lobe here.

1182
01:08:59,220 --> 01:09:02,020
And we had the little
model that showed you

1183
01:09:02,020 --> 01:09:03,644
that there was a Heschl's gyrus.

1184
01:09:04,689 --> 01:09:07,729
And that is the site of
primary auditory cortex, or A1,

1185
01:09:07,729 --> 01:09:08,229
in humans.

1186
01:09:10,310 --> 01:09:15,370
All around that region,
an area that's sometimes

1187
01:09:15,370 --> 01:09:17,870
called perisylvian cortex.

1188
01:09:19,229 --> 01:09:23,390
And it gets its name from
this big sylvian fissure,

1189
01:09:23,390 --> 01:09:26,620
if you will, that divides
the temporal lobe down here

1190
01:09:26,620 --> 01:09:30,439
from the rest of the brain,
especially the parietal lobe.

1191
01:09:30,439 --> 01:09:32,760
All around this
perisylvian cortex

1192
01:09:32,760 --> 01:09:35,380
is associated with
language processing.

1193
01:09:35,380 --> 01:09:36,480
And how do we know that?

1194
01:09:36,480 --> 01:09:37,855
Well, of course,
imaging studies.

1195
01:09:39,229 --> 01:09:42,720
But in the beginning,
the early pathologists

1196
01:09:42,720 --> 01:09:46,680
like Broca and Wernicke,
who studied patients

1197
01:09:46,680 --> 01:09:51,120
who had lesions in the
cortex, mostly from strokes.

1198
01:09:51,120 --> 01:09:52,569
But sometimes from
other injuries.

1199
01:09:53,856 --> 01:09:58,390
It showed that lesions in
this region of the brain

1200
01:09:58,390 --> 01:10:01,620
left patients with deficits
in language processing,

1201
01:10:01,620 --> 01:10:04,640
especially with a
deficit called aphasia.

1202
01:10:06,280 --> 01:10:06,780
OK?

1203
01:10:06,780 --> 01:10:12,800
Disorders of comprehending
or producing spoken language

1204
01:10:12,800 --> 01:10:13,865
are known as aphasia.

1205
01:10:16,120 --> 01:10:20,670
And these aphasias are
often classified into types.

1206
01:10:21,750 --> 01:10:26,710
If you're a neurology resident,
or you do your medical rotation

1207
01:10:26,710 --> 01:10:29,440
in neurology, you
will see patients

1208
01:10:29,440 --> 01:10:31,520
with so-called Broca's aphasia.

1209
01:10:33,550 --> 01:10:38,200
And this, originally, was
brought to light by Broca.

1210
01:10:38,200 --> 01:10:41,910
We saw such patients
with lesions

1211
01:10:41,910 --> 01:10:43,170
in this part of the brain.

1212
01:10:43,170 --> 01:10:45,525
That's come to be
known as Broca's area.

1213
01:10:46,570 --> 01:10:50,180
That's part of the
frontal cortex, the lower

1214
01:10:50,180 --> 01:10:52,740
frontal cortex,
near motor areas.

1215
01:10:55,070 --> 01:11:00,750
And the clinical manifestation
is a major disturbance

1216
01:11:00,750 --> 01:11:04,890
in speech production, with
sparse or halting speech.

1217
01:11:04,890 --> 01:11:09,270
It's often misarticulated,
missing function words,

1218
01:11:09,270 --> 01:11:10,220
and parts of words.

1219
01:11:10,220 --> 01:11:15,960
So this is clearly a problem
with producing speech.

1220
01:11:15,960 --> 01:11:17,700
Sometimes this is
called motor aphasia.

1221
01:11:22,050 --> 01:11:24,850
Wernicke is another
early physician

1222
01:11:24,850 --> 01:11:27,950
who saw patients with
damaged cortices.

1223
01:11:30,330 --> 01:11:34,200
He saw some of them with
damage to this region,

1224
01:11:34,200 --> 01:11:39,350
in the caudal temporal lobe
and associated parietal lobe.

1225
01:11:39,350 --> 01:11:44,580
It's an area which has become
known as Wernicke's area.

1226
01:11:46,520 --> 01:11:48,946
And here, the
clinical manifestation

1227
01:11:48,946 --> 01:11:49,945
is completely different.

