
What Neurons Look Like as Drawn by Students, Grad Students, and Professors - rosser
http://www.theatlantic.com/technology/archive/2013/05/what-neurons-look-like-as-drawn-by-students-grad-students-and-professors/276446/
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albertyw
I think the creativity argument is bull. I would bet that the reason why
there's a difference between the groups of diagrams is the depth of knowledge
in neurons. Undergrads, who I believe we can safely assume have less in depth
knowledge of neurons, memorize the physical shape of neurons because their
cursory knowledge of neurons. On the other hand, professors have a much more
depth (and specialized) knowledge of neurons and therefore may not even know
what the neuron as a whole looks like (you could probably get a few PhDs just
by studying the signalling mechanism across the neuron membrane). I'm guessing
this because for example Figure 22 looks suspiciously like a circuit diagram.

For example, one wouldn't expect an EE/Physicist (the professors) who works on
designing MOSFETs (neuron transmitters) to be able to draw a wiring diagram
(neurons) that the MOSFETs would be used in, even though that EE/Physicist
might be called a chip designer.

Of course, a simpler answer is that professors are busier than undergrads so
they just put less time and effort into drawing these diagrams. So Occam's
Razor?

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nhebb
I didn't see it as creativity either. Professors who have probably had to draw
a lot of neurons over the years have naturally developed a symbolic
representation of the object, which is common in many fields.

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te_platt
I was immediately struck by the similarity to how Picasso drew a cow (see:
[http://3.bp.blogspot.com/_yAdxTp2HDQM/S_P7lZz46-I/AAAAAAAAB1...](http://3.bp.blogspot.com/_yAdxTp2HDQM/S_P7lZz46-I/AAAAAAAAB1o/65qlC1Oh6so/s1600/Picasso+Cow.jpg)
). It seems the professors have come to the point where they see the essence
of "neuronness".

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masklinn
Also reminds me of this Pratchett quote (about "a horse" carved in The Chalk):

> Tain't what a horse looks like. It's what a horse be.

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GabrielF00
A professor of mine was fond of pointing out that the textbook images of
neurons were all of rat neurons. Many human cortical neurons have a structure
called an apical dendrite which isn't depicted in undergraduate neuroscience
textbooks. He was really obsessed with those apical dendrites.

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rdl
It would be interesting to ask people to draw a resistor. Ignorant savages
would draw a sketch of the physical shape minus all useful details (maybe with
random color bands in no particular pattern except maybe because they look
pleasing; maybe a new palette too); artists would draw something fairly
realistic, and engineers would draw a schematic symbol.

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jstanley
I would also argue that the top row is drawn from a biology viewpoint, while
the bottom row is drawn from a neuroscience viewpoint. Perhaps this could also
explain some of the differences? For example, if you were interested only in
neuroscience, why would you bother to draw the fatty layer around the neuron?
It isn't useful to you.

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a-priori
It also depends what kind of neuron you're talking about. Plenty of neurons
have unmyelinated axons. In particular, most of the neurons in the grey matter
on the surface of the neocortex don't have myelin sheaths. It's the fat in the
myelin that gives white matter its lighter colour.

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claudius
I begin to understand what a standard physics text must look like to an
outsider.

Utter gibberish at first view, then there are some words you can make out if
you look closer and after lots of googling you can remotely comprehend the
approximate meaning.

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cdcox
<http://onlinelibrary.wiley.com/doi/10.1002/sce.21055/full> Link to the
research article. The link in the article is dead.

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andreyf
It's not dead, it's behind a paywall, just as on the site you linked. Can
anyone post the actual pdf?

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setenta
<http://libgen.org/scimag5/10.1002/sce.21055.pdf>

~~~
andreyf
Interesting. Who runs libgen.org? How are they in compliance with copyright
laws?

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Aqueous
Author doesn't mention obvious observation, that professional scientists'
drawings looked more like circuit diagrams for the most part whereas the other
two groups' looked like portraits of biological neurons of varying accuracy.

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keithpeter
I noticed that as well. It struck me that the third group may have been
focussing on the _function_ more than the _physiology_.

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slacka
As someone with a strong background in Biology who took several AI classes at
an Ivy League school, I found many of my CS professors models oversimplified
neurons to absurd levels.

Teaching CS students to use perceptron that can't even change its own behavior
is like teaching MechEs to built rockets out of Legos. Sure you can do some
cool things with them, but the sooner you move on, the sooner you can make
some real progress.

After 2 AI winters, I'm happy to see that many schools like Berkeley are
finally starting to combine their neuroscience and AI labs.

