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[INTERPOSING VOICES]

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00:00:22,482 --> 00:00:23,930
AUDIENCE: I don't know.

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Everybody's getting it.

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I am working.

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00:00:26,630 --> 00:00:27,982
I'm trying.

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[GROANS] Is there
any scan [INAUDIBLE]

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that let's you see
their own activity?

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00:00:33,740 --> 00:00:36,800
ABBY NOYCE: Activity?

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00:00:36,800 --> 00:00:40,300
Sure, an fMRI or an EEG
is going to you activity.

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00:00:40,300 --> 00:00:43,400
But if you want to think about
how many neurons are there,

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then what you want
is small slices

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of brain on a microscope
slide and a good microscope.

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Which should tell you something
about what kind of subjects

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you can use for that study.

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AUDIENCE: Not humans.

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ABBY NOYCE: Not humans.

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AUDIENCE: Rats.

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00:00:54,250 --> 00:00:57,230
[INAUDIBLE] Humans
with no identity.

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ABBY NOYCE: Humans who have
donated their brains to science

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00:00:59,900 --> 00:01:02,720
is the exception to
that, but they're

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00:01:02,720 --> 00:01:03,950
hard to get your hands on.

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There are very few of those
on the grand scale of things.

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00:01:08,372 --> 00:01:11,774
[INTERPOSING VOICES]

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AUDIENCE: It would have to die.

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It would have to.

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Well, it wouldn't have to.

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[INAUDIBLE]

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00:02:46,319 --> 00:02:48,360
ABBY NOYCE: There are ways
of euthanizing animals

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00:02:48,360 --> 00:02:50,899
so that you don't affect
what you want to measure.

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00:02:50,899 --> 00:02:52,940
AUDIENCE: OK, so we're
going to kill it humanely.

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00:02:52,940 --> 00:02:53,940
ABBY NOYCE: Yeah.

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00:02:53,940 --> 00:02:56,970
"Euthanasia," "sacrifice"
are both terms

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00:02:56,970 --> 00:02:58,850
that you would
see used for that.

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[INTERPOSING VOICES]

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00:05:01,607 --> 00:05:03,690
ABBY NOYCE: Is there any
way you can measure what?

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AUDIENCE: [INAUDIBLE]

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ABBY NOYCE: Like the
presence of neurotransmitter?

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AUDIENCE: Yeah.

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ABBY NOYCE: Yup.

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00:05:10,710 --> 00:05:13,830
It usually involves
synthesizing a molecule that

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will both bind to
the neurotransmitter

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that you want and then will
also bind to some kind of dye,

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and then use the dye.

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So there's some
cytochemistry involved.

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00:05:22,490 --> 00:05:23,579
But yeah, you can do that.

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AUDIENCE: OK.

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AUDIENCE: Do we have to do all
of those things or just one?

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ABBY NOYCE: Just one.

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AUDIENCE: Oh, OK.

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ABBY NOYCE: You guys feel pretty
confident that you've come up

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with a scenario with some rats?

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AUDIENCE: Wait, I
have a question.

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This is not hypothetical
[? anymore. ?]

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If there are more
synapses, right?

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Do more neurons mean more likely
to have an action potential?

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If, for example, you have one
synapse and [INAUDIBLE] one

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synapse in here, then that
[INAUDIBLE] fire or not fire?

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00:06:04,260 --> 00:06:06,980
If there are more synapses,
does it affect more?

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ABBY NOYCE: Well, so what you're
likely to see in that case--

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remember, you're not
going to see more neurons,

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but you might see this one
presynaptic neuron and one

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00:06:12,590 --> 00:06:14,131
postsynaptic neuron,
but then there'd

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be three or four synapses
going between them,

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the axon terminals
branching out at the end.

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It's synapsing in
four different places

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and releasing transmitter
in four different places,

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changing the
postsynaptic potential

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in four different places.

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AUDIENCE: Oh, OK.

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So there'd be more postsynaptic
neurons with [INAUDIBLE]

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ABBY NOYCE: Or even
one postsynaptic neuron

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would be more strongly affected
by having more connections

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with the presynaptic neuron.

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AUDIENCE: Oh.

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[INAUDIBLE]

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ABBY NOYCE: But
also you might also

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see them branching out
onto other [? nods. ?]

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00:06:43,474 --> 00:06:45,350
You just tend to see
more connection would be

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what you might expect to see.

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AUDIENCE: OK, so it
would be stronger

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than action potentials?

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ABBY NOYCE: Action potentials
are all or nothing.

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You know that.

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AUDIENCE: Oh.

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00:06:56,741 --> 00:06:58,617
[INTERPOSING VOICES]

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ABBY NOYCE: How
are you guys doing?

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AUDIENCE: We're thinking.

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ABBY NOYCE: Still thinking?

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00:07:11,499 --> 00:07:12,540
How to measure the brain.

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00:07:12,540 --> 00:07:14,498
What about the brain
would you like to measure?

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AUDIENCE: We want to
learn what changes.

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00:07:20,659 --> 00:07:22,200
AUDIENCE: How old
do they have to be?

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00:07:22,200 --> 00:07:25,222
AUDIENCE: So [INAUDIBLE] a
maze, and there's a marked right

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00:07:25,222 --> 00:07:26,125
path and a left path.

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ABBY NOYCE: OK.

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AUDIENCE: The right
path has cheese.

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00:07:28,840 --> 00:07:30,595
[INAUDIBLE]

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[INTERPOSING VOICES]

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ABBY NOYCE: To turn
away from the smell.

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[INTERPOSING VOICES]

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ABBY NOYCE: OK.

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00:07:46,620 --> 00:07:49,170
So what kind of changes do you
think-- what kind of changes

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do you want to look for?

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[INTERPOSING VOICES]

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ABBY NOYCE: Olfactory?

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[INTERPOSING VOICES]

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ABBY NOYCE: Maybe, but
remember, it's still

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going to detect the cheese
smell just as well as ever,

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where it's got to
do-- where it's

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making doing something
different isn't

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in how it's perceiving it.

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Where is it making a change?

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00:08:18,873 --> 00:08:20,316
[INTERPOSING VOICES]

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ABBY NOYCE: It's a decision
and it's a decision about what?

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AUDIENCE: Motor.

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00:08:27,960 --> 00:08:30,418
ABBY NOYCE: That's where I
would suspect you'd see changes,

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would be in the
connection between

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that olfactory
information coming in

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and the motor
coordinating areas,

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in a purely hypothetical sense.

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[INTERPOSING VOICES]

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ABBY NOYCE: You
ladies sound finished.

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We can close the blinds.

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Maybe.

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00:08:58,846 --> 00:08:59,845
Can we close the blinds?

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Nope.

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00:09:06,092 --> 00:09:07,580
Is there a wand?

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00:09:07,580 --> 00:09:08,500
There it is.

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Better?

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00:09:13,281 --> 00:09:16,230
AUDIENCE: Yeah.

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ABBY NOYCE: All right.

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So what did we come up with?

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Who would like to
share an experiment

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00:09:22,690 --> 00:09:24,820
design that they thought about?

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Sure.

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All right.

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00:09:26,740 --> 00:09:28,414
Show me your awesome.

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AUDIENCE: So.

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00:09:29,776 --> 00:09:30,400
ABBY NOYCE: So.

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AUDIENCE: So we have
monkeys that [INAUDIBLE]..

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00:09:34,824 --> 00:09:36,815
And [INAUDIBLE] for five years--

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ABBY NOYCE: OK.

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00:09:37,440 --> 00:09:41,320
AUDIENCE: And then we
have different shapes,

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like recognition.

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We showed them-- you
know the things where

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you have the silhouette
of something,

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and they give you
a [? wholestock ?]

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pile of random shapes and you're
supposed to move them around?

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ABBY NOYCE: Like tangrams?

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AUDIENCE: Tangrams.

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Yeah, those.

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We would arrange them
from easy, medium, hard.

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AUDIENCE: And see if the monkeys
are able to do it properly.

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ABBY NOYCE: OK.

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00:10:07,511 --> 00:10:10,780
AUDIENCE: And we'd try
to do it basically.

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Yeah, and then we'd have
to sacrifice them and look

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at their brains.

