Science Series 3: Dr Lisa Gabel / Neurology / Dyslexia / Mind Controlled Drones / Music & the Brain

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Welcome to another episode of
Come Together.

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And we're live.
Doctor Lisa Gabel, how are you?

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Welcome.
So thank you so much.

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Oh my gosh, I ruined it already.
Thank you so much for coming up.

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How are you?
I'm good.

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Thank you for inviting me.
Thank you so much for getting

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back to me so quickly and just
hopping on and I'm really,

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really excited, excited to talk
to you because you study two

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things that I think are
absolutely some of the most

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fascinating aspects of people,
which is psychology and

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neurology.
And I actually didn't know

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really the difference between
them for a little bit.

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I know that I'm sure neurology
sounding has a little bit more

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of a scientific basis.
I know that psychology tends to

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be a little bit more
observation.

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I mean it's people described it
as soft science, right?

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Or softer science?
They do, although I think some

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of the colleagues in psychology
would argue against.

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That.
So, so think of psychology as

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like behavior, cognition and
experience, right What is

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happening?
And think of neuroscience or

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neurology as how something is
happening.

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So brain structure, function,
biology.

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Neuroscience is actually a
culmination of the majority of

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the natural sciences.
It requires an understanding of

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physics and chemistry and
biology and psychology in order

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to try and understand the
connection between behavior and

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neural function.
Right, right.

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So you kind of as I imagine you
get a little, you definitely get

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a little bit of everything when
you study neurology, you get a

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little bit of the, you get a
little bit of everything like

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you just said.
And then you'd want to just have

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a little more of an intensive or
more concentrated perspective on

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the psychology side, I guess,
from your end.

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So from my end.
So my PhD is actually in

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Physiology and neurobiology, and
I have a master's in psychology

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and behavioral neuroscience.
So I've really, you know, gone

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from one end to the other.
So my interest actually is, is

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quite broad.
And I tend to study a lot of

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different things in a lot of
different ways because I tend to

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just follow whatever the
question is and then learn what

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I need to learn in order to
answer that question.

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So I think it's all important.
I that sounds super cool.

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I love that, especially because
I think that when you're

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starting with a question as
opposed to starting with an

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answer, then it gives you a lot
more space to be creative and to

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kind of play around with a lot
more, with a lot more in the

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playground.
You know, as opposed to just

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having to box yourself into
trying to find one particular

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solution that you hope to get.
Exactly.

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And there's, you know, there are
good reasons to, you know, be an

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expert in one thing and focus on
that because we need that.

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But a lot of science now is very
collaborative and very

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interdisciplinary or
multidisciplinary in order to

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answer like complex questions.
So I like sort of jumping down

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different rabbit holes and
seeing where it takes me.

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Yeah.
So, so how'd you get?

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So what was the first one of the
first issues that you're trying

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to kind of get answers to or
trying to understand?

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So actually the the students in
my lab, I have like 5 different

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research projects going on at
any one time.

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Some of them are related, some
of them are not related.

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So I study brain computer
interface with another professor

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in electrical and computer
engineering.

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His name is Yi Chung Yu.
He's phenomenal.

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We built that research program
from the ground up.

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Neither one of us had done it
before, but we saw a need and is

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a great way to bring our
students from engineering and

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neuroscience together toward a
common goal.

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But then I also study
neurodevelopmental disorders

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like seizure disorder or
dyslexia or autism.

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Dyslexia research is a really
big component of my lab right

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now.
We do both animal and human

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studies.
How does dyslexia manifest in an

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animal?
Answers that question a lot, and

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it's a great question because
mice don't read, you know?

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So how, how how?
Dyslexia and it is, you know,

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sort of a human feature.
But so if you take reading and

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you break it down into it's very
complex.

