(click) (beeping)
(inspirational techno music)
- What I'm gonna try to do
is to tell you what the challenge is
and how far we've gotten.
First of all, this diagram,
which Pat Churchland and I first published
in our book in 1992, The Computational Brain,
illustrates the real difficulty here,
because there's 11 orders of spacial magnitude
between molecules down here at the very bottom
and the entire central nervous system
that gives rise to behavior
up at the very top at the meter of scale.
And we've heard talks today at every one of these levels.
We've heard about hormones,
the important impact that they have
on remodeling the brain, especially during adolescence.
Synapses, we've heard that pruning
may be of critical importance,
both in the development and then degeneration.
So that's clearly very important,
and understanding how the molecules
at the synapses in particular
are responsible for maturation is critical.
We know that there are changes occurring in networks.
For example, we heard about the impact of sound
on the maturation of a baby's auditory system
and how important that was
for being able to later have normal language
and learning ability.
If you can't hear properly,
then it's very difficult to know what people are saying,
and especially if you start going to school,
it puts you at a great disadvantage.
We heard about the brain imaging,
the important technique that allows us
to tap into large scale patterns of brain activity.
But how do you jump from
these large scale patterns way up here, global activity,
down all the way through all the systems and the maps?
We heard about visual system
is a sequence of maps from primary visual cortex,
dozens, up to the very higher areas
that are responsible for being able to recognize objects.
How are we gonna connect the dots
between all these areas?
That's really the challenge.
And it's not gonna be necessarily
jumping from molecules to CNS,
although we'd always like the magic pill
that is targeting a specific molecule
and then hoping that that will solve everything.
I don't think that's a good model.
The fact that we've had how many clinical trials
for Alzheimer's that have failed
in the last two or three years is at least a dozen trials
saying that amyloid plaque by itself,
getting rid of it isn't necessarily
the way to solve the problem.
Now there's something missing from this,
and I have to say that there's a lot missing from it,
but just from today's talks
I think you've heard that we have to add
at least one more type of cell to this diagram.
Half the cells in your brain are glial cells,
and in particular there's the astrocytes.
We've heard a lot about the microglia.
The oligdendrocytes are very important, too,
because they're the ones that wrap around the axons
and they speed the action potential down the axons.
That has to do with timing,
and so we really have to put them front and center
if we're gonna especially understand
something about when things go wrong.
Now when I was young,
I was told that space is the final frontier
from watching Star Trek.
(audience laughs)
But I now come to believe
that the final frontier is going to be time,
understanding how the temporal processing
occurring in different circuits
and delays that occur between communication,
between different parts of the brain,
may be critically important.
We've neglected it,
so I've worked on networks for my entire career,
and I've always thought of networks
as being the tightly interconnected group of neurons,
typically in the cortex,
a single neuron connecting to 10,000 neighbors,
and in a single column 100,000 neurons,
and that adds up to at the end
billions of synapses in a single column.
But there's another kind of network,
and that's a communication network.
A communication network is the one that extends,
broadcasts the signals in your cell phones, right,
are being broadcast through a communication network,
and the brain has one that is just as sophisticated
as anything that we've ever come across.
But I want to take you back to the early days
when Carla was a young puppy,
or young kitten, I guess.
I'm not sure what would be the proper way of putting it,
which he made a very important (laughs),
sorry, Carla.
(audience laughs)
It was a very important observation
about traveling waves in the retina.
The reason why it's important is that these occur
even before the eye opens,
so there's dynamic patterns of activity
that are already spreading through the retina.
And here you can see,
this is now from a more recent paper,
but this from an array of electrodes
that are put on the retina that's slapped down.
And these are the action potentials
coming from the ganglion cells.
And you can see over seconds this wave of activity
sweeps across the retina.
Now, why is that interesting?
Well, it turns out that these waves
are giving a temporal structure to the action potentials
going up to the next stage in the lateral geniculate,
and it's essential for getting that pathway
wired up properly, being able to sort out
the input from the two eyes, first of all,
'cause the waves are independent,
but secondly is information about location,
because as the wave spreads from one location to the next,
the action potentials arrive one position to the next,
and that helps sort out the map in LGN
and ultimately into the cortex.
Now, very recently,
we discovered waves in the cerebral cortex,
global waves, unbelievably large scale patterns of activity
that we still don't understand the significance of,
although I have a pretty good hypothesis,
and they occur while you are sleeping.