1228
01:11:51,040 --> 01:11:56,060
In this case, the production
of speech is fine.

1229
01:11:56,060 --> 01:11:58,580
But it's a major disturbance
in auditory comprehension.

1230
01:12:00,830 --> 01:12:01,330
OK.

1231
01:12:01,330 --> 01:12:06,130
So you ask the patient something
and they cannot understand you.

1232
01:12:06,130 --> 01:12:08,385
But they have fluent
speech production.

1233
01:12:08,385 --> 01:12:12,110
It's fluent speech
with maybe disturbances

1234
01:12:12,110 --> 01:12:13,990
of the sounds and
structures of the words.

1235
01:12:13,990 --> 01:12:17,474
But the major deficit is in
the auditory comprehension,

1236
01:12:17,474 --> 01:12:18,432
language comprehension.

1237
01:12:21,670 --> 01:12:26,690
So the question,
then, has always been,

1238
01:12:26,690 --> 01:12:30,270
is this Broca's
area the motor area

1239
01:12:30,270 --> 01:12:34,070
for production of
speech and language?

1240
01:12:34,070 --> 01:12:37,600
And is this Wernicke's
area the area

1241
01:12:37,600 --> 01:12:39,830
for comprehension of speech?

1242
01:12:39,830 --> 01:12:42,670
And clearly, this is a
very simplistic idea,

1243
01:12:42,670 --> 01:12:46,780
in what would be called
the localizational idea.

1244
01:12:46,780 --> 01:12:48,375
I'm not sure if
that word is here.

1245
01:12:49,920 --> 01:12:57,560
But if you're a so-called
localization proponent,

1246
01:12:57,560 --> 01:12:59,940
you would say each
little part of the cortex

1247
01:12:59,940 --> 01:13:01,030
has its own function.

1248
01:13:01,030 --> 01:13:03,870
And they do that independently
of all the other areas.

1249
01:13:03,870 --> 01:13:08,600
So the Broca's area is
involved in producing speech.

1250
01:13:08,600 --> 01:13:12,140
And Wernicke's area is
responsible for comprehending

1251
01:13:12,140 --> 01:13:13,120
speech.

1252
01:13:13,120 --> 01:13:16,890
And this is clearly
from imaging studies

1253
01:13:16,890 --> 01:13:21,210
that we know now is a very
simplistic view, and probably

1254
01:13:21,210 --> 01:13:22,320
an incorrect view.

1255
01:13:22,320 --> 01:13:28,030
It's more likely this
whole of perisylvian cortex

1256
01:13:28,030 --> 01:13:29,755
contributes to
language processing.

1257
01:13:30,770 --> 01:13:35,950
And so people who
subscribe to that theory

1258
01:13:35,950 --> 01:13:37,530
would be called holistic.

1259
01:13:37,530 --> 01:13:41,650
They'd have the holistic
view of processing in cortex.

1260
01:13:44,900 --> 01:13:48,190
And we'll go over the imaging
studies in just a minute.

1261
01:13:48,190 --> 01:13:50,760
One thing I want
to make sure to say

1262
01:13:50,760 --> 01:13:59,490
is that language processing is
clearly a cortical phenomenon.

1263
01:13:59,490 --> 01:14:02,200
That is, if you have
injury to the cortex

1264
01:14:02,200 --> 01:14:06,355
in these specific areas,
you're likely to have aphasia.

1265
01:14:07,420 --> 01:14:11,180
If you have injuries to the
brain stem, to the thalamus,

1266
01:14:11,180 --> 01:14:14,310
you are much less likely to
have any kind of aphasia.

1267
01:14:15,510 --> 01:14:18,240
So clearly, the
cortex is the place

1268
01:14:18,240 --> 01:14:19,790
where language is processed.

1269
01:14:21,530 --> 01:14:24,490
Another thing about cortex
and language processing

1270
01:14:24,490 --> 01:14:29,600
is that it's usually lateralized
into one hemisphere or another,

1271
01:14:29,600 --> 01:14:30,100
OK?

