This is Paul Verchure with Sam Wang. And Sam has been coming out of physics,
dove into the cerebellum, using very advanced and novel technologies to actually
study the properties of the cerebellum.
And what you emphasized very much was this whole issue of how the cerebellum
is so important in the processing of unexpected events. events,
or in something you called about interrupt handling.
So what does that exactly mean? How should I think about that?
Well, probably, let's see. So when I talked about that in my lecture,
there are a few things that I meant.
So when I came out of physics coming into neuroscience, I first worked in cell
physiology for my graduate degree, calcium release phenomena,
and that was very much the biophysics of single cell phenomena, not even neurons.
But there's something that's really attractive to a physical scientist about
the cerebellum because it's got a really small number of cell types.
It looks like it should be analyzable by some kind of simple means,
even theoretical means.
And people, of course, have been interested in this going back to Marr and Albus.
So what I meant in my lecture about the cerebellum actings in Interrupt is that
there are two major pathways of excitatory information coming into the cerebellum.
One of them culminates in the production of a stream of spikes coming out of the Purkinje cells.
So Purkinje cells are like many inhibitory neurons of the brain in the sense
that they're firing all the time, tonically.
And what I meant is that there's this second input pathway, a second excitatory
pathway coming in via this funny structure called the inferior olive.
An input that comes in through the inferior olive fires much less frequently.
Each individual neuron of the olive fires maybe once a second,
and then it comes in and innervates, each one of those neurons innervates a
few dozen neurons in the cerebellum, these Purkinje cells, which are the output
of the cerebellar cortex.
And what I meant was that the system looks like it's a low-frequency firing
pathway, and so right off the bat, it seems like it's probably not going to
be encoding a lot of information in the rate of spikes.
It's more like the timing of these things is important.
Specifically, what I meant by the interrupt is that these individual spikes
trigger events that can drive plasticity, so they can drive plasticity at the Purkinje cells.
The thing I was showing today in my talk was also the possibility that we've
demonstrated with our optical methods that a number of these cells can fire together at once.
And that might be some kind of control signal that just sends a reset to the
cerebellar cortex or to the deep nuclei of the cerebellum.
And the idea is that it sends some kind of signal that can happen as an isolated
event in time that maybe resets the output of the Purkinje cells or perhaps can teach plasticity.
So the idea is that there's a unitary signal that can either reset in real time
or can drive learning on the long term.
But how should i think about this because then in some sense
what you're saying is well i can have my my inferior
olive neurons um through the climbing fibers talking to
the cells but what they convey can be
either like if you want a blind reset that is okay whatever was going on reset
this or a more specific signal for learning it doesn't sound like a possible
contradiction uh yeah so i guess one example that's going to be familiar to
many listeners of this podcast is, um...
Hebbian plasticity, right? So people talk about sequences of neurons firing
in order, and somehow that sequence of neurons firing in order,
which Hebb called the cell assembly, is some kind of re-remembered experience.
Remember that Hebb suggested that when we have an experience,
we have a bunch of neurons that fire in order.
If we imagine just one chain of neurons, just as an idealized example,
it would be A, then B, then C, then D, then E, right? So that would be a set
of neurons that fire in order.
And what Hebb suggested approximately, I mean, he didn't say all these things
when he formulated his hypothesis,
but what he was getting at was, okay, when you have the initial experience,
you have A, B, C, D, E firing, and then you can have plasticity processes that
strengthen the connections so that A, B, C, D, E is more likely to fire by itself.
And so that's a familiar example, I think, to many people who are students of
neuroscience, that somehow signals that go through the system can also instruct the system, right?
The experience itself has an effect that's immediate, and then there's some
kind of long-term plasticity. And when I was giving my lecture today,
I pointed out the fact that these complex spikes could likewise play two roles.
One, immediate role in driving processing right then and there to guide behavior.
And then the other thing they could do is they could teach plasticity.
So in some respects, I would say that this idea is not any different from Hebb's idea.
So the idea that this interrupt signal can do something right away and can also
drive a plasticity process. And I guess what I was getting at is that,
at least given what people know
now about this pathway, it's not really possible to separate those two.
At least at the level of the Purkinje cells, they happen together.
When one happens, the other happens. Okay, now I should say that there actually
is an exception to this, and it's okay if I go into the exception.
The exception occurs at the level of the synchrony. So I showed in my talk today
imaging data that suggests to us that many olivary neurons can fire together,
and therefore they evoke synchrony.