When you go to sleep, you go through several stages
from awake down to deep slow wave sleep,
but on the way, you go through stage two.
It's called intermediate sleep,
and it's characterized by these sleep spindles.
These are bursting activity that originates in the thalamus,
projects to the cortex.
They are 10 to 14 hertz.
They last one or two seconds.
They recur every five seconds.
And there are some people who spend
up to half of the night in this slow wave sleep
during which the spindles are occurring.
Now, I've done some very detailed biophysical modeling,
so I can tell you precise mechanisms
that give rise to the spindles.
It's a bursting.
It has to do with new ion channels that are uncovered
when the cells hyper-polarize.
It means that membrane potential goes down.
But what I would've never guessed is how the activity
between the thalamus and the cortex organizes itself.
In the textbooks, what you hear is that it's synchronous.
That is to say it occurs the same place in the cortex
at exactly the same time.
And it is approximately synchronous.
But I wanted to let you decide for yourself
how synchronous it really is.
So this is an array of electrodes,
eight by eight, 64 electrodes,
that have been placed on the surface of the cortex
in an epilepsy patient who has gone to the hospital
with a form of epilepsy
that can't be treated with any drugs.
And so what they have to do is isolate the focus
so they can go in and take it out
and hopefully keep that person from having seizures again.
So here is the electrodes.
And by the way, they have these electrodes in
for about a week waiting for a seizure to occur,
so it's a fantastic opportunity for someone like me,
a neuroscientist, who wants to ask fundamental questions
about a human brain, about things like language
for which there is no other model system.
Okay, so what we've done is color each in gray,
from white to black, as you can see, the amplitude.
And this is the one that you're gonna see here in red,
is this one, but all the other electrodes
are gonna be represented that way,
and I want you just to follow the white dots
and tell me what pattern they form.
This is going around once every 70 milliseconds, right?
So this is going around at roughly 14 hertz.
And you can see as it goes up and down.
So did everybody see what I saw?
It's a rotating, circular, traveling wave, and it's global.
It goes from, as you can see,
it goes from the temporal cortex to the parietal cortex
up to the prefrontal cortex.
And if you look at the pattern on the side of my head,
this should remind of you Princess Leia.
(audience laughs)
So this occurs thousands of times during the night.
What is it doing?
We think it has something to do with synaptic plasticity,
because the timing is just right for something called
spike-time-dependent plasticity.
And so it may be that, we know there's replay
from the hippocampus during the night.
It's called memory consolidation,
and it occurs over many, many nights,
and this might be the mechanism.
So we have a really great opportunity here
to actually explore it.
Now, we know that there are long range connections
between different parts of the cortex,
these are called association fibers,
and also across between the hemispheres.
And it's really these that we think
are carrying the time delayed signals.
And it may be that these time delays are really important,
getting them right.
We know that in, for example, traumatic brain injury
when soldiers come back from the Middle East
with traumatic problems with traumas,
they often have problems with concentration and attention,
and concussions on football players and so forth,
and when you look in the brain with MR,
the only thing you can find
are little spots in the white matter.
So, it could well be that the white matter
is really important for integrating globally
all the information in different parts of the cortex,
and it could be that by strengthening connections
between these distant areas
through spindles or some other mechanism
that we're able to connect up all the different parts
of the sensory cortices and association
in the prefrontal cortex.
Now, the timing is also, obviously,
very important in the auditory cortex
and in the motor systems.
So this is, I think, something that hasn't been explored.
We focus so much on the gray matter
and not so much on the white matter.
There are some really intriguing observations that
when learning takes place, it's not just the synapses
that change their strength,
the volume of the white matter changes.
How could that be?
Well, the oligodendrocytes that wrap around the axons
change the speed.
So maybe what's happening is you're adjusting
the timing of the spike as it goes across
these large scale connections
between different parts of the cortex.
That's all speculative, but I think it really means
we have to start looking carefully at the axons
as well as the dendrites.
Now, I'm gonna play a science fiction movie for you.
It's animated, but it's based on the connections we see,
and it also gives you, you'll see an impression
of the activity that might be taking place
within the cortex.
So these little white flashes
are actually action potentials, spikes,
going down the axons that you just saw
between these different cortical areas.
