On Mon, Feb 18, 2019 at 4:01 PM Ben Goertzel <b...@goertzel.org> wrote:

> ***
> ...
> And likely the way to do this is to set the network oscillating, and
> vary inhibition to get the resolution of "invariants" you want.
> ***
>
> But we are not doing that.  Interesting...


Cool. Maybe there could be a match. I want hardware to try this. I've been
playing with the open SpiNNaker interface with the European Human Brain
Project. But it's batch jobs, and lots of fiddling with Python interfaces
for neurosimulators. I'd love to collaborate on it.

I've always thought the set based representations Open Cog was using could
be fitted to what I was doing.

But I didn't realize you were doing anything like clustering raw sequence
networks on the fly for language. As I recall when I talked to Ruiting in
2013 she was using rules??

I only started looking in detail at networks after 2013. I was trying to
fit it to Jeff Hawkins' sequence networks. I finally figured out the whole
thing, even the "cross-product" in my original formulation, would reduce to
something as simple as diamond shaped "cliques" in the network. But I
didn't know how to isolate them. Then I came across this paper:

A Network of Integrate and Fire Neurons for Community Detection in Complex
Networks
Marcos G. Quiles, Liang Zhao, Fabricio A. Breve, Roseli A. F. Romero
http://www.sbmac.org.br/dincon/trabalhos/PDF/invited/69194.pdf

I immediately googled to see if there was any evidence this mapped to
perception experimentally. And found "binding by synchrony" has been
observed since the '80s, but no-one knew why!

Nice for me, because I'm working from the other direction. I have the
network, and the network predicts binding by synchrony.

If you want to compare notes and see if there are any cross insights which
could inform, we can talk over email if you like.

-Rob

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