Stephen Grossberg: A Unified Theory of Consciousness? Adaptive Resonance Theory & The Hard Problem

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The main focus.
I'll put links to the your 2017

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paper on the hard problem of
consciousness, but for the most.

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Part.
That would be nice.

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Yeah.
Yeah.

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So I'm going to.
Put a direct link to that in the

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paper because I I mean in the
video because I think people

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should read this.
It's very long, very, very in

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depth, and I liked it.
I mean that's when someone has a

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lot to say about something so
complicated, I think you can't

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really summarize it.
It's it's it's something that

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does require that level of
detail.

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So to all those who are going to
read this paper, just bear that

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in mind this you gotta, it
probably takes repeat readings

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for most people to really
understand and grasp most of the

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concepts.
But you do a great job at

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putting some imagery.
And I mean it's it's a wonderful

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paper overall.
Well, thank you.

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Two things come to mind.
One is that it's a long paper,

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but it compresses a huge amount
of knowledge.

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So if you can get through that,
you've saved an enormous amount

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of time.
And that's one thing that my

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students always came to realize
it.

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It was a way that they could get
an entree into so much

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psychological, neurobiological
knowledge and start organizing

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it for themselves.
Whereas if all you did was you

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gave them 200 articles which may
be explained or explanation off

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it in this one article of mine
or they they wouldn't know where

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to begin and they wouldn't they
would have to build up a model

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in their mind and that's what
I'm giving them.

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Not to say it's the final model,
but it's been validated each of

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the models in multiple ways and
and it gives them a way to start

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organizing all this information
cause ultimately the model as a

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thing in itself isn't what we're
interested in.

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We're interested in
understanding what the hell is

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going on, and if models help us
to create stories about what's

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going on and those stories make
sense and help us to clarify

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what we're learning, well,
that's what they're for.

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So I was going to say something
else, but slipped my mind.

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I should write notes now anyway.
The, the.

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The.
Huge chunk of this conversation

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will be about the hard problem
of consciousness in your paper.

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On that topic and I think the
best place for us to start.

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I've I've got a list of
questions from from the general

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fans, audience, listeners and
viewers, and I'll just go

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through those later on in the
conversation.

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But at the beginning, I think,
let's start with what is the

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hard problem to you?
And if you could tell me your

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philosophical history of the
hard problem and your perception

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of it, what would that story be?
Well, I don't have my 2017 paper

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in front of me, but it was David
Chalmers who described what he

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considered the hard problem.
And my comment about it was the

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following.
How to put it?

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Let's go back to the orbits of
the planets.

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If we can predict the orbits of
the planets with great

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precision, we don't have to
necessarily visit them.

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We don't have to touchy feely
them.

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It's a description that's
predictably effective.

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And so my comment at the
beginning of my magnum opus and

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I think I made a very similar
comment in my 2017 paper is

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let's say you have a neural
network model which describes

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identified brain cells in
identified regions of the brain

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interacting in a way that's
validated by neurobiological

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data, anatomical and
physiological, in some cases

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biochemical.
And let's say the emerging

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properties map quantitatively
onto lots of behaviors that

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interest you, including
parametric properties of

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conscious experiences like
seeing, hearing, feeling,

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knowing things.
That's all equations can do for

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you.
And if you expect an equation to

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see color or to hear musical
tone, that will never happen.

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And it doesn't happen in mind
brain science, but it doesn't

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happen in physics or chemistry.
And people have come to

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understand that if you get
predictive insight based on

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harmonious laws that make things
seem clear, that's enough.

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You know it's to think you would
get more, which is implicit in

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the definition of the hard
problem, is asking for something

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that equations can never give
you in any science and only look

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to sciences that are better
developed to realize you don't

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really need it to feel quite
satisfied that you've understood

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something.
So that's my response.

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It's it's sufficient.
Of course, it is a mystery, you

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know.
And as I point out, let's say

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right down to the photons.
And you know, for example, GAIL

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Carpenter and I, among other
colleagues did very detailed

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models of the transduction of
color signals, invertebrate

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cones.
And we were able to

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quantitatively simulate very
hard data using designs that you

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could see had been using many
other parts of our brains.

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But the model doesn't see color,
It just describes how we see

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color.
And there is that explanatory

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gap.
And I for one don't see how

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equations can ever bridge the
gap.

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But we don't need equations to
do it because we have our

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conscious minds, so.
One of your.

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I don't know.
What one of your quotes in the

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in the paper was, as in quantum
theory, there are measurements

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limitations in understanding our
brains.

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We can no more personally ride
an electron than we can enter a

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neuron that is participating in
a conscious experience.

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That's that's pretty much along
the lines of what you're trying

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to say.
Yeah, it is what I'm trying to

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say.
And of course there are superb

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neurophysiologists now who do
antineurons.

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In fact, a colleague or Omilla
at MIT might put an an array of

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100 or more electrodes in three
different parts of the brain and

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do experiments with the weight
behaving monkeys to try to

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correlate what the monkeys are
seeing and doing with the

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recordings.
And it's very insightful.

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And if you have a strong enough
theory to explain what these

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patterns mean for emerging
properties, to link brain to

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mind, to link brain to the
perception of the action.

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But that's extremely useful.
But in itself, without a theory,

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it's not satisfying enough.
You need more, you know.

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Where's the spice?
Yeah, so.

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What are your thoughts on on
Thomas Nagel's What is it like

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that that that specific
component of consciousness, the

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what is it like and the fact
that we'll never really be able

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to say what it's like to be a
bat low?

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Well, to the extent to which
what it's like is that having

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having an equation that that is
the quality, you can't do that.

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That's what I just said.
But there are cases already, in

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many cases, where we've
developed models, principled

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models that you can understand
are using principles that are

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parsimoniously used in many
processes that can tell you a

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lot about different percepts and
where the end, like what's the

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difference between vision and
audition say?

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Well, even though the circuits,
even though the equations, I

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mean the local neuronal
processes and the modules.

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As I talked about last time, a
certain number of conserved

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micro circuits that are used for
many things may be shared in

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vision and addition.
If you look at how they're

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specialized in order to be
sensitive to environmental

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invariants of those signals in
the world, photons and phonons,

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and how they're organized by
sound sources, then you can

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begin to understand, wow, this
is really fascinating because

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here is a universal
computational substrate that can

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be specialized to resonate with
the invariants of different

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environmental experiences.
And that is the power of how

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evolution has crafted our brains
in order to be able to do that.

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And we know that, you know,
there are a variety of species

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that are resonating on things
that we can't do, like consider

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honey bees, or consider the
vision of birds.

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You know, certain birds from
hundreds of feet in the air can

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detect the movement of a fish
under the water and dive

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straight down to it.
But we can't do that.

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But that doesn't mean that
they're neurons.

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The fundamental components are,
you know, something totally

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unfamiliar.
That's not true.

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And that's why for quite a while
people studied invertebrate

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circuitries like crayfish,
swimmer reps, etcetera,

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etcetera.
And one of my colleagues many

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years ago, Al Selbersten out in
California, I I I hope he's

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still like the wonderful
scientist.

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You know, he he had I guess the
study, the stomatogastric

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ganglion of I think it was the
lobster.

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And he had characterized on
multiple levels of Physiology

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and anatomy, all the parts.
And when it was all and said and

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done, he still didn't know how
it worked.

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And he said that and that was
because it's an emergent

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property of all those parts
interacting in a highly

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nonlinear feedback manner.
And I'll acknowledge that he did

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what you could do with brilliant
experiments.

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And then you need a level of
description, notably A

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sufficiently powerful model,
that can show how those

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components interact to generate
the emerging properties that are

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the adaptive behavior of the
stomatic gastric ganglion, or

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whatever else we're considering.
So it's that speculative leap we

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talked about a little last time.
You know how you discover that

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it's not, We don't have an
algorithm for it.

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In fact, my my colleague Rudy
Karlman, I don't know if she

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studied the Kalman filter which
is used in many problems in

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prediction and engineering and
he was trying to characterize in

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a in a very rigorous way linear
controllers.

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But at least at the time he said
when he got the multi linear

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controllers he couldn't even do
that.

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You know the methods he had just
weren't powerful enough.

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So the miracle is that somehow
the methods that I've been lucky

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enough to discover have not hit
that brick wall yet and and lots

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of other people use use them in
one form or another, including

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in technology.
And as I I may have mentioned

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last time, one of the reasons
why GAIL Carpenter and I and a

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number of our PhD students and
post docs were eager to

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specialize our model discoveries
into applications in engineering

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technology and AI, was to to
show they work in the real

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world.
And you know, one way you can

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show they work in a way that
people who don't really care at

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all about mind and brain is by
doing a technological

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application that they do care
about and frankly can make a lot

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of money for them.
Yeah.

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So Steve, the approach that the
science of the brain and the

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approach of philosophy of mind
are very different as a

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scientist fundamentally involved
in this interface of mind and

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body, what are your thoughts on
philosophy as a whole regarding

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this, their approach to this
topic or or philosophy's

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engagement in this field?
Because the definitions play a

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big role, and they often there's
often arguments.

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I mean, within philosophy, even
merely starting with the brain

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as as the source of
consciousness seems to be

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problematic for many
philosophers.

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You have philosophers who claim
that consciousness is

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fundamental to reality.
You have others that that claim

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that consciousness is a
fundamental feature of reality.

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So pan psychism, which
integrated information theory,

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is pretty much a form of that.
Do you are you able as a

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scientist to even have a
conversation with those people?

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But such different views from
your own.

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Well, I always ask, what can you
explain with your concepts?

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And by explaining I mean facts,
data.

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If you can't explain anything,
then you're not even in the

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ballpark yet.
Now one of the things that

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fascinated me personally is I
don't know if you looked at a

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later chapter in my book.
It's about really simple

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evolutionary precursors of
brains.

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I talk about a universal
developmental code and show how

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mathematical laws and primitive
circuits that are controlling

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the development of non neural
single cell or multicellular

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organisms have many of the
features that the laws have that

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I might use to explain amalgam
in human data.

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You know, I I talked about
hydrous heads and slime, old

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aggregation and you know, stuff
like that.

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And to me, it wasn't an accident
that I published an article in

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1978 called Communication,
Memory and Development where I

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described these things if
theoretically.

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And in the same year I
published, you know, early

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magnum opus called the Theory of
Human Memory colon.

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And then more stuff about what
was in it.

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In fact, together they were book
length and I originally planned

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to publish it as a book.
But I was young and foolish.

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I didn't know what I was doing.
And so Robert Rose and Bob Rosen

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00:18:42,320 --> 00:18:49,160
was very sweet and you know,
significant mathematical

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00:18:49,160 --> 00:18:55,160
biologist also was an editor of
a book series called Progress in

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00:18:55,160 --> 00:19:01,120
Theoretical Biology and and he
was eager to publish the two

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00:19:01,120 --> 00:19:04,840
articles as articles.
But by putting it in something

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00:19:04,840 --> 00:19:09,080
called Progress in theoretical
biology, it buries it from the

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00:19:09,080 --> 00:19:14,200
viewpoint of marketing.
So that was one of many naive

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00:19:14,480 --> 00:19:17,320
things I've done in my life that
I could kick myself for.

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00:19:17,320 --> 00:19:22,680
But I'm just a naive guy,
basically, and and I welcome it

238
00:19:22,680 --> 00:19:27,480
because having a naive approach
to stuff really helps you to be

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00:19:27,480 --> 00:19:30,720
creative.
You don't come in with, you

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00:19:30,720 --> 00:19:32,680
know, too many preconceived
ideas.

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00:19:32,680 --> 00:19:36,880
So there's a cost for it.
And so far the cost has been

242
00:19:36,880 --> 00:19:40,040
worth it.
But I should have published a

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00:19:40,040 --> 00:19:45,720
major book in 78 on Mind and
Brain.

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00:19:46,560 --> 00:19:53,600
As it is, I wised up a little
and by 82 I published a book

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00:19:53,600 --> 00:19:55,800
that brought together my
articles.

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00:19:55,800 --> 00:20:00,680
But it you know, and that I
think a lot of people were

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00:20:00,680 --> 00:20:04,480
influenced by.
It was called Studies of Mind

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00:20:04,480 --> 00:20:07,160
and Brain.
I think it's still in print in

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00:20:07,160 --> 00:20:12,920
some form.
Anyway, so so.

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00:20:13,080 --> 00:20:15,640
It's you have people like
Edelman and Tononi.

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00:20:16,120 --> 00:20:20,600
I order Information Theories and
Integrated Information Theory at

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00:20:20,600 --> 00:20:22,520
some point.
This is quite a lengthy quote,

253
00:20:22,520 --> 00:20:24,480
so bear with me.
It's it's your words.

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00:20:24,960 --> 00:20:28,040
I mean, they used the word
information as a critical

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00:20:28,040 --> 00:20:31,560
component of the hypothesis.
But what is information?

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00:20:31,920 --> 00:20:34,520
The scientific concept of
information in the mathematical

257
00:20:34,520 --> 00:20:38,400
sense of information theory by
Shannon requires that a set of

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00:20:38,400 --> 00:20:42,800
states exist whose information
can be computed, and that fixed

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00:20:42,800 --> 00:20:45,320
probabilities exist for
transitions between these

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00:20:45,320 --> 00:20:48,400
states.
In contrast, but brain is a self

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00:20:48,400 --> 00:20:51,760
organizing system that
continually creates new states

262
00:20:51,760 --> 00:20:54,320
through development and
learning, and whose probability

263
00:20:54,320 --> 00:20:56,760
structure is continually
changing along with them.

264
00:20:57,280 --> 00:21:01,440
Without a theory that explains
how these states arise and how

265
00:21:01,440 --> 00:21:04,400
their transition probabilities
may change through time in

266
00:21:04,400 --> 00:21:06,560
response to changing
environmental statistics and

267
00:21:06,560 --> 00:21:09,760
internal representations
thereof, the classical concept

268
00:21:09,760 --> 00:21:13,600
of information is useless.
You want to unpack that a bit

269
00:21:13,600 --> 00:21:17,400
for us.
Well, I think you just did.

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00:21:17,440 --> 00:21:26,160
I mean, I'm not sure what else.
I mean, yeah, well, Jerry

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00:21:26,160 --> 00:21:33,600
Edelman was a very brilliant man
and a Nobel laureate, and there

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00:21:33,600 --> 00:21:36,720
are a lot of Jerry Edelman
stories I won't go into.

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00:21:36,760 --> 00:21:43,600
But he was a faculty member at
the Rockefeller University when

274
00:21:43,600 --> 00:21:47,520
I was a graduate student there.
In one of the more favorable

275
00:21:47,520 --> 00:21:55,720
descriptions, the jury was the
black knight, and I won't go

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00:21:55,720 --> 00:22:00,040
beyond that in this public
forum.

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00:22:00,360 --> 00:22:05,360
But he he made very many useful
contributions.

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00:22:05,360 --> 00:22:11,200
And then as many Nobel laureates
decided, hey, you know, the next

279
00:22:11,200 --> 00:22:15,760
great frontier is brain, I'm
going to get my next Nobel

280
00:22:15,760 --> 00:22:19,360
laureate in brain.
But the problem was Jerry didn't

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00:22:19,360 --> 00:22:24,920
know any data, you know, and I
was lucky to grow up, Dave, in

282
00:22:24,920 --> 00:22:29,800
data, which is where I
comfortably live.

283
00:22:30,560 --> 00:22:35,440
And you can't go very far if you
don't know the data.

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00:22:36,960 --> 00:22:41,640
And to Noni initially, although
I haven't kept track of his

285
00:22:41,640 --> 00:22:50,040
work, he's a clever person.
Try to give a scalar to discuss.