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ABBY NOYCE: All right.

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So you're training monkeys
to solve tangram puzzles.

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AUDIENCE: Yeah.

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00:10:19,846 --> 00:10:22,928
And then we'd have one monkey
that hasn't done anything.

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He'd just be in the house
[? sitting ?] there.

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The control group.

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ABBY NOYCE: The control
monkey, or the control group.

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Do you have multiple levels
of your independent--

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00:10:31,940 --> 00:10:34,581
what's your independent
variable, kids?

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AUDIENCE: Oh.

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00:10:35,122 --> 00:10:36,108
Independent variable?

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ABBY NOYCE: The thing that
you, the experimenter,

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are manipulating.

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AUDIENCE: The level of
difficulty for the tangrams.

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ABBY NOYCE: All right,
so you're operationally

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00:10:44,440 --> 00:10:47,230
defining learning as how hard
the tangrams they have to solve

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are.

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AUDIENCE: And their
ability to do it.

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ABBY NOYCE: And
their performance.

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00:10:53,270 --> 00:10:54,880
OK.

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And your dependent variable is?

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What are you measuring to--

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AUDIENCE: The neurons.

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00:11:00,840 --> 00:11:01,840
ABBY NOYCE: The neurons.

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00:11:01,840 --> 00:11:05,216
And what kind of neurons
are you going to measure?

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00:11:05,216 --> 00:11:08,110
AUDIENCE: [INAUDIBLE]

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00:11:08,110 --> 00:11:10,600
AUDIENCE: The brain.

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00:11:10,600 --> 00:11:12,994
ABBY NOYCE: What kind of
changes do you want to look for?

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AUDIENCE: Big changes.

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00:11:14,462 --> 00:11:14,962
[LAUGHTER]

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ABBY NOYCE: Do you want
to look for changes

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00:11:17,140 --> 00:11:18,670
in neurotransmitter?

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00:11:18,670 --> 00:11:21,960
Changes in synapses?

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00:11:21,960 --> 00:11:23,490
AUDIENCE: We
basically compare them

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00:11:23,490 --> 00:11:27,395
to the control monkey, who has
nothing going on in the slide.

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00:11:27,395 --> 00:11:28,020
ABBY NOYCE: OK.

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00:11:28,020 --> 00:11:29,370
AUDIENCE: And look at
all the differences.

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ABBY NOYCE: So you're looking
for all kinds of differences.

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00:11:31,828 --> 00:11:35,040
You're going to run a bajillion
analyzes on these brains?

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All right.

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00:11:37,820 --> 00:11:38,820
Who else wants to share?

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00:11:42,748 --> 00:11:44,230
AUDIENCE: They do.

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00:11:44,230 --> 00:11:45,287
ABBY NOYCE: Zechariah.

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AUDIENCE: So we're going to
take a sample of hamsters.

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AUDIENCE: Sample?

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00:11:56,057 --> 00:11:57,140
ABBY NOYCE: A core sample?

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00:11:57,140 --> 00:11:58,050
No.

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00:11:58,050 --> 00:12:00,391
OK, so you're going to
have a group of hamsters.

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00:12:00,391 --> 00:12:01,253
AUDIENCE: A sample.

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00:12:01,253 --> 00:12:04,366
You know, a sample
from the population.

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00:12:04,366 --> 00:12:06,074
AUDIENCE: Your
[? thing's ?] on hamsters.

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00:12:06,074 --> 00:12:08,010
You make them sound like food.

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00:12:08,010 --> 00:12:08,980
[LAUGHTER]

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00:12:08,980 --> 00:12:11,150
ABBY NOYCE: It's OK.

219
00:12:11,150 --> 00:12:12,030
Take a deep breath.

220
00:12:12,030 --> 00:12:12,530
Keep going.

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00:12:12,530 --> 00:12:14,154
We're going to have
a group of hamsters

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00:12:14,154 --> 00:12:16,220
that is not every hamster
in the entire universe.

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00:12:16,220 --> 00:12:16,978
Check.

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00:12:16,978 --> 00:12:18,436
What are you going
to do with them?

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00:12:18,436 --> 00:12:20,816
AUDIENCE: We're going to put
them [INAUDIBLE] [? in a ?]

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00:12:20,816 --> 00:12:22,190
maze.

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00:12:22,190 --> 00:12:23,495
ABBY NOYCE: What kind of maze?

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00:12:23,495 --> 00:12:24,527
AUDIENCE: [INAUDIBLE]

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00:12:24,527 --> 00:12:25,610
ABBY NOYCE: Like a T-maze.

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00:12:25,610 --> 00:12:26,330
OK.

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00:12:26,330 --> 00:12:29,276
AUDIENCE: There are two
of them and one of them

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00:12:29,276 --> 00:12:31,712
has to smell cheese.

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00:12:31,712 --> 00:12:33,170
ABBY NOYCE: I need
to diagram this.

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00:12:37,346 --> 00:12:39,047
AUDIENCE: That's definitely a T.

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00:12:39,047 --> 00:12:40,130
ABBY NOYCE: It's a T-maze.

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00:12:40,130 --> 00:12:41,360
It could be a Y-maze,
too, but you're

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00:12:41,360 --> 00:12:43,100
more likely to see T-mazes
because they take up

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00:12:43,100 --> 00:12:43,640
less space.

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00:12:43,640 --> 00:12:45,410
If you want to run these off
at angles, they get longer

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00:12:45,410 --> 00:12:47,450
and then they're hard
to put on the table.

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00:12:47,450 --> 00:12:48,660
All right, hamster.

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00:12:51,576 --> 00:12:53,034
AUDIENCE: Is that a cow?

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00:12:53,034 --> 00:12:56,390
ABBY NOYCE: It does
not look like a cow.

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00:12:56,390 --> 00:12:59,870
All right, we have a
hamster and a T-maze.

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00:12:59,870 --> 00:13:02,516
AUDIENCE: On the left
side there will be

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00:13:02,516 --> 00:13:04,796
a tray set filled with cheese.

247
00:13:10,010 --> 00:13:16,446
On the right side, there will
be cheese with a scent, a scent

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00:13:16,446 --> 00:13:18,374
but no scent.

249
00:13:18,374 --> 00:13:21,266
AUDIENCE: Scentless.

250
00:13:21,266 --> 00:13:24,814
Cheese with no smell.

251
00:13:24,814 --> 00:13:25,730
ABBY NOYCE: All right.

252
00:13:25,730 --> 00:13:27,900
We have scentless cheese
and we have a cheese aroma.

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00:13:27,900 --> 00:13:29,408
AUDIENCE: Cheese
flavored something.

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00:13:32,480 --> 00:13:35,120
ABBY NOYCE: This is my
smelly thing of cheese.

255
00:13:35,120 --> 00:13:36,420
It's like a pod of cheese.

256
00:13:36,420 --> 00:13:39,980
Anyway, all right,
cheese and no cheese.

257
00:13:39,980 --> 00:13:42,590
And what does the hamster
have to learn to do?

258
00:13:42,590 --> 00:13:44,170
AUDIENCE: The
hamster has to learn

259
00:13:44,170 --> 00:13:48,830
to turn away from
its natural sense

260
00:13:48,830 --> 00:13:51,150
to turn towards the cheese--

261
00:13:51,150 --> 00:13:53,050
the smell of the cheese.

262
00:13:53,050 --> 00:13:55,700
And it will turn it's
back on the smell

263
00:13:55,700 --> 00:13:57,620
and then find the real cheese.

264
00:13:57,620 --> 00:14:01,040
ABBY NOYCE: The hamster
has to go that way.

265
00:14:01,040 --> 00:14:02,240
OK.

266
00:14:02,240 --> 00:14:04,910
So you're training
the hamster to ignore

267
00:14:04,910 --> 00:14:08,260
the olfactory
information coming in.

268
00:14:08,260 --> 00:14:11,700
What's your
independent variable?

269
00:14:11,700 --> 00:14:13,706
AUDIENCE: Well, we can
make the maze harder.

270
00:14:13,706 --> 00:14:18,446
Say, instead of two different
choices, three or four.

271
00:14:18,446 --> 00:14:19,880
Those would be our levels.