1272
01:14:30,100 --> 01:14:34,160
So if you're right handed,
usually your language

1273
01:14:34,160 --> 01:14:36,830
is processed in your
opposite hemifield,

1274
01:14:36,830 --> 01:14:39,750
in the left cortical area.

1275
01:14:39,750 --> 01:14:41,110
And so how is that known?

1276
01:14:41,110 --> 01:14:45,070
Well, if you have a stroke
patient whose right handed,

1277
01:14:45,070 --> 01:14:47,320
they have a lesion
in the left cortex.

1278
01:14:47,320 --> 01:14:48,460
They show up with aphasia.

1279
01:14:49,560 --> 01:14:52,370
If they have a lesion
in the right cortex,

1280
01:14:52,370 --> 01:14:54,940
there's minimal effect on
their language functions.

1281
01:14:55,960 --> 01:14:59,110
Another way is by the
so-called Wada test.

1282
01:14:59,110 --> 01:15:07,376
So people who are getting ready
to have cortical neurosurgery--

1283
01:15:07,376 --> 01:15:09,750
so why would you ever want to
have cortical neurosurgery?

1284
01:15:27,500 --> 01:15:28,000
Anybody?

1285
01:15:29,230 --> 01:15:35,800
So another big disease in the
cortex is epilepsy, right?

1286
01:15:35,800 --> 01:15:38,817
Epilepsy is uncontrolled
activity, usually starting

1287
01:15:38,817 --> 01:15:39,400
in the cortex.

1288
01:15:40,860 --> 01:15:43,280
Of course, the first line
of attack is by medication.

1289
01:15:44,590 --> 01:15:49,140
But some epileptic
patients have epilepsy

1290
01:15:49,140 --> 01:15:50,940
that is not controlled
by medication.

1291
01:15:50,940 --> 01:15:53,985
And they have seizures
every half hour.

1292
01:15:55,120 --> 01:15:57,530
And it's pretty
much intractable.

1293
01:15:57,530 --> 01:16:02,150
So the last line of attack,
then, by the neurosurgeons

1294
01:16:02,150 --> 01:16:06,140
is to try to go into the cortex
and find the part of the cortex

1295
01:16:06,140 --> 01:16:09,710
where the epileptic
focus begins.

1296
01:16:09,710 --> 01:16:10,960
And then they'd lesion that.

1297
01:16:10,960 --> 01:16:12,640
And this is a
successful treatment.

1298
01:16:13,740 --> 01:16:18,740
But if the surgeon goes in and
lesions part of the language

1299
01:16:18,740 --> 01:16:22,930
areas, you have a patient
that wakes up as an aphasic.

1300
01:16:22,930 --> 01:16:24,440
That's not a happy patient.

1301
01:16:24,440 --> 01:16:29,470
So the surgeons do lots of
tests before such surgery.

1302
01:16:29,470 --> 01:16:33,980
And one is to try to figure out
which hemisphere is processing

1303
01:16:33,980 --> 01:16:34,730
the language.

1304
01:16:34,730 --> 01:16:36,490
So they do the Wada test.

1305
01:16:36,490 --> 01:16:38,010
Has anybody heard
of the Wada test?

1306
01:16:39,800 --> 01:16:40,300
OK.

1307
01:16:40,300 --> 01:16:44,320
They take the patient, of
course, and-- if they're smart

1308
01:16:44,320 --> 01:16:46,120
and they plan ahead,
the patient is seated.

1309
01:16:47,670 --> 01:16:48,170
OK?

1310
01:16:48,170 --> 01:16:51,960
And they have a carotid
artery on the left side,

1311
01:16:51,960 --> 01:16:53,800
and a carotid artery
on the right side.

1312
01:16:55,090 --> 01:16:58,150
And into the carotid
artery is injected

1313
01:16:58,150 --> 01:17:00,710
a quick acting
barbiturate anesthetic.

1314
01:17:02,580 --> 01:17:06,570
On one side, that carotid
artery feeds one hemisphere

1315
01:17:06,570 --> 01:17:08,470
of the cortex and not the other.

1316
01:17:09,860 --> 01:17:11,770
So the patient is seated
because the patient

1317
01:17:11,770 --> 01:17:13,270
is likely to slump
because they're

1318
01:17:13,270 --> 01:17:14,700
going to have some
motor problems.

