Cheers Aseem,
The column activation in the CLA is a simplification, which reflects the fact
that the feed forward axons pass up through the column and so all the cells are
getting similar inputs.
One advantage of maintaining individual feed forward dendrites for each cell is
that the cells will form better connections to inputs which they had predicted,
thus improving the detection of all the sequences the CLA is learning.
The other advantage is that reconstruction less ambiguous. Each cell is
detecting "these inputs during this sequence" so the reconstruction is more
precise.
I've identified the biological basis for this extension. Before the inputs are
considered, the previous pattern of activity feeds into the cells via distal
dendrites, which causes many cells to depolarise (raise their potential towards
the activation threshold). When you add the feed forward inputs, the first cell
to fire has the highest predictive + feed forward potential. This cell is
chosen to activate and may vertically inhibit the others.
This suggests that predictive potential could be added to feed forward in the
SP to improve the identification of the right SDR.
Regards
Fergal Byrne
—
Sent from Mailbox for iPhone
On Tue, Oct 29, 2013 at 11:17 AM, Aseem Hegshetye <[email protected]>
wrote:
> Hi,
> I was thinking of a reconstruction method because look up tables looked to
> artificial to me but I do get it that reconstruction from network itself is
> very important for motor implementation. I dont know if it would be possible
> to convert outputs from look up tables back as an input to motor system with
> much efficiency. That was great Fergal !
> Probably current method of converting raw input data to a 121 bits input
> pattern is not the best way we can provide data to CLA.
> If inputs also can be diffusely represented before putting them into the CLA
> like sensory inputs from medial lemniscus pathway that would be more awesome
> i guess. I did not understand much what Fergal said about adjusting those
> buckets, but I am looking forward to the talk.
> There is definitely a lot of load being put on cla due to lack of
> preprocessing. I have seen some projects where raw images were fed to CLA.
> In Humans we have retina, LGN than the cortex. As CLA is a layer of Cortex,
> its hard to imagine connecting optic nerve to occipital cortex directly. 4
> layers in retina simplify an image to such an extent that it becomes very
> easy for cortex to extract invariant patterns out of it. Also LGN provides
> help in arranging the topography. If raw input gets preprocessed (i dont know
> how) that would be great.
> If a column is representing something and active cells in that column vary
> with respect to past events, then PROBABLY every cell in a column will have
> same connection permanence with input bits. It needs to be verified.
> That review paper provided by Jeff Hawkins was good. Now I am getting a
> surface idea of how motor reinforcement will help in better predictions.
> Going through these discussions, suddenly this brain appears to be so simple
> and comprehensible .
> Something great is on its way !!
> Aseem Hegshetye
> _______________________________________________
> nupic mailing list
> [email protected]
> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
_______________________________________________
nupic mailing list
[email protected]
http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