286
00:22:50,640 --> 00:22:54,160
You know, I don't remember the
details in such a long time

287
00:22:54,760 --> 00:23:03,360
whether the system was complex
enough to, you know, I think to

288
00:23:03,360 --> 00:23:08,400
consciousness or something.
My remark was, hey you, you

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00:23:08,400 --> 00:23:13,080
can't do anything with a scalar,
you know, I mean, we have a

290
00:23:13,080 --> 00:23:19,840
brain after all for a reason,
but to the extent to which

291
00:23:19,840 --> 00:23:28,640
everyone's contribution is
useful, hey, do it.

292
00:23:31,000 --> 00:23:36,520
I only view problems if work is
useful and it's not just I but

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00:23:36,520 --> 00:23:40,920
which we know today.
There's a huge amount of ibend

294
00:23:43,400 --> 00:23:47,600
if it's done in a solipsistic
environment.

295
00:23:49,840 --> 00:23:55,000
I always taught my students, and
it was a policy about apartment

296
00:23:55,480 --> 00:23:58,760
whenever we were studying models
to do it in a comparative

297
00:23:58,760 --> 00:24:02,080
setting.
What are all the models out

298
00:24:02,080 --> 00:24:03,640
there?
What are their strengths and

299
00:24:03,640 --> 00:24:08,080
weaknesses?
If we have models we favor, do

300
00:24:08,080 --> 00:24:10,680
they have weaknesses that are
the models have overcome?

301
00:24:10,680 --> 00:24:15,280
And if they have, how can our
models be refined and further

302
00:24:15,280 --> 00:24:19,760
developed to also do that?
So that's a certain attitude,

303
00:24:20,480 --> 00:24:25,080
and if everyone's making their
proposal in the context of a

304
00:24:25,080 --> 00:24:29,480
comparative analysis, then hey,
go for it.

305
00:24:29,480 --> 00:24:35,400
It's good, but if it's
solipsistic and if it's aimed at

306
00:24:35,400 --> 00:24:41,480
selling any idea in a I'll push
it to the limit here.

307
00:24:41,480 --> 00:24:48,080
A cult like setting.
We know that's bad news, and to

308
00:24:48,080 --> 00:24:57,480
me the worst part of it is
students go into courses with

309
00:24:57,480 --> 00:25:02,280
famous professors or many
professor who they like as a

310
00:25:02,280 --> 00:25:07,600
teacher, and they're going to
try to absorb everything the

311
00:25:07,640 --> 00:25:14,000
teacher says at the time of
life, when you can learn better

312
00:25:14,000 --> 00:25:17,440
than at any other time in your
life, if only to get a good

313
00:25:17,440 --> 00:25:22,840
grade and it's really not
proper.

314
00:25:23,360 --> 00:25:28,920
I would almost go so far to say
it's not ethical to give kids a

315
00:25:28,960 --> 00:25:34,600
misleading view of the world
that they're about to have to

316
00:25:34,600 --> 00:25:38,800
live in.
If you know better, if you don't

317
00:25:38,800 --> 00:25:40,960
know something, stop there.
Hey, you do the best you can.

318
00:25:40,960 --> 00:25:44,720
That's all any of us can do.
But if you know something's out

319
00:25:44,720 --> 00:25:48,920
there and you try to shield your
kids from it because hey, your

320
00:25:48,920 --> 00:25:53,440
work isn't as good and you want
your kids to do what you do so

321
00:25:53,440 --> 00:25:58,400
you can publish more papers or
whatever, that's unethical.

322
00:25:59,040 --> 00:26:02,320
In my mind, that's the strongest
I put it.

323
00:26:02,320 --> 00:26:06,360
Usually I'd say it's just in a
weak character, OK?

324
00:26:08,040 --> 00:26:11,360
Opportunism.
Marketing.

325
00:26:11,400 --> 00:26:13,640
You know those words are bad
enough.

326
00:26:15,480 --> 00:26:18,520
The last, so the last time we
went very in depth on in

327
00:26:18,520 --> 00:26:21,320
adaptive residence theory in in,
in most of your work.

328
00:26:21,320 --> 00:26:25,040
Obviously it's just scratching
the surface of what is very

329
00:26:25,040 --> 00:26:29,200
complex, and as a scientist I
mean huge respect for your work

330
00:26:29,200 --> 00:26:32,040
and everybody seems to have a
consensus regarding that.

331
00:26:32,040 --> 00:26:34,440
So I've tried to frame this
conversation slightly more

332
00:26:34,440 --> 00:26:37,160
philosophically so that people
can get a deeper understanding

333
00:26:37,160 --> 00:26:40,560
of the science behind the work
and what its implications on the

334
00:26:40,560 --> 00:26:44,920
heart problem as a whole are.
And with that in mind, the

335
00:26:45,120 --> 00:26:47,560
understanding of other theories
of consciousness are important

336
00:26:47,560 --> 00:26:50,720
because with yours you can
highlight flaws within theirs

337
00:26:51,080 --> 00:26:53,720
just the same way you did with
the information aspect of this

338
00:26:53,720 --> 00:26:56,320
one.
Along those lines of Nobel

339
00:26:56,320 --> 00:26:59,120
laureates doing that, then
you've got others like Francis,

340
00:26:59,120 --> 00:27:03,920
Crick, Penrose, very different
types of ears of consciousness.

341
00:27:03,920 --> 00:27:06,120
You've got someone who was
approaching it from a

342
00:27:06,120 --> 00:27:09,000
panpsychist perspective who's
claiming that consciousness is

343
00:27:09,000 --> 00:27:12,080
that fundamental feature.
And then you've got someone like

344
00:27:12,080 --> 00:27:17,120
Penrose who claims that
consciousness is almost quantum

345
00:27:17,120 --> 00:27:22,600
in a in a sense and beyond what
classical physics can interpret,

346
00:27:22,600 --> 00:27:26,720
and therefore the data in this
case would not be as easily

347
00:27:26,720 --> 00:27:29,080
applicable.
What do you think about that?

348
00:27:30,600 --> 00:27:34,320
So that is a very long question.
Well, well, I don't want to

349
00:27:34,600 --> 00:27:40,760
sound like a broken record, but
it's always, you know, what

350
00:27:40,920 --> 00:27:49,520
theories have the broadest and
most principled explanatory

351
00:27:49,520 --> 00:27:56,080
range, and how many of their
predictions have been supported

352
00:27:56,080 --> 00:28:04,080
by subsequent data.
And in terms of quantum brain,

353
00:28:04,080 --> 00:28:07,760
you know, there's an obvious
sense in which our brains are

354
00:28:07,760 --> 00:28:11,480
quantum, hey, well, matter comes
out of quantum mechanics, so.

355
00:28:11,680 --> 00:28:17,080
Or some kind of quantum reality,
even if quantum mechanics is not

356
00:28:17,080 --> 00:28:20,080
yet a complete theory as some
people think.

357
00:28:20,080 --> 00:28:22,160
And you know string theory and
all that.

358
00:28:23,120 --> 00:28:29,720
So obviously you know the
structure of matter would embody

359
00:28:29,720 --> 00:28:34,520
ourselves in a world that has a
quantum substrate.

360
00:28:35,600 --> 00:28:42,640
But I take the kind of work I've
done as an existence proof, and

361
00:28:44,960 --> 00:28:50,360
there have been many times in my
life when I've been dying to use

362
00:28:50,360 --> 00:28:59,400
some kind of concepts to explain
the kinds of phenomena that I'm

363
00:28:59,400 --> 00:29:05,680
really yearning to understand.
And the existence proof here is

364
00:29:05,680 --> 00:29:11,080
that if you look at all the
things that I and my colleagues

365
00:29:11,080 --> 00:29:15,560
have explained, which I think
has the broadest and deepest

366
00:29:15,600 --> 00:29:20,240
interdition or explanatory range
linking brain to mind of any

367
00:29:20,240 --> 00:29:27,200
existing theory, I've never
needed quantum theory except

368
00:29:27,440 --> 00:29:37,080
except for example at the
sensory level.

369
00:29:38,640 --> 00:29:45,680
So for example, I mentioned
briefly GAIL Carpenter and I did

370
00:29:45,680 --> 00:29:54,120
some work on photoreceptor
transduction, invertebrate

371
00:29:54,120 --> 00:30:00,680
cones, and what that means is
photons come in photon to the

372
00:30:00,680 --> 00:30:06,880
quantum constituents of light.
You know the whole thing with

373
00:30:06,880 --> 00:30:10,880
Einstein and wave particle
dualism and all those profound

374
00:30:10,880 --> 00:30:16,680
things.
But photons come in and the

375
00:30:16,680 --> 00:30:21,600
question is how does, how does a
photo detector, which is at the

376
00:30:21,600 --> 00:30:28,400
front end of registering that
there's something going on in

377
00:30:28,400 --> 00:30:33,200
the visual world, how does it
generate a signal through the

378
00:30:33,200 --> 00:30:38,120
retina to the optic nerve?
And one of the things we

379
00:30:38,120 --> 00:30:46,440
realized is that the brain, our
brains in many species, I think

380
00:30:46,440 --> 00:30:51,600
we were doing turtle, I think
with turtle photoreceptors

381
00:30:51,600 --> 00:31:00,560
because oh gosh, you know, it's
been so long ago, some really

382
00:31:00,560 --> 00:31:04,000
wonderful experimentalists had
worked up turtle

383
00:31:04,000 --> 00:31:09,440
phototransduction and it was a
parametric database, really

384
00:31:09,440 --> 00:31:14,400
challenging.
And there's some really bizarre

385
00:31:14,400 --> 00:31:19,080
at the first lush properties of
the data curves.

386
00:31:20,200 --> 00:31:29,080
And what we showed is that if
you had a temporal averaging of

387
00:31:29,080 --> 00:31:36,400
the photons, just so you're
computing A photon density and

388
00:31:36,400 --> 00:31:41,680
you know it would rise and then
it would fall when a little

389
00:31:41,680 --> 00:31:45,880
event occurred, we showed with
simple ideas like that you could

390
00:31:45,880 --> 00:31:49,200
quantitatively explain all those
data.

391
00:31:49,200 --> 00:31:56,480
So we we face the problem that
you have to transduce from

392
00:31:56,480 --> 00:32:01,600
individual photons, which is on
the quantum level, into a

393
00:32:01,600 --> 00:32:07,000
classical description of
neuronal dynamics.

394
00:32:08,360 --> 00:32:14,200
We needed some stuff you don't
use everywhere, and that is a

395
00:32:14,200 --> 00:32:19,640
simple version that goes way
back in phylogeny and I've

396
00:32:19,680 --> 00:32:27,280
talked about with some of my
graduate students, we we looked

397
00:32:27,280 --> 00:32:31,840
at multiple species that have
these precursors.

398
00:32:31,840 --> 00:32:35,200
What?
Ultimately a discovery I made

399
00:32:35,200 --> 00:32:49,440
called spectral timing, which is
both in space and in time, our

400
00:32:49,440 --> 00:32:56,440
brains face the problem of going
from, you know, you could

401
00:32:56,440 --> 00:33:00,320
respond to a single photon, but
that's too short to register any

402
00:33:00,600 --> 00:33:08,840
microscopic event.
Or in space, you could have a

403
00:33:08,840 --> 00:33:12,920
cell that's selective to just a
very little region, but that's

404
00:33:12,920 --> 00:33:15,840
not going to influence your
navigational behavior.

405
00:33:16,680 --> 00:33:22,000
So one of the things I talked
about in my book, I like to sort

406
00:33:22,000 --> 00:33:25,440
of say it in a cute way.
How do little nerve cells

407
00:33:26,200 --> 00:33:33,240
generate spatial and temporal
representations that can

408
00:33:33,240 --> 00:33:40,000
influence adaptive behaviors?
And and a key ingredient on

409
00:33:40,000 --> 00:33:47,200
that, turns out are called grid
cells and time cells.

410
00:33:48,160 --> 00:33:50,840
And one of the things I loved
about this modeling, much of

411
00:33:50,840 --> 00:33:56,760
which I did with Praveen Tilley,
a brilliant PhD student of mine

412
00:33:56,760 --> 00:34:04,160
who then worked with me in much
more senior positions before he

413
00:34:04,160 --> 00:34:07,280
got.
I think, I think he's got quite

414
00:34:07,280 --> 00:34:15,840
a an important job at Intel now
and they obeyed basically the

415
00:34:15,840 --> 00:34:21,560
same laws and they're in two
parallel streams in the

416
00:34:21,560 --> 00:34:32,679
enterrhino to hippocampal cortex
and because of this homology

417
00:34:32,679 --> 00:34:35,120
between the spatial and temporal
laws.

418
00:34:35,159 --> 00:34:38,360
I I love to.
Say you know, give me a break

419
00:34:38,360 --> 00:34:44,360
here, Space and time are one,
and I called it neural

420
00:34:44,760 --> 00:34:48,360
relativity because.
Space and time.

421
00:34:48,360 --> 00:34:52,600
Are one, but the parsimony of it
was breathtaking.

422
00:34:53,239 --> 00:34:59,240
Now you know the evolutionary
precursors of that someone else

423
00:34:59,240 --> 00:35:04,040
is going to have to look at.
But I'm condensed.

424
00:35:05,120 --> 00:35:09,680
They'll love the answer, you
know, and it'll be well worth

425
00:35:09,680 --> 00:35:14,280
their time.
But to be able to say space and

426
00:35:14,280 --> 00:35:16,920
time will want and to show, you
know.

427
00:35:16,920 --> 00:35:18,960
And we're talking about
entorhinal cortex.

428
00:35:19,160 --> 00:35:23,040
I didn't know from entorhinal
cortex when I was young.

429
00:35:23,720 --> 00:35:27,600
It's in a quiet taste.
You get forced into it by

430
00:35:27,600 --> 00:35:34,560
conceptual questions that you
then get stuck on, you get hung

431
00:35:34,600 --> 00:35:37,840
up on until you've got to get an
answer.

432
00:35:37,840 --> 00:35:42,120
Not the final answer.
There's no final answer, but a a

433
00:35:42,120 --> 00:35:47,760
computationally effective and
experimentally remarkably

434
00:35:47,760 --> 00:35:55,120
successful pair of models.
They, Praveen and I didn't,

435
00:35:55,280 --> 00:36:00,320
mainly the space part of it, but
we were able to simulate

436
00:36:01,040 --> 00:36:05,360
quantitatively very challenging
parametric data about grid cell

437
00:36:05,360 --> 00:36:13,240
dynamics and then the time stuff
I did with a series of other PhD

438
00:36:13,240 --> 00:36:18,040
students and Esther Schmeich and
John Merrill, among others.

439
00:36:21,040 --> 00:36:25,440
So I had called.
It spectral timing because

440
00:36:25,440 --> 00:36:31,320
there's a spectrum of cells.
If you want to go from little

441
00:36:31,320 --> 00:36:34,880
nerve cells to temporal delays,
you could bridge.

442
00:36:34,880 --> 00:36:38,360
So let's say they give a simple
example.

443
00:36:38,360 --> 00:36:47,040
Let's say I'm a a human, or a
pigeon or a rat, Or let's say

444
00:36:47,040 --> 00:36:55,120
that I have to wait two or three
seconds after a stimulus to make

445
00:36:55,120 --> 00:36:57,320
a response in order to get my
reward.

446
00:36:57,920 --> 00:37:01,680
And if I prematurely make the
response, I might get punished.

447
00:37:03,920 --> 00:37:06,320
Not so different like a student
in a classroom.

