Patrick,
A good analogy from vision would be the current CLA encoders are like
looking at pictures composed on binary black or white pixels.  You
definitely lose some subtlety over a gray scale image, but for most uses it
will work well enough.

I don't know what the equivalent would be for audition.  The dynamic range
of any individual neuron is fairly limited, I think it is much less than the
dynamic range you are able to perceive and detect.  So distributed
representations are somehow making up for the limited dynamic range of
neurons.  I suspect that a lot is known about how the cochlea does this but
I am not familiar with that research.
Jeff

-----Original Message-----
From: nupic [mailto:[email protected]] On Behalf Of Patrick
Higgins
Sent: Sunday, September 01, 2013 7:16 AM
To: NuPIC general mailing list.
Subject: Re: [nupic-dev] Inter-layer plumbing

Thank you Jeff,

Add me to the list of captivated members!

That makes a lot of sense. I've wondered myself why the CLA looked boolean
to me and does not use FSK for scaler encoding. It doesn't seem helpful for
the case you describe, a quick match, but would it be helpful for a long
gaze looking for subtle detail or the richness of experience once gets after
the initial recognition / risk / anomaly assessment?

How does scaler encoding work say, in the ear for the loudness of a
frequency or say the eye for the brightness of a blue pixel in the retina?
I understand it to be the rate of firing or as I tend to think if it, a FSK
encoding of magnitude of the singular
(granular) input. Is the current NuPIC way of encoding scalers achieving a
similar result seen in the brain, where the rate of firings are converted to
an SDR by distributing the information thru many pathways?
Adding robustness and converting it to a boolean binary form much like the
familiar sliding set of 1s?

Thanks, I really appreciate it when you go into detail, when you have the
time and interest. You certainly have other people here who feel the same.




Patrick





On Aug 31, 2013, at 2:12 PM, Jeff Hawkins wrote:

> Ian,
> I have nothing against scalar activations.  Here are some more details
about why the CLA doesn't have scalar cell activations today.
>  
> - I have no doubt that scalar activations exist in the cortex and that 
> they can help in some situations.  But.
> - It has been shown that some pretty significant cognitive tasks can occur
in the cortex too quickly to allow for scalar activations to help.  E.g. a
human or monkey can recognize a visual object in just a few hundred
milliseconds.  Neurons in a region such as IT (four levels up in the
hierarchy) indicate that the cortex has recognized the object.  If you count
the minimum number of neuron to neuron transitions (add up all the delay
times) there isn't enough time for a second spike to have an effect.
Remember a fast spiking cell might produce spikes every 20msec.  To
represent a scalar cell output you need at least two spikes.  So a realistic
cortical model cannot require scalar cell activations all the time.
> - The value of scalar activations is reduced in distributed
representations.  This is the biggest reason for me.  The cortex always uses
distributed representations.  In a distributed representation the
contribution of any individual cell is reduced.  Any individual cell could
die and the system keeps working just fine.  The brain represents subtle
differences by changing which cells are active in an SDR.
>  
> I don't think it would be too burdensome to add scalar activations to the
CLA, but at the moment I don't see how it will help us make the CLA more
useful or resolve issues.  If we understood how scalar activations would
solve an outstanding CLA issue I wouldn't hesitate to add them.
>  
> The SP actually uses scalar activations of a sort.  The connections to
each SP bit produce a scalar depolarization of the cell.  Biologically the
cell which depolarizes the fastest first fires and disables others.  That is
pretty accepted scheme.
> Jeff


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