
Network Neuroscience Theory of Human Intelligence - marchenko
http://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(17)30221-8
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Jeff_Brown
Graphs (networks, webs) are a data structure we have not exploited enough.
Tons of research is going into using graphs for artificial intelligence, and
for understanding human intelligence (as in this article). But what about
using knowledge graphs to augment human intelligence, like a prosthetic?

This is the power of Google search. It uses a knowledge graph that models the
world (with an emphasis on the internet). The graph is big, but the view of it
offered to users is minuscule -- in part to keep the interface as simple as
possible, and in part for economic reasons.

There is open source software that lets people keep their own knowledge
graphs. In Semantic Synchrony [1] you can keep a knowledge graph and merge it
with others' knowledge graph. Joshua Shinavier (who wrote Semantic Synchrony)
and I share a graph with over 400,000 nodes, and most views load in the blink
of an eye.

A sister project, Digraphs with Text[2], offers a more flexible system of
expression: It generalizes the graph, allowing relationships to involve more
than two members, and allowing relationships to be members of other
relationships. It also offers a search facility very much like natural
language: To search, for instance, for reasons neurons need vitamin B, you
would use a query like "(neurons #need vitamin B) #because /it". (The # mark
indicates a joint between members of a relationship.)

[1]
[https://github.com/synchrony/smsn/wiki/](https://github.com/synchrony/smsn/wiki/)
[2] [https://github.com/JeffreyBenjaminBrown/digraphs-with-
text](https://github.com/JeffreyBenjaminBrown/digraphs-with-text)

~~~
ismail
Thanks for the links. Will experiment with these.

I have been building a personal knowledge graph based on concept maps[0] using
cmap tools[1].

[0]
[https://en.m.wikipedia.org/wiki/Concept_map](https://en.m.wikipedia.org/wiki/Concept_map)

[1] [https://cmap.ihmc.us](https://cmap.ihmc.us)

~~~
joshsh
It would be interesting to visualize a SmSn knowledge graph as a Concept Map.
I feel that text buffers are best for viewing and editing a graph when you are
seated at a keyboard, but graphical views have their place, as well.

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neom
This is an awesome lecture that really helps understand how the brain works at
a neurological level:

Jack Gallant - Working toward a complete functional atlas of the human brain -
[https://www.youtube.com/watch?v=Z0Qiq22PRWQ](https://www.youtube.com/watch?v=Z0Qiq22PRWQ)

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forapurpose
A psychology professor once said to me that throughout history our theories of
the mind tend to analogize the dominant research paradigm of the time. At one
time it was chemistry, then physics, and now it's computer science.

I write that because it suggests that our theories of mind depend our own
perspectives to a great degree - perhaps in their conclusions, or in how we
describe them, or in our choice of research. (I wish I could remember the
chemistry or physics analogies ATM.)

~~~
alexpetralia
That's exactly the first thing I thought as well.

This article is relevant: [https://aeon.co/essays/your-brain-does-not-process-
informati...](https://aeon.co/essays/your-brain-does-not-process-information-
and-it-is-not-a-computer)

~~~
eli_gottlieb
>This article is relevant: [https://aeon.co/essays/your-brain-does-not-
process-informati...](https://aeon.co/essays/your-brain-does-not-process-
informati..).

That article is a piece of shit which misunderstands the definition of
computation, the claims of naive versus modern computationalism in philosophy
of mind, _and_ modern neuroscience, all at once. Without any judgement, I'd
like to ask that we all stop sharing it.

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iraphael
This is going a little over my head. Can anyone with more expertise help
summarize / ELI5?

~~~
jugg1es
My undergrad is in Neurobiology, but I don't work in the field, but I can give
you my understanding.

This article is basically an article that reviews the current theories
regarding the neuroscience of intelligence. It's saying that there seems to be
evidence of 'g' (which you could call IQ, but is the variance in cognitive
abilities) that dictates the efficiency of our brain as a network of networks.
It describes the brain as a interconnected global network of local networks
that have discrete responsibilities. The reason these local networks to handle
specific things is because it's more efficient to process in close proximity.
And that the communication between these 'nodes' and the ability to tap into
stored memory and intuition is described by 'g'.

~~~
Gibbon1
That matches what I sussed out growing up with a high functioning older
brother and friends of his, also special needs. Some things they understood or
could do easily as anyone else. Others not so much. interestingly one of my
brothers friends could spell and write perfectly, way above average for his
age.

My assumption was some parts of they brains didn't develop normally which made
it much more difficult for them to learn certain tasks. I've also run into
people that have other deficits, friend didn't drive because of spacial
deficits. But had a PhD in math. Bonus my brother drives.

~~~
beautifulfreak
There's some evidence that autism results from hyperconnected brain regions.

[http://www.medicaldaily.com/kids-autism-have-
hyperconnected-...](http://www.medicaldaily.com/kids-autism-have-
hyperconnected-brain-areas-could-brain-imaging-one-day-diagnose-
disorder-262261)

~~~
Gibbon1
> autism

99% of these autism studies are garbage.

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curuinor
This would actually indicate that spearman's g cannot distributed ~Gaussian.
CLT wouldn't apply, anyhow, but positive feedback effects (a la small world
RG) would apply. Very SFI sort of thing