448
00:37:06,320 --> 00:37:10,720
You have to know when it's OK to
raise your hand, and so spectral

449
00:37:10,720 --> 00:37:13,360
timing.
You have lots of nerve cells,

450
00:37:13,360 --> 00:37:22,960
each with its own local firing
delay because they all have

451
00:37:22,960 --> 00:37:27,880
different rates of firing.
So 1 cell might fire bump,

452
00:37:27,880 --> 00:37:31,040
another cell might fire bump,
another still might fire, bump,

453
00:37:31,560 --> 00:37:37,920
bump, bump, and and it's a
stimulus activates the whole

454
00:37:37,920 --> 00:37:41,040
spectrum.
It turns out that each of those

455
00:37:41,040 --> 00:37:45,920
cells has an adaptive way
assigned to it, and the

456
00:37:45,920 --> 00:37:50,800
correlation between the stimulus
and when the action is trained

457
00:37:50,800 --> 00:37:55,720
to occur is going to strengthen
some cells in the spectral

458
00:37:55,960 --> 00:38:03,160
spectrum of better than others.
So for example, you could train.

459
00:38:03,160 --> 00:38:06,360
I'm not sure if I can show you
this one SEC.

460
00:38:07,640 --> 00:38:09,280
Steve.
Do you mind bringing it more to

461
00:38:09,280 --> 00:38:11,760
your left?
I'm.

462
00:38:11,920 --> 00:38:13,520
Going to jiggle.
I didn't do it.

463
00:38:13,520 --> 00:38:17,840
Bring it more to your tips.
Steve, of the other way, yes,

464
00:38:18,680 --> 00:38:19,840
can you see?
OK.

465
00:38:20,480 --> 00:38:23,000
Can you?
So there, there they are, there

466
00:38:23,000 --> 00:38:26,760
the curve.
There the curve so you know it's

467
00:38:26,760 --> 00:38:30,600
in an time is plotted against
activity.

468
00:38:31,080 --> 00:38:35,880
And for example, you can get
spectral cells to fire

469
00:38:35,880 --> 00:38:41,960
selectively at 2 distinct times.
And if you notice the bump at

470
00:38:41,960 --> 00:38:46,840
the earlier time is narrower
than the bump at the later time.

471
00:38:47,280 --> 00:38:54,480
That is a signature of spectral
timing and you find it in the

472
00:38:54,480 --> 00:38:57,760
cerebellum, You find it in the
basal ganglia.

473
00:39:01,880 --> 00:39:04,960
I'm blocking the several other
parts of the brain, you find it

474
00:39:04,960 --> 00:39:07,680
and I can't pull it all up fast
enough.

475
00:39:08,240 --> 00:39:14,760
It is a conserved mechanism and
you also find evolutionary

476
00:39:14,760 --> 00:39:21,000
precursors of it in very
primitive organisms where it

477
00:39:21,000 --> 00:39:24,720
isn't even neural.
It is a way of.

478
00:39:24,720 --> 00:39:29,480
Doing a kind of blocks law, a
trade off between time and

479
00:39:29,480 --> 00:39:35,320
energy, that's what's behind it.
But that kind of speculating

480
00:39:35,320 --> 00:39:40,600
that I just showed you, you can
record from in Cerebella

481
00:39:44,160 --> 00:39:47,320
parallel fiber Pekingese cell
synapses.

482
00:39:50,400 --> 00:39:54,040
So, Steve, sorry, you finished
that first.

483
00:39:54,040 --> 00:39:56,880
No, no, I I just want.
I was.

484
00:39:56,880 --> 00:40:00,840
Forgetting why I was telling you
this, what triggered this reply?

485
00:40:01,160 --> 00:40:02,400
It's fine.
Maybe if I ask the next.

486
00:40:02,400 --> 00:40:05,520
Question.
It'll come back to you on that

487
00:40:05,520 --> 00:40:09,200
note, you you're talking about
the fact that it's also not just

488
00:40:09,200 --> 00:40:13,200
in neural cells there.
There's work being done by

489
00:40:13,200 --> 00:40:17,000
people like Michael Levin.
He's at Tufts University, where

490
00:40:17,360 --> 00:40:19,680
they're starting to show this
blurry nature of what

491
00:40:19,680 --> 00:40:22,680
intelligence seems to be.
Now, it's fair enough.

492
00:40:22,880 --> 00:40:25,880
Some people might argue that
defining the word intelligence

493
00:40:26,160 --> 00:40:29,360
here plays a big role.
But in a nutshell, what he's

494
00:40:29,360 --> 00:40:32,400
trying to say is there's bio
electrical communication

495
00:40:32,400 --> 00:40:36,960
occurring between cells that
goes beyond what our hardwired

496
00:40:37,160 --> 00:40:40,680
DNA is producing to communicate
between cells.

497
00:40:41,160 --> 00:40:45,680
And because of that they're able
to actually do some incredible

498
00:40:45,680 --> 00:40:48,880
work at this lab at it's called
Levin Lab and if you want to

499
00:40:48,880 --> 00:40:51,320
check this out afterwards, but
they're able to create well, I

500
00:40:51,320 --> 00:40:55,040
I've I've.
Interacted with Michael Levin in

501
00:40:55,040 --> 00:41:02,040
the past, but you're not giving
me a good focus in the prime.

502
00:41:02,640 --> 00:41:05,760
You need to remember what we
were interacting about, and

503
00:41:06,400 --> 00:41:10,360
because there was something he
was doing that I thought some of

504
00:41:10,360 --> 00:41:13,200
my work clarified.
But just talking about

505
00:41:13,200 --> 00:41:16,880
intelligence, I can't.
Well, I can't remember.

506
00:41:17,080 --> 00:41:18,280
In.
Essence his work's.

507
00:41:18,280 --> 00:41:23,120
Starting to almost confirm
panpsychism as a theory of

508
00:41:23,120 --> 00:41:25,720
consciousness in the sense that
there is.

509
00:41:25,720 --> 00:41:28,520
What does that mean?
Panpsychism.

510
00:41:28,560 --> 00:41:32,520
Basically means that
consciousness is a fundamental

511
00:41:32,520 --> 00:41:35,600
feature of reality.
Not not in the sense that

512
00:41:35,960 --> 00:41:38,440
consciousness is just
everywhere, like as a lot of

513
00:41:38,440 --> 00:41:40,120
people.
Well, technically that is what

514
00:41:40,120 --> 00:41:43,080
they mean, but OK, well, let me
interrupt.

515
00:41:43,320 --> 00:41:46,840
You there just 'cause that That
reminded me of why I was telling

516
00:41:46,840 --> 00:41:52,400
you a lot of this stuff.
The reason why I was telling you

517
00:41:52,600 --> 00:42:05,160
about some of these primitive
and not even neural mechanisms

518
00:42:05,160 --> 00:42:13,840
is, is because for example, they
were very primitive processes

519
00:42:14,480 --> 00:42:17,800
which have properties of
resonance.

520
00:42:17,800 --> 00:42:22,560
In fact adaptive resonance and
one of the ones that I talked

521
00:42:22,560 --> 00:42:25,920
about in my communication,
memory and development paper way

522
00:42:25,920 --> 00:42:29,520
back in 78.
And then I review it and what

523
00:42:29,720 --> 00:42:38,400
chapter 15 or 16, I forget in my
17 in my magnum opus, has to do

524
00:42:38,400 --> 00:42:43,840
with the process whereby A
blastula during when you have a,

525
00:42:44,520 --> 00:42:49,880
you know, single cell, very
early embryo becomes a gastrula.

526
00:42:51,440 --> 00:42:56,320
You know you.
Start with a spherically

527
00:42:57,520 --> 00:43:05,200
symmetric set of cells after the
first few stages of mitosis, and

528
00:43:05,200 --> 00:43:09,560
then some of the cells get
selectively active and they

529
00:43:09,560 --> 00:43:20,680
start sending pseudopodia to the
other side of the blastula and

530
00:43:20,680 --> 00:43:26,000
on the other side certain cells
develop adhesiveness.

531
00:43:27,280 --> 00:43:33,320
And when some of those.
Pseudopodia hit the adhesive

532
00:43:33,320 --> 00:43:37,120
cells they stick.
And then this.

533
00:43:37,200 --> 00:43:39,560
Accumulates until enough of
these.

534
00:43:40,040 --> 00:43:43,920
It's an autocatalytic
interaction till enough of these

535
00:43:43,920 --> 00:43:47,960
pseudopodes connect.
Now what?

536
00:43:48,320 --> 00:43:51,560
Why is that going to do
something?

537
00:43:51,560 --> 00:43:56,080
It's because the pseudopodes
have contractual properties.

538
00:43:56,640 --> 00:43:59,280
You know if they go up and they
don't hit, they might come down

539
00:43:59,280 --> 00:44:04,000
and go up and if enough of them
stick it becomes like a

540
00:44:04,000 --> 00:44:10,280
primitive muscle and they
contract and then they pull the

541
00:44:10,280 --> 00:44:15,360
cells on the two sides together
and that starts to create a gas

542
00:44:15,360 --> 00:44:21,080
relations next step in cellular
development and it's in my

543
00:44:21,080 --> 00:44:23,120
communication memory and
development paper.

544
00:44:23,120 --> 00:44:29,360
Way way back I I began to
realize that you know these

545
00:44:30,600 --> 00:44:38,800
morphogenetic processes already
embodied primitive versions of

546
00:44:38,800 --> 00:44:45,200
things like adaptive resonance
because the when the connections

547
00:44:45,200 --> 00:44:52,080
occur the the prediction is they
get more and more tuned which

548
00:44:52,080 --> 00:44:56,840
strengthens this sensation.
And as I recall, there was some

549
00:44:56,840 --> 00:45:00,720
later data that were at least
partially consistent but very

550
00:45:00,720 --> 00:45:05,320
hard experiment to do directly.
But my prediction would be it's

551
00:45:05,320 --> 00:45:10,800
a simple form of adaptive
resonance in, you know, an early

552
00:45:10,800 --> 00:45:13,440
stage of morphogenesis in
multiple species.

553
00:45:15,160 --> 00:45:18,720
And I there.
Are a number of examples of

554
00:45:18,720 --> 00:45:22,000
these.
Remember I talked about

555
00:45:22,000 --> 00:45:26,680
complementary computing, the
kind of yin Yang sitting

556
00:45:26,680 --> 00:45:34,480
together and that goes in
multiple parts of biology too.

557
00:45:34,480 --> 00:45:39,640
And although I'm going to make a
statement now that you know I

558
00:45:39,640 --> 00:45:44,080
have it, it's the rank is form
of speculation.

559
00:45:44,080 --> 00:45:48,160
It doesn't give you any
predictive ability beyond what

560
00:45:48,400 --> 00:45:52,640
wonderful scientists have
already done.

561
00:45:53,400 --> 00:45:57,480
I think an example of that
complementary computing is the

562
00:45:57,480 --> 00:46:01,800
double Helix DNA and RNA double
helixes.

563
00:46:02,680 --> 00:46:03,960
It's.
It's a way.

564
00:46:03,960 --> 00:46:14,920
Of bringing complementary stuff
together and into a, you know, a

565
00:46:15,120 --> 00:46:18,200
more complete representation of
the information you need to do

566
00:46:18,200 --> 00:46:21,680
stuff.
I I would love to, you know.

567
00:46:24,280 --> 00:46:29,760
Barbara Mcclintock then did
wonderful work on what's she

568
00:46:29,760 --> 00:46:33,360
called dancing genes.
I don't, I don't think that was

569
00:46:33,360 --> 00:46:38,480
quite it, but trying to get at
the dynamics of how the double

570
00:46:38,480 --> 00:46:43,520
Helix, which usually you see in
a, you know, a static form and

571
00:46:43,520 --> 00:46:50,440
some wonderful chemical
architecture, but it's very

572
00:46:50,440 --> 00:46:53,920
dynamic, it's always doing
stuff.

573
00:46:55,800 --> 00:47:01,600
So I think there's resonance and
complementarity everywhere.

574
00:47:01,880 --> 00:47:06,120
And remember last time I talked
about the fact that in many

575
00:47:06,120 --> 00:47:09,560
parts of my work they're
principles of complementarity,

576
00:47:11,080 --> 00:47:15,600
uncertainty and resonance.
And we know, coming back to

577
00:47:15,600 --> 00:47:19,520
quantum theory, those are
principles at the core of

578
00:47:19,520 --> 00:47:22,960
quantum theory, that.
Doesn't mean that.

579
00:47:22,960 --> 00:47:25,440
We are operating on a quantum
level.

580
00:47:25,920 --> 00:47:30,480
It just means these are kind of
universal principles of nature

581
00:47:31,160 --> 00:47:37,400
and we, through evolutionary
adaptation over the eons, have

582
00:47:37,400 --> 00:47:42,560
been built embodying them in a
form that could support animal

583
00:47:42,560 --> 00:47:46,320
intelligence.
So if you ask.

584
00:47:46,320 --> 00:47:53,040
About an psychism and stuff,
well, you're never going to get

585
00:47:53,040 --> 00:47:56,800
into that system, just like
you're not going to ride an

586
00:47:56,800 --> 00:48:00,440
electron.
But hey, they're built on very

587
00:48:01,360 --> 00:48:10,440
similar principles as we are,
And and I feel I've understood

588
00:48:10,440 --> 00:48:15,640
more by commenting about these
three general principles that

589
00:48:15,640 --> 00:48:24,440
are conserved over phylogeny and
evolutionary time than just

590
00:48:24,440 --> 00:48:27,920
saying the word pants like his.
In which I I want to know

591
00:48:27,920 --> 00:48:32,160
exactly what are you talking
about because it's a lovely

592
00:48:32,280 --> 00:48:36,200
phrase and it's important to
have a lovely phrase, but I need

593
00:48:36,200 --> 00:48:39,080
to know, where's the beef here?
Where is the beef?

594
00:48:39,920 --> 00:48:41,200
So where is it?
What?

595
00:48:41,280 --> 00:48:43,080
What?
What's the beef?

596
00:48:43,600 --> 00:48:46,160
So.
Just just just to define it a

597
00:48:46,160 --> 00:48:50,720
little bit, MM once wrote a
paper with Daniel Dennett.

598
00:48:50,800 --> 00:48:53,640
I think this would be a nice way
to to reel it in.

599
00:48:53,880 --> 00:48:55,800
It's called Cognition all the
way down.

600
00:48:56,840 --> 00:48:58,640
And the reason why I bring that
paper up is because at some

601
00:48:58,640 --> 00:49:00,440
point I was going to mention did
it.

602
00:49:00,440 --> 00:49:03,840
You do mention him in your paper
did.

603
00:49:03,840 --> 00:49:05,360
It doesn't have a panpsychist
view.

604
00:49:05,360 --> 00:49:09,360
So panpsychism is pretty much
the the IT pretty much means

605
00:49:09,600 --> 00:49:12,840
consciousness is everywhere.
Not always in the very mystical

606
00:49:12,840 --> 00:49:14,840
sense that a lot of people seem
to think of it.

607
00:49:14,920 --> 00:49:19,440
They they're pretty much trying
to come across by saying that

608
00:49:20,320 --> 00:49:23,760
cognition or proto cognition or
even proto consciousness can be

609
00:49:23,760 --> 00:49:28,800
found within smaller layers of
of reality in terms of a human.

610
00:49:28,800 --> 00:49:31,480
So you can go down into like
let's say tissues and cells and

611
00:49:31,720 --> 00:49:36,120
and within those bio biological
processes you can find forms of

612
00:49:36,120 --> 00:49:39,800
proto consciousness.
Well, I.

613
00:49:39,880 --> 00:49:41,280
Don't necessarily.
Agree with it.

614
00:49:41,280 --> 00:49:42,520
But I'm, I'm.
I'm.

615
00:49:43,200 --> 00:49:47,080
Wait, wait.
Let me let me you.

616
00:49:47,160 --> 00:49:51,120
You really have to be clear
about what you mean by

617
00:49:51,120 --> 00:49:53,440
consciousness.
Yes, I agree.