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Reading is very complex.
It requires phonological

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processing, visual processing,
auditory processing, working

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memory, so on and so forth.
Well, I can study each one of

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those things in an animal.
And there are different models

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of dyslexia based on, from a
neural perspective, either

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malformations in the brain that
are identified in humans,

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animals that have those
spontaneously developing, or

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more commonly genetics.
So there are certain genes

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associated with dyslexia.
We can modify those genes in an

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animal.
And then if you say you modify a

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gene and check the behaviors
between an animal that has the

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gene modified and that an animal
that doesn't, the behavior that

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is altered in the animal that
has the gene modified, then you

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start to look at the connection
between that gene and that

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behavior or that process.
And then we can translate what

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we see in the animal to humans.
So I also work with kids.

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Wow.
Yeah.

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How how comfortable or how often
or how many studies you have to

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do in an animal before you feel
like you're ready to take, you

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know, to observe a kid or do
take it to the next level.

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That isn't, that's an excellent
question, and it probably

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depends on whatever your line of
research is and and what you're

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doing.
I've been studying dyslexia in

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some form with an animal model
since I was a graduate student.

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So I've been at Lafayette
College now for 20 years.

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So I've been doing this for
quite some time.

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I won't tell you exactly how
old.

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Yeah.
So in my case there, I used a

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particular model of the
disorder.

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It was a particular disruption
in a gene called DCDC 2 in an

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animal.
And one of the tasks that I did,

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I described it to people as, you
know, on the back of the cereal

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boxes where they have the maze
and you have to get the mouse to

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the cheek.
It's very much like that.

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So we saw this really
interesting finding, whereas if

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you altered the gene, that
particular gene, the animal

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couldn't learn the task.
Wow, remember it?

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Or would it be able to actually
carry out the function?

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It could carry out the function,
but it wouldn't is behavior

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would sort of stay stable over
time.

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So if I put you in a maze, you
would probably take a

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considerable amount of time and
you would probably make some

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errors because you've never been
in it before, right?

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But then the second time you
were in the maze, you're like,

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OK, I've been here before and
you'll be a little bit faster

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and you'll make fewer errors,
and you get this nice little

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learning curve.
So the mice that had this

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genetic mutation, it was flat.
They never really learned the

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task.
So people would always ask me

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the question that you just asked
me.

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When I'd go to give talks,
they'd be like, well, how can

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you really say that?
You know, this is like human?

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And it's a fair enough question.
So I read a paper by a

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scientist's name.
I forgetting his first name.

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His last name is Shore.
So Professor Shore had created a

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virtual version of this
particular task, and he compared

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mice to humans, both males and
females.

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And I'm like, oh, that's really
interesting.

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So we created a virtual version
and we compared our college

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kids, 18 to 22 year olds with
mice and they had similar

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behaviors.
And I'm like, oh, OK.

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So then I went a little younger
and I did 8 to 12.

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And then Long story short, after
years of going back and forth, I

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started testing kids with and
without reading impairment to

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see whether or not kids with
reading impairment were impaired

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at this task.
And they are, which was

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interesting, especially since,
you know, in mice we control

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everything about their
environment, where they live,

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their genetics, everything.
Humans are not, you know that

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restricted, right?
They have a lot of experiences

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different, there are different
genes associated with dyslexia.

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So it could be a whole mix.
So I didn't actually expect to

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see anything.
And the fact that I did.

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Hey everyone real quick if
you're enjoying the show, click

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subscribe and rate the show. 5
stars helps a ton.

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Thanks so much.
And I consistently do.

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I even went to Germany and I
tested native German speaking

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children and children who are
multilingual at an International

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School and I always do the same
thing.

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If you have an impairment with
reading or impaired at this

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particular task, now we're
actually using it to identify

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kids with dyslexia before they
can read.

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That's really cool.
And I would imagine so are we

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misdiagnosing dyslexia as being
a reading disorder and it's

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really ability to retain this
kind of or at least from that

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gene, right, that like that
mouse gene that you described

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earlier where it wouldn't be
able to process the learning and

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have that learning curve, is
that not?

