Lowest processing structure of HTM

[Paul_Lamb]

@david.pfx

The (HTM) diagram shows what I take to be SDR bit patterns as inputs. How many? The example would appear to show 9, and if each is 2000 bits, that’s 18000 bits of input. How many cells are needed to generate that?

Is that a serious question, or are you making a point that I should provide more detail? If the former… well, a typical configuration sets an upper boundary at 255 synapses per segment, and 255 segments per cell. But that might be a little busy to draw…

@david.pfx

The OR gate is shown as a separate operator. Is that not part of the (HTM) cell?

The whole diagram depicts the concept of an HTM cell.

@david.pfx

Is that algorithm spelled out? Is it fixed, or is there variability between cells?

Again, I assume you are trying to make a point that I should post more detail. I don’t think that is necessary here – folks can refer to Numenta’s papers and BAMI among many other resources here on the forum.

@david.pfx

Given an SDR of 2000 bits, it would take 2000 cells like this one to generate a single SDR, yes?

@david.pfx

So, does the minimum processing unit capable of generating an SDR correspond to a column?

Assuming by “column” you mean minicolumn, then no, a collection of cells in different minicolumns produce an SDR. A single minicolumn (when not bursting) is only capable of generating one bit of an SDR. If you are referring to a cortical column, then sure - it takes a network of cells to construct an SDR. Of course you also changed the subject here – I was referring to the “lowest processing structure” in the HTM algorithm, not the “minimal processing unit capable of generating an SDR”.

Relating this back to the original subject:

@Cairo

In HTM, as I recall, an individual cell and lowest processing structure is called a “column”. A column connects itself to the input field and has weights. In most algorithms ranging from optimization based techniques to Sparsey and other brain inspired algorithms, this is called a neuron

Clearly, by “column” Cairo was talking about HTM minicolumns here – specifically the SP algorithm which has an optimization whereby multiple cells sharing a receptive field are modeled as all sharing a single proximal segment (as if the minicolumn itself were a neuron in the case of feedforward processing). He was not talking about cortical columns. I don’t think anyone would assert that a cortical column in HTM is equivalent to a neuron in other algorithms.

BTW, for Cairo’s benefit, that particular optimization applies only to feedforward processing in the SP algorithm. There is more to HTM than just the SP algorithm, though, so from a broader perspective I do not feel it is accurate to think of single HTM minicolumns in general as being equivalent to single neurons in other algorithms.