Complex spikes in many Purkinje cells at once. And so the exception to this
is that this interrupt signal, when it's in the form of synchrony across many
cells, could be processed elsewhere, not in the cerebellar cortex.
But when they fire all together, individually, they can drive plasticity in the Purkinje cells.
But when they fire together, that might be something special.
And I didn't get to talk about this much during the lecture.
But there's an idea that we've been been very interested in my laboratory,
which is that when these neurons all fire together, they can converge,
and then that convergence can be detected as a special event in the deep nuclei.
And that's another kind of event that can be encoded in this pathway.
Okay, clear. Because that would mean that then you might be able to distinguish,
let's say, a more localized reset versus really a plasticity controlling signal.
Yeah. So I would say that if one olivary neuron fires and one Purkinje cell
receives that, or sorry, a few dozen PNG cells receive that,
then that's an interrupt to those neurons, and it's something that could drive
plasticity in those neurons.
If a bunch of olivary neurons fire at once because they're coupled by gap junctions,
then that's the signal that has the additional property of maybe triggering
something interesting in the deep nuclei.
Okay. And that interesting thing could be, again, immediate readout or it could
be teaching plasticity.
And there's evidence in the literature. If you look in the literature,
you can find evidence that there's something interesting that happens in deep
nuclear cells, conditions under which you can get plasticity of the deep nuclei.
And this could be an event that drives that plasticity.
But that plasticity would then depend on this step over the Purkinje cells,
or it would depend on the collaterals from the climbing fibers directly to the deep nucleus?
Direct collaterals. So when I think about the cerebellum, what I visualize in my mind is this.
I think about relatively direct arcs that are purely excitatory,
for instance, input from the rest of the brain into the olive,
and then an excitatory arc from the olive to the deep nuclei,
and then the deep nuclei come back out to the rest of the brain.
So think of that as a direct excitatory reflex arc, perhaps like what Sherrington
said about the reflex arc with the knee reflex in the spinal cord.
And the pen in the slip machine.
I guess, yeah, right. Things that we don't think of as being too cognitively sophisticated.
And then sitting on top of that is the second loop, and the second loop is some
inhibitory thing that involves Purkinje cells, where you have excitation from
the same axon, except it's a branch of that axon, and that branch is called a climbing fiber.
Then it goes up to the Purkinje cells, and then that guy is an inhibitory neuron
that again comes to the deep nuclei.
It's a direct excitatory arc and an indirect inhibitory arc.
One can even think of the mossy fiber pathway as being, with some details different,
the same kind of system, where you have a direct arc that's excitatory and an
indirect arc that's inhibitory.
Basically, I guess when I look at cerebellar cortex, I see this inhibitory neuron.
These Purkinje cells are basically inhibitory interneurons that got out of control.
They hypertrophied over the course of evolution.
They became so big and important that they started developing this massive convergence of parallel fibers.
And they're so big and important, they get their own interneurons.
And so you have an interneuron that's got its own assistance.
So you've got layers of interneurons.
But these interneurons you would see as...
Controlling the function of deep nucleus
and downstream motor pathways or you see it
as an inhibitory control over if you
want the rest of the brain as well well everything that they do has to get filtered
through the deep nuclei because they only synapse onto the deep nuclei and so
ultimately everything has to go through the deep nuclei so i would think of
them either as getting back to the immediate versus long-term thing either as
neurons whose output shapes the deep nuclei,
the activity in the deep nuclear neurons,
or perhaps as a source of instruction.
So again, we have these two branches from, say, the olive going directly to
the deep nuclei, and another branch going up to the Purkinje cells and then into the deep nuclei.
Present one branch of input to the uh to the deepness yeah is that right okay yeah but then,
if so if we if you focus a bit on
these on these climbing fibers okay here we go with climbing fibers inferior
olive going off one hertz more or less yeah and then we might have some modulation
of this signal now on top of this we have a negative feedback on those responses
going back from the perkin yourself to the deep nucleus with inhibition onto
the inferior olive which can maybe
add some jitter now to this one Hertz activity.
Yeah. And on top of this, we can have now, let's say special kinds of events coming in.
Let, let's say I, um, air air puffs to the, to the eye. If we talk about eye blink conditioning.
So it's not a lot of mixing of, of possible states onto these,
these oscillating, slow oscillating neurons, how do perky yourselves disentangled is right.