272
00:14:19,880 --> 00:14:22,738
ABBY NOYCE: That's
one possibility.

273
00:14:22,738 --> 00:14:24,954
An easier one would be to
have a bunch of hamsters

274
00:14:24,954 --> 00:14:26,870
that you don't teach to
run through this maze,

275
00:14:26,870 --> 00:14:28,320
and then you have
a control group.

276
00:14:28,320 --> 00:14:30,170
And remember that having one
experimental group and one

277
00:14:30,170 --> 00:14:31,586
control group
counts as two levels

278
00:14:31,586 --> 00:14:34,650
of your independent variable.

279
00:14:34,650 --> 00:14:37,400
And for a nice,
big, vague change--

280
00:14:37,400 --> 00:14:39,388
AUDIENCE: Our control group--

281
00:14:39,388 --> 00:14:43,035
looking at the brains
of the hamsters

282
00:14:43,035 --> 00:14:45,001
before they learned
how, and then we're

283
00:14:45,001 --> 00:14:47,386
going to-- our
dependent variable

284
00:14:47,386 --> 00:14:52,716
is the amount of change in the
pathway between the senses,

285
00:14:52,716 --> 00:14:54,025
olfactory.

286
00:14:54,025 --> 00:14:54,650
ABBY NOYCE: OK.

287
00:14:54,650 --> 00:14:57,290
AUDIENCE: And then the motors.

288
00:14:57,290 --> 00:14:58,790
ABBY NOYCE: What
methodology are you

289
00:14:58,790 --> 00:15:01,604
going to use to look at
these hamster's brains?

290
00:15:01,604 --> 00:15:02,605
AUDIENCE: Slice them up.

291
00:15:02,605 --> 00:15:03,979
ABBY NOYCE: And
then you're going

292
00:15:03,979 --> 00:15:05,358
to have them run the maze?

293
00:15:05,358 --> 00:15:06,810
AUDIENCE: That was nice.

294
00:15:06,810 --> 00:15:08,262
There's so many.

295
00:15:08,262 --> 00:15:11,162
[INAUDIBLE]

296
00:15:11,162 --> 00:15:13,370
ABBY NOYCE: Slice them up
is a perfectly adequate way

297
00:15:13,370 --> 00:15:14,000
of doing this.

298
00:15:14,000 --> 00:15:17,360
It's perhaps not the most
professional way of wording it.

299
00:15:17,360 --> 00:15:19,940
But the flaw here is that,
how are you going to measure,

300
00:15:19,940 --> 00:15:21,320
if you want to do this--

301
00:15:24,000 --> 00:15:27,230
ladies-- if you
want to do this--

302
00:15:27,230 --> 00:15:29,570
within samples group, where
you have the same subjects

303
00:15:29,570 --> 00:15:31,700
both as your control and
the experimental group,

304
00:15:31,700 --> 00:15:34,158
you need to figure out a way
of measuring them when they're

305
00:15:34,158 --> 00:15:35,522
in the control condition.

306
00:15:35,522 --> 00:15:37,490
AUDIENCE: Oh.

307
00:15:37,490 --> 00:15:39,458
[INTERPOSING VOICES]

308
00:15:43,890 --> 00:15:47,030
ABBY NOYCE: And
most of the things

309
00:15:47,030 --> 00:15:49,700
that we're interested in,
even if you-- some of them,

310
00:15:49,700 --> 00:15:53,780
there are ways of measuring
in vivo, in a living organism,

311
00:15:53,780 --> 00:15:57,020
but not on a scale that is
probably useful for this,

312
00:15:57,020 --> 00:15:59,780
especially when we're talking
about hamster brains, which are

313
00:15:59,780 --> 00:16:02,029
probably all of about that big.

314
00:16:02,029 --> 00:16:04,070
So I think you want an
experimental and a control

315
00:16:04,070 --> 00:16:08,970
group so that you can
slice up brains from both.

316
00:16:08,970 --> 00:16:11,667
What's your dependent variable?

317
00:16:11,667 --> 00:16:16,657
AUDIENCE: The amount of change
in the synapse and change

318
00:16:16,657 --> 00:16:19,160
in the [INAUDIBLE]

319
00:16:19,160 --> 00:16:21,094
ABBY NOYCE: You have a
change in what pathway?

320
00:16:21,094 --> 00:16:25,698
AUDIENCE: From the olfactory
sensors to the motor

321
00:16:25,698 --> 00:16:29,177
that would control its movement.

322
00:16:29,177 --> 00:16:30,171
ABBY NOYCE: OK.

323
00:16:30,171 --> 00:16:33,790
And what operational definition?

324
00:16:33,790 --> 00:16:35,540
What operational
definition of that change

325
00:16:35,540 --> 00:16:36,400
are you going to use?

326
00:16:36,400 --> 00:16:38,150
What kinds of changes
are you looking for?

327
00:16:46,920 --> 00:16:50,190
I'll take input from anyone
else who is in on this project.

328
00:16:50,190 --> 00:16:53,162
What kind of changes would
you look for in that pathway?

329
00:16:53,162 --> 00:16:55,870
AUDIENCE: For synapse?

330
00:16:55,870 --> 00:16:57,400
ABBY NOYCE: Sure.

331
00:16:57,400 --> 00:16:59,450
Changes in number of synapses.

332
00:16:59,450 --> 00:17:03,480
AUDIENCE: Yeah, and [INAUDIBLE]

333
00:17:03,480 --> 00:17:04,500
ABBY NOYCE: Yup.

334
00:17:04,500 --> 00:17:06,690
So changes in
synapse arrangements,

335
00:17:06,690 --> 00:17:08,099
or changes in
number of synapses,

336
00:17:08,099 --> 00:17:10,440
you probably would
look for by taking

337
00:17:10,440 --> 00:17:14,280
very thin slices of hamster
brain, drop it on a microscope,

338
00:17:14,280 --> 00:17:16,680
hire some poor slogging
undergraduate to sit there

339
00:17:16,680 --> 00:17:17,940
and count synapses.

340
00:17:17,940 --> 00:17:20,280
AUDIENCE: That's horrible.

341
00:17:20,280 --> 00:17:21,990
ABBY NOYCE: Yeah.

342
00:17:21,990 --> 00:17:23,052
I can vouch for that one.

343
00:17:23,052 --> 00:17:25,260
It's not as bad as it sounds,
but it's definitely not

344
00:17:25,260 --> 00:17:28,200
fun and exciting.

345
00:17:28,200 --> 00:17:28,789
And compare.

346
00:17:28,789 --> 00:17:30,330
Are there more
synapses in the slides

347
00:17:30,330 --> 00:17:34,440
that came from the learning
group than the control group?

348
00:17:34,440 --> 00:17:34,950
Cool.

349
00:17:34,950 --> 00:17:35,450
Good.

350
00:17:35,450 --> 00:17:38,610
Who else would like to discuss
an experiment they came up

351
00:17:38,610 --> 00:17:41,265
with?

352
00:17:41,265 --> 00:17:43,197
AUDIENCE: Our
experiment's awesome.

353
00:17:49,702 --> 00:17:51,910
ABBY NOYCE: You guys sounded
pretty excited about it,

354
00:17:51,910 --> 00:17:53,600
I don't know.

355
00:17:53,600 --> 00:17:56,000
All right, so you have the
hypothesis that learning

356
00:17:56,000 --> 00:17:58,567
involves physiological
changes in the brain.

357
00:17:58,567 --> 00:17:59,900
How are you going to study this?

358
00:17:59,900 --> 00:18:02,830
AUDIENCE: All right, so we're
going to take some rats and--

359
00:18:06,604 --> 00:18:07,520
ABBY NOYCE: Some rats.

360
00:18:07,520 --> 00:18:09,521
AUDIENCE: A large
sample of rats.

361
00:18:09,521 --> 00:18:13,497
And we're going to split them up
into two groups, and one group,

362
00:18:13,497 --> 00:18:14,988
we're going to teach them.

363
00:18:14,988 --> 00:18:16,884
They're going to be
our control group.

364
00:18:16,884 --> 00:18:18,467
And we're just going
to use the knives

365
00:18:18,467 --> 00:18:20,327
and cut up their
brains [INAUDIBLE]

366
00:18:20,327 --> 00:18:20,952
ABBY NOYCE: OK.