618
00:49:53,680 --> 00:49:54,520
With that.
Completely.

619
00:49:54,840 --> 00:49:58,920
I've already given.
You examples with guest relation

620
00:49:58,920 --> 00:50:06,600
and with talking about
complementarity and resonance

621
00:50:06,600 --> 00:50:13,800
and uncertainty, going all
through the natural world, that

622
00:50:14,080 --> 00:50:15,720
these things go all the way
down.

623
00:50:15,880 --> 00:50:19,640
Yes, yes, now.
The question is.

624
00:50:19,640 --> 00:50:21,880
What are?
What's the definition of

625
00:50:21,880 --> 00:50:25,240
cognition that you're using
here?

626
00:50:25,240 --> 00:50:28,320
And what's the definition of
consciousness?

627
00:50:29,200 --> 00:50:32,240
We there are these shared
processes.

628
00:50:33,280 --> 00:50:42,640
As I remarked in our last
discussion, I'm happy to believe

629
00:50:43,480 --> 00:50:48,360
that every species that solves
the stability plasticity dilemma

630
00:50:49,240 --> 00:50:54,080
has some form of consciousness.
Because, you know, my own work,

631
00:50:54,080 --> 00:50:59,600
I showed that to do that, at
least in everything I've seen

632
00:50:59,600 --> 00:51:06,640
and experiments and models, you
need a combination of learning,

633
00:51:06,640 --> 00:51:09,800
expectation, attention,
resonance, and synchrony.

634
00:51:10,560 --> 00:51:17,960
And when you have all those
things, if you're exposed to an

635
00:51:17,960 --> 00:51:23,440
external world that has stable
enough events.

636
00:51:24,640 --> 00:51:27,160
For you to.
Actually learn something with

637
00:51:27,640 --> 00:51:34,760
spatial and temporal stability.
Then the process will also give

638
00:51:34,760 --> 00:51:40,400
you a form of consciousness,
either of recognition or of

639
00:51:40,400 --> 00:51:45,200
perception.
But that was a big if too.

640
00:51:45,840 --> 00:51:51,480
You know, what is the stable
world that the resonant events

641
00:51:51,480 --> 00:51:56,760
are interacting with and is it
what we would call consciousness

642
00:51:56,760 --> 00:52:00,760
or cognition?
So I think that until I hear

643
00:52:00,760 --> 00:52:03,240
their definitions and how
they've used to explain

644
00:52:03,240 --> 00:52:08,400
something interesting, I would
be more comfortable just saying

645
00:52:08,840 --> 00:52:11,320
stuff like I said, giving
examples of.

646
00:52:12,960 --> 00:52:16,520
Shared mechanisms.
Like adaptive resonance and

647
00:52:17,440 --> 00:52:22,560
gastrulation, and is
complementarity all over the

648
00:52:22,560 --> 00:52:29,720
place but cognition all the way
down.

649
00:52:29,720 --> 00:52:34,280
It's cute in your paper.
You mentioned, you know, as I

650
00:52:34,320 --> 00:52:41,120
pointed out in my book.
Dan who is a very bright and

651
00:52:41,880 --> 00:52:49,240
leading of philosopher of mind
also wrote things about neon

652
00:52:49,240 --> 00:52:52,160
color spreading that are just
wrong.

653
00:52:52,800 --> 00:52:57,560
And then he he became sarcastic
about all the fools who actually

654
00:52:57,560 --> 00:53:05,560
believe it's a phenomenon and it
really sarcasm and sciences ad

655
00:53:05,560 --> 00:53:10,120
hominem and gratuitous and he
especially embarrassing when he

656
00:53:10,120 --> 00:53:13,120
was wrong and.
At a meeting.

657
00:53:13,120 --> 00:53:16,400
Where I invited him to speak
'cause I don't only invite

658
00:53:16,400 --> 00:53:20,600
people who I agree with.
He said to the.

659
00:53:20,640 --> 00:53:25,200
Audience that he was wrong, but
I'm not sure if after he left

660
00:53:25,200 --> 00:53:29,880
the meeting he still said he was
just surrounded by good

661
00:53:29,880 --> 00:53:34,120
psychophysicists and
neuroscientists and modelers and

662
00:53:34,240 --> 00:53:35,640
what exactly did?
He say.

663
00:53:37,160 --> 00:53:44,920
What he he Well, I think I part
of my talk was, I think, you

664
00:53:44,920 --> 00:53:49,840
know, so long ago explaining a
lot of the data about how we

665
00:53:50,360 --> 00:53:56,480
consciously see, you know,
brightness perception form the

666
00:53:56,480 --> 00:54:01,520
end color spreading, you know,
general surface filling in the

667
00:54:01,520 --> 00:54:04,600
complementarity of perceptual
boundaries and surfaces.

668
00:54:06,520 --> 00:54:09,520
And he was one of.
Two philosophies of mind I

669
00:54:09,520 --> 00:54:14,000
invited.
Anyway, he just got up and

670
00:54:14,000 --> 00:54:18,200
started his talk with that
retraction.

671
00:54:20,280 --> 00:54:23,640
Cause what you know, if he had
claimed it again, people would

672
00:54:23,640 --> 00:54:28,400
say but but Steve just explained
data about it.

673
00:54:28,480 --> 00:54:33,480
It exists.
You can see it you.

674
00:54:33,480 --> 00:54:36,520
Know with your own.
Mind.

675
00:54:38,400 --> 00:54:40,840
So I don't know where.
He stands on it now.

676
00:54:40,840 --> 00:54:45,360
He's very bright and very
creative, but he he went too far

677
00:54:45,360 --> 00:54:48,800
there and he was wrong.
And what made what annoyed me

678
00:54:48,800 --> 00:54:52,320
was it's my current
understanding that he first

679
00:54:52,320 --> 00:54:55,600
heard.
About me on color.

680
00:54:55,600 --> 00:54:59,080
Spreading When he came kindly.
I don't take it for granted.

681
00:54:59,080 --> 00:55:02,240
People come to my lecture.
He came to a talk I gave on

682
00:55:02,240 --> 00:55:07,320
vision in which one of the kinds
of data I was explaining was

683
00:55:07,320 --> 00:55:14,200
neon color spreading data.
And, you know, as part of a more

684
00:55:14,280 --> 00:55:19,840
integrated view of a lot of
visual processes like the

685
00:55:19,840 --> 00:55:23,960
uncolor spreading is.
You know the reason it got

686
00:55:23,960 --> 00:55:28,240
popular?
Well, one reason it got popular

687
00:55:28,240 --> 00:55:32,440
is because we pulled it out of
anonymity.

688
00:55:33,560 --> 00:55:42,280
Because I could see that it gave
really good visible evidence of

689
00:55:42,280 --> 00:55:45,800
our predicted laws of how
boundaries and surfaces

690
00:55:45,800 --> 00:55:48,720
interact.
Because there were colors where

691
00:55:48,720 --> 00:55:50,240
there shouldn't have been
colors.

692
00:55:51,440 --> 00:55:57,080
And.
I actually emphasize it, and

693
00:55:57,080 --> 00:56:01,040
then Kanakayama and Mike
Paradiso and other people picked

694
00:56:01,040 --> 00:56:04,680
up on it and started doing more
experimental work on it.

695
00:56:04,720 --> 00:56:11,440
But it was it was lying
unnoticed until the theory

696
00:56:11,440 --> 00:56:15,400
clarified how remarkable the
interactions were and gave

697
00:56:17,240 --> 00:56:19,960
compelling evidence of surface
filling in.

698
00:56:20,160 --> 00:56:24,720
Which is precisely what Dan was
saying doesn't exist.

699
00:56:26,560 --> 00:56:29,160
Yes, that is something.
He And it's not the only one.

700
00:56:29,160 --> 00:56:34,200
You know Mike, my very gifted
colleague Benjo Pinner has what

701
00:56:34,200 --> 00:56:37,320
he calls the watercolor effect,
which is all about surface

702
00:56:37,320 --> 00:56:40,560
filling in.
And you know.

703
00:56:41,000 --> 00:56:44,000
You could say this is due to the
first competitive state doing

704
00:56:44,000 --> 00:56:46,360
that interacting with the
attack.

705
00:56:47,080 --> 00:56:51,320
I mean we can explain it all in
and you can see it.

706
00:56:52,880 --> 00:56:54,320
Are there any?
Are there any philosophers?

707
00:56:54,320 --> 00:56:59,080
Of mine who that who's working
familiar with who you feel does

708
00:56:59,080 --> 00:57:02,600
represent your you're a form of
emergentism in a great way.

709
00:57:02,600 --> 00:57:05,320
Or your view on consciousness in
a similar way?

710
00:57:05,560 --> 00:57:07,320
Well.
People don't.

711
00:57:07,320 --> 00:57:12,600
Have to.
Do what I do in any way I'm I'm

712
00:57:12,600 --> 00:57:16,640
blocking on his name, the other
philosopher of mine.

713
00:57:18,040 --> 00:57:23,880
Who I invited to that?
Meeting long ago is a Canadian

714
00:57:24,160 --> 00:57:28,360
guy and.
I forget his name.

715
00:57:28,840 --> 00:57:33,080
It's I shouldn't forget it, but
I, you know, I'd have to prime

716
00:57:33,080 --> 00:57:35,560
my stuff.
My mind's elsewhere now and he

717
00:57:35,560 --> 00:57:38,160
gave a lovely tour.
I really thought it was a

718
00:57:38,160 --> 00:57:41,680
useful, interesting tour.
Was it Paul Churchland?

719
00:57:43,440 --> 00:57:48,120
No, it's not Paul.
No, Paul also did serious work.

720
00:57:49,440 --> 00:57:49,960
I'm.
Not.

721
00:57:51,800 --> 00:57:58,200
Sure anyway, but but my.
Advice to anyone who wants to

722
00:57:58,200 --> 00:58:03,680
talk scientifically about mind
and brain is read the data and.

723
00:58:03,680 --> 00:58:05,720
Then read.
The state of the modeling

724
00:58:05,720 --> 00:58:10,800
community 'cause you don't want
to make a fool of yourself.

725
00:58:12,640 --> 00:58:15,960
OK, so.
With that in mind so we've we've

726
00:58:16,160 --> 00:58:19,240
we've discussed the, the people
who have.

727
00:58:19,840 --> 00:58:22,320
Let me let me make a.
Remark about that you know.

728
00:58:25,680 --> 00:58:30,880
I forget who said.
It but a very distinguished guy

729
00:58:31,120 --> 00:58:38,120
who I very much admired and and
he gave a keynote lecture and

730
00:58:39,000 --> 00:58:43,520
and he said you know everybody
thinks they can have a theory

731
00:58:43,520 --> 00:58:48,200
about how our minds work because
we have a mind but by extension

732
00:58:48,200 --> 00:58:54,160
we also have electrons and
photons and atomic nuclei.

733
00:58:54,600 --> 00:58:57,040
Do we feel we're immediately
physicists?

734
00:58:57,040 --> 00:59:02,480
You know, I mean, it's people
think introspective evidence

735
00:59:02,480 --> 00:59:07,000
will explain their mind.
But remember, the main point of

736
00:59:07,000 --> 00:59:11,520
cognitive impenetrability is
that you and I can see each

737
00:59:11,520 --> 00:59:14,320
other, hear each other, have
feelings about each other, learn

738
00:59:14,320 --> 00:59:18,320
from each other.
Because we have no cognitive

739
00:59:18,760 --> 00:59:21,520
penetrability.
We don't know what's up here.

740
00:59:22,240 --> 00:59:24,600
We don't know that even the
brain is the seed of

741
00:59:24,600 --> 00:59:26,680
intelligence from our daily
experience.

742
00:59:26,680 --> 00:59:30,760
And as you know, anyone who
studied the history of

743
00:59:31,240 --> 00:59:36,560
neuroscience knows, people
originally thought that other

744
00:59:36,560 --> 00:59:40,080
organs were the seed of
intelligence, the heart or the

745
00:59:41,600 --> 00:59:48,120
pancreas even, you know, So
yeah, so so do you.

746
00:59:48,120 --> 00:59:50,000
I mean.
Fundamentally the that

747
00:59:50,000 --> 00:59:54,840
phenomenological first person,
subjective qualia, a qualitative

748
00:59:54,840 --> 00:59:59,000
feel, is explainable via
scientific theory.

749
00:59:59,200 --> 01:00:01,040
I'm just obviously I'm just
playing devil's advocate.

750
01:00:01,040 --> 01:00:03,920
I know what your view pretty
much is, but I I want people to

751
01:00:03,920 --> 01:00:05,360
understand this as much as
possible.

752
01:00:05,560 --> 01:00:08,120
That intentionality that people
talk that.

753
01:00:08,120 --> 01:00:13,000
Intentionality.
That aboutness of of reality for

754
01:00:13,000 --> 01:00:15,880
you, that's nothing specifically
and special about this.

755
01:00:17,280 --> 01:00:20,640
Again, you have to be very clear
about how you're using the word

756
01:00:20,640 --> 01:00:26,320
intentionality.
I mean, for example, an adaptive

757
01:00:26,320 --> 01:00:30,400
resonance theory.
There are top down expectations

758
01:00:30,400 --> 01:00:32,440
which are a form of
intentionality.

759
01:00:32,920 --> 01:00:36,840
There are predictions of what's
going to happen next, which are

760
01:00:36,840 --> 01:00:42,280
a form of intentionality.
I'd have to know an example that

761
01:00:42,280 --> 01:00:45,920
would be different from that to
realize that someone's talking

762
01:00:45,920 --> 01:00:50,560
about something else.
So using the nice word in some

763
01:00:50,560 --> 01:00:55,600
words are better as chapter
headings.

764
01:00:56,160 --> 01:01:00,960
And then you write what you mean
by the word in and of

765
01:01:00,960 --> 01:01:02,160
themselves.
They don't tell you.

766
01:01:02,160 --> 01:01:07,600
Do you know what what meaning of
intentionality is being

767
01:01:07,600 --> 01:01:11,080
expressed here?
Can you articulated better, did

768
01:01:11,080 --> 01:01:13,640
I say something irrelevant?
What would be?

769
01:01:13,640 --> 01:01:16,440
I think maybe.
The best way for me to do that?

770
01:01:16,800 --> 01:01:21,040
Let me define it from the
Stanford Encyclopedia

771
01:01:21,040 --> 01:01:22,560
philosophy, just to make it
easier.

772
01:01:24,200 --> 01:01:28,840
In philosophy, intentionality is
the power of minds and mental

773
01:01:28,840 --> 01:01:33,680
states to be about to represent
or to stand for things,

774
01:01:33,680 --> 01:01:35,720
properties and states of
affairs.

775
01:01:36,040 --> 01:01:39,760
Now I know in your theory
obviously you address these, but

776
01:01:39,760 --> 01:01:43,680
to a philosopher of mind this is
considered almost a a very

777
01:01:43,680 --> 01:01:48,200
special property, a qualitative.
It's difficult for me to

778
01:01:48,200 --> 01:01:49,200
actually explain it, to be
honest.

779
01:01:49,960 --> 01:01:52,800
Well, that that's.
What all my work is about Yeah I

780
01:01:52,840 --> 01:01:57,240
know that's the no, but you know
that's what the work does.

781
01:01:57,240 --> 01:02:03,320
But but you know when you're
talking about what it's about,

782
01:02:04,440 --> 01:02:10,040
you know there are multi
dimensional aspects of that

783
01:02:10,680 --> 01:02:15,560
knowing including the
perceptual, the cognitive, the

784
01:02:15,560 --> 01:02:22,520
recollective, the emotional, the
action, the appetitive.

785
01:02:23,400 --> 01:02:27,840
You know so.
It's too vague.