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Not necessarily reading.
So as a like I was saying

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before, reading is very complex,
right?

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So there's lots of processes
that underlie it.

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So you can have a child with
reading impairment and they have

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this set of challenges and you
could have another child's

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completely different set of
challenges.

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So it's not it, it's not that
it's not a reading disorder,

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it's that we were able to create
a task or use a task that could

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tap into the same neural
circuitry that is used for

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reading.
And then see whether see how

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that's operating.
Exactly.

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I see so cool.
Then what do you do if it's not?

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And what are some, what are some
potential treatments or some

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kind of breakthroughs that could
respond or, or if there aren't,

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then how do you recommend
someone with dyslexia learn, you

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know?
That's, that's a great question

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because so with my, with the
task that we do, we can identify

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kids who have a reading pair,
but I still can't tell you what

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the specific impairment is, just
that they haven't.

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So it's a nice way of
identifying kids early so that

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they can go and get the
additional testing, particularly

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if you are a non-native speaker.
So a lot of our trouble is when

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you have somebody who is an
English language learner, are

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they impaired at the task
because of the language barrier

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or are they paired at the task
because there's a reading

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deficit?
So if you can take that factor

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out of the equation, it can be
helpful.

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But there are lots of
interventions that have been

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developed that are quite
successful.

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The the challenge seems to be
getting the child help as soon

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as possible because the earlier
that the interventions are

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applied, the greater the success
rate.

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Sure, I imagine that'd be the
case.

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That makes a lot of sense.
I'm curious.

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And I mean, I don't expect to
know the answer.

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I'm just, I'm just thinking off
the cuff.

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But you know, I, I'm, I'm
Orthodox Jewish and so I am, I'm

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fluent in reading English,
obviously, and Hebrew.

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And the difference between
English and Hebrew from a

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reading perspective is enormous,
right.

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And I think there's a couple
other languages that go English

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is, I think left to right and
then Hebrews right to left and

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enormously context driven.
And so a lot of times I don't

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want no definitions of words
until I I'm able to identify the

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root or the context in which,
you know, it's, you know, it's

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just placed and the words around
it.

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And then and then I get it and,
and I may never even see the

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word again after that, you know,
like it might even be like a one

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time use or something weird like
that, as opposed to the English

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language, which I think requires
a different part of our brain.

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Have you noticed any difference
in terms of like you know,

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different languages that
dyslexia manifests?

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Yeah, so, you know, it's really
interesting and the the so in

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the United States we have a very
non term transparent language.

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English is very non transparent,
right.

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So there are exceptions to
rules.

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And this letter has this sound
in this condition, but not in

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that condition.
But there are other languages

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which are are completely
transparent.

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So Finnish is apparently not
that I know or speak Finnish.

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It's a very transparent
language.

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So the letter always has the
sound regardless of the context.

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Hopefully I am picking the right
language to describe that

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theory, but there.
So there's a continuum and then

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there's also Lobo graphic
languages which require images

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as opposed to let alphabetic
languages which are letters and

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sounds.
So that is actually one of the

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things that I was really curious
about because depending on the

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type of language too also
correlates with the incidence of

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reading impairment.
So and so try so when I'm

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studying this, one of the things
that I've really wanted to do is

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see how that type of language.
So whether you're Lobo graphic

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or whether you're very
transparent or non transparent

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00:13:23,240 --> 00:13:27,000
language has any influence on
the outcome of our study as and

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what influence that has on on
reading, which is why I went to

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00:13:31,000 --> 00:13:33,840
well, not the reason I went to
Germany, but why I did the study

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00:13:33,840 --> 00:13:37,040
in Germany, because their
language is more transparent

245
00:13:37,040 --> 00:13:39,480
than English.
And then I wanted to look at

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00:13:39,480 --> 00:13:41,640
children who come from different
language backgrounds.