367
00:18:20,952 --> 00:18:23,039
AUDIENCE: And the
other group, we're

368
00:18:23,039 --> 00:18:26,782
going to teach them
how to push a button.

369
00:18:26,782 --> 00:18:31,522
I don't know, move the button
[INAUDIBLE] walk over to it

370
00:18:31,522 --> 00:18:34,100
and then push it, instead
of having it right in front

371
00:18:34,100 --> 00:18:35,265
of them, pushing it.

372
00:18:35,265 --> 00:18:39,257
And then we're going to,
after we've run this, also

373
00:18:39,257 --> 00:18:41,594
these are [INAUDIBLE]

374
00:18:41,594 --> 00:18:42,510
ABBY NOYCE: All right.

375
00:18:42,510 --> 00:18:44,494
So it sounds like your
independent variable

376
00:18:44,494 --> 00:18:46,160
is the amount of
learning they're doing,

377
00:18:46,160 --> 00:18:48,920
and your dependent
variable then is what?

378
00:18:52,371 --> 00:18:55,330
AUDIENCE: The amount
of neuron activity.

379
00:18:55,330 --> 00:18:57,010
AUDIENCE: Yeah, OK.

380
00:18:57,010 --> 00:18:58,744
the amount of neuron activity.

381
00:18:58,744 --> 00:19:05,320
And you'd measure that after
you cut up their brains.

382
00:19:05,320 --> 00:19:09,310
You look at the
number of synapses.

383
00:19:09,310 --> 00:19:11,390
Is that what [INAUDIBLE]
Yeah, I think so.

384
00:19:11,390 --> 00:19:12,455
ABBY NOYCE: You're going to
measure the number of synapses?

385
00:19:12,455 --> 00:19:14,225
AUDIENCE: And then compare it.

386
00:19:14,225 --> 00:19:17,224
Kind of like theirs.

387
00:19:17,224 --> 00:19:18,140
ABBY NOYCE: That's OK.

388
00:19:18,140 --> 00:19:20,600
AUDIENCE: But with
a different animal.

389
00:19:24,050 --> 00:19:25,744
ABBY NOYCE: Helen and Oshu?

390
00:19:25,744 --> 00:19:26,660
AUDIENCE: [? Sashi. ?]

391
00:19:26,660 --> 00:19:30,567
ABBY NOYCE: [? Sashi. ?]

392
00:19:30,567 --> 00:19:33,022
AUDIENCE: We're
going to use bats.

393
00:19:36,950 --> 00:19:38,830
ABBY NOYCE: Oh, lab
rats are sweeties.

394
00:19:38,830 --> 00:19:40,984
Well, except for the one
who bit me once, but.

395
00:19:40,984 --> 00:19:42,359
AUDIENCE: So the
independent will

396
00:19:42,359 --> 00:19:44,270
be the amount of [INAUDIBLE].

397
00:19:44,270 --> 00:19:44,936
ABBY NOYCE: Mhm.

398
00:19:44,936 --> 00:19:46,418
AUDIENCE: Yeah, I guess.

399
00:19:46,418 --> 00:19:48,394
And then we'd have
different levels of these.

400
00:19:48,394 --> 00:19:50,370
[INAUDIBLE] difficult
control group.

401
00:19:50,370 --> 00:19:53,334
[INAUDIBLE] there will
be an easy maze and then

402
00:19:53,334 --> 00:19:56,298
a medium maze and then
a super hard maze.

403
00:19:56,298 --> 00:20:02,720
[INAUDIBLE]

404
00:20:02,720 --> 00:20:09,636
AUDIENCE: [INAUDIBLE] number
and the mazes and synapses.

405
00:20:09,636 --> 00:20:14,576
So you slice up the brains and
look at it under a microscope

406
00:20:14,576 --> 00:20:16,570
and look at the changes.

407
00:20:16,570 --> 00:20:17,672
ABBY NOYCE: Cool.

408
00:20:17,672 --> 00:20:19,010
Good.

409
00:20:19,010 --> 00:20:21,895
Excellent.

410
00:20:21,895 --> 00:20:23,270
And what would
you expect to find

411
00:20:23,270 --> 00:20:25,630
if your hypothesis was true?

412
00:20:25,630 --> 00:20:26,630
AUDIENCE: More synapses.

413
00:20:26,630 --> 00:20:27,713
ABBY NOYCE: More synapses.

414
00:20:27,713 --> 00:20:29,589
And if your hypothesis
was wrong, what would

415
00:20:29,589 --> 00:20:30,380
you expect to find?

416
00:20:30,380 --> 00:20:31,213
AUDIENCE: No change.

417
00:20:31,213 --> 00:20:32,480
ABBY NOYCE: No change.

418
00:20:32,480 --> 00:20:33,070
Good.

419
00:20:33,070 --> 00:20:33,569
Cool.

420
00:20:36,050 --> 00:20:38,810
Jessica, did you want to share?

421
00:20:38,810 --> 00:20:42,650
I know we're kind of dropping
you in in the middle here.

422
00:20:42,650 --> 00:20:44,510
OK.

423
00:20:44,510 --> 00:20:45,950
Your call.

424
00:20:45,950 --> 00:20:48,650
So moving right along,
we've thought a little bit

425
00:20:48,650 --> 00:20:51,900
about how you would
find these things out.

426
00:20:51,900 --> 00:20:54,560
Let's take a look at how some
people who actually do this

427
00:20:54,560 --> 00:20:55,700
found this out.

428
00:20:55,700 --> 00:20:58,760
And the original classic study
on this is from the '60s.

429
00:20:58,760 --> 00:21:00,710
And these guys, I
think, were afraid

430
00:21:00,710 --> 00:21:02,750
that they wouldn't find
big enough differences

431
00:21:02,750 --> 00:21:06,530
in most of the scenarios
that you guys have proposed.

432
00:21:06,530 --> 00:21:09,890
So they split things,
critters, into three groups.

433
00:21:09,890 --> 00:21:13,530
They had standard laboratory
living conditions.

434
00:21:13,530 --> 00:21:15,410
The standard condition,
where you've got

435
00:21:15,410 --> 00:21:16,880
three animals in a little cave.

436
00:21:16,880 --> 00:21:19,040
They've got food-- little
cage-- they've got food,

437
00:21:19,040 --> 00:21:21,290
they've got water.

438
00:21:21,290 --> 00:21:23,990
And they wanted to compare this
to both an isolated condition,

439
00:21:23,990 --> 00:21:26,270
where animals were
living on their own,

440
00:21:26,270 --> 00:21:27,650
and then this
enriched condition,

441
00:21:27,650 --> 00:21:29,120
where they had a big cage.

442
00:21:29,120 --> 00:21:31,460
Think of the big ferret cages
you see at the pet store

443
00:21:31,460 --> 00:21:34,880
sometimes with ramps
and ladders and wheels

444
00:21:34,880 --> 00:21:37,460
and things to climb on, and
things, little bells hanging

445
00:21:37,460 --> 00:21:39,650
that they could play
with, all sorts of toys

446
00:21:39,650 --> 00:21:43,280
and other stimulus objects,
and a large group of animals

447
00:21:43,280 --> 00:21:45,230
all interacting.

448
00:21:45,230 --> 00:21:49,190
And the theory here
is that learning

449
00:21:49,190 --> 00:21:52,520
is going on even when
you're not deliberately

450
00:21:52,520 --> 00:21:54,260
being trained on a task.

451
00:21:54,260 --> 00:21:56,584
Just by walking around and
interacting with your world,

452
00:21:56,584 --> 00:21:57,500
you're learning stuff.

453
00:21:57,500 --> 00:21:59,840
We talked yesterday about
this latent learning idea,

454
00:21:59,840 --> 00:22:02,030
where animals that
weren't actually being

455
00:22:02,030 --> 00:22:04,280
rewarded for
running a maze still

456
00:22:04,280 --> 00:22:09,350
seemed to be learning
something about it's layout.

457
00:22:09,350 --> 00:22:11,990
You'll see the same thing
with little kids who are just

458
00:22:11,990 --> 00:22:13,374
playing house, playing kitchen.