1319
01:17:14,700 --> 01:17:19,100
And the patient might fall
over if they were standing up.

1320
01:17:19,100 --> 01:17:21,270
But in the test, the
patient is supposed

1321
01:17:21,270 --> 01:17:25,580
to recite from reading
or from memory.

1322
01:17:25,580 --> 01:17:27,760
And the anesthetic is injected.

1323
01:17:27,760 --> 01:17:30,870
And as soon as that anesthetic
hits the hemisphere that's

1324
01:17:30,870 --> 01:17:35,050
processing language, the
patient stops reciting.

1325
01:17:35,050 --> 01:17:38,760
That's if they injected
on the correct side.

1326
01:17:38,760 --> 01:17:40,310
If they injected
on the other side,

1327
01:17:40,310 --> 01:17:42,760
the patient keeps
reading, keeps reciting.

1328
01:17:42,760 --> 01:17:43,965
So that's the Wada test.

1329
01:17:48,215 --> 01:18:08,570
Language function is
mostly in one hemisphere

1330
01:18:08,570 --> 01:18:12,700
in right handed individuals
In left handers,

1331
01:18:12,700 --> 01:18:14,460
things are a little
bit different.

1332
01:18:14,460 --> 01:18:16,790
Left handed
individuals sometimes

1333
01:18:16,790 --> 01:18:20,790
have the opposite
hemispheric dominance.

1334
01:18:20,790 --> 01:18:22,930
Sometimes they have
language function

1335
01:18:22,930 --> 01:18:24,110
distributed bilaterally.

1336
01:18:25,770 --> 01:18:28,240
Sometimes they have
language function

1337
01:18:28,240 --> 01:18:31,691
in the same side as
their handedness.

1338
01:18:31,691 --> 01:18:32,190
OK.

1339
01:18:32,190 --> 01:18:36,510
But for this, I'm talking
about right handers, OK?

1340
01:18:36,510 --> 01:18:38,090
Here's some very
interesting work

1341
01:18:38,090 --> 01:18:43,630
looking at the language
areas in people.

1342
01:18:46,000 --> 01:18:49,480
In postmortem, material has
been done by Al Galaburda.

1343
01:18:49,480 --> 01:18:52,425
So he's at Beth Israel
Deaconess Hospital now.

1344
01:18:53,430 --> 01:18:58,157
And he looked at
the left hemisphere

1345
01:18:58,157 --> 01:18:59,240
and the right hemispheres.

1346
01:19:00,370 --> 01:19:04,610
And he looked at the very,
of course, closely associated

1347
01:19:04,610 --> 01:19:07,800
language areas,
especially right near A1.

1348
01:19:09,360 --> 01:19:13,770
And so here is-- you can't see
them on a side view like this--

1349
01:19:13,770 --> 01:19:18,740
but if you cut off the top of
the cortex, which you can do.

1350
01:19:18,740 --> 01:19:20,560
This is postmortem material.

1351
01:19:20,560 --> 01:19:25,350
You look down on the superior
surface of the temporal lobe,

1352
01:19:25,350 --> 01:19:27,540
you see these views here.

1353
01:19:27,540 --> 01:19:33,720
And the area that's just caudal
to the primary auditory cortex

1354
01:19:33,720 --> 01:19:35,150
is called the plenum temporally.

1355
01:19:36,760 --> 01:19:41,350
And there are clearly some
left-right asymmetries

1356
01:19:41,350 --> 01:19:45,920
in that region of the brain
that almost certainly relate

1357
01:19:45,920 --> 01:19:48,040
to language processing
in that area.

1358
01:19:49,481 --> 01:19:49,980
OK?

1359
01:19:49,980 --> 01:19:53,500
So there are
anatomical asymmetries

1360
01:19:53,500 --> 01:19:55,560
in the perisylvian regions.

1361
01:19:55,560 --> 01:19:57,890
And so this is the first
time in our course,

1362
01:19:57,890 --> 01:20:02,010
now, where right and left
makes a big difference.

1363
01:20:02,010 --> 01:20:04,330
All along, we said
it doesn't matter

1364
01:20:04,330 --> 01:20:06,505
if we simulated the right
ear or the left ear.