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00:13:41,640 --> 00:13:45,680
So, you know, multilingual
children who might speak their

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00:13:45,680 --> 00:13:48,480
primary language might be
transparent and their and the

249
00:13:49,200 --> 00:13:53,160
another language that they speak
might be non transparent and how

250
00:13:53,160 --> 00:13:59,320
that impacts Long story short,
the the the task, the

251
00:13:59,320 --> 00:14:02,720
performance associated with
reading still holds regardless

252
00:14:02,720 --> 00:14:05,640
of the, you know, the level of
transparency of the language,

253
00:14:05,640 --> 00:14:08,720
which is interesting.
But I'm, I'm really curious

254
00:14:08,720 --> 00:14:12,480
whether or not logo graphic
languages which are more visual

255
00:14:12,480 --> 00:14:17,640
spatially needed would if the
outcomes would be different

256
00:14:17,720 --> 00:14:20,880
because the task IU news
absolutely requires visual

257
00:14:20,880 --> 00:14:24,680
spatial processing, right?
So I'm wondering if the degree

258
00:14:24,680 --> 00:14:27,880
of that and the degree in which
the language requires visual

259
00:14:27,880 --> 00:14:31,600
spatial processing, if they
would correlate highly in terms

260
00:14:31,600 --> 00:14:34,160
of performance.
So I don't have that answer yet.

261
00:14:34,520 --> 00:14:36,000
That's cool.
Well, when you do, we'll get

262
00:14:36,000 --> 00:14:40,960
back on another podcast, talk
about it because yeah, I love

263
00:14:40,960 --> 00:14:43,640
this stuff.
And, you know, and I'm always

264
00:14:43,640 --> 00:14:45,960
thinking about this.
I grew up, you know, I might,

265
00:14:45,960 --> 00:14:48,280
my, my grandfather taught my mom
Hebrew.

266
00:14:48,280 --> 00:14:51,600
My mom spoke to us, but a little
bit less profusely.

267
00:14:51,600 --> 00:14:53,840
And we're, you know, we're a
little bit less fluent and

268
00:14:53,840 --> 00:14:55,360
naturally really, as things kind
of go.

269
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And then my kids, you know, in
particular, like I'm really not

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00:14:59,240 --> 00:15:00,600
speaking a lot of Hebrew to them
at all.

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00:15:00,880 --> 00:15:07,680
And, you know, and my wife and I
went on our honeymoon to Italy

272
00:15:08,200 --> 00:15:09,400
or Greece.
We went to both.

273
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But in Greece, they told that
everyone speaks every, you know,

274
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several languages when you, when
you travel.

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And so we're, you know, we're
hanging out talking a couple of,

276
00:15:17,040 --> 00:15:21,760
of local business owners just at
a regular cafe or whatever, and

277
00:15:21,760 --> 00:15:23,400
they tell us a joke.
What do you speak?

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00:15:23,400 --> 00:15:26,080
Someone speaks three language,
trilingual, Someone speaks 2

279
00:15:26,080 --> 00:15:27,840
languages, bilingual.
And someone that speaks one

280
00:15:27,840 --> 00:15:33,640
language is American, you know,
and there has to be something

281
00:15:33,640 --> 00:15:36,320
to, to speaking more than one
language.

282
00:15:36,320 --> 00:15:38,080
My brother-in-law is from
Brazil.

283
00:15:38,080 --> 00:15:40,640
He speaks Spanish, Portuguese,
English, Hebrew.

284
00:15:41,520 --> 00:15:45,080
The way he thinks you could see
is so different than I am.

285
00:15:45,080 --> 00:15:49,920
And, and I'm sure that it's
because your brain is working

286
00:15:49,920 --> 00:15:53,600
and expanding to, to, to
encompass all sorts of different

287
00:15:53,800 --> 00:15:56,960
contexts that's required for
those different skills, right?

288
00:15:57,400 --> 00:15:59,880
Yeah, it's really my husband's
actually.

