On Fri, Nov 22, 2013 at 6:07 PM, Scott Purdy <[email protected]> wrote:
> To be clear, when I say reconstruction in this email I am talking about > the process of 1) taking the columns for each predicted cell in the TP and > 2) selecting the connected input bits (possibly including the connectedness > as a weight) to those corresponding SP coincidences/columns and 3) using > the encoders to select the closest value to the selected input bits as the > predicted value. > 2->3 is where the juicy and interesting bits are. It would be good to pull out a version that still had this implemented from git history and review. There was also an exploration done by an intern that we could probably review and release. > On Fri, Nov 22, 2013 at 3:54 PM, Ian Danforth <[email protected]> > wrote: > > > Scott, > > > > Reconstruction was implemented because it was much closer to biology > than any classifier. > > I think your rationale here is that there is information propagation > "downwards" in the brain and that this is what we are doing with > reconstruction. That may be true, but the way that the information is used > in reconstruction is different then the way it is used in feedback or other > processes that actually happen in the brain. So it is true that information > flows downward, but not true that the brain performs reconstruction with > that information. > I may be misunderstanding you, but that's demonstrably false. The Kanizsa triangle is a great example (http://en.wikipedia.org/wiki/Illusory_contours) where the brain is using a high level gestalt to reconstruct missing information. You see activations in V1 from these figures *as if* the input were a complete triangle. The feed back inhibitory pathway reduces the inhibitory signals in a select group of neurons that it expects to be firing and then the naturally noisy input is sufficient to cause actual feed forward input in those areas, reinforcing the perception that there are lines/edges where there are none. There are also cases where excitatory feedback drives lower level activations which is exactly what reconstruction does. It reconstructs missing parts of the input from whatever was fed in. Ian
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