So, so one, let's see, that's a great question. Um, I, uh, I'm not necessarily
going to give a very clear answer about this, but one thing I'm thinking about is this.
If you look at an individual olivary neuron that sends its climbing fibers to
the Purkinje cells, it fires on average about once a second.
What's observed is that it seems like most of the time it fires about once a
second. Maybe transiently it can go faster or slower, but basically at one hertz.
And that's a hard coding problem, because if you imagine, just imagine that
you're receiving input from the inferior olive, and you're getting about one spike a second.
Pop, pop, pop, pop, pop, right?
Five of them came in five seconds and now you're supposed to extract,
you know, you're the Purkinje cell or you're the deep nucleus and you're trying
to extract meaning from that.
And that's kind of a hard problem. But now if you add synchrony on top of that,
now imagine that two different Purkinje cells are receiving those kinds of inputs.
And then at certain points, this magical event happens where a number of them
all receive an input at the same time.
That can extract some olivary spikes from a background of ongoing activity.
And so I think the synchrony is interesting because it allows the possibility
of extracting features from this ongoing stream of slow asynchronous spikes.
And again, coming back to the deep nuclei, I mean, maybe one answer to your
question is that the deep nuclei are one way for this information to get read
out, and the Purkinje cells are another way. So let's back up and think about it a little bit.
Think about what the olive sounds like to these two structures.
If you look at the olive-to-deep-nuclear pathway, that's an excitatory projection,
and the only thing that's coming in on it is olivary spikes.
So that's an easy detection problem. Okay, now if you think about...
Olive, to the Purkinje cells, to the deep nuclei.
That's a hard detection problem because those same spikes are coming in,
but they're against this continuous wash of simple spikes that are being driven
by the parallel fiber pathway, right?
And so there's this wash of spikes coming through with these little guys riding
on top of it. And it's not so obvious how you would detect that.
Right. But you gave a pretty good imitation of that in your lecture.
So what does it sound like in the lab?
Well, so it's in the, you know, these things are recorded optically.
And so So actually, it turns out it doesn't sound like anything.
But the thing I was doing in front of the, you know, in the lecture today is
I was having each of my fingers be one Purkinje cell.
And when they're firing asynchronously, it looks like you're playing some kind
of random set of keys, say, on a piano.
But when you have a synchrony event, what that looks like is like playing a chord on a piano.
And so you have many fingers all coming down at the same time.
And so what I was demonstrating for people is the idea that somehow these synchrony
events are like chords being played in the olive. Right.
So then, already now we look at what you call this hard coding problem for the
Purkinje cells with respect to the inferior olive.
But apparently this became more complex because now with this imaging work that
you have been developing,
here we have the mouse on the styrofoam ball
running around and you're imaging the climbing fibers
and the Purkinje cells in particular and
suddenly what we see is that it's fairly complex synchronized responses among
the subgroups of Purkinje cells so is it still in the same ballpark as you just
described the dynamics of the system or do you think it adds a whole new layer
of complexity complexity.
Oh boy. Let's see. So I don't know how to answer that because I know that people
in the field have been very interested in the idea that somehow the signals
themselves are used in processing.
So for instance, people are interested in the fact that when a Purkinje cell
fires a complex spike, there's a brief pause of tens of milliseconds right after
it fires the complex spike where there are no sodium spikes,
and then the sodium spikes begin again.
So it sounds like, if you slow it down, it sounds like where the complex spike
comes in, and there's a pause, and then the sodium spikes go and start up again.
And so there's this characteristic shape, and one focus of research has been
the idea that that and the pause somehow encode information,
and that's a salient feature that then presumably gets picked up by the deep nuclei.
So that's a feature that can sit on top of the simple spike stream.
And that's a candidate for what could get processed by the deep nuclei.
So I think I'm giving you a little bit of an unclear answer,
but I'm saying that essentially it could be a feature that could be processed
on top of the sodium spike stream.
So are you confident that there's enough evidence available that would show
us that indeed the deep nucleus could make sense from such a response?
Because in some sense, the deep nucleus has to invert this now.
If the deep nucleus wants to report to the rest of the system,
something happened in the cerebellar cortex, it has to convert this pause into
an action potential. So how do we do that?
That's a great question. I think
that biophysically, it feels like it's a little bit of a hard problem.
This pause, when people have recorded it in vivo, has only been a few tens of milliseconds.