289
00:15:59,880 --> 00:16:03,280
He's a native German speaker,
but he also speaks English and

290
00:16:03,280 --> 00:16:08,080
Italian and he knows Latin and,
you know, so I've and I always

291
00:16:08,080 --> 00:16:12,560
feel incredibly unintelligent
when I go and meet all of his

292
00:16:12,560 --> 00:16:14,720
friends from Europe because they
all speak multiple languages.

293
00:16:14,720 --> 00:16:17,280
It just seems to be and nothing
gets Americans.

294
00:16:17,280 --> 00:16:21,640
I love America, but we not to,
you know, push that as much.

295
00:16:21,640 --> 00:16:24,320
Ours are.
I have 3 kids and they all take

296
00:16:24,320 --> 00:16:28,000
a language in in school.
But it's not something and not

297
00:16:28,000 --> 00:16:32,040
in the same way it appears as in
other countries.

298
00:16:32,400 --> 00:16:36,240
But yeah, it's it's really
interesting to see.

299
00:16:36,240 --> 00:16:38,920
That was one of the reasons why
I was curious about kids who are

300
00:16:38,920 --> 00:16:43,520
multilingual.
They're living in Germany, but

301
00:16:43,520 --> 00:16:47,160
they're attending the school
that's taught in English, and I

302
00:16:47,160 --> 00:16:51,040
was wondering how they would
perform on these particular

303
00:16:51,040 --> 00:16:54,080
tasks.
And although the performance was

304
00:16:54,080 --> 00:16:58,640
the same, there's still probably
a great deal of difference in

305
00:16:58,640 --> 00:17:02,400
how they're processing the
information as opposed to

306
00:17:02,400 --> 00:17:06,920
somebody who is monolingual.
But unfortunately that that's

307
00:17:06,960 --> 00:17:08,800
one area that I haven't studied
in a great.

308
00:17:08,800 --> 00:17:10,920
Yeah.
And I imagine that there's so

309
00:17:11,440 --> 00:17:16,240
it's got to be such a dense
study because there's so many

310
00:17:16,280 --> 00:17:18,720
factors to consider and there's
so many different.

311
00:17:18,720 --> 00:17:22,480
And again, I guess you almost
need your, your neurology, you

312
00:17:22,480 --> 00:17:25,880
know, I guess the neurological
aspect where you kind of able to

313
00:17:25,880 --> 00:17:29,120
understand everything from a
different part, you know, piece

314
00:17:29,120 --> 00:17:31,640
of the playing field.
And then, and then you have to

315
00:17:31,640 --> 00:17:34,480
collect the, the data and kind
of figure out what everything

316
00:17:34,480 --> 00:17:37,040
has in common.
And I mean, that's got to be an

317
00:17:37,080 --> 00:17:39,080
enormous, it's got to be an
enormous amount of research.

318
00:17:39,760 --> 00:17:42,520
Yes, absolutely.
And fascinating.

319
00:17:42,800 --> 00:17:44,560
Yeah, for sure.
It's got to be fun, you know,

320
00:17:44,560 --> 00:17:46,760
but I, but I imagine, you know,
I can't imagine it's going to be

321
00:17:46,760 --> 00:17:49,200
like a 9 or 100 person study and
you're like, Oh well, we figured

322
00:17:49,200 --> 00:17:52,760
it out, you know, like, I mean.
Anecdotally, when, you know, I

323
00:17:52,760 --> 00:17:56,200
took French when I was in high
school and when, you know, I was

324
00:17:56,200 --> 00:17:58,720
living in Germany and trying to
remember German words, for

325
00:17:58,720 --> 00:18:02,080
whatever reason, the, the word,
you know, in French, French

326
00:18:02,080 --> 00:18:04,920
would come out before the word
in and, you know, So I'm very

327
00:18:04,920 --> 00:18:07,880
interested in how, you know, the
circuitry behind that.