1365
01:20:06,505 --> 01:20:09,860
And here, clearly, there
is a dominant hemisphere

1366
01:20:09,860 --> 01:20:10,800
for language.

1367
01:20:14,560 --> 01:20:17,710
Now finally,
imaging studies have

1368
01:20:17,710 --> 01:20:21,950
shown us a great deal about
the cortical processing

1369
01:20:21,950 --> 01:20:22,650
of language.

1370
01:20:22,650 --> 01:20:28,060
And here's data from a pet
study, in which the subjects

1371
01:20:28,060 --> 01:20:30,790
are listening to
language stimuli.

1372
01:20:32,300 --> 01:20:36,020
And these happen to be
French speaking subjects.

1373
01:20:36,020 --> 01:20:38,785
So the last condition
is a story in French.

1374
01:20:39,950 --> 01:20:44,930
And obviously, the subjects
understood the story.

1375
01:20:44,930 --> 01:20:47,420
They could tell you
what was going on.

1376
01:20:47,420 --> 01:20:50,700
And these are, by the way,
right handed subjects.

1377
01:20:50,700 --> 01:20:55,570
And here's the imaging of the
areas in the left hemisphere,

1378
01:20:55,570 --> 01:20:58,209
which would be expected to
be the dominant hemisphere

1379
01:20:58,209 --> 01:20:58,750
for language.

1380
01:21:00,000 --> 01:21:01,500
And this is in the
other hemisphere,

1381
01:21:01,500 --> 01:21:03,350
which shows a lot
less activation.

1382
01:21:05,730 --> 01:21:09,260
The activation in the areas
where the subjects were

1383
01:21:09,260 --> 01:21:12,690
listening to language
they understood

1384
01:21:12,690 --> 01:21:18,190
is the superior temporal
area, superior temporal gyrus.

1385
01:21:18,190 --> 01:21:21,372
That's including the temporal
pole here, in purple.

1386
01:21:21,372 --> 01:21:22,830
You can't see the
yellow very well.

1387
01:21:22,830 --> 01:21:27,060
But believe there's a
lot of activation here.

1388
01:21:27,060 --> 01:21:33,080
This blue area, labeled
IFG inferior frontal gyrus,

1389
01:21:33,080 --> 01:21:34,345
this is Broca's area.

1390
01:21:36,520 --> 01:21:38,980
And why does it light up
if Broca's area is only

1391
01:21:38,980 --> 01:21:40,370
a motor area?

1392
01:21:40,370 --> 01:21:43,280
It's clearly involved
in motor functions.

1393
01:21:43,280 --> 01:21:49,730
But here is imaging results from
subjects just listening, not

1394
01:21:49,730 --> 01:21:53,000
producing language, where
Broca's area lights up.

1395
01:21:53,000 --> 01:21:56,050
It's activated on
the dominant side,

1396
01:21:56,050 --> 01:21:57,440
just in the listening task.

1397
01:21:59,260 --> 01:22:03,120
Contrast that to when the
subjects were listening

1398
01:22:03,120 --> 01:22:07,390
to a story in a language
that they did not understand,

1399
01:22:07,390 --> 01:22:09,490
this language is called Tamil.

1400
01:22:09,490 --> 01:22:11,170
And none of the
subjects could speak it.

1401
01:22:11,170 --> 01:22:15,730
There's hardly any
activation in the original.

1402
01:22:15,730 --> 01:22:19,020
There's a little bit
of yellow activation

1403
01:22:19,020 --> 01:22:22,080
near the primary
auditory cortex.

1404
01:22:22,080 --> 01:22:24,490
It's pretty symmetric,
left to right.

1405
01:22:24,490 --> 01:22:26,010
And that's just
what you'd expect

1406
01:22:26,010 --> 01:22:30,230
if you were, for example,
given pure tones or noise.

1407
01:22:30,230 --> 01:22:35,120
This is a nice control because,
presumably, this language

1408
01:22:35,120 --> 01:22:37,033
has about the same
frequency content.

1409
01:22:38,450 --> 01:22:41,580
And other factors are fairly
similar between these two

1410
01:22:41,580 --> 01:22:42,250
languages.