786
01:02:30,280 --> 01:02:37,560
The issue is explanatory power.
You know as, as.

787
01:02:38,640 --> 01:02:43,120
People have written about.
Time and again, you know, in

788
01:02:43,120 --> 01:02:47,600
physics people were doing
natural philosophy until they

789
01:02:47,600 --> 01:02:50,480
could explain stuff, and then it
was called physics.

790
01:02:51,240 --> 01:02:54,360
I think that's true of
philosophy of mine too.

791
01:02:55,040 --> 01:02:57,880
I mean, I took philosophy
courses.

792
01:02:59,480 --> 01:03:03,480
In.
College and what they were good

793
01:03:03,480 --> 01:03:06,560
at was.
I'm posing questions,

794
01:03:07,560 --> 01:03:11,400
articulating questions.
But if you wanted the answers,

795
01:03:11,400 --> 01:03:18,440
you have to turn to science.
But also what I found is by.

796
01:03:20,200 --> 01:03:24,640
Getting to a A.
Deep principled understanding of

797
01:03:24,640 --> 01:03:28,480
something.
It helps me to articulate new

798
01:03:28,480 --> 01:03:33,400
questions that I couldn't have
done just based on intuition

799
01:03:33,400 --> 01:03:36,880
alone.
Intuition is.

800
01:03:38,040 --> 01:03:43,240
Limited, I mean.
It is so important that because

801
01:03:43,240 --> 01:03:46,840
we can't consciously see,
because we can't consciously

802
01:03:46,840 --> 01:03:50,760
feel and so on, that helps us to
know at least well what are we

803
01:03:50,760 --> 01:03:54,280
trying to explain.
I want to explain how I see, you

804
01:03:54,280 --> 01:03:57,360
know how I see color and
brightness and texture and

805
01:03:58,120 --> 01:04:03,240
shading and objects and you know
motion and you know all this

806
01:04:03,240 --> 01:04:07,320
stuff so it gives.
Us a whole.

807
01:04:07,360 --> 01:04:12,320
Series of chapter headings, but
to actually explain it.

808
01:04:13,720 --> 01:04:16,920
You have to think in a.
Totally different way and

809
01:04:16,920 --> 01:04:23,760
finding that way I have found
requires an immersion into large

810
01:04:23,760 --> 01:04:26,960
databases that probe the
different aspects of the

811
01:04:26,960 --> 01:04:29,960
properties that you're trying to
explain you.

812
01:04:30,480 --> 01:04:33,960
You can't just say, hey, I bet
it's like this and be right.

813
01:04:34,400 --> 01:04:38,400
The chances are is as close to 0
as you can imagine.

814
01:04:41,320 --> 01:04:43,640
Hunches are good.
Don't get me wrong.

815
01:04:44,560 --> 01:04:47,920
I mean, hunches help theorists
think about.

816
01:04:47,920 --> 01:04:50,640
Oh, I should have been thinking
about that.

817
01:04:51,520 --> 01:04:55,080
But the hunch you'll have after
you know a lot will be very

818
01:04:55,080 --> 01:04:58,320
different from the hunch you
have when you know very little.

819
01:04:58,840 --> 01:05:01,280
Steve, you you.
Mentioned, you know Paul

820
01:05:01,280 --> 01:05:04,840
Churchland and he he was a very
prominent No, I don't I.

821
01:05:04,840 --> 01:05:06,920
Don't know, Paul.
OK, But you know.

822
01:05:06,920 --> 01:05:09,760
Often I just knew.
Yeah, I I knew.

823
01:05:09,760 --> 01:05:12,360
I knew that he did some good
work, but I haven't looked at it

824
01:05:12,360 --> 01:05:14,800
for many years.
OK, so there was Paul and.

825
01:05:15,120 --> 01:05:19,120
Patricia Churchland and they
with a theory known as

826
01:05:19,240 --> 01:05:24,280
eliminative materialism.
And what that was was it was

827
01:05:24,280 --> 01:05:27,840
it's a very radical claim.
Basically ordinary common sense

828
01:05:27,840 --> 01:05:31,000
terms.
So common sense understandings

829
01:05:31,000 --> 01:05:32,840
of the mind.
They claim to be deeply

830
01:05:32,840 --> 01:05:35,160
incorrect.
They felt that folk

831
01:05:35,160 --> 01:05:38,400
psychological terms that we use,
so even saying things like

832
01:05:38,800 --> 01:05:43,400
learning or thought etcetera,
don't technically work in the

833
01:05:43,400 --> 01:05:45,600
physical world.
Because when you take

834
01:05:46,040 --> 01:05:50,800
materialism to be true, you have
to realize that reality is just

835
01:05:50,800 --> 01:05:52,800
neurons fire.
It's actually got.

836
01:05:52,800 --> 01:05:56,880
There is no secondary reality in
psychology where we could say

837
01:05:56,880 --> 01:06:01,440
things like, OK, that's thought,
that's memory, that's conscious

838
01:06:01,480 --> 01:06:04,840
experiences because in reality
that's just neurons firing,

839
01:06:05,080 --> 01:06:08,280
that's just blood circulating
etcetera, etcetera.

840
01:06:09,120 --> 01:06:11,320
So, yeah, well.
What do you think?

841
01:06:11,440 --> 01:06:16,160
Well, the well, The well.
First words like learning.

842
01:06:16,160 --> 01:06:19,200
And thought are more chapter
headings.

843
01:06:20,160 --> 01:06:23,720
You know they they're not
theories, they're not

844
01:06:23,720 --> 01:06:25,480
principles.
They're chapter headings.

845
01:06:25,920 --> 01:06:29,800
Then you've got if you're going
to continue using those words at

846
01:06:29,920 --> 01:06:32,400
all, you've got to say what you
mean.

847
01:06:32,400 --> 01:06:37,880
So, for example, I invented the
phrase adaptive resonance in

848
01:06:37,880 --> 01:06:44,560
order to describe a brain
process for which there was a

849
01:06:44,560 --> 01:06:49,600
great deal of evidence that I
could explain the word wasn't

850
01:06:49,600 --> 01:06:51,360
there before, and I've done
that.

851
01:06:51,960 --> 01:06:54,000
We've talked about spectral
timing.

852
01:06:54,000 --> 01:06:56,920
I invented the word spectral
timing.

853
01:06:58,520 --> 01:07:01,040
We talked about neural
relativity.

854
01:07:01,320 --> 01:07:04,160
I indented the word neural
relativity.

855
01:07:04,720 --> 01:07:09,880
You know, I mean, all these
words come out of an analysis of

856
01:07:09,880 --> 01:07:13,600
lots of data.
But you know, again, we're just

857
01:07:13,600 --> 01:07:16,320
getting back to the problem of
emergent properties.

858
01:07:17,080 --> 01:07:21,640
It's not just neurons.
It's neuronal interactions that

859
01:07:21,640 --> 01:07:28,840
generate emergent properties
that often cause actions that

860
01:07:28,840 --> 01:07:34,840
lead to feedback, that create a
cycle of perception, cognition,

861
01:07:34,840 --> 01:07:39,000
emotion, action, over and over
and over as you evolve in the

862
01:07:39,000 --> 01:07:44,600
world and through that cycle, if
there are statistically

863
01:07:46,280 --> 01:07:51,280
repeatable enough or stable
enough properties of that

864
01:07:51,280 --> 01:07:56,640
interaction, you will learn
about them as appropriate to the

865
01:07:56,640 --> 01:08:03,360
circuits that are resonating
with those particular

866
01:08:03,360 --> 01:08:06,800
invariants.
And as I mentioned last time,

867
01:08:06,800 --> 01:08:09,120
you know we talked briefly about
cognitive emotional

868
01:08:09,120 --> 01:08:13,680
interactions.
To me it was very satisfying

869
01:08:14,360 --> 01:08:19,080
that cognitive and emotional
circuits share many properties

870
01:08:20,040 --> 01:08:26,080
but one thing they don't share
is their inputs and their

871
01:08:26,080 --> 01:08:29,160
outputs.
Like with emotion, you have a

872
01:08:29,160 --> 01:08:37,359
lot of inter receptive inputs of
hunger, satiety, pain, you know

873
01:08:37,359 --> 01:08:46,000
whatever relief, happiness and
and and with cognition usually

874
01:08:46,000 --> 01:08:52,600
there's a perceptual front end
in vision or addition, you know

875
01:08:52,600 --> 01:08:58,560
tactile that drive the hose and
then there's an interface that

876
01:08:58,560 --> 01:09:01,880
resonates.
So a lot.

877
01:09:01,880 --> 01:09:08,560
Of the circuitry can be shared
but specialized in order to be

878
01:09:08,560 --> 01:09:12,800
able to resonate with particular
invariants of the environments

879
01:09:13,359 --> 01:09:19,479
that they are trying to.
Understand.

880
01:09:19,479 --> 01:09:23,160
That's a bad words to loaded
work to the environments for

881
01:09:23,160 --> 01:09:29,120
which they have adapted.
Yes, so emergent properties.

882
01:09:29,120 --> 01:09:32,359
Emergent properties, emergent
property, which you cannot

883
01:09:32,359 --> 01:09:35,960
understand without a
sufficiently powerful and

884
01:09:35,960 --> 01:09:42,359
principal computational
mathematically rigorous theory.

885
01:09:43,359 --> 01:09:50,600
And there is that explanatory
gap without theory.

886
01:09:52,359 --> 01:09:53,560
In your work, I mean you.
Refer to.

887
01:09:53,560 --> 01:09:57,080
This as a establishing A linking
hypothesis.

888
01:09:59,280 --> 01:10:03,280
Between brain and mind.
Yeah, well, it's a familiar

889
01:10:03,280 --> 01:10:10,120
phrase.
Linking hypothesis, yeah.

890
01:10:10,120 --> 01:10:17,960
And I don't want us to go in
circles, but if you don't have a

891
01:10:17,960 --> 01:10:21,800
way to generate the emerging
properties linking to behaviour,

892
01:10:22,600 --> 01:10:25,160
then you really can't
mechanistically explain

893
01:10:25,160 --> 01:10:27,200
behaviour.
OK, now so.

894
01:10:27,320 --> 01:10:30,680
I've got a lot of questions from
from fans and audience members

895
01:10:31,160 --> 01:10:34,520
in general, but I tell that some
of them are going to take us in

896
01:10:34,560 --> 01:10:37,800
circles.
So I'm well, that's OK.

897
01:10:38,480 --> 01:10:42,680
You know, I don't think it's bad
to say the same thing more than

898
01:10:42,680 --> 01:10:43,720
once.
OK.

899
01:10:44,440 --> 01:10:49,280
I think I might have mentioned I
I would sometimes give the same

900
01:10:49,280 --> 01:10:53,760
keynote at two different
conferences and assuming that

901
01:10:53,760 --> 01:10:57,520
because they were in different
continents or whatever, a lot of

902
01:10:57,520 --> 01:11:00,960
the people hadn't heard it.
And then I'd see in the audience

903
01:11:01,240 --> 01:11:04,760
some of the same people and they
said, you know, it's good to

904
01:11:04,760 --> 01:11:08,120
hear more than once.
Oh, by the way, I forgot to

905
01:11:08,120 --> 01:11:15,000
mention, you know there are when
it when it comes to my 2017

906
01:11:15,000 --> 01:11:20,400
paper on the hard problem, I do
have Keynote lectures about that

907
01:11:20,400 --> 01:11:26,200
on my web page.
My web page URL again is Sites

908
01:11:26,240 --> 01:11:35,800
SITE
s.buforbostonuniversity.edu.

909
01:11:36,280 --> 01:11:46,280
For education slash Steve G
that's STEV e.g sites WWW slash

910
01:11:46,360 --> 01:11:49,840
DG.
So for people who want to hear

911
01:11:50,880 --> 01:11:56,320
that lecture, given I I might
have given that one in more than

912
01:11:56,320 --> 01:12:00,200
one form.
I forget and sometimes I will

913
01:12:00,920 --> 01:12:02,720
have both of them put on my web
page.

914
01:12:02,720 --> 01:12:07,200
But there are a number of
keynotes that I try to make

915
01:12:07,200 --> 01:12:12,400
self-contained for
interdisciplinary audiences.

916
01:12:13,600 --> 01:12:15,960
But you know as.
We were joking before.

917
01:12:16,400 --> 01:12:19,760
self-contained.
Depends on where you're coming

918
01:12:19,760 --> 01:12:22,720
from, but they keep.
Inviting me?

919
01:12:22,720 --> 01:12:26,400
Back.
So I assumed I couldn't have

920
01:12:26,400 --> 01:12:29,200
been that bad.
I keep getting invited back so

921
01:12:30,280 --> 01:12:34,760
well, yeah as well will help.
To solidify some of these

922
01:12:34,760 --> 01:12:37,280
concepts for people because I
think it does require repeat

923
01:12:37,280 --> 01:12:40,320
reading, repeat watching and
repeat listening.

924
01:12:40,320 --> 01:12:42,520
Just to get all of these well in
your way.

925
01:12:42,520 --> 01:12:46,920
Well Steve feel and experience
this a lot more resonate with it

926
01:12:46,920 --> 01:12:48,360
a bit.
Well, I I would.

927
01:12:48,360 --> 01:12:52,440
Recommend you know.
A discussion such as.

928
01:12:52,440 --> 01:12:58,080
Ours, I think for me, is
successful if it motivates

929
01:12:58,080 --> 01:13:02,120
someone to want to learn more.
And then I would.

930
01:13:02,120 --> 01:13:08,560
Recommend someone go to one of
the videos on my web page or

931
01:13:08,560 --> 01:13:17,120
YouTube or wherever and listen
to the lecture and.

932
01:13:17,120 --> 01:13:19,520
All and and.
Maybe listen more than once and

933
01:13:19,520 --> 01:13:22,920
stop it and repeat if you what
is he talking about?

934
01:13:23,800 --> 01:13:27,320
And after you've done that until
you feel I know a little better,

935
01:13:27,320 --> 01:13:31,400
then go to some of the articles.
And some of the articles are

936
01:13:31,400 --> 01:13:37,960
heuristic like my 2017 paper is
in a way, even though it breaks

937
01:13:37,960 --> 01:13:40,400
new ground.
In a way it's a review paper

938
01:13:41,160 --> 01:13:44,000
because a lot of the
foundational mathematical work

939
01:13:44,000 --> 01:13:48,080
is earlier or I wouldn't have
had the nerve to write that

940
01:13:48,080 --> 01:13:52,600
paper because I knew everything
I was writing is supported by

941
01:13:53,160 --> 01:13:58,400
mathematical models and computer
simulations of challenging data.

942
01:13:59,400 --> 01:14:07,640
So you know, there were levels
from an SNOR chat to videos of

943
01:14:07,640 --> 01:14:09,880
self-contained lectures to
reading.

944
01:14:11,480 --> 01:14:15,160
Hopefully non-technical.
To view papers to technical

945
01:14:15,160 --> 01:14:19,400
ones, but really the best
resource I can recommend is my

946
01:14:19,400 --> 01:14:26,240
magnum opus Conscious mind,
resonant brain colon and how

947
01:14:26,280 --> 01:14:30,600
each brain makes mind.
Because there I I work really

948
01:14:30,600 --> 01:14:37,120
hard to write a self-contained
and non-technical synthesis and

949
01:14:37,120 --> 01:14:41,920
overview of, and I work in many
different areas, as well as to

950
01:14:42,720 --> 01:14:45,920
bring together and try to
clarify the meaning of the work

951
01:14:45,920 --> 01:14:48,680
of really hundreds of other
scientists.

952
01:14:48,680 --> 01:14:51,520
So but.
As we might have.

