So I'm here with, this is Paul Vachure with Kathy Roepland at the Catherly Center
for Theoretical Physics.
We're both attending a workshop on network architecture and the brain.
And Kathy, you gave us a presentation yesterday where you really gave us quite
a broad overview of the anatomy of mainly cerebral cortex.
Yes. So, what do you think are the key properties of a neocortex that we should
be aware of? Of the neocortex?
Well, let me start with what may seem backwards and say I think the distributed property.
Most people are not going to say this first thing. But if you look at these
axons, and you look at the divergence, and you look at the collateralization.
The first word, English word, that comes to your mind is distributed or divergent.
Now we can proceed a little bit more. That immediately gets you into questions
of probably random or specific, which we can come back to.
I'm not saying random, I'm just saying simple fact of distributed.
And so that's one thing we can come back to. Probably what most people would
then talk about the cortex is because it's been promoted and promoted and promoted,
a uniform organization,
this is what we were talking about at lunch.
But that really, if you look closely at the anatomy, that's not the first thing that comes to mind.
I could show you pictures later. We can develop that theme also.
Having said that, I would then introduce the idea that, which many people are
saying, that the anatomy and the function is a little bit discrepant.
We've been, again, trained to say structure-function correlation.
But now it's very clear that there can be functional aspects and structural
aspects, and sometimes there's an apparent discrepancy.
Cortex, of course, can deal with it, but for us it looks... Can you give an
example of discrepancy? Yeah, I think, and we might have talked about this yesterday also.
One of my favorite examples, and you can pick this apart, please,
is ocular dominance columns in the monkey.
So you are shown ocular dominance columns with beautiful 2DG,
so an eye is blocked and you see the 2DG pattern more or less through the layers.
It's very convincing. It's very real. Then you are told what is the truth,
that the basis of this is thalamocortical connectivity.
Now, there are actually several things to say about that. One is,
if you look at the scale of the anatomy and the functional column,
there's an immediate mismatch.
So in layer 4C, the main layer, parvosellular axons are smaller than 500.
I should say the ocular functional columns are about 500 microns in diameter.
But the parvosellular LGN is smaller, 250.
Magnocellular is larger, with two or three clusters.
Then 4A, you have another population of thalamocortical axons.
It's very small, 100 microns, center to center.
Sometimes they're collaterals in layer 6. These tend to be smaller.
The cytochrome oxidase population is the axons are less than,
equal or less than 100 microns.
And in layer 1, whatever goes up there from the LGM is very divergent.
So I was puzzled by this for a long time, and my own explanation is there must
be some operation, something, some operation, which is making those axons converge,
and the key word here would be maybe something operation, and converge in a 500 micron space.
And the two candidates would be something molecular.
Going back to development presumably, maybe extracellular matrix,
and activity-related, or and or both.
Okay, so here, let me summarize. The functional column is unambiguously bicarbonate
microns, but the anatomical basis of this, the primary anatomical basis,
is all, I'll use the same term probably several times, all around the block.
Now, of course, the reconciliation, we think, would be from the intrinsic processing, But that gets you in.
It's not the same thing as saying thalamocortical connections are the basis
of ocular dominance columns.
It means that the cortex is doing, the intrinsic cortex is doing something on those connections.
But how do you then define this functional scale of organization of 500 micron?
What you would see, well, so my first response is operationally that you can link.
I think if you have a functional marker like 2-D-alcyclicose or CFOS,
and you can link it to a behavior, you will tend to see a columnar,
often a columnar organization of this amount.
Does that, does that want to go a little bit further? No, go ahead, go ahead.
But having said that, there is some beautiful work, and I'm sorry I forget the
authors here, but it was within the last five years on the CFOS of...
Might have been Japanese group Yamamori where
they were looking at different
conditions of ocular deprivation in
the monkey in CCOS which is a better resolution than the 2DG and they would
see they were able to see several laminar patterns depending on the time interval
and what they had actually done with the ocular dominant.
So even there, there is a suggestion that when you're looking at average techniques.
It's telling you part of reality, but not the whole.