459
00:22:13,374 --> 00:22:16,040
They're playing with all of this
stuff and they're, by doing it,

460
00:22:16,040 --> 00:22:18,060
exploring and learning
about their world.

461
00:22:18,060 --> 00:22:21,507
So the idea here is that by
changing what living conditions

462
00:22:21,507 --> 00:22:23,090
these animals are
in, they're changing

463
00:22:23,090 --> 00:22:26,240
the amount of
informal, not really

464
00:22:26,240 --> 00:22:29,000
structured or goal-driven,
but how much changes

465
00:22:29,000 --> 00:22:32,210
in their environment are
leading to informal learning.

466
00:22:35,300 --> 00:22:38,870
So they were all littermates.

467
00:22:38,870 --> 00:22:41,240
They'd be littermates
of the same genders.

468
00:22:41,240 --> 00:22:43,400
They take all the boy
rats from a letter

469
00:22:43,400 --> 00:22:45,860
and split them out
evenly among conditions.

470
00:22:45,860 --> 00:22:48,900
An over-simplified version
of what's going on there.

471
00:22:48,900 --> 00:22:52,040
And there's also other
neurons modulating

472
00:22:52,040 --> 00:22:55,130
that circuit that
are saying, hey look,

473
00:22:55,130 --> 00:22:56,760
there's nothing dangerous.

474
00:22:56,760 --> 00:23:00,500
We don't actually
need to contract

475
00:23:00,500 --> 00:23:01,970
that gill reflex muscle.

476
00:23:06,701 --> 00:23:09,200
This is what seems to be working
in something like Pavlovian

477
00:23:09,200 --> 00:23:14,150
conditioning, where if
every time that tuning fork

478
00:23:14,150 --> 00:23:18,770
gets rung, then these salivary
control neurons start going.

479
00:23:18,770 --> 00:23:21,050
Then a connection
between the two of them

480
00:23:21,050 --> 00:23:24,607
would start to form, which is
assuming a really simplified

481
00:23:24,607 --> 00:23:26,690
understanding of what that
neural circuit actually

482
00:23:26,690 --> 00:23:30,080
probably looks like, but the
key underlying idea is valid.

483
00:23:32,700 --> 00:23:35,430
Neurons that fire together wire
together, which isn't actually

484
00:23:35,430 --> 00:23:37,800
Hebbs' formulation of it.

485
00:23:37,800 --> 00:23:41,310
But it's catchy and easy to
remember, so everybody says it.

486
00:23:41,310 --> 00:23:44,060
So remember, what's
happening here

487
00:23:44,060 --> 00:23:46,970
is it's not just
if one neuron is--

488
00:23:46,970 --> 00:23:50,350
if the first neuron in the
chain is often excited.

489
00:23:50,350 --> 00:23:52,350
It's if the first neuron
in the chain is excited

490
00:23:52,350 --> 00:23:55,615
and it's successful at
exciting the second neuron,

491
00:23:55,615 --> 00:23:57,740
then you're going to see
this kind of strengthening

492
00:23:57,740 --> 00:23:59,640
in synapses.

493
00:23:59,640 --> 00:24:02,190
You guys might remember
when we talked about vision

494
00:24:02,190 --> 00:24:04,644
two weeks ago, back in the day.

495
00:24:04,644 --> 00:24:06,060
One of the things
we discussed was

496
00:24:06,060 --> 00:24:09,751
that in very young kittens--

497
00:24:09,751 --> 00:24:12,000
remember, a lot of visual
work has been done in cats--

498
00:24:12,000 --> 00:24:14,190
in very young
kittens, you'll see

499
00:24:14,190 --> 00:24:16,830
that most of the neurons
in primary visual cortex

500
00:24:16,830 --> 00:24:19,660
don't have a strong preference
for one eye or the other.

501
00:24:19,660 --> 00:24:21,360
They'll take input from both.

502
00:24:21,360 --> 00:24:24,510
And then as the visual
system develops to adulthood,

503
00:24:24,510 --> 00:24:27,210
each of these cells will
usually develop a preference

504
00:24:27,210 --> 00:24:29,214
for the left eye
or the right eye.

505
00:24:29,214 --> 00:24:30,630
And you can think
of this as being

506
00:24:30,630 --> 00:24:32,520
if input from the
left or the right eye

507
00:24:32,520 --> 00:24:35,790
is slightly more effective
than the other one

508
00:24:35,790 --> 00:24:39,380
at exciting this neuron
in primary visual cortex,

509
00:24:39,380 --> 00:24:43,250
then that synapse will just get
strengthened in relative to it,

510
00:24:43,250 --> 00:24:45,690
this other synapse will
become much less strong.

511
00:24:45,690 --> 00:24:49,110
So you'll see cells develop
these very strong preferences

512
00:24:49,110 --> 00:24:52,395
from relatively weak
initial set states.

513
00:24:58,220 --> 00:24:59,960
Five minute break, and be quick.

514
00:24:59,960 --> 00:25:03,260
And actually five minutes
because we have a big chunk of,

515
00:25:03,260 --> 00:25:04,790
what's happening
in these synapses,

516
00:25:04,790 --> 00:25:06,797
anyway, to get through.

517
00:25:06,797 --> 00:25:09,611
AUDIENCE: What determines
whether your eyes are

518
00:25:09,611 --> 00:25:12,002
stronger or more dominant?

519
00:25:12,002 --> 00:25:13,960
ABBY NOYCE: For an
individual neuron, you mean?

520
00:25:17,060 --> 00:25:18,856
So you have a primary
visual cortex, right?

521
00:25:18,856 --> 00:25:21,230
And we talked last two weeks
ago about how cells in there

522
00:25:21,230 --> 00:25:23,150
respond to different
things, but most of them

523
00:25:23,150 --> 00:25:25,370
respond preferentially
to edges in the left eye

524
00:25:25,370 --> 00:25:27,050
or edges in the right eye.

525
00:25:27,050 --> 00:25:29,090
As far as anyone can
tell, if you are normal

526
00:25:29,090 --> 00:25:32,480
and you have decent
input from both eyes,

527
00:25:32,480 --> 00:25:36,260
then they're set up kind of at
random, but one or the other

528
00:25:36,260 --> 00:25:39,230
will have slightly stronger
input in the beginning.

529
00:25:39,230 --> 00:25:43,820
And then because that
synapse is already stronger,

530
00:25:43,820 --> 00:25:47,930
then that synapse is going to
be more effective at exciting

531
00:25:47,930 --> 00:25:50,930
the cell than a synapse
coming in from the other eye.

532
00:25:50,930 --> 00:25:53,360
And then so it'll get
strengthened by this Hebbian

533
00:25:53,360 --> 00:25:56,940
process, and then it'll
become stronger and, yeah.

534
00:25:56,940 --> 00:25:58,299
AUDIENCE: [INAUDIBLE]

535
00:25:58,299 --> 00:26:00,590
ABBY NOYCE: That's how it
was originally thought about,

536
00:26:00,590 --> 00:26:01,850
although--

537
00:26:01,850 --> 00:26:03,680
can you not ladies today?

538
00:26:03,680 --> 00:26:05,690
Draw on that one.

539
00:26:05,690 --> 00:26:06,310
Here.

540
00:26:06,310 --> 00:26:07,550
AUDIENCE: I think she's
just rolling them.

541
00:26:07,550 --> 00:26:08,600
ABBY NOYCE: Are you just
rolling them or are you drawing?

542
00:26:08,600 --> 00:26:09,558
AUDIENCE: Just rolling.

543
00:26:09,558 --> 00:26:11,060
ABBY NOYCE: You can roll them.

544
00:26:11,060 --> 00:26:12,080
I don't know,
sometimes I come in

545
00:26:12,080 --> 00:26:13,580
and there's graffiti
all over my chalkboard.

546
00:26:13,580 --> 00:26:14,860
AUDIENCE: I don't do that.

547
00:26:14,860 --> 00:26:17,227
That's all Jen.

548
00:26:17,227 --> 00:26:18,185
ABBY NOYCE: Yeah, yeah.

549
00:26:22,050 --> 00:26:23,454
Whatever.