953
01:14:51,520 --> 01:14:56,080
Mentioned last time, you know we
are talking about this and this

954
01:14:56,080 --> 01:14:59,600
is one of the hard things to
understand in the world.

955
01:14:59,600 --> 01:15:04,200
So nothing that I would write
about it I hope would be

956
01:15:05,200 --> 01:15:09,440
trivial, but I hope it's you
could see oh he's writing

957
01:15:09,440 --> 01:15:12,760
clearly.
I just have to stop and think

958
01:15:12,760 --> 01:15:17,600
about what he just wrote.
And one reason I have over 600

959
01:15:17,600 --> 01:15:26,600
colour figures is to help people
to visualize the concepts that

960
01:15:26,600 --> 01:15:31,000
the words are trying to express.
Because until you can get a

961
01:15:31,000 --> 01:15:35,720
picture in your mind, it's often
hard to know what the hell

962
01:15:35,720 --> 01:15:38,560
someone's talking about.
And it's not only me, it's

963
01:15:38,600 --> 01:15:46,800
anything.
So yeah, Steve talked to me

964
01:15:46,800 --> 01:15:49,960
about.
One of the one of the other very

965
01:15:50,360 --> 01:15:54,320
leading theories of
consciousness which is Global

966
01:15:54,320 --> 01:15:58,000
Neuronal workspace.
What are your views on that

967
01:15:58,040 --> 01:16:02,240
theory of consciousness?
Well.

968
01:16:03,400 --> 01:16:10,280
I I'm not going to give a.
A professional review.

969
01:16:10,280 --> 01:16:15,440
Like you would for a journal
article, I'm blocking on who's I

970
01:16:15,440 --> 01:16:17,880
know.
The very nice fellow who

971
01:16:18,280 --> 01:16:20,760
promotes it.
What is his name but not bars?

972
01:16:21,920 --> 01:16:25,240
Yeah, I know.
Bernie bars, he's very nice guy

973
01:16:25,240 --> 01:16:28,560
and he's very dedicated and
sincere.

974
01:16:31,040 --> 01:16:35,200
Just check what his predictive
and explanatory range is.

975
01:16:35,200 --> 01:16:41,440
That's all I could say.
I mean, it's not for me to try

976
01:16:41,440 --> 01:16:43,440
to give a review of Bernie's
work.

977
01:16:43,520 --> 01:16:45,920
You should ask Bernie to review
his work.

978
01:16:46,640 --> 01:16:49,000
I think it's.
Always intriguing to see where I

979
01:16:49,000 --> 01:16:51,440
mean you guys either align or
disagree.

980
01:16:51,640 --> 01:16:53,920
It's fascinating for
particularly for the audience to

981
01:16:53,920 --> 01:16:57,560
kind of get a get a grasp of
where you guys diverge or

982
01:16:57,560 --> 01:17:01,000
intersect.
Well, I could discuss.

983
01:17:01,000 --> 01:17:05,480
If Bernie had an explanation of
a certain fact and.

984
01:17:05,480 --> 01:17:06,960
I thought it.
Was correct.

985
01:17:06,960 --> 01:17:09,560
I'd say yeah, I agree.
But if I thought it was

986
01:17:09,560 --> 01:17:12,240
incorrect, I'd say, well, I
would explain it as follows.

987
01:17:12,240 --> 01:17:17,400
That I can do but to give some
holistic way, hand waving

988
01:17:17,960 --> 01:17:20,800
evaluation of Bernie's hard
work.

989
01:17:20,800 --> 01:17:26,360
No, I I I won't play that game
if I don't think it's

990
01:17:26,360 --> 01:17:30,880
constructive.
If people find value in reading

991
01:17:30,880 --> 01:17:32,640
Bernie's work, they should read
it.

992
01:17:33,520 --> 01:17:36,280
If there are still questions
they'd like answered and they

993
01:17:36,280 --> 01:17:40,200
can find some of those questions
given more complete answers in

994
01:17:40,200 --> 01:17:41,800
my work, they should read my
book.

995
01:17:43,160 --> 01:17:44,840
There is a.
There is.

996
01:17:45,160 --> 01:17:45,240
A.
A.

997
01:17:45,720 --> 01:17:48,240
Section within the book where
you do discuss it and and the

998
01:17:48,240 --> 01:17:52,000
fact that that theory sort of
does provide a little bit more

999
01:17:52,000 --> 01:17:54,120
information here when you
compare it to the other ones

1000
01:17:54,120 --> 01:17:56,520
that we briefly discussed.
Oh yeah, Bernie.

1001
01:17:56,560 --> 01:17:58,560
Bernie.
Is is more serious?

1002
01:17:58,960 --> 01:18:03,080
I think.
OK, OK.

1003
01:18:03,160 --> 01:18:07,360
Let's let's you know.
I'd like to leave it at that,

1004
01:18:07,360 --> 01:18:09,800
really.
So what if Summit was that?

1005
01:18:10,200 --> 01:18:13,160
Was that one of the questions
some what someone wanted to

1006
01:18:13,440 --> 01:18:14,400
comment?
I haven't yet.

1007
01:18:14,440 --> 01:18:16,400
Gotten to those well, get you
better.

1008
01:18:16,400 --> 01:18:20,360
Get to that because it's an hour
and a half in and they can go up

1009
01:18:20,360 --> 01:18:22,760
to two hours or so, but let's
go.

1010
01:18:23,760 --> 01:18:27,800
So one of my friends actually
asked this question, this

1011
01:18:27,800 --> 01:18:30,000
question, this first question
one of my friends asked us.

1012
01:18:30,640 --> 01:18:34,880
He wants to remain UN unnamed
but he wants to know at what.

1013
01:18:35,080 --> 01:18:40,880
So let me just read this.
At what point?

1014
01:18:41,240 --> 01:18:43,880
Would, no.
Sorry, I just missed.

1015
01:18:43,920 --> 01:18:46,000
OK.
At what point would Professor

1016
01:18:46,200 --> 01:18:53,040
Grossberg delineate between 0
conscious experience and

1017
01:18:53,040 --> 01:18:57,080
conscious experience?
Are all conscious experiences

1018
01:18:57,680 --> 01:19:00,360
considered to be resonance
states in that regard?

1019
01:19:01,800 --> 01:19:10,400
Well, you know, later in my book
I I, I talk about quite a few

1020
01:19:10,400 --> 01:19:16,600
mental disorders.
And for example, without talking

1021
01:19:16,600 --> 01:19:23,040
about parametric properties of
behavioral symptoms and the

1022
01:19:23,040 --> 01:19:27,480
mechanisms that caused them and
what has gone wrong there in

1023
01:19:27,480 --> 01:19:31,000
altering consciousness.
You know, if you don't have a

1024
01:19:31,000 --> 01:19:35,400
sufficiently sustained and
energetic adaptive resonance

1025
01:19:36,080 --> 01:19:41,480
that is resonating with.
Either.

1026
01:19:41,480 --> 01:19:47,160
External stimuli or internal
memory representations.

1027
01:19:47,160 --> 01:19:51,040
It won't get to consciousness.
You know what?

1028
01:19:51,040 --> 01:19:55,920
I'm blocking on his name now.
Oh, he does very nice work, you

1029
01:19:55,920 --> 01:19:59,560
know.
Oh, I talk about a little in my

1030
01:19:59,560 --> 01:20:08,600
book where, you know, usually
the stimulation our senses get

1031
01:20:08,600 --> 01:20:15,080
by the time we're consciously
aware of it can be 150 to 300

1032
01:20:15,080 --> 01:20:18,360
milliseconds later.
And.

1033
01:20:20,440 --> 01:20:26,320
That's partly.
Because in addition to the all

1034
01:20:26,320 --> 01:20:32,280
the pre processing stages you
then have to activate resonating

1035
01:20:32,280 --> 01:20:38,960
circuits that have to resonate
for a sufficiently sustained and

1036
01:20:38,960 --> 01:20:42,520
energetic interval before it
becomes conscious.

1037
01:20:43,000 --> 01:20:47,640
So anything that prevents that
will not become conscious.

1038
01:20:48,640 --> 01:20:50,760
And there are many ways it can
be prevented.

1039
01:20:56,400 --> 01:20:58,560
Yeah, your work.
I mean, you clearly do.

1040
01:20:58,920 --> 01:21:01,040
And in your work, you're clear
also, but you address the fact

1041
01:21:01,040 --> 01:21:04,000
that not not all resonance
states are conscious states, but

1042
01:21:04,000 --> 01:21:06,560
conscious states are always
resident states.

1043
01:21:10,040 --> 01:21:14,040
Yes, Not all resonance states
are conscious and I give

1044
01:21:14,040 --> 01:21:17,920
examples of that.
For example, I mentioned grid

1045
01:21:17,920 --> 01:21:23,200
cells and play cells will enter
rhino hippocampal resonances

1046
01:21:23,200 --> 01:21:28,880
which support the stable
learning, stable and coordinated

1047
01:21:28,880 --> 01:21:34,840
learning of grid and play.
Cell receptor fields are not

1048
01:21:34,840 --> 01:21:39,920
conscious.
They are not linked to internal

1049
01:21:39,920 --> 01:21:46,680
or external sources of of
sensory experience.

1050
01:21:49,120 --> 01:21:54,200
Not directly.
You know, for example, grid

1051
01:21:54,200 --> 01:22:00,560
cells are sensitive to linear
motions and rotational motions,

1052
01:22:01,200 --> 01:22:08,520
but those sensors aren't
designed to support qualia, and

1053
01:22:08,520 --> 01:22:12,000
so you know, there's just no
nothing.

1054
01:22:12,000 --> 01:22:14,200
Like a conscious?
Awareness there.

1055
01:22:14,920 --> 01:22:18,200
There are inputs, but the inputs
are very low level.

1056
01:22:20,640 --> 01:22:25,960
Now it's another matter entirely
if you try to link the spatial

1057
01:22:25,960 --> 01:22:29,960
representations that are learned
in grid and play cells with

1058
01:22:30,800 --> 01:22:38,560
information like optic flow
visual cues that are being

1059
01:22:38,760 --> 01:22:43,480
synthesized when you navigate.
So you use combinations of

1060
01:22:43,480 --> 01:22:47,800
visual and motor information to
know where you are.

1061
01:22:47,800 --> 01:22:52,960
And then if you suddenly in the
dark, you use path integration

1062
01:22:52,960 --> 01:22:55,960
information.
That's what the information

1063
01:22:55,960 --> 01:23:00,560
about the linear and angular
movement is all about.

1064
01:23:00,600 --> 01:23:04,160
Path integration.
You're integrating how far these

1065
01:23:04,160 --> 01:23:08,880
senses think you've gone.
That's your ground truth and.

1066
01:23:08,880 --> 01:23:13,320
My.
PhD student Bill Gnad and I

1067
01:23:14,120 --> 01:23:25,360
developed a rather comprehensive
animat model of how, for

1068
01:23:25,360 --> 01:23:31,480
example, how an animat would,
under visual guidance, learn.

1069
01:23:33,320 --> 01:23:43,720
To.
Efficiently acquire a a food

1070
01:23:43,720 --> 01:23:49,760
reward, say that's in a maze.
You know how you would first you

1071
01:23:49,760 --> 01:23:54,920
would just be randomly exploring
the maze, you know that would be

1072
01:23:55,360 --> 01:24:02,160
endogenous exploratory behavior.
And then how that as you explore

1073
01:24:02,160 --> 01:24:08,360
it, how that is transformed into
an efficient goal oriented

1074
01:24:09,040 --> 01:24:13,960
series of actions to efficiently
acquire the goal in some distal

1075
01:24:14,200 --> 01:24:17,760
part of the maze?
And there we do.

1076
01:24:17,760 --> 01:24:23,520
Combine the visual and the path
integration information to help

1077
01:24:24,160 --> 01:24:28,960
learn how to solve that problem.
I forget what we call the model.

1078
01:24:28,960 --> 01:24:35,960
It was a oh the sovereign model,
sovereign for self organizing.

1079
01:24:38,400 --> 01:24:42,400
Visual.
Expectation you know one of the

1080
01:24:42,400 --> 01:24:49,440
rates sovereign maybe I can
solver and I think that Bill

1081
01:24:49,440 --> 01:24:52,000
thought of this one.
I thought, hey, that's not bad

1082
01:24:53,000 --> 01:24:54,440
self.
Organizing vision.

1083
01:24:54,440 --> 01:24:58,200
Expectation, resonance, and on
and on.

1084
01:24:58,200 --> 01:25:01,720
I can't even remember what the
other letters stand for, but it

1085
01:25:01,720 --> 01:25:07,160
is an acronym that captures the
essence of what the

1086
01:25:07,160 --> 01:25:10,200
architecture's doing.
And I say architecture because

1087
01:25:10,200 --> 01:25:20,760
not just a model.
It's a very, you know, you know,

1088
01:25:22,040 --> 01:25:27,160
sparse version of a full animat.
It doesn't have higher

1089
01:25:27,160 --> 01:25:29,760
cognition, but it has working
memory.

1090
01:25:30,520 --> 01:25:36,320
You know, it can learn
sequential action, etcetera,

1091
01:25:36,320 --> 01:25:40,960
etcetera.
And there you know the design.

1092
01:25:40,960 --> 01:25:42,920
Of working memory.
I don't think we talked much

1093
01:25:42,920 --> 01:25:46,080
about that.
But you know, you can do derive

1094
01:25:46,080 --> 01:25:50,800
all working memories from a
couple of simple postulates.

1095
01:25:52,200 --> 01:25:55,800
Both having to do with.
Stable learning it's.

1096
01:25:55,800 --> 01:25:58,280
Not surprisingly, but.
This is stable learning of

1097
01:25:58,280 --> 01:26:02,520
sequences, so even though in a
working memory it would be like

1098
01:26:03,440 --> 01:26:07,520
you know to have remember the
following series of letters

1099
01:26:07,520 --> 01:26:12,280
528-8953.
And you know you can repeat.

1100
01:26:12,280 --> 01:26:17,800
It back to me 528-8953, but if I
distract you and say, hey,

1101
01:26:17,840 --> 01:26:21,520
repeat it back to me, you can't
because it's in a short term,

1102
01:26:21,520 --> 01:26:27,840
temporary working memory buffer.
You know when computer science

1103
01:26:27,840 --> 01:26:32,120
algorithms sometimes call it a
blackboard, but this is more

1104
01:26:32,120 --> 01:26:37,600
than a blackboard, This is a
self organizing blackboard and.

1105
01:26:37,640 --> 01:26:41,360
One of the key.
Issues here is how do you know

1106
01:26:41,360 --> 01:26:45,400
which subsequence of all the
sequences you've just

1107
01:26:45,400 --> 01:26:48,720
experienced is predicted in a
given context?

1108
01:26:50,160 --> 01:26:53,520
And you know the.
Theory gives a solution to that

1109
01:26:53,520 --> 01:26:59,120
problem and what I'm sorry, you
were you sorry.

1110
01:26:59,120 --> 01:27:02,280
Continues to.
Well, well, and you know you

1111
01:27:02,280 --> 01:27:04,680
can.
See immediately there are there

1112
01:27:04,680 --> 01:27:09,320
are issues.
Let's say I have already learned

1113
01:27:09,320 --> 01:27:16,080
the word my and I've learned the
word self and in.

1114
01:27:16,080 --> 01:27:19,120
Particular I've learned.
Recognition categories of my and

1115
01:27:19,120 --> 01:27:22,360
self but.
Now for the first time.

1116
01:27:22,360 --> 01:27:27,280
In working memory, I represent
myself a new word with a new

1117
01:27:27,280 --> 01:27:32,200
meaning.
First problem, why doesn't

1118
01:27:32,800 --> 01:27:42,040
adding self after my undermine
the previously learned inputs to

1119
01:27:42,040 --> 01:27:46,760
the my and self category?
But the second problem is how do

1120
01:27:46,760 --> 01:27:48,840
you learn a new category for
myself?