If you think about synaptic mechanisms that could read that out,
that's a little bit of a hard problem.
And I think the way that that problem becomes easier is to get back to the synchrony
is if a lot of, it may be a pretty short pause, but if a lot of Purkinje cells
do it at once, then it has the advantage of summing, right?
So if you think about, I don't know, 100 Purkinje cells all converging on one
deep nuclear neuron, and they're all pounding away with their sodium spikes,
if those pauses come at different times, that is not going to be a very impressive
event to the deep nucleus.
But the moment you synchronize them all with one another, now you have everybody pausing.
It's like those moments in the orchestra when the orchestra is playing and playing
and playing, and then everybody stops all at once.
That's a really interesting event when you're listening to the orchestra.
And so it's something like that, where synchrony buys you something that the
pause itself might not be very good at without the synchrony.
Would you say that we need something like a rebound polarization to invert the pause into activity?
That is certainly the feeling that's been prevalent in the field.
Not all deep nuclear neurons rebound, but the phenomenon, to remind people,
is that when you hyperpolarize a deep nuclear neuron and then you let go,
at the moment that you let go, there's a rebound and there's a little burst
of spikes, and then the neuron resumes spiking again.
So one major belief in the field of people who study cerebellum is that that
could happen, for instance,
when you say, when the Purkinje cells pause, they provide inhibition,
they stop providing inhibition, and that's the equivalent of release from inhibition,
and then you get a rebound. So that's the prevailing view in the field.
I think that is a candidate for how information could be encoded.
Another possibility is that there might be other interesting biophysical events
that nobody's observed yet.
So one possibility we're very interested in in my laboratory is the idea that
at the time of that rebound, there might be something biophysically interesting
happening in deep nuclear cells.
Something like, say, a dendritic action potential, something like that.
And so I think there are levels of that that haven't yet been explored because
people have not had the imaging technology available.
Some of the data you showed us showed this very curious phenomenon where,
for instance, you might initially be able to trigger climbing fiber responses
driven by some metasensory stimulus like an air puff to the snout.
And later, you might see the same climbing fiber responding in a way that seems
to be correlated with motor action.
So how should I interpret this?
Well, okay. So first, the empirical observation is this. the empirical observation
is that these climbing fibers are active the animal is under the microscope
it's a mouse and it's also standing on a foam ball and it can walk freely and
it's an awake animal and under this condition,
this is collaborative work that we've done with David Tank, under this condition
what we can see is that the climbing fibers sorry, the complex spikes that we observe.
Are activated when the animal's resting when we give a stimulus to the animal.
Like if we give it a clapping sound, or if we apply an air puff to its hindquarters.
And we originally did this to try to get the animal to walk.
And because we were trying to get the animal to do something,
we've got the animal on the ball, we think, well, if we could poke it,
maybe it'll start walking, and then that'll be interesting. So that was our
original reason for doing it.
So we give the animal a poke, and we can see that a bunch of these complex spikes
fire across the population of Purkinje cells at once.
So a chord is played to follow the musical metaphor.
And that happens when the animal's resting, when there's a stimulus given.
But then when the animal starts walking, there's something that happens that.
There's some kind of switch that happens. And the switch that happens is that
the same population of cells that we've been observing all along,
dendrites that we've been imaging, start generating lots of cords without our input.
So it's some kind of cords that are synchronous firing events that are self-generated.
Somehow by the animal's movement, there's something about the animal's movement
that generates lots of these.
And under that condition, there's lots of these synchronous events happening.
But the other thing that happens is that now when we apply stimuli, no response.
It just becomes insensitive to those stimuli. So the same set of Purkinje cells,
whose complex spikes were previously sensitive to external input,
now seem to be sensitive to self-generated activity, something that the animal itself is doing.
And so there's some kind of gating where it gates from external to internal events. Right.
So how can you be sure that it's really internally generated?
You could argue like, well, maybe it is just another form of somatosensory stimulation
because of the movement.
It could be. It could be things like joint movement.
We've done a little bit in that regard to try to tease that apart.
One thing we've done is when the animal's standing there passively, we rotate the ball.
When we rotate the ball and the animal's standing there, we're inducing some
degree of passive movements, and we do not see synchronous firing events under that condition.
So that suggests to us that it's something more than just, say,
a joint movement or some kind of somatosensory or proprioceptive event.