550
00:26:23,454 --> 00:26:25,939
[INTERPOSING VOICES]

551
00:26:32,650 --> 00:26:35,946
ABBY NOYCE: How are
you doing, Jessica?

552
00:26:35,946 --> 00:26:37,000
You hanging in there?

553
00:26:39,790 --> 00:26:41,680
Let me know if you're
like, oh my God, what

554
00:26:41,680 --> 00:26:42,700
is she talking about?

555
00:26:42,700 --> 00:26:46,304
Because I know you're coming
in halfway through, so.

556
00:26:46,304 --> 00:26:47,702
[SIDE CONVERSATIONS]

557
00:28:09,420 --> 00:28:11,850
ABBY NOYCE: I need you guys
back in here in two minutes.

558
00:28:11,850 --> 00:28:12,600
AUDIENCE: What?

559
00:28:12,600 --> 00:28:13,702
ABBY NOYCE: Two minutes.

560
00:28:13,702 --> 00:28:15,118
[SIDE CONVERSATIONS]

561
00:30:12,660 --> 00:30:15,450
ABBY NOYCE: OK,
kids, class time.

562
00:30:15,450 --> 00:30:17,460
Class, we will have class.

563
00:30:17,460 --> 00:30:18,990
You should be in here.

564
00:30:18,990 --> 00:30:21,334
Thank you, gentlemen.

565
00:30:21,334 --> 00:30:23,750
If one of you could get the
window on your way in, please.

566
00:30:28,700 --> 00:30:29,710
All right.

567
00:30:29,710 --> 00:30:34,140
So discussing a process.

568
00:30:34,140 --> 00:30:37,200
We've been talking about this
kind of Donald Hebb's idea

569
00:30:37,200 --> 00:30:41,490
of what sorts of changes you
would see in the nervous system

570
00:30:41,490 --> 00:30:45,405
if you've got this kind
of to instantiate learning

571
00:30:45,405 --> 00:30:48,180
in a synapse.

572
00:30:48,180 --> 00:30:50,310
And in the '70s, people
started identifying

573
00:30:50,310 --> 00:30:54,050
a process that seems to be one
way that this could happen.

574
00:30:54,050 --> 00:30:56,250
It's called long-term
potentiation.

575
00:30:56,250 --> 00:30:58,320
So long-term, we
know what that means.

576
00:30:58,320 --> 00:31:01,650
And potentiation, meaning that
it makes a synapse stronger.

577
00:31:01,650 --> 00:31:04,590
It causes the
postsynaptic cell to be

578
00:31:04,590 --> 00:31:06,630
more responsive to
action potentials

579
00:31:06,630 --> 00:31:08,070
in the presynaptic cell.

580
00:31:11,160 --> 00:31:14,250
And it was discovered in
rabbit hippocampuses is

581
00:31:14,250 --> 00:31:15,810
in the '70s, although
at this point,

582
00:31:15,810 --> 00:31:20,250
it's been documented in
invertebrates and aplysia,

583
00:31:20,250 --> 00:31:24,050
and just every kind of little
mammal that somebody studies.

584
00:31:24,050 --> 00:31:28,256
It's been documented in human
samples, all sorts of stuff.

585
00:31:28,256 --> 00:31:29,880
So long-term potentiation
is definitely

586
00:31:29,880 --> 00:31:31,680
something that happens.

587
00:31:31,680 --> 00:31:35,850
Whether it is the one
thing underlying memory

588
00:31:35,850 --> 00:31:38,482
is still a bit open,
but it definitely

589
00:31:38,482 --> 00:31:40,190
seems to be at least
part of the process.

590
00:31:50,770 --> 00:31:57,733
So slidey board.

591
00:32:01,044 --> 00:32:02,470
All right.

592
00:32:02,470 --> 00:32:17,600
So we have a synapse,
synapse going up.

593
00:32:17,600 --> 00:32:22,170
So here's our presynaptic
and our postsynaptic cells.

594
00:32:22,170 --> 00:32:25,860
And just for review,
let's talk about so

595
00:32:25,860 --> 00:32:28,050
what happens when an
action potential comes

596
00:32:28,050 --> 00:32:31,830
along down the axon of
the presynaptic cell?

597
00:32:31,830 --> 00:32:33,320
What happens?

598
00:32:33,320 --> 00:32:34,140
AUDIENCE: Calcium.

599
00:32:34,140 --> 00:32:35,520
ABBY NOYCE: Calcium.

600
00:32:35,520 --> 00:32:37,770
So there's a voltage-gated
calcium channel.

601
00:32:37,770 --> 00:32:40,900
So calcium goes in.

602
00:32:40,900 --> 00:32:42,166
And what does calcium do?

603
00:32:45,638 --> 00:32:48,230
AUDIENCE: [INAUDIBLE]
receptor [INAUDIBLE] bone.

604
00:32:48,230 --> 00:32:48,980
ABBY NOYCE: Right.

605
00:32:48,980 --> 00:32:52,580
So the neurotransmitter
that's in the axon terminal

606
00:32:52,580 --> 00:32:56,300
is inside these little vesicles,
these little like pouches

607
00:32:56,300 --> 00:32:58,190
of membrane material.

608
00:32:58,190 --> 00:33:01,820
And the calcium binds
to that and causes

609
00:33:01,820 --> 00:33:05,510
these vesicles to do what?

610
00:33:05,510 --> 00:33:06,687
Somebody--

611
00:33:06,687 --> 00:33:08,150
AUDIENCE: Binds to the membrane.

612
00:33:08,150 --> 00:33:09,566
ABBY NOYCE: Binds
to the membrane.

613
00:33:09,566 --> 00:33:12,950
So this vesicle actually
ends up cutting down

614
00:33:12,950 --> 00:33:17,420
and binding to the
membrane and opens up.

615
00:33:17,420 --> 00:33:20,930
And when the vesicle
binds to the membrane,

616
00:33:20,930 --> 00:33:26,540
the neurotransmitter gets
released into the synapse.

617
00:33:26,540 --> 00:33:27,900
Excellent.

618
00:33:27,900 --> 00:33:32,630
And neurotransmitter in
the synapse does what?

619
00:33:32,630 --> 00:33:34,580
Binds to?

620
00:33:34,580 --> 00:33:35,450
AUDIENCE: Receptors.

621
00:33:35,450 --> 00:33:39,782
ABBY NOYCE: Receptors on
the postsynaptic cell.

622
00:33:39,782 --> 00:33:41,491
AUDIENCE: [INAUDIBLE]

623
00:33:41,491 --> 00:33:42,240
ABBY NOYCE: Right.

624
00:33:42,240 --> 00:33:44,680
So [? biased ?] receptors
on the postsynaptic cell

625
00:33:44,680 --> 00:33:47,040
causes one of a
variety of changes,

626
00:33:47,040 --> 00:33:48,700
depending on what
kind of receptor

627
00:33:48,700 --> 00:33:50,850
and what kind of
neurotransmitter

628
00:33:50,850 --> 00:33:53,040
we're considering
at this synapse.

629
00:33:53,040 --> 00:33:56,430
And then, shortly afterwards,
it gets cleaned up,

630
00:33:56,430 --> 00:33:59,940
either by an enzyme that comes
along and breaks it down,

631
00:33:59,940 --> 00:34:03,000
or by a re-uptake transmitter
that vacuums it back

632
00:34:03,000 --> 00:34:05,520
up into the presynaptic cell.

633
00:34:05,520 --> 00:34:08,580
So it all gets cleared
out of the synapse.

634
00:34:08,580 --> 00:34:09,635
All right, good.

635
00:34:09,635 --> 00:34:11,760
So when we're talking about
long-term potentiation,

636
00:34:11,760 --> 00:34:15,120
we're talking about
glutamatergic synapses,

637
00:34:15,120 --> 00:34:21,000
synapses where glutamate
is the neurotransmitter.

638
00:34:21,000 --> 00:34:25,340
And it requires two different
kinds of cellular receptors.

639
00:34:30,340 --> 00:34:33,670
So backing up a step.

640
00:34:33,670 --> 00:34:37,750
So long-term potentiation refers
to a particular kind of change

641
00:34:37,750 --> 00:34:40,330
that you'll see at a synapse,
in terms of how responsive it

642
00:34:40,330 --> 00:34:43,659
is to the previous cell.

