Toni Westbrook dot Com

The Joy of Computer Science and Engineering

Just a quick note – I need to think up a name for the visualization routine – the problem is it doesn’t strictly show the same activity of a functional MRI scan, but it also doesn’t show the same activity as a PET or SPECT scan. Something to think about, not really a big deal in the grand scheme of things.

Also, while I’m thinking about it, I would like to include functionality of post-synaptic generated neurotrophins leading to axon growth and branching within the presynaptic neurons. This will be pretty easy, in the code used to increase synaptic weight, I can also setup new synaptic connections to geographically neighboring neurons. I’m not sure at what rate to do this though, from the literature it suggests it doesn’t happen as often or as quickly as synaptic reinforcement.

Just a quick update today, no pictures.

I took out the old, incorrect synapse alteration routines today and replaced them with the new routines which match the functionality of Hebbian Learning’s “Fire Together Wire Together”. I actually used a different, more efficient algorithm than what I had originally planned, so the drop in speed is nothing at all. It did increase the size (in bytes) of each neuron, but speed is more a problem than space at this point.

Now that this is finished, all the underlying functionality is (to my knowledge) correct. From this point onward it’s simply a matter of testing different methods of construction with different values for threshold rates, plasticity level, degredation amount, physical placement, etc.

Also, I would like to take a day and just sit down with the code and see if I can get it any more efficient. Right now when I start generating neural matrices in the tens of thousands level, along with a high synaptic density, the thing just grinds to too much of a halt, though this may be OpenGL processing all the graphical representation of the net and not the net taking that time up itself. I will test it out without the graphics routine running and see how it does.

But regardless more efficient code is always a good thing. I know some places where I used a little more memory than I needed and added a few extra steps, I can shave it down a bit.

Everything’s going great though! Once I activated the Hebbian routines activity no longer followed a systematic pattern, or at least I couldn’t see one – which I believe is a very very good thing.