1121
01:27:49,480 --> 01:27:53,440
Given you have two perfectly
good categories, my and self,

1122
01:27:53,920 --> 01:27:58,680
that have already learned, how
do you overcome the salience

1123
01:27:58,680 --> 01:28:03,160
that have been known to self
organize a larger grouping?

1124
01:28:03,160 --> 01:28:06,440
That's unknown.
And of course, if you couldn't

1125
01:28:06,440 --> 01:28:09,640
do this, you couldn't learn
language or dance or

1126
01:28:10,120 --> 01:28:15,520
navigational sequential skills
because we're talking here about

1127
01:28:15,680 --> 01:28:19,200
short words by and self.
The same problem arises with

1128
01:28:19,200 --> 01:28:21,800
individual phonemes grouped into
words.

1129
01:28:23,880 --> 01:28:30,960
And so, you know, my theory of
working memories off is a

1130
01:28:31,600 --> 01:28:36,560
computational solution to that
you know, based on very simple

1131
01:28:36,560 --> 01:28:40,880
principle.
Remarkably, that also was first

1132
01:28:40,880 --> 01:28:45,240
published in my human memory
paper in 78 when Communication,

1133
01:28:45,240 --> 01:28:51,280
Memory and Development came out.
It was a good year and and one

1134
01:28:51,280 --> 01:28:57,360
of the reasons I got into it was
because it often fails.

1135
01:28:59,280 --> 01:29:02,160
You know you might.
Not know, but there was a.

1136
01:29:02,160 --> 01:29:04,080
Let me give you the simplest
example of it.

1137
01:29:04,080 --> 01:29:08,400
I was interested more in verbal
learning from when I was a boy,

1138
01:29:08,400 --> 01:29:16,520
but but did you ever hear George
Miller's The Magical #7 ± 2?

1139
01:29:18,400 --> 01:29:21,320
Well, George.
Miller was the person who

1140
01:29:21,320 --> 01:29:23,200
introduced the notion of a
chunk.

1141
01:29:24,320 --> 01:29:29,320
And he basically.
Showed that most people, if you

1142
01:29:29,320 --> 01:29:35,560
tell them a series of numbers or
letters or whatever, they can't

1143
01:29:35,680 --> 01:29:40,080
repeat it right back to you
without learning.

1144
01:29:41,400 --> 01:29:45,600
Well, without actively trying to
learn if the sequence is more

1145
01:29:45,600 --> 01:29:52,000
than five to maybe 9 depending
on the person units, but.

1146
01:29:52,000 --> 01:29:57,560
Then what he showed.
About chunks is that you know

1147
01:29:57,560 --> 01:30:01,120
you could do that for much
higher level chunks.

1148
01:30:03,160 --> 01:30:06,800
You know, like let's.
Say you're controlling the

1149
01:30:06,800 --> 01:30:09,640
movements of a dance and you
know each movement.

1150
01:30:09,640 --> 01:30:15,640
You're, you know, professional
bell ballet dancer, and you can

1151
01:30:15,640 --> 01:30:21,040
do all the individual movements.
And now you know George Bell and

1152
01:30:21,040 --> 01:30:26,600
Shane is teaching the new dance.
Well, you have to be able to put

1153
01:30:26,600 --> 01:30:31,120
that sequence of movements into
working memory, where each of

1154
01:30:31,120 --> 01:30:37,480
the items in working memory is a
chunk of a familiar dance

1155
01:30:37,480 --> 01:30:41,400
gesture.
And so that he realized you

1156
01:30:41,400 --> 01:30:48,560
could have, you know, sequences
of chunks creating another chunk

1157
01:30:50,200 --> 01:30:52,040
and you could get higher and
higher.

1158
01:30:52,040 --> 01:30:56,760
And that's how we learn so many
of the higher order things,

1159
01:30:56,760 --> 01:31:01,520
because we chunked all the lower
order stuff and automated it so

1160
01:31:01,520 --> 01:31:05,320
we don't have to pay focal
attention to things that are

1161
01:31:05,320 --> 01:31:08,680
already chunked.
They more or less can be done

1162
01:31:08,680 --> 01:31:13,760
under very much less oversight.
Anyway.

1163
01:31:13,760 --> 01:31:20,200
So that's what this theory is
about, how you get this

1164
01:31:20,200 --> 01:31:24,120
chunking.
Really by?

1165
01:31:24,120 --> 01:31:30,400
Solving the myself problem by in
a stable way.

1166
01:31:30,480 --> 01:31:34,760
It's sort of like the stability
plasticity dilemma solved for

1167
01:31:34,760 --> 01:31:41,400
sequence learning, but that was
too far afield, maybe.

1168
01:31:42,120 --> 01:31:46,680
But it did get a new IT got a
new information and it wasn't.

1169
01:31:47,080 --> 01:31:48,520
Oh, I was talking about
Sovereign.

1170
01:31:48,520 --> 01:31:53,240
You need that to learn sequences
of terms in sovereign.

1171
01:31:55,400 --> 01:31:57,080
Yeah.
OK.

1172
01:31:57,080 --> 01:31:59,200
So the next question is.
Is from YouTube.

1173
01:31:59,680 --> 01:32:05,200
It's by Extazy I.
Don't know if I'm not in.

1174
01:32:05,520 --> 01:32:10,880
The at all different functional
different functional modalities

1175
01:32:11,320 --> 01:32:15,040
have been proposed to explain
the emergence of qualia from

1176
01:32:15,040 --> 01:32:18,680
physical properties under the
given ART framework.

1177
01:32:19,080 --> 01:32:22,520
How would residents, even in
principle, explain the

1178
01:32:22,520 --> 01:32:24,920
perception of a qualitative
state?

1179
01:32:27,960 --> 01:32:30,200
I'm not sure what a qualitative
state is.

1180
01:32:30,200 --> 01:32:33,280
I don't mean to be perverse.
I mean, the first thing that

1181
01:32:33,280 --> 01:32:35,480
comes to my mind, of course, is
that.

1182
01:32:37,200 --> 01:32:40,520
We have to.
Ask ourselves what flavor of

1183
01:32:40,520 --> 01:32:43,640
what we're talking about.
You know the category learning

1184
01:32:43,640 --> 01:32:46,120
stuff.
As I had briefly reviewed last

1185
01:32:46,120 --> 01:32:49,680
time, it's about feature
category resonances.

1186
01:32:50,360 --> 01:32:54,080
But if you're talking about
experiences from the external

1187
01:32:54,080 --> 01:32:58,920
world, let's say visual
experience, what?

1188
01:32:58,920 --> 01:33:01,120
You're often.
Conscious of is the surface

1189
01:33:01,160 --> 01:33:07,280
route resonance, which is a
conscious seeing and if you

1190
01:33:07,280 --> 01:33:11,440
synchronize surface routing,
feature category resonances, you

1191
01:33:11,440 --> 01:33:17,000
know and see about the object or
event and then the surface

1192
01:33:17,000 --> 01:33:22,320
shroud resonance via posterior
parietal cortex can control

1193
01:33:23,520 --> 01:33:26,720
actions which we've learned in
response to that combination of

1194
01:33:26,720 --> 01:33:29,880
events.
But now I didn't understand the

1195
01:33:29,880 --> 01:33:32,360
last two words there.
I don't know what they mean.

1196
01:33:33,280 --> 01:33:37,080
What would a place to work in
qualitative state is basically

1197
01:33:37,080 --> 01:33:39,720
referring to?
Qualia that qualia like state.

1198
01:33:41,440 --> 01:33:44,920
Well, I just commented on.
That yeah, you know you have you

1199
01:33:44,920 --> 01:33:49,120
have you have surface route
resonance you have stream shroud

1200
01:33:49,120 --> 01:33:52,520
resonances.
They're not the same as basic

1201
01:33:52,520 --> 01:33:59,480
category learning.
And they and when I hear and see

1202
01:34:00,000 --> 01:34:04,040
and know things about you,
you're a coordinated

1203
01:34:04,040 --> 01:34:12,880
synchronizations of surface,
route, stream, shroud, feature

1204
01:34:12,880 --> 01:34:16,240
category and to the extent of
which you're processing

1205
01:34:16,240 --> 01:34:19,760
sequences, you know their item
list, resonances responding to

1206
01:34:19,760 --> 01:34:24,560
all this 'cause that's where you
get understanding of speech and

1207
01:34:24,560 --> 01:34:26,840
language.
So there are all these

1208
01:34:26,840 --> 01:34:31,480
resonances that are being
coordinated quite wonderfully.

1209
01:34:34,080 --> 01:34:36,880
And you know you have.
Resonance in recent resonance in

1210
01:34:36,880 --> 01:34:43,960
recent so as as our visual
representations of a momentary

1211
01:34:44,560 --> 01:34:49,440
visual experiences reset by your
movement to what have you.

1212
01:34:50,080 --> 01:34:55,560
And I have another frame and so
I have a sequence of these, you

1213
01:34:55,560 --> 01:34:57,720
know.
Likewise, we're updating all our

1214
01:34:57,720 --> 01:35:01,760
working memories because the
sequential information that's

1215
01:35:01,760 --> 01:35:06,520
forming the context of is
changing.

1216
01:35:06,920 --> 01:35:14,160
One of my articles, you know, I
try to bring together a lot of a

1217
01:35:14,160 --> 01:35:22,720
lot of these ways of thinking in
an article that I I think that I

1218
01:35:22,720 --> 01:35:33,120
publish it in 2019-2020.
I it's an article that starts.

1219
01:35:34,400 --> 01:35:38,840
Well, I think it it's.
One of the later, maybe it's.

1220
01:35:40,680 --> 01:35:50,240
One of the latest.
Chapters in my book Let me do

1221
01:35:50,240 --> 01:35:52,880
you have the chap, the names in
front of you By chance?

1222
01:35:54,040 --> 01:35:58,200
Let me Let me let me try to
search for.

1223
01:36:00,880 --> 01:36:04,440
It because it's important.
That I make this comment.

1224
01:36:04,440 --> 01:36:12,680
Let me OK, I'll go to my OK now
let me see.

1225
01:36:15,280 --> 01:36:18,240
Oh, I have to turn off airplane
mode.

1226
01:36:18,920 --> 01:36:22,440
That was to stop me from getting
bothered.

1227
01:36:23,320 --> 01:36:28,880
Airplane mode OK.
I'll be there in a minute, I.

1228
01:36:28,960 --> 01:36:31,280
Have No Fear, it's fine.
I'm just coming these other.

1229
01:36:31,840 --> 01:36:46,200
Questions.
OK, I think this is.

1230
01:36:46,200 --> 01:36:48,920
It.
As a list of the chapter.

1231
01:36:48,920 --> 01:36:55,880
Titles on the Oxford listing.
Oops, I hit the wrong thing.

1232
01:36:56,440 --> 01:36:57,960
Damn.
OK.

1233
01:37:03,200 --> 01:37:04,560
OK.
Let me see.

1234
01:37:04,560 --> 01:37:05,640
OK.
OK.

1235
01:37:05,640 --> 01:37:14,360
Yeah.
Yeah, yeah, yeah.

1236
01:37:14,360 --> 01:37:20,720
It was chapter 14 How prefrontal
cortex works.

1237
01:37:23,640 --> 01:37:26,320
Colon Cognitive.
Working memory, planning and

1238
01:37:26,320 --> 01:37:32,680
emotion can jointly achieve
valued goals.

1239
01:37:34,120 --> 01:37:41,400
And yeah, sorry, Steve, my, my
copy.

1240
01:37:41,400 --> 01:37:42,560
Of the book isn't in this
office.

1241
01:37:44,600 --> 01:37:45,480
No, it's fine.
I'm.

1242
01:37:45,480 --> 01:37:50,880
I'm looking.
At it but but yeah and I'm I'm

1243
01:37:51,880 --> 01:37:57,920
it's not I have the abstract and
the keywords here but.

1244
01:37:57,920 --> 01:38:00,960
It's let me.
Get the book one second, I'll

1245
01:38:01,000 --> 01:38:03,680
get it.
I have a copy in the next room.

1246
01:38:04,760 --> 01:38:07,760
Anyway, for people who haven't
seen the cover, this is the

1247
01:38:07,760 --> 01:38:12,360
cover and the background around
the brain is neon color

1248
01:38:12,360 --> 01:38:14,440
spreading.
If you look carefully at it,

1249
01:38:14,960 --> 01:38:18,800
you'll see the red or the blue
spreading out of their crosses,

1250
01:38:20,360 --> 01:38:24,160
'cause I thought of that, you
know as such an important

1251
01:38:24,160 --> 01:38:32,720
example of the complementarity
of boundaries and surfaces.

1252
01:38:33,600 --> 01:38:36,240
And let me go here.
OK, 5 something.

1253
01:38:38,080 --> 01:38:40,160
I want to do that artwork see.
What?

1254
01:38:40,160 --> 01:38:41,760
What?
Except for that aspect?

1255
01:38:43,680 --> 01:38:45,200
What is that?
The artwork.

1256
01:38:45,240 --> 01:38:46,800
Well, what?
How did you come up with the

1257
01:38:46,800 --> 01:38:48,760
with that as the idea for the
artwork?

1258
01:38:50,800 --> 01:38:52,960
ASA how did?
I come up with the idea.

1259
01:38:54,600 --> 01:39:06,600
Oh well, I wanted a cover that.
So I said what the book is.

1260
01:39:06,600 --> 01:39:12,840
About so you know the title is
on A Brain and.

1261
01:39:15,320 --> 01:39:19,640
The brain.
Is into hemifield and I fiddled

1262
01:39:19,640 --> 01:39:23,200
with trying to indicate the
complementarity of the

1263
01:39:23,200 --> 01:39:26,920
hemifields cause the water and
where streams and stuff like

1264
01:39:26,920 --> 01:39:29,400
that.
Other parts of the brain made it

1265
01:39:29,400 --> 01:39:32,200
too complicated, but so that's
it.

1266
01:39:32,200 --> 01:39:35,720
It's just brain, but neon color
spreading.

1267
01:39:36,360 --> 01:39:39,480
The spreading is an emergent
property that happens in our

1268
01:39:39,480 --> 01:39:42,880
mind.
It's a property of our conscious

1269
01:39:43,680 --> 01:39:48,200
visual awareness, and I thought
it would be nice to emphasize on

1270
01:39:48,200 --> 01:39:52,040
the cover.
It's about emergent properties.

1271
01:39:54,560 --> 01:40:03,800
And I'm trying.
I thought I Oh yes, yeah, yeah,

1272
01:40:07,560 --> 01:40:17,560
I Betsy Murray stimulated me to
write to make some of these

1273
01:40:17,560 --> 01:40:22,840
discoveries, cause Betsy told me
that they had all this wonderful

1274
01:40:23,480 --> 01:40:26,680
data in prefrontal cortex that
no one could explain.

1275
01:40:27,360 --> 01:40:32,560
And so she sent me the paper and
I realized that not only could I

1276
01:40:32,560 --> 01:40:36,200
explain it, but I predicted some
of it.

1277
01:40:36,200 --> 01:40:42,120
And you know, and they have you
know words like desirability and

1278
01:40:42,120 --> 01:40:46,760
availability, stuff like that,
which are good words for the

1279
01:40:47,400 --> 01:40:49,320
phenomena they were talking
about.

1280
01:40:49,320 --> 01:40:55,000
But you know a macro circuit
incomplete one of of the.

1281
01:40:55,000 --> 01:40:58,120
Predictive.
Adaptive resins theory I needed

1282
01:40:58,120 --> 01:41:01,480
for this.
I don't know if you could see.

