We are no different than computers

[emjay]

That is what the article suggests as the holy grail, as it were, of ctm..yes.  It's the route most commonly taken, and it shows the most promise in the way of supporting the theory.  

I'm suggesting something simpler, and probably not much different from what you're doing.  Create a machine capable of "seeing red" -however you describe it, or a machine that gets as close as you can manage*.  An HDL is a hardware description language.  It's used to design and test/sim circuits before they're built.  So it can show you how existent materials and structures can achieve an effect - rather than how an effect can be described mathematically.  I find that sort of explanation more compelling than all of the theories, algorithms, and theoretical math the world could possibly assemble - particularly in that the greater question being asked is how we, as organisms with structure and discernible systems...might achieve the effect we call mind - or whether or not any of our discernible structures and systems -can- achieve (or explain) mind.   Think of it this way, a brilliant programmer can only make a pocket calculator do so much - and nature is not a brilliant programmer.  The machine itself -must- be robust, if this even approximates an accurate explanation of our minds.  Trying an HDL over algorithm puts the focus on the hardware, the system used and built for practical effect...and whatever our minds may be, or may be made of..they are at least providing that practical effect...rather than abstract algorithmic potential.   I think...... I'm suggesting that you try something that you already do, using an unfamiliar tool.  How do you model your NNs?

also, IDK if you need a ctm for dummies, because you probably have an understanding of computational architecture if you model NNs, CTM doesn;t propose anything novel to comp architecture(or anyone familiar with it), it proposes that known architecture -could- account for mind.  That they are somewhat forced to use algorithm has at least a little bit to do with how difficult arranging a useful experiment would be on a human brain.  If you don;t have diagnostics (which we don't) then the only way to learn how a comp actually works is to take it apart, preferably while it's running..to see what happens as you remove or add components..............this is a problem that plague every area of cognitive science, of course.  Theres a big CTM/NN split, btw, NN definitely describes the architecture of the brain, so far as we can tell, much better than "classic" CTM.  We aren't digital or analog computers with circuits built efficiently-to-task..that's for damned sure and no one can argue with the NN guys on that count.  CTM proponents simply insist that the reliable functions of an NN lie in their ability to emulate a classical comp, or classical computational relationships......but, if you're looking for a dummies guide I'll suggest you start even lower, a "dummies guide" to computational architecture.  NAND2Tetris.  
http://www.nand2tetris.org/

*at the very least, doing so will help us to separate what is machine and what is mind, if we decide that the two are not interchangeable in this instance.  We would have some metrics upon which to decide that this effect, or this part of the overall effect is "programming" or "other" after we've exhausted what the comp is capable of via machine language alone.

It has been a long time since I was really into neural networks, probably about five years, and it was never in any professional capacity, but just an interest/obsession. The book I mentioned came with, or linked to, some simulation software called Leabra/PDP++, which was later upgraded to something much better called Emergent. If you bear with me I'll try and find the links to it so you can try it out for yourself. That's what you'd use to model the NNs and failing that they are pretty simple to program, albeit without quite so many bells and whistles as that software.

How far have you managed to get with your own models?

Here is the link to the current version of the software:
http://grey.colorado.edu/emergent

You've spurred me on now to get back into it, if I can just get it to work in my distro of Linux (or in Wine) Not likely unfortunately