[ExI] Why stop at glutamate?

Brent Allsop brent.allsop at gmail.com
Mon Apr 10 22:56:48 UTC 2023

On Mon, Apr 10, 2023 at 11:11 AM Jason Resch via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

> On Sun, Apr 9, 2023 at 5:20 PM Giovanni Santostasi via extropy-chat <
> extropy-chat at lists.extropy.org> wrote:
>> If this doesn't destroy completely anybody illusion that the a brain made
>> of meat (and particular stuff like glutamate) I don't know what else it
>> could. These people will always believe that meat brains are necessary
>> because God made them so. No amound of science would convince them.
> 2) You can train an AI to recognize activation patterns in the brain and
>> associate them with particular stimuli. This has been tried with words and
>> even images both in wake and dreaming state. Here an example that should
>> blow everybody minds:
>> https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf
>> Again, from this study we can see that it doesn't matter how the pattern
>> is generated, but that there is a pattern of activation. These patterns are
>> unique for each individual but statistically they are similar enough that
>> after training over many subjects you can give a statistical estimate that
>> the person is seeing or even thinking about something in particular. Again,
>> IT WORKS people !
> I consider this a knock-down argument against the functional role of
> glutamate (or other molecules) in the sensation of red. These tests use
> only blood flow data, which is a proxy for neural activity. They are not
> measuring ratios of specific neurotransmitters or molecules, or
> introspecting the activity within the cell, the fMRI looks only at which
> neurons are more vs. less active. And yet, from this data we can extract
> images and colors. This proves that neural activity embodies this
> information.

I guess I've failed to communicate something important about why we use
glutamate.  The primary reason we use glutamate is precisely because of
its ease of falsifiability.  I fully expect redness to be falsified
(someone will experience redness with no glutamate present) and something
different from glutamate will then be tried, and eventually something will
be found to be experimentally proven to be redness.  Easy and obvious
falsifiability is what everyone is missing, so THAT is what I'm most
attempting to communicate with the glutamate example.

If you guys think there are knock down arguments for why a redness quality
is simply due to recursive network configurations (I am not yet convinced,
and am still predicting otherwise (see below), and it's much easier to say
glutamate than whatever stuff you guys are talking about, which nobody is
concisely stating, and I have problems understanding), then please, every
time I say 'glutamate', do a substitution for anything you like such as
'Recursive network model A', or any other yet to be falsified theory.  And
let's leave it up to the experimentalists to prove who is right, like good,
humble, theoretical scientists should.

At least that paper
<https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf> you
referenced has pictures (composed of real qualities), not just abstract
text (tells you nothing about qualities), as text only would be completely
meaningless, right?
But why don't you guys ask the publishers of that paper, how they came up
with the qualities displayed on the images depicting what they are
Here is a link to Jack Galant's work
<https://www.youtube.com/watch?v=6FsH7RK1S2E&t=1s>, done over a decade ago,
to which all these modern examples are just derivative works, easily done
with modern AI tools.
When I saw Jack Galant's work
<https://www.youtube.com/watch?v=6FsH7RK1S2E&t=1s> back then, I knew he had
a problem determining what qualities to display on his screens, depicting
what he was detecting.  The fMRI only providing abstract qualityless data
which is meaningless without a quality grounded dictionary.
So I called him and asked him how he knew what qualities to display.  He
immediately admitted they "false-colored" them (Jack Gallant's words).
They used the original color codes in the digital images they were showing
to their subjects, to determine what color to display.  In other words,
they were grounding their colors to physical light, which is nothing like
either the properties of a strawberry, which the light merely represents,
or the very different properties of conscious knowledge they are detecting
and describing with qualityless abstract text.  As Giovanni admits, they
are correcting for any changes in physical properties or qualities they are
detecting so they can falsely map all those diverse sets of properties they
are detecting back to the same false colored light, blinding them to any
possible inverted qualities they may be detecting in all that diversity.

By the way, I added this Japanese paper
<https://www.biorxiv.org/content/10.1101/2022.11.18.517004v2.full.pdf> to
the list of yet another example of quality blind papers, including Jack
Galant's work that only uses one falsely grounded abstract word for all
things representing 'red' here

If anyone finds a peer reviewed paper that is not quality blind. (other
than mine
which is about to be published) will you please let me know about one?  As
I will trust someone that believes and understands that qualities are
necessarily real properties of real hallucinations in our brain.  I predict
they are just the physical properties they are detecting but only
abstractly describing and then false coloring.
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