~~~
jerf
jergosh is right too, but I think the real reason is that academic computer
scientists want models they can mathematically reason about. Real neurons are
fine and dandy, and can obviously do fantastic things like drive muscles in
certain ways to post semantically meaningful content to Hacker News, but we
still don't have a general model that can explain how they work in concert at
scale. Perceptron's popularity arises not from their accuracy... I'm pretty
sure everybody knew they were inaccurate models, though the hope was (falsely)
that the inaccuracies wouldn't matter. Their popularity derives from the
discovery of the backpropagation algorithm. In fact, if one were to take a
mathematical view of the situation, arguably backpropagation is what was
really discovered, and perceptrons are incidentally the moving parts in the
backpropagation algorithm.

It is not generally useful in AI to have some horrifically complicated
algorithm that is based on something vaguely realistic, but that nobody know
how to make do anything, or update based on new input, or figure out what's
wrong when it doesn't work.

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slacka
I have no issue with using perceptrons as a learning tool. But they have clung
to this model for far too long. The main problem I see is the biogical
learning mechanism comes from some feedback mechanism that causes the neurons
to grown new connections.

Perceptrons have no way to mimic this and instead resort to sending an error
from the output units back toward the input units duringing the learning
phase. But when we go to use them, the information only flows forward. So you
can never produce a dynamic learning system with these Legos. No matter how
much super-glue you use, this rockets never going to make it into space. Yet
many of these new deep learning neural nets continue to use back propagation
for their learning phase.

I never said we needed EXACT models. And, I know perceptrons are simple to
model mathematically and have 40 years of research and tools backing them. But
after 40 years, isn't it time we try just a little harder to make something
that is a little closer to how biological neurons really work?

~~~
jerf
"But after 40 years, isn't it time we try just a little harder to make
something that is a little closer to how biological neurons really work?"

We _have_ been trying. It has proved to be very difficult to get them to do
anything useful, though, which was my point. Dedicated AI researchers are
actually intensely aware of the differences between real neurons and their
neurons, but getting fake neurons to do anything useful has not been as easy
as just "simulate what the neurons do".

There was an interesting breakthrough 6 months to a year ago, some new
algorithm that is apparently able to update a more interesting neural net, but
I don't know much more than that at the moment.

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slacka
I agree. From what I've read many of the younger AI researchers are
interested. As I mentioned earlier, some school have recently created special
labs and programs for them to work together.

My point was just 10 years ago, none of my CS professors showed much interest
in neurobiology. Fortunately I think this attitude is changing.

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ewbuoi
Honestly, I'm not surprised at all. Students need to be thorough to show they
understand the material, so their drawings are detailed. Professionals just
need to put an idea on paper quickly and easily, so they only draw the details
that are relevant.

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keithpeter
Working out what are the 'details that are relevant' is perhaps a measure of
knowledge in the field?

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super-serial
What a worthless study and article.

It's like if you asked a group of people from the 1930s to "draw an alien",
and you compared that to modern people asked to draw an alien.

People from the present would draw the "gray" aliens you see on TV. Are they
less creative than the people from the 1930s? No - they're just relating what
they think is the accepted or most likely "correct" drawing of an alien.

Then theatlantic.com comes along and writes an article asking "do modern
people really understand SCIENCE? Why are their alien drawings all the SAME?
Are they missing a significant IMAGINATIVE STEP?"

No they are not - you idiots. Next time ask them to draw an "original
interpretation" of some concept if you want them to draw something creative...
otherwise people will just draw what they think is the commonly accepted
answer among their peers.

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JoeAltmaier
Yet the undergrads did NOT draw a modern concept of a neuron. They drew the
1890s conception. So some temporal inversion thingy going on there?

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return0
Isn't this coming to the wrong conclusion? Students probably just didn't know
the extent of the dendrites and their structure, the fact that the axon is
usually longer and thinner etc so they drew what they see in Books/magazines.
What does that have to do with creativity? If anything, the scientists'
drawings are the unimaginative ones, because they are realistic

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sp332
The higher variety of shapes is what showed increased creativity. It's not
anything about the shape in particular.

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return0
Again, how is this attributed to "creativity" and not to "scientists know that
the structures of dendrites and axons neurons vary widely but still they are
quite narrow so that's how they draw them"? Because that's how it seems to me.

