I know that the goal is efficiency in training and storage but how is the hierarchy in the neocortex done exactly? Is it a result of a mathematical equation? Or is it the throw it in the wall and see if it sticks process of evolution?
My mathematical theory is very simple and it's based on binomial coefficients. Let's say that the human body consist of a K number of sensors. The number of regions X in the hierarchy should be equal to X = !K / (2! * (K - 2)!) + K (for each sensor). That's the number of all possible duplets of sensors with no repetitions. This equation creates a pool of the highest variety but least density that we can use for representations. And it also explains the tree like shape of the hierarchy and why it converges and diverges and you up and down. For example, if the human body consisted of just three sensors: S1 = Optic, S2 = Acoustic, S3 = Touch The number of regions would be X = 3 * 2 / (2 * 1) + 3 = 3 + 3 = 6 1. R1 = S1 (Optic) 2. R2 = S2 (Acoustic) 3. R3 = S3 (Touch) 4. R4 = R1, R2 (Optic + Acoustic) 5. R5 = R2, R3 (Acoustic + Touch) 6. R6 = R4, R5 (Optic + Acoustic + Touch) Let's consider the part of the neocortex that handles language. The number of characters in the alphabet is much smaller than the number of words and the number of words is tiny compared to the number of phrases. This simple observation makes me assume that the hierarchy in the brain is like this: 1. Letters (Highest level concepts) 2. Words 3. Phrases Using a single region we would have to assign columns to letters and sequences of cells to words. For example, the words "god" and "dog" would share the same spatial pattern but different temporal patterns. Since, the higher regions get only spatial patterns from below how does the distinction of those two gets communicated above? What happens if the word has multiple identical letters? Do the cells in a column connect to other cells in the same column? For example, the word "good" has two "o"s. To summarise, if one region wasn't enough and I wanted to reconstruct the human neocortex based on a K number of sensors, how would I know how many regions I would need, and in what way should I connect them to make it all work? Thats a problem you will face in the future. One day, one region won't be enough. I 've implemented a huge part of the CLA in Xcode and got it running on an iPhone, I've seen a dozen videos of Jeff Hawkins' presentations and I 've also bought the book On Intelligence but I haven't found any answers to these questions. I'm counting on you guys. :)
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