643
00:34:43,659 --> 00:34:47,500
So the classic
demonstration of this

644
00:34:47,500 --> 00:34:52,449
is if we stick an electrode
in the presynaptic cell

645
00:34:52,449 --> 00:34:54,820
and we just keep
stimulating it electrically,

646
00:34:54,820 --> 00:34:58,000
like maybe a pulse
a second, and about

647
00:34:58,000 --> 00:34:59,950
an action potential a second.

648
00:34:59,950 --> 00:35:05,470
Then you'll see the cell
causing excitatory postsynaptic

649
00:35:05,470 --> 00:35:07,860
potentials, because it's
glutamate and glutamate

650
00:35:07,860 --> 00:35:11,260
is an excitatory
neurotransmitter.

651
00:35:11,260 --> 00:35:16,010
And they'll all be about
the same size, very steady,

652
00:35:16,010 --> 00:35:20,150
and will cause a steady stream
small excitatory postsynaptic

653
00:35:20,150 --> 00:35:21,730
potentials.

654
00:35:21,730 --> 00:35:26,830
And if we then go from this
slow and steady stimulation

655
00:35:26,830 --> 00:35:31,870
of the presynaptic
cell and stimulate it

656
00:35:31,870 --> 00:35:34,600
much more so that it just
starts suddenly firing off

657
00:35:34,600 --> 00:35:38,040
action potentials as fast as
it can go, about a thousand

658
00:35:38,040 --> 00:35:40,140
a second, that upper limit--

659
00:35:40,140 --> 00:35:43,480
this is called a tetanus,
this sudden burst of action

660
00:35:43,480 --> 00:35:45,530
potentials all at once.

661
00:35:45,530 --> 00:35:47,770
So if we do that for
a couple of seconds

662
00:35:47,770 --> 00:35:53,170
and then go back to our previous
slow and steady stimulation,

663
00:35:53,170 --> 00:35:58,060
what we'll see is that after the
synapses had that tetanus, that

664
00:35:58,060 --> 00:36:03,730
set of really fast action
potentials coming in,

665
00:36:03,730 --> 00:36:05,890
which has presumably
caused enough changes

666
00:36:05,890 --> 00:36:08,680
in that secondary cell
to cause it to fire,

667
00:36:08,680 --> 00:36:11,260
then what you'll see is
that action potentials that

668
00:36:11,260 --> 00:36:14,860
come in now will cause larger
postsynaptic potentials.

669
00:36:14,860 --> 00:36:17,980
It will cause a bigger change
in the membrane potential

670
00:36:17,980 --> 00:36:20,020
of the postsynaptic cell.

671
00:36:20,020 --> 00:36:21,820
That is long-term potentiation.

672
00:36:21,820 --> 00:36:24,880
That's this difference
in how big of an effect

673
00:36:24,880 --> 00:36:29,090
the presynaptic cell has
on the postsynaptic cell.

674
00:36:29,090 --> 00:36:31,070
So how does it do it?

675
00:36:31,070 --> 00:36:32,890
Well, we know we're
working with glutamate.

676
00:36:32,890 --> 00:36:37,300
Glutamate has two main receptor
types that are involved here.

677
00:36:37,300 --> 00:36:41,120
Glutamate has a bunch, but
we'll talk about these two.

678
00:36:41,120 --> 00:36:47,160
AMPA receptors are sodium
channels, primarily.

679
00:36:47,160 --> 00:36:49,330
So they're an
ionotropic receptor.

680
00:36:49,330 --> 00:36:51,280
When the glutamate binds
to an AMPA receptor,

681
00:36:51,280 --> 00:36:56,650
the AMPA receptor opens up
and is a sodium channel.

682
00:36:56,650 --> 00:37:02,440
NMDA receptors are both
sodium and calcium channels,

683
00:37:02,440 --> 00:37:04,860
but there's a catch.

684
00:37:04,860 --> 00:37:09,460
An NMDA receptor-- here's
our cell membrane--

685
00:37:09,460 --> 00:37:10,750
looks about like this, right?

686
00:37:10,750 --> 00:37:13,000
We'll think of it as looking
like most of our receptor

687
00:37:13,000 --> 00:37:13,870
proteins.

688
00:37:13,870 --> 00:37:18,790
But it has a little
magnesium ion that hangs out,

689
00:37:18,790 --> 00:37:21,160
blocking its channel.

690
00:37:21,160 --> 00:37:26,560
Magnesium, Mg2+, a
little magnesium ion.

691
00:37:26,560 --> 00:37:31,760
So unless that magnesium ion
gets gotten rid of in some way,

692
00:37:31,760 --> 00:37:35,830
no matter how much glutamate
binds to this NMDA receptor,

693
00:37:35,830 --> 00:37:37,960
calcium can't get in.

694
00:37:37,960 --> 00:37:42,640
So the NMDA receptor needs
to have the cell depolarized

695
00:37:42,640 --> 00:37:44,150
past a certain point.

696
00:37:44,150 --> 00:37:47,830
This magnesium ion is held here
because the inside of the cell

697
00:37:47,830 --> 00:37:50,830
is more negative than
the outside of the cell,

698
00:37:50,830 --> 00:37:52,540
that resting potential.

699
00:37:52,540 --> 00:37:55,350
So there's an electrostatic
force holding that magnesium

700
00:37:55,350 --> 00:37:57,880
ion there, and it's
not until the cell

701
00:37:57,880 --> 00:38:01,780
gets depolarized to a certain
point that it pops out.

702
00:38:01,780 --> 00:38:08,530
It gets pushed out and then
calcium and sodium can go in.

703
00:38:11,290 --> 00:38:16,810
So NMDA receptors depend
both on the neurotransmitter,

704
00:38:16,810 --> 00:38:19,270
on glutamate, and on
a significant voltage

705
00:38:19,270 --> 00:38:27,250
change at the synapse.

706
00:38:31,932 --> 00:38:32,640
We've come along.

707
00:38:32,640 --> 00:38:35,640
We've had our glutamate
released into the synapse

708
00:38:35,640 --> 00:38:37,860
here after an actual
potential comes

709
00:38:37,860 --> 00:38:39,960
from this presynaptic cell.

710
00:38:39,960 --> 00:38:47,175
And the glutamate--
here's our AMPA receptor.

711
00:38:47,175 --> 00:38:49,410
The glutamate binds
to an AMPA receptor,

712
00:38:49,410 --> 00:38:56,370
and sodium can flow into
the postsynaptic cell.

713
00:38:56,370 --> 00:38:57,900
That's a positive ion coming in.

714
00:38:57,900 --> 00:39:01,550
Is that an excitatory
or an inhibitory change?

715
00:39:01,550 --> 00:39:02,640
Excitatory, right.

716
00:39:02,640 --> 00:39:05,340
It's making the
membrane less polarized.

717
00:39:05,340 --> 00:39:08,890
It's moving it towards
that firing threshold.

718
00:39:08,890 --> 00:39:13,920
Now, what happens is if there's
only the occasional impulse

719
00:39:13,920 --> 00:39:16,530
coming in from this
presynaptic cell?

720
00:39:16,530 --> 00:39:19,380
Then the potential
along the membrane

721
00:39:19,380 --> 00:39:23,479
here doesn't change a whole lot.

722
00:39:23,479 --> 00:39:25,020
The cell gets excited,
but it doesn't

723
00:39:25,020 --> 00:39:29,670
get excited enough to fire on
its own or anything like that.

724
00:39:29,670 --> 00:39:36,540
It's not unless you get a whole
bunch of action potentials

725
00:39:36,540 --> 00:39:40,830
at once so that there's a whole
bunch of sodium flowing in

726
00:39:40,830 --> 00:39:43,040
and the cell can
really depolarize,

727
00:39:43,040 --> 00:39:48,276
that that magnesium ion on
the NMDA receptors pops out.

728
00:39:48,276 --> 00:39:49,650
So eventually,
once the cell gets

729
00:39:49,650 --> 00:39:52,770
depolarized to about
minus 35 millivolts.

730
00:39:52,770 --> 00:39:55,130
Notice that's even further
than the firing threshold.

