I’ve just implemented a HTM region in JS. Although its not perfect I thought I’d share an animation that I think helps illustrate the learning process in the region. It is a very simple repeating alternating input pattern.
The top row is the input space. The cells in the columns span vertically. The proximal connections are a generalized sum of segment connections. Red is active, and yellow is predictive.
From the start the columns are bursting. As the columns compete, different sets of columns burst until the dominant columns are set. Then as segments form, the columns activate depolarized cells. Due to Hebbian backpropagation the segment synapses are pruned away to react to specific patterns.
I’ve still got more to do. As you might notice the global inhibition for SP is not working well for one of the input cells. I’ll need to implement local column inhibition. I may update this as I progress.
If anyone else notices any problems based on what they see here I’d appreciate feedback.
(click to enlarge repeating gif)