1411
01:22:42,250 --> 01:22:44,510
The one difference
is the subjects

1412
01:22:44,510 --> 01:22:48,310
were not perceptually aware
of what they were learning

1413
01:22:48,310 --> 01:22:51,065
about in the story, in the
case of the unfamiliar.

1414
01:22:52,870 --> 01:22:55,330
These intermediate
conditions, some

1415
01:22:55,330 --> 01:22:59,250
of them having pseudo words
and anomalous sentences,

1416
01:22:59,250 --> 01:23:03,230
didn't light up the language
areas to a great degree.

1417
01:23:03,230 --> 01:23:06,870
But listening to a list, in this
case, of French words-- which

1418
01:23:06,870 --> 01:23:11,490
the subjects were familiar
to-- again, showed activation.

1419
01:23:11,490 --> 01:23:14,690
I'll point out to
you in Broca's area

1420
01:23:14,690 --> 01:23:17,850
in the dominant hemisphere, in
these right handed subjects.

1421
01:23:17,850 --> 01:23:21,780
So again, clearly,
just a listening task

1422
01:23:21,780 --> 01:23:24,180
can light up Broca's area.

1423
01:23:24,180 --> 01:23:27,125
And so that is a
very clear example.

1424
01:23:28,220 --> 01:23:32,170
I'll show you that
these so-called motor

1425
01:23:32,170 --> 01:23:34,480
areas, like Broca's
area, are involved

1426
01:23:34,480 --> 01:23:41,150
in listening and cortex
processing of language stimuli.

1427
01:23:41,150 --> 01:23:46,100
It's not just involved in
motor production of speech,

1428
01:23:46,100 --> 01:23:51,680
even though what we call
clinically Broca's aphasia

1429
01:23:51,680 --> 01:23:53,720
has a major disturbance
in speech production.

1430
01:23:55,850 --> 01:23:56,850
OK.

1431
01:23:56,850 --> 01:23:58,850
And one final thing
to leave you with.

1432
01:24:00,900 --> 01:24:05,170
Broca's area tends to
light up, in this case,

1433
01:24:05,170 --> 01:24:07,950
in fairly simple stimuli.

1434
01:24:07,950 --> 01:24:11,160
But it tends to light
up in other studies,

1435
01:24:11,160 --> 01:24:13,340
like in cases where
the substances have

1436
01:24:13,340 --> 01:24:17,390
difficult grammar
or complex meaning.

1437
01:24:17,390 --> 01:24:19,070
And so the subjects,
you can imagine,

1438
01:24:19,070 --> 01:24:21,980
are really listening
hard and trying

1439
01:24:21,980 --> 01:24:23,860
to figure out the meaning
of a sentence that

1440
01:24:23,860 --> 01:24:25,260
has a complicated grammar.

1441
01:24:25,260 --> 01:24:27,610
I think we've all
written such senses.

1442
01:24:27,610 --> 01:24:30,270
We've all tried to read
them from other writers.

1443
01:24:30,270 --> 01:24:34,310
And it takes a lot of brain
power, then, to decode that,

1444
01:24:34,310 --> 01:24:36,290
and figure out the meaning.

1445
01:24:36,290 --> 01:24:39,460
And maybe that's
what happens here.

1446
01:24:39,460 --> 01:24:41,860
Broca's area's called
in when the task gets

1447
01:24:41,860 --> 01:24:45,390
more difficult than just
a simple list of words.

1448
01:24:45,390 --> 01:24:46,610
In this case, it lit up.

1449
01:24:46,610 --> 01:24:50,020
And in other studies, it's
clearly showing more activation

1450
01:24:50,020 --> 01:24:52,252
when the task gets
more difficult.

1451
01:24:55,521 --> 01:24:56,020
OK.

1452
01:24:56,020 --> 01:24:57,585
So we're out of time.

1453
01:24:58,920 --> 01:25:00,735
I can take a question or two.

1454
01:25:03,490 --> 01:25:06,443
And just a reminder,
class meets at Mass.

1455
01:25:06,443 --> 01:25:09,240
Eye and Ear on Wednesday
for the lab tour.

1456
01:25:09,240 --> 01:25:11,660
So I'll see you over there.