Honestly, I'm not sure we know exactly what it is, but we do know that we can't
get it by the animal passively being moved around.
But then, so in the concepts that you're developing, we started with this notion
of climbing fibers as interrupt signals.
Yes. And now we move to this notion of gating, which more has to do with the
different input streams can be sort of re-channeled into driving the same set
of these interrupt signals.
So what are the functional consequences of that? How should I think about gating and interrupt?
That's a great question. I think that for the time being, tentatively,
I might imagine that the system is sensitive to different kinds of signals depending
on what is behaviorally needed.
So when the animal's at rest, what it needs is to be sensitive to external events
that say, okay, it's time for you to walk.
Something surprising has happened. It's time for you to react in some way.
And then once the animal's walking, well, under that condition,
then there are a lot of internal signals being generated that are more important
for the animal to deal with when it's handling its walking. So,
I think that I was talking to you or someone else earlier today when I made the joke.
It's something like, don't talk to me now, I'm tying my shoes.
And it's like that, where when you're tying your shoes, what you don't want
is someone telling you stuff.
What you want is to focus on your shoes, or whatever it is that you're doing
in order to tie your shoes.
So what I suspect is that some kind of gating whose behavioral function could
be to let in relevant information and not let in information that's of less
use at that particular moment.
But in some sense, this raises the next question fairly automatically, no?
Because then you're implying that the circuit that is affected by these climbing
fiber signals is playing a functional role in both behavioral contexts.
Yes, that is what I'm implying. There's some work that precedes this from a
single-neuron recording in The Olive and also upstream of The Olive,
I think mainly in The Olive, from this fellow in the UK, Richard Apps.
And Apps and his collaborators have been very interested in that kind of switched information.
And I believe, if I recall correctly, that they can see switching on a pretty rapid timescale.
One result that comes to mind is that when a cat is walking on a treadmill,
if you deliver a tactile stimulus to the cat's foot,
How much climbing fiber response you get depends on what stage of the stride.
So if the animal's in stance, then if I remember correctly, if the animal's
in stance, then there's no response.
If the animal's in stride, then there is a response.
And the functional difference there is that when the animal's in stance,
it's getting tactile impotence. So of course, something that touches it might not be so interesting.
But if the animal's in stride, then touching it is going to be a more interesting event.
And that's been demonstrated at the level of single cells using electrophysiological
conventional electrode-based methods, but with pretty rapid time switching,
like on the timescale of walking.
Still seconds or hundreds of milliseconds. Yeah, definitely pretty fast.
I mean, as you know, the pace of a cat walking on a treadmill.
Okay. So then in some sense you're saying it's like the parsing of sensory information
in the context of behavior.
Yeah. So for instance, we're now getting pretty far away from any of the data that I showed.
But think of one common thing that people talk about when they talk about cerebellar
function, which is the phenomenon that you can't tickle yourself.
There's some kind of sensory cancellation where when you stroke yourself in
your abdomen, then that doesn't tickle. But when someone else does it, then that does tickle.
And so there's very clearly this contextual processing of the
same sensory information whether you're generating it or
whether you know whether somebody else is doing it under some silly condition
right and so something like that is very clearly something we have to do every
day at every moment and so one possibility here is that this is one neural correlate
of that okay so now um to switch a little bit topic um.
So coming from physics, in some sense, you've made a rather dramatic transformation
because now you're really a very much data-oriented physiologist, if you want.
And you would expect as a physicist, you still be looking for,
let's say, theory models and so on.
So what's your opinion of the current state of the art in our,
let's say, theoretical understanding of this system? For instance,
you have these theories floating around about, let's say, inverse models or
forward models, adaptive filters, reinforcement learning models.
How well are we doing there, in your opinion?
Well, I think those ideas are all very interesting ideas. I mean,
basically, we're talking about ideas in which people either take inspiration
from physics or from control theory, from engineering, to try to understand
how these neural systems work. So let's see.
So I'll state the positive thing, which is that these are simplified ideas that
give us some conceptual framework for thinking about how neural systems work.
They come from engineering in many cases, which is a very positive thing because
nervous systems are shaped by natural selection.
And in some sense, natural selection is basically nature's engineer that's trying
to get things to work well. So those are positives.
I think that one thing that those theories do is they provide a framework for
then doing experiments to test the ideas.
And so I think that right now we're at a stage where there's lots of ideas,
and then I think well-designed experiments can then go in and test those ideas.