1283
01:41:01,480 --> 01:41:07,400
That, but I couldn't put in the
basal ganglia or a number of

1284
01:41:07,400 --> 01:41:10,280
other things and those different
colors.

1285
01:41:10,280 --> 01:41:15,800
The red, green, what have you
are systems and.

1286
01:41:15,800 --> 01:41:19,840
So it just showed.
That like for prefrontal cortex,

1287
01:41:20,400 --> 01:41:29,520
I needed and and explained data
from 7 interacting parts of the

1288
01:41:29,720 --> 01:41:34,200
prefrontal cortex.
It's not a unitary thing it's a

1289
01:41:34,200 --> 01:41:40,360
complex organ and and then I
also in red I had some of the

1290
01:41:40,360 --> 01:41:46,080
main reinforcement learning kind
of things that and then I'm just

1291
01:41:46,080 --> 01:41:48,400
black and white.
I had some of the main vision

1292
01:41:48,400 --> 01:42:00,080
and spatial kind of things.
Anyway, I Roy you want me to.

1293
01:42:02,120 --> 01:42:03,440
Move.
I think the point I would.

1294
01:42:03,880 --> 01:42:11,760
The point was I was trying to
clarify that you know, the

1295
01:42:11,760 --> 01:42:18,480
prefrontal cortical work really
is a synthesis of a lot of work.

1296
01:42:21,720 --> 01:42:31,000
And I.
And I think, I think that things

1297
01:42:31,120 --> 01:42:33,920
really came together in a nice
way.

1298
01:42:38,520 --> 01:42:39,760
You know what a number of points
in.

1299
01:42:39,760 --> 01:42:43,520
My book, I point out you
shouldn't take for granted that

1300
01:42:43,520 --> 01:42:48,080
the next step could be taken.
And this happened to me.

1301
01:42:48,280 --> 01:42:52,120
Over and over again, how the
previous work sort of thrust me

1302
01:42:52,760 --> 01:42:55,840
into a new area where I knew
they were interacting with them,

1303
01:42:56,280 --> 01:42:58,840
and the same things with the
prefrontal cortical work.

1304
01:42:58,840 --> 01:43:04,280
So many parts of the brain are
interacting there to explain

1305
01:43:04,600 --> 01:43:07,920
really challenging quantitative
data.

1306
01:43:07,920 --> 01:43:14,080
Physiological data mostly, but.
You know it's all.

1307
01:43:14,080 --> 01:43:22,400
An accumulation of evidence.
And if you're a really good

1308
01:43:22,400 --> 01:43:27,680
theorist, you can weigh the
amount of evidence for this part

1309
01:43:27,680 --> 01:43:31,920
of that part of the other part.
You know where the weaknesses

1310
01:43:31,920 --> 01:43:37,720
are, where where you might have
variations on the theme that

1311
01:43:37,720 --> 01:43:42,560
don't undermine any of the
principles as you would expect

1312
01:43:43,160 --> 01:43:46,800
for species specific variations
of the design.

1313
01:43:48,680 --> 01:43:54,960
And you also know what you can't
explain and and that keeps you

1314
01:43:54,960 --> 01:44:00,600
up nice until you can.
So this is not, this is not

1315
01:44:00,600 --> 01:44:03,920
finished.
But I think if someone wanted to

1316
01:44:03,920 --> 01:44:08,920
get into an overview of some of
my work after this discussion,

1317
01:44:08,920 --> 01:44:13,560
and maybe looking at a lecture
of mine on my web, you might

1318
01:44:13,960 --> 01:44:17,000
look at my magnum opus And I
wanted to emphasize one thing.

1319
01:44:18,720 --> 01:44:22,400
It's a long book.
After you read the preface in

1320
01:44:22,480 --> 01:44:27,080
introductory chapter one, I
wrote it so that you could jump

1321
01:44:27,080 --> 01:44:32,320
directly to any chapter that's
topic interested.

1322
01:44:32,320 --> 01:44:36,640
You don't have to read it all.
I don't expect even interested

1323
01:44:36,640 --> 01:44:39,200
people have the time or interest
to redraw.

1324
01:44:39,840 --> 01:44:43,880
The chapters are written
independently of each other and

1325
01:44:43,880 --> 01:44:50,080
so you know, if you wanted to
read more about art in the sense

1326
01:44:50,080 --> 01:44:53,760
of feature category resonance,
jump jump to chapter 5.

1327
01:44:55,240 --> 01:44:58,040
But if you wanted to read.
About prefrontal cortex, you'd

1328
01:44:58,040 --> 01:45:02,680
go to chapter 13 if you.
Wanted to know about.

1329
01:45:02,680 --> 01:45:05,880
Spatial navigation.
I think it was chapter 16.

1330
01:45:06,920 --> 01:45:07,920
Yes.
Do you want to?

1331
01:45:07,920 --> 01:45:12,560
Know about.
Visual perception go to the

1332
01:45:12,560 --> 01:45:17,360
first few chapters and so on.
Yeah, I I I really.

1333
01:45:17,360 --> 01:45:19,000
Enjoyed that aspect?
I said this the last time.

1334
01:45:19,000 --> 01:45:22,840
It's that that easily accessible
nature of the book, the way you

1335
01:45:22,840 --> 01:45:25,640
can just jump from chapter to
chapter without having a

1336
01:45:25,640 --> 01:45:28,240
preconceived idea of the
previous chapter, makes it very

1337
01:45:29,040 --> 01:45:31,960
accessible.
Steve, one last question, and

1338
01:45:31,960 --> 01:45:36,360
this one's from Facebook.
This is a funny one, Francina,

1339
01:45:38,200 --> 01:45:43,440
who resonates most in the
Grossberg Carpenter household.

1340
01:45:46,760 --> 01:45:50,120
Whoa.
Now this is getting very

1341
01:45:50,120 --> 01:45:53,400
personal.
Who resonates most with what?

1342
01:45:53,880 --> 01:45:55,240
I have no idea.
That's just the.

1343
01:45:55,400 --> 01:45:59,720
That's where the question ends.
Well, I was.

1344
01:45:59,840 --> 01:46:02,520
Meant to be funny and yet.
Also highlighted the fact that

1345
01:46:02,520 --> 01:46:04,160
you both are powerhouses in the
field.

1346
01:46:05,560 --> 01:46:08,280
Well, all I could say.
Is that?

1347
01:46:10,600 --> 01:46:12,680
GAIL Carpenter is the love.
Of my life.

1348
01:46:13,280 --> 01:46:15,760
We've been together for 1/2
century.

1349
01:46:19,080 --> 01:46:24,000
She has strict instructions that
she can't predecease me because

1350
01:46:24,000 --> 01:46:29,440
she's younger than I am.
We already spoke on the phone

1351
01:46:29,440 --> 01:46:32,600
earlier today.
I'm in Truro on Cape Garden.

1352
01:46:32,600 --> 01:46:37,240
She's back in Newton where we
have our main residence.

1353
01:46:38,120 --> 01:46:39,280
I'll be.
Talked to at.

1354
01:46:39,280 --> 01:46:47,720
Least 2-3 more times today,
she's a brilliant neural network

1355
01:46:47,720 --> 01:46:54,840
modeler.
She's done foundational work as

1356
01:46:54,840 --> 01:47:00,040
well as really doing some of the
best work on large scale

1357
01:47:00,040 --> 01:47:04,720
applications.
Like, she did really important

1358
01:47:04,720 --> 01:47:13,360
work on remote sensing, on
medical database prediction, and

1359
01:47:13,360 --> 01:47:17,920
one of the things she did that I
think should be studied more.

1360
01:47:17,920 --> 01:47:25,080
And I think she'd agree.
In a remote sensing.

1361
01:47:25,080 --> 01:47:29,080
Context where you can have
multiple observers.

1362
01:47:30,040 --> 01:47:34,640
They're each looking at
different pieces of a remotely

1363
01:47:34,640 --> 01:47:40,920
sensed terrain, maybe with
different combinations of

1364
01:47:40,920 --> 01:47:43,200
sensors.
They.

1365
01:47:43,200 --> 01:47:47,360
Will.
Create their own personal labels

1366
01:47:47,920 --> 01:47:50,200
for what they're trying to
describe.

1367
01:47:52,240 --> 01:47:57,720
One person might say water, one
person might say pond, Another

1368
01:47:57,720 --> 01:48:01,640
person might say lake for the
very same object.

1369
01:48:02,320 --> 01:48:07,360
And they only do this for a
subset, usually a pretty small

1370
01:48:07,360 --> 01:48:16,320
subset of the remotely sensed
terrain.

1371
01:48:16,320 --> 01:48:18,680
Because it's expensive to get
ground truth.

1372
01:48:19,160 --> 01:48:21,040
Someone has to be running around
down there.

1373
01:48:22,400 --> 01:48:23,800
How?
Do.

1374
01:48:23,800 --> 01:48:28,480
You input this kind of
information which may be

1375
01:48:31,200 --> 01:48:37,840
incomplete, probabilistic,
sometimes self contradictory and

1376
01:48:37,840 --> 01:48:43,400
out of it, automatically learn a
cognitive hierarchy of rules,

1377
01:48:44,360 --> 01:48:47,000
including the confidence you
have in the links in the

1378
01:48:47,000 --> 01:48:51,160
hierarchy, whereas you get
higher and higher in the in the.

1379
01:48:54,160 --> 01:48:56,240
Higher and higher in the.
Rules.

1380
01:48:56,680 --> 01:49:02,160
They get more and more abstract.
I think that is a foundational

1381
01:49:03,760 --> 01:49:08,240
contribution, really quite a
wonderful one that needs a lot

1382
01:49:08,240 --> 01:49:12,920
more work, you know?
GAIL and I are.

1383
01:49:12,920 --> 01:49:19,880
Both no longer teaching.
We're both emeritus and it

1384
01:49:19,880 --> 01:49:24,920
doesn't mean we're brain dead.
I just published my last paper,

1385
01:49:25,440 --> 01:49:29,360
I think a few weeks ago, and I'm
writing another book.

1386
01:49:29,360 --> 01:49:33,480
But but you know, Gail's not
going to work on that project

1387
01:49:33,480 --> 01:49:37,120
again.
And that project could really be

1388
01:49:37,120 --> 01:49:41,280
very interesting, especially if
you're in some kind of a

1389
01:49:42,840 --> 01:49:49,680
technology AI lab that's a kind
of project for Google could

1390
01:49:49,680 --> 01:49:56,320
really sink its teeth into.
'Cause you could do it for.

1391
01:49:56,320 --> 01:49:59,720
The whole world and.
You know, part of it.

1392
01:50:00,040 --> 01:50:03,440
We got into it cause many years
ago.

1393
01:50:03,440 --> 01:50:08,360
I gave a lecture at the Optical
Society meeting about some of

1394
01:50:09,080 --> 01:50:12,840
the vision modeling work and
there were several program

1395
01:50:12,840 --> 01:50:17,920
managers from MIT Lincoln Lab
there which is one of the great

1396
01:50:18,040 --> 01:50:22,720
sensor houses in the world.
You know they've laid on multi

1397
01:50:22,720 --> 01:50:28,280
spectral IR synthetic habituator
and so on and very much

1398
01:50:28,280 --> 01:50:34,000
pixelated data with you know
very intense pixels and drop out

1399
01:50:34,000 --> 01:50:39,400
pixels and a lot of noise.
And they realize that the kind

1400
01:50:39,400 --> 01:50:45,360
of work even then that we were
doing in vision modeling could

1401
01:50:45,360 --> 01:50:48,520
help them process their sensor
data.

1402
01:50:48,520 --> 01:50:54,160
And in fact there was a very
active project at Lincoln Live

1403
01:50:54,160 --> 01:50:59,320
for a while doing that.
They also designed a robot, a

1404
01:50:59,320 --> 01:51:03,440
robot based on some of our ideas
and Sense Remoting control

1405
01:51:03,440 --> 01:51:05,440
course.
Some of the models I developed

1406
01:51:05,440 --> 01:51:10,240
with my students and platform
independent, they work with

1407
01:51:10,240 --> 01:51:16,000
wheels or legs or what have you.
Yeah, so.

1408
01:51:17,000 --> 01:51:21,920
So what more should I say about
my wife my?

1409
01:51:21,920 --> 01:51:24,320
Best friend?
The love.

1410
01:51:24,320 --> 01:51:27,480
Of my life.
The mother of a wonderful

1411
01:51:27,480 --> 01:51:30,840
daughter and we have wonderful
grandchildren.

1412
01:51:30,840 --> 01:51:34,360
We feel super lucky.
Super lucky.

1413
01:51:34,960 --> 01:51:37,200
I love the way your face.
Lights up when you talk about us

1414
01:51:37,480 --> 01:51:39,200
Steve.
Sorry for the personal question

1415
01:51:39,200 --> 01:51:41,920
but I thought it's it's quite
cool that you both such great

1416
01:51:41,920 --> 01:51:44,440
pioneers in this field and I
thought it would be a nice

1417
01:51:44,440 --> 01:51:47,800
question to ask from well, it
wasn't mine but the Rubio, but I

1418
01:51:47,800 --> 01:51:52,600
chose it well.
To sum it up, we've been a real

1419
01:51:52,600 --> 01:51:57,600
mom and pop show where I have
many projects without GAIL, she

1420
01:51:57,600 --> 01:52:03,560
many without me, and we've done
I think, at least 20 projects

1421
01:52:03,560 --> 01:52:05,200
together.
And, you know, they're sort of

1422
01:52:05,200 --> 01:52:10,120
like our scientific children.
Well, I I think it's absolutely.

1423
01:52:10,120 --> 01:52:12,200
Beautiful and keep up, keep up
the great work.

1424
01:52:12,480 --> 01:52:13,920
Steve.
Thank you again for joining me,

1425
01:52:13,920 --> 01:52:16,560
Sir.
I I really appreciate your round

1426
01:52:16,560 --> 01:52:22,720
two And you you've also written
a paper on on illusions that

1427
01:52:22,720 --> 01:52:25,160
I've that I find very
fascinating and I hope at some

1428
01:52:25,160 --> 01:52:27,840
point we can also dissect one of
those and and with that one it

1429
01:52:27,840 --> 01:52:30,360
will be far less philosophical
and a lot more scientific.

1430
01:52:30,360 --> 01:52:32,480
So I think you'll enjoy it a lot
more as well.

1431
01:52:33,560 --> 01:52:34,600
Yeah.
Well, I I love.

1432
01:52:34,600 --> 01:52:39,080
Studying especially Visual
illusions course.

1433
01:52:40,480 --> 01:52:43,960
You know it's.
Sort of like how very young

1434
01:52:43,960 --> 01:52:50,920
people can get excited by
mathematics.

1435
01:52:50,920 --> 01:52:53,960
Some of the hardest problems in
number theory you can say to any

1436
01:52:53,960 --> 01:52:57,920
child and then it takes Ferbmat
to solve it.

1437
01:53:00,560 --> 01:53:03,360
But visual illusions?
It's it's right there.

1438
01:53:03,360 --> 01:53:09,240
You're, it's in your face.
And the immediacy of it raises

1439
01:53:09,240 --> 01:53:13,160
questions of how do you see
anything?

1440
01:53:14,640 --> 01:53:17,840
Yeah, that's next step for
having me on.

1441
01:53:18,560 --> 01:53:21,880
And so this would be part.
This would be Part 2 of the

1442
01:53:21,880 --> 01:53:23,680
series.
Yes, definitely.

1443
01:53:24,560 --> 01:53:26,200
Thanks so much.
I enjoyed this.

1444
01:53:26,440 --> 01:53:28,120
Thank you so much, Steve.
I appreciate.

1445
01:53:28,160 --> 01:53:29,040
It very the.