Okay, so one bottom line of this is that structural and functional organization
does not necessarily matter.
Not to the investigative view. So it works in biology, but not in the way we
might think. There's no simple mapping between the two. Often not.
In fact, when it occurs, it's almost the exception.
And one exception would be, for example, corticospinal tract,
where you have the difference of primate with the fine pincer movement versus
the carnivores that cup. And there is an anatomical basis.
Or even the development of the corticospinal tract, so babies can't walk until
the corticospinal tract does something, myelination, maybe other things.
But I've come to think it's almost the exception.
Okay. But now in your presentation, you also went a bit further than that, right?
Because you also pointed out that the sort of standard notions of feed forward
and feed back that people have been using to describe the structure of the cortex
might not be that clear-cut either.
Absolutely. And I think in several ways.
One, even if you take the schematic, the strong view with layers and so on,
There are many exceptions, really abundant exceptions.
And when you go to the rodent, it's been well known for years that the laminar-based
scheme breaks down in a big way.
You have a layer one is favored maybe by what could be feedback.
Layer four is favored, but there's a tremendous blurring.
But even within primate, you have a lot of exceptions. But what are the rules,
really, on which we have these exceptions?
What do you mean by that? Well, as you say, you have many exceptions in rodent
and also in monkey, but then there's a rule to which you have an exception,
right? So what's the rule for it?
All right. Well, the old rule, which has some basis, in fact,
in static anatomical fact, is that… Okay, feed forward.
See, it's really based on a relay view of the brain, and I don't think that's very useful.
But if you accept that relay view, the visual information goes to the eye,
goes to the LGN, goes to V1, and so on.
Then, and of course, V1 goes to LGN, but also other things go to LGN.
So none of these are pairwise. Absolutely none.
When you get to V1, and you say, okay, let's start the relay from there. and if you do V1, V2, V3,
let's just put in MT, extra striate, V4, infratemporal cortex,
there is, you can plausibly say layer 3 goes to layer 4, an input layer, in your feedforward.
And the feedback is actually usually two layers, layer 6 and layer 2,
feeding back to layer 1 and sometimes layer 6.
But there is a dissociation, one can present a dissociation of a Layer 4-based
feed-forward and a Layer 1-based feedback.
And there also is, this was the data, these were the data I was showing yesterday,
a dissociation in spatial organization.
Feed-forward tends to have smaller arbors, sometimes multiple,
feedback divergent in Layer 1.
But I would still, I suggested yesterday and would still like to suggest that
you can rephrase this in terms of a Layer 1 organization or a Layer 1 biased
connection and a Layer 4 biased connection.
There's no real need to say feed forward and feed back in that.
And it has a very bad assumption of saying, well, something happened,
and then there was a feedback.
But we don't know when the film started.
So there is a strong assumption in the terminology of this temporal or relay
pattern, which I think is not, it can be useful to an extent,
but it cannot be the whole truth.
Right. Okay. Okay, but then another issue then becomes this so-called uniformity of cortex, right?
So, for instance, you would say, well, we have a layered structure.
And pseudo-architectonically, it sort of roughly remains the same if we sort
of go from the front to the back, right?
And also there would then be this idea that maybe in terms of their functional
organization, things will change in the sort of occipital areas and parietals,
more sensory, and if we go more frontal, we go more motor.
Is that then at least a pattern we can still sort of adhere to?
Yes, by all means. But of course, I'm going to say but.
And you have to keep in mind the threshold problem, which is glaringly obvious in fMRI.
So if you set your, if I understand correctly, if you set your threshold low
enough, you're going to see lots of stuff.
And it's apparent...
I think, well, V1, your sensory areas in the adult, in the primate,
probably do function strongly unimodal. But there are these cross-modal connections.
Even in monkey, I'm going to say it's in the peripheral visual field.
Maybe a little bit less in the fovea. So this, again, would substantiate the threshold phenomenon.
But in monkey V2, to some extent V1, you have, in V2 it's quite respectable.
You have auditory input, you have sensory input, in the rodent you have.