But if I had to really be frank, I would say that many of those ideas will probably
end up being wrong, right?
Because those are tentative things, those are frameworks that we have to work
with. and we go in and if we do a well-designed experiment, if we do a good
experiment, then we can start weeding out wrong ideas.
I think that one strong role of a well-formed theory is that you go do an experiment,
and I've slowly formed the impression over time that it's perfectly okay to throw out the theory.
That one should not get too sentimental about a particular theoretical idea.
Of course, I'm an experimentalist, and so I guess the theorists say the same
thing about the experimentalists. Sure.
Where do you see this experimental protocol or the paradigm going that you are
developing, which is fairly advanced?
So the things that we are very interested in right now, basically,
to state the obvious, the thing that these imaging methods can buy you is the
capacity to probe many neurons at once in a working neural system.
And that's very exciting.
I think that the kinds of things that are coming up in the near future are development
of tools to get better temporal resolution.
So, for instance, if the tool we're talking about is use of a calcium-sensitive
fluorescent dye to get those dyes to perform more quickly, Perhaps if a voltage-sensitive
indicator ever becomes able to report single cells in vivo, then that would be the ultimate of that.
Another direction that's exciting is using molecular biology to target these
indicators so you can see specific cell types. That's obviously of interest.
Another direction is optogenetics, which I believe came up during the discussion
of my talk, where you can have light-activated ways of perturbing the tissue.
So instead of the tissue telling you something, now you tell the tissue something,
and you can perturb function.
And then totally independent of all these things.
So I think those are the natural outgrowths of imaging technology.
And then there's this other thing that's sort of looming on the horizon that
we haven't talked about at all, which is this other field of connectomics in
which people are starting to do tracing with better and better technologies
to reconstruct entire neural circuits.
And I think that that's some distant future point of convergence between this
kind of methodology to monitor and perturb function, and then anatomical methods
to reconstruct the whole circuit. Right. So that would be the global...
Very good. So to close off, I have two questions for you.
So on the one hand, in your experience in this field, and this very sort of
dedicated study of, in this case, the cerebellum, on the basis of the experience,
what's the law of Sam Wang you would like to give to us we should adhere to?
Oh, good Lord. Are you serious? Yeah, of course.
A general rule for how to conduct oneself? Yes. Oh.
How to study the brain, how to gain knowledge, how to explain brain function. You have freedom.
It's not only about morality and ethics. I don't know.
There are several things that I've been very interested in lately,
and they were touched upon a little bit during Parthometra's talk,
which he gave last Friday on September 3rd.
He talked about principles that could guide a theorist as being development and evolution.
I would say as an experimentalist, I'm very interested in that as well.
So, so far, what we've talked about is experimental tools that one can bring
to bear on understanding a neural system.
But one thing I've been thinking about a lot lately is the role of natural selection
in, say, conserving a system, namely that these neural tissues cost a lot of
energy to operate, and the bigger they are, the more energy they take.
And so maybe I want you to think a little bit about energetics as a guiding
principle, because maybe neural
systems are trying not to spend too much energy in doing what they do.
And then evolution. Evolution can take any number of forms, but one thing that's
very interesting to me these days is homology between different systems.
Looking at different neural systems to look for guidance in how one,
in my case, the mouse cerebellum works, maybe I should be interested in, say, electric fish.
Or maybe I should be interested in, I don't know what, neuromodulatory systems
in other parts of the brain.
And I don't have a very good specific piece of advice to give,
but the reason I'm bringing up these things is that these areas,
development, evolution, and even neuroanatomy,
are things that a physicist does not necessarily naturally take to.
And so the reason I'm bringing these up is that as a former physicist.
These have been unusually, unexpectedly interesting to me.
I never thought that I would be interested in neuroanatomy, especially comparative
neuroanatomy, but it turns out that against my will, I've become very interested in that.
Okay, very good. And then the last one, if five years from now,
I'm going to go visit you in your lab and say, look, Sam, five years back,
you made this one prediction, and today I'm going to check whether it turned out to be false or true.
What's this one prediction you would like to make today you really would stick your neck out for?
A prediction? Yeah, one prediction. The inferior olive is a teacher to both
the Purkinje cells and to the deep nuclei.
And its main role is as a teacher of the Cerebellar circuit.
Perfect. Sam Wang, thank you very much for this conversation.
Okay, see you in five years. Good.