And this gives you an impression of what it might be
if you could actually see into your brain,
the person sitting next to you,
and actually see what they're thinking
or what they're seeing or what it is that they're doing
in terms of their motor system.
Every single thought is gonna be represented
by some pattern of activity in some part of your brain,
and specifically in different parts of the cortex.
Now, right now this is science fiction for the human,
but, on April 2nd, 2013,
Obama announced this grand initiative.
These grand initiatives only occur once every decade or two,
and when they do, it really has an impact,
and it has had a huge impact on the neuroscience community
over the last three years.
The key letters, by the way, in the acronym IN
is innovative neurotechnology.
And I have to say that our sponsors, the Kavli Foundation,
were critically important in bringing this opportunity
to the notice of the White House.
And Miyoung Chun in particular was the spark plug
who actually got the thing off the ground,
so we really owe the Kavli Foundation
a great debt of gratitude.
But what's happened since this announcement
is really astonishing,
because new tools and techniques are coming online
that are accelerating research by orders of magnitude,
and let me give you one example.
And this is not science fiction.
This is real.
This, you are seeing a zebra fish larval brain.
You could see, it's only a millimeter or so across.
It contains about 80,000 neurons.
It has a genetic marker that will light the neuron up
when it's activated.
So here's a neuron, here's a neuron, here's a neuron.
These are the ones that are firing
at this particular moment in time,
and this is looking at it from below,
from above, from the front, and from the side.
We can record from all the neurons
at the same time from this brain.
And I'm gonna play a movie just to prove that.
Now, I hate to tell you this.
This zebra fish larva is just sitting there.
It's immobilized, and there's no sensory input.
There's no light.
So what you're seeing is called spontaneous activity.
But every once in a while, the spontaneous activity,
the pattern changes, like right there.
What's happening?
Something happened in the brain of the zebra fish
that is unrelated to anything
that the zebra fish is experiencing or is actually moving.
But it's really clear,
to me, at least, that we don't understand the first thing.
(audience laughs)
It's a Chinese curse, "May you get what you wish for,"
and this is something we've always wanted,
to be able to have access to all of the neurons
and the activity occurring.
For all we know,
this is what the zebra fish does when it thinks.
What do you do when you go to bed at night
and you're sitting there, right?
There's no sensory input coming, you're not moving,
but thoughts go through your head, right?
So that's gotta be represented somewhere,
so this is getting tools and techniques
that allow us to decode what those patterns are
is really the challenge.
And we're very fortunate that tools and techniques
are coming online exactly when we needed them.
It's called machine learning,
and there's a meeting that's been held for the last 30 years
called Neural Information Processing Systems, NIPS,
and the next meeting will be held in Barcelona next week.
6,000 people will show up.
At the first meeting, there were 600,
so that's a factor of 10 greater.
And every single high tech company is showing up to recruit.
And why?
It turns out that these tools and techniques
that have been developed
and have been inspired by the brain,
the N is neural, it turns out have
fantastic applications in the real world.
You've heard about deep learning.
Well, deep learning came from this NIPS community.
And, those same tools and techniques can be used
for understanding those patterns of activity
that you just saw, for analyzing large scale recordings,
for working out the detailed wiring diagram
called connectomics, and for quantifying behavior.
It turns out that we can go way beyond
the simple having an animal press a button
with having it move around freely,
and this can be done automatically and scored.
And it's been done on flies, it's been done on mice.
They have a sequence of stereotyped behavior.
They groom themselves and so forth.
And interestingly, on humans.
We can now detect and automatically score
your facial expressions.
Like, we saw some pictures of the fearful face.
Well, we've worked with Paul Ekman,
and we've developed these deep learning tools
to actually be able to do that automatically,
and we can detect these fleeting moments of expression
across your face.
They're called micro-expressions,
and they're very telling, because they're brain leaks.
They're feelings you're having inside that leak through,
and you may not even be aware of 'em yourself,
but they can be picked up now,
and that can be a way that we can understand
a little bit more about the internal state of your brain.
Okay, so I just wanna end by saying that Lyle Muller,
who was responsible for doing
that beautiful rotating traveling wave,
is on the job market.
So if you have a job (audience laughs)
for a budding young experimentalist and theoretician
and data analyst, he's your man.
Thank you.
(audience applauds)
(inspirational techno music)