731
00:39:55,130 --> 00:39:59,160
This only happens when you have
lots of excitatory input coming

732
00:39:59,160 --> 00:40:01,110
into a cell.

733
00:40:01,110 --> 00:40:05,160
So the NMDA receptors
then finally open up

734
00:40:05,160 --> 00:40:10,530
and you get both calcium
and sodium coming in

735
00:40:10,530 --> 00:40:12,103
through your NMDA receptors.

736
00:40:18,019 --> 00:40:21,330
So sodium is an
excitatory ion flowing in.

737
00:40:21,330 --> 00:40:24,690
It's making the second
cell more likely to fire.

738
00:40:24,690 --> 00:40:27,060
Calcium, though,
is also excitatory,

739
00:40:27,060 --> 00:40:29,100
but we know that
calcium does a lot

740
00:40:29,100 --> 00:40:31,080
of really interesting stuff.

741
00:40:31,080 --> 00:40:35,190
Mostly, calcium tends to act
to activate other proteins

742
00:40:35,190 --> 00:40:39,240
in the cell and cause them to
go off and do a whole cascade

743
00:40:39,240 --> 00:40:42,790
of interesting things.

744
00:40:42,790 --> 00:40:45,150
So in this case,
NMDA receptors are

745
00:40:45,150 --> 00:40:49,630
acting like both an
ionotropic, because they've

746
00:40:49,630 --> 00:40:51,150
got ions coming in,
but they're also

747
00:40:51,150 --> 00:40:53,310
acting like a metabotropic
receptor in that they're

748
00:40:53,310 --> 00:40:55,950
causing these long-term changes.

749
00:40:55,950 --> 00:41:02,030
So what this calcium
does is calcium comes in

750
00:41:02,030 --> 00:41:05,585
and it binds to a bunch of
protein kinases, protein kinase

751
00:41:05,585 --> 00:41:10,490
A, protein kinase C, CAM kinase.

752
00:41:14,470 --> 00:41:16,990
Kinases have that
-ase ending on them,

753
00:41:16,990 --> 00:41:19,920
so they're an enzyme, right?

754
00:41:19,920 --> 00:41:23,020
So they're cells,
they're proteins,

755
00:41:23,020 --> 00:41:25,950
that encourage a
reaction of some sort.

756
00:41:25,950 --> 00:41:29,730
Kinases phosphorylate
other things.

757
00:41:29,730 --> 00:41:35,525
They stick phosphate groups
onto other molecules.

758
00:41:35,525 --> 00:41:37,940
And they all do
different things.

759
00:41:37,940 --> 00:41:39,720
CAMK here does a
couple of things.

760
00:41:39,720 --> 00:41:42,140
One of the things
that CAMK does is

761
00:41:42,140 --> 00:41:52,390
it goes back up to
those AMPA receptors

762
00:41:52,390 --> 00:41:55,480
and it phosphorylates those.

763
00:41:55,480 --> 00:41:59,770
Sticks a phosphate group
onto that AMPA receptor,

764
00:41:59,770 --> 00:42:02,920
and that makes the AMPA
receptors stay open longer.

765
00:42:02,920 --> 00:42:05,240
Every time that they get
opened by the glutamate,

766
00:42:05,240 --> 00:42:06,820
those receptors open up.

767
00:42:06,820 --> 00:42:08,530
They stay opened longer.

768
00:42:08,530 --> 00:42:11,620
More sodium can
come into the cell.

769
00:42:11,620 --> 00:42:14,890
And so the excitatory effect of
that receptor being activated

770
00:42:14,890 --> 00:42:16,510
is increased.

771
00:42:16,510 --> 00:42:21,100
So one of the ways that the NMDA
receptor, letting the calcium

772
00:42:21,100 --> 00:42:25,350
in, strengthens the synapse
is by phosphorylating the AMPA

773
00:42:25,350 --> 00:42:27,490
receptors so that
they, in turn, can

774
00:42:27,490 --> 00:42:32,620
allow more sodium in every time
that a glutamate bonds to them.

775
00:42:36,510 --> 00:42:46,780
CAMK also moves up the neuron
to other AMPA receptors

776
00:42:46,780 --> 00:42:49,000
that are not on the
membrane yet but have

777
00:42:49,000 --> 00:42:52,660
been produced by the
neuron and are hanging out.

778
00:42:52,660 --> 00:42:55,900
And it goes and gets
these AMPA receptors

779
00:42:55,900 --> 00:42:57,620
and it brings them
up to the membrane.

780
00:42:57,620 --> 00:43:01,540
So it encourages the movement
of more AMPA receptors

781
00:43:01,540 --> 00:43:04,090
from the interior of the
cell to the membrane.

782
00:43:04,090 --> 00:43:08,459
So it's not only increasing the
effectiveness of this receptor,

783
00:43:08,459 --> 00:43:10,000
it's actually causing
them to be more

784
00:43:10,000 --> 00:43:12,868
of them sitting there waiting
to soak up neurotransmitter.

785
00:43:40,810 --> 00:43:44,290
And the other thing that all
of these kinases seem to do

786
00:43:44,290 --> 00:43:49,330
is that they seem to all be
involved in phosphorylating

787
00:43:49,330 --> 00:43:53,500
a protein called CREB, which
is this Cyclic AMP Responsive

788
00:43:53,500 --> 00:43:54,805
Element Binding protein.

789
00:44:01,255 --> 00:44:02,225
Question?

790
00:44:02,225 --> 00:44:03,680
AUDIENCE: No.

791
00:44:03,680 --> 00:44:04,870
ABBY NOYCE: OK.

792
00:44:04,870 --> 00:44:09,557
So the Cyclic AMP Responsive
Element Binding protein,

793
00:44:09,557 --> 00:44:12,140
when it's phosphorylated, when
these other proteins come along

794
00:44:12,140 --> 00:44:14,810
and stick a phosphate
group onto it,

795
00:44:14,810 --> 00:44:18,470
it moves down, actually,
into the nucleus

796
00:44:18,470 --> 00:44:23,750
of the cell and binds to
specific regions of the cell's

797
00:44:23,750 --> 00:44:28,790
DNA, particularly the cyclic
AMP responsive elements

798
00:44:28,790 --> 00:44:32,000
of the DNA, which is why
it's called the Cyclic AMP

799
00:44:32,000 --> 00:44:35,350
Responsive Element
Binding protein.

800
00:44:35,350 --> 00:44:40,760
And so it binds to specific
regions of the cell's DNA

801
00:44:40,760 --> 00:44:44,570
and it promotes transcription
of the genes that

802
00:44:44,570 --> 00:44:47,120
are next to those
regions, so it's

803
00:44:47,120 --> 00:44:51,740
modulating which proteins
are actually formed.

804
00:44:51,740 --> 00:44:56,120
You'll remember from Bio that
you've got your DNA to RNA

805
00:44:56,120 --> 00:45:00,620
to protein model
of how cells work,

806
00:45:00,620 --> 00:45:04,070
the central dogma of
molecular biology.

807
00:45:04,070 --> 00:45:05,480
Nod if you've heard this before.

808
00:45:05,480 --> 00:45:06,770
Yes.

809
00:45:06,770 --> 00:45:07,370
Right.

810
00:45:07,370 --> 00:45:11,630
So by going down here
and binding to the DNA,

811
00:45:11,630 --> 00:45:15,230
this CREB protein
can cause it can

812
00:45:15,230 --> 00:45:19,460
control the rates
of transcription

813
00:45:19,460 --> 00:45:20,420
of some of these genes.

814
00:45:20,420 --> 00:45:24,397
So it's controlling how
fast the cell builds

815
00:45:24,397 --> 00:45:25,480
these particular proteins.

816
00:45:28,970 --> 00:45:33,320
And this is where this
starts getting kind of vague.

817
00:45:33,320 --> 00:45:34,010
What genes?

818
00:45:34,010 --> 00:45:35,480
What proteins?

819
00:45:35,480 --> 00:45:36,050
I don't know.

820
00:45:36,050 --> 00:45:39,680
I think people do know, at this
point, what some of them are.

821
00:45:39,680 --> 00:45:43,540
We know there's more
than 100 regions in