328
00:18:08,120 --> 00:18:09,680
I just haven't had the
opportunity.

329
00:18:10,240 --> 00:18:13,800
I do that too, by the way, my,
my, my most of the most of my Co

330
00:18:13,800 --> 00:18:16,760
workers for my sales job are
they speak Spanish and they're,

331
00:18:16,800 --> 00:18:20,680
they're Dominican and I'll end
up speaking instead of broken

332
00:18:20,680 --> 00:18:22,040
Spanish.
I'll throw in a couple of Hebrew

333
00:18:22,040 --> 00:18:24,600
words every now because I'm not
even saying the right thing and

334
00:18:24,600 --> 00:18:26,040
they, they look as confused as I
am.

335
00:18:26,040 --> 00:18:28,720
But I mean, I, I, I, I'm just
pulling from the right.

336
00:18:28,720 --> 00:18:30,280
I guess I'm just pulling from
the wrong place.

337
00:18:30,840 --> 00:18:34,560
What are some other, what are
some other, I guess reading or

338
00:18:34,560 --> 00:18:37,920
developmental diseases that or
or yeah, I mean, do you call

339
00:18:37,920 --> 00:18:39,240
them diseases?
How do you refer to them?

340
00:18:39,240 --> 00:18:43,280
Disorders?
So there's actually a lot of

341
00:18:43,280 --> 00:18:46,360
debate about whether it should
be considered a disorder or not.

342
00:18:46,360 --> 00:18:48,720
It's just, you know, we all have
strengths and.

343
00:18:48,720 --> 00:18:50,120
Weakness.
Right.

344
00:18:50,360 --> 00:18:54,520
And you know, I believe at least
because I'm a neuroscientist

345
00:18:54,520 --> 00:18:56,920
that it all comes down to wiring
and function.

346
00:18:57,280 --> 00:19:00,000
But just because you have a
challenge in one area does not

347
00:19:00,000 --> 00:19:01,920
mean that you have challenge in
all areas.

348
00:19:02,920 --> 00:19:05,440
And I know that, you know,
people.

349
00:19:05,600 --> 00:19:09,120
So I have three children and
they all have dyslexia, you

350
00:19:09,120 --> 00:19:11,520
know, they've had, I know, which
is really unusual.

351
00:19:11,560 --> 00:19:12,880
What are the odds?
It's crazy.

352
00:19:13,240 --> 00:19:19,000
The odds are so ridiculously
low, you know, and they as much

353
00:19:19,000 --> 00:19:23,000
as many kids went through the
the same issues in school where

354
00:19:23,000 --> 00:19:24,800
they were.
You know, you sort of doubt your

355
00:19:24,800 --> 00:19:27,600
intelligence when you have a
learning disability, regardless

356
00:19:27,600 --> 00:19:29,200
of what that learning disability
is.

357
00:19:30,320 --> 00:19:33,440
You know, hearing it from their
friends or expectations, even

358
00:19:33,440 --> 00:19:36,400
sometimes of teachers, although
they've had phenomenal teachers,

359
00:19:37,760 --> 00:19:41,960
you know, and it, it, it can
make you so in that I don't like

360
00:19:41,960 --> 00:19:44,560
to think of it as a disorder as
much as it is a challenge.

361
00:19:44,560 --> 00:19:47,640
They have certain difficulties
with learning certain types of

362
00:19:47,640 --> 00:19:50,960
things, but they are really
exceptional in other areas.

363
00:19:50,960 --> 00:19:55,160
Being able to put connect
different concepts together with

364
00:19:55,160 --> 00:19:57,400
something they could always do
really rapidly and something

365
00:19:57,400 --> 00:20:00,800
that's very hard to teach.
So, but we all have different

366
00:20:00,800 --> 00:20:02,920
strengths and weaknesses in
different areas.

367
00:20:03,160 --> 00:20:04,240
Yeah, it's a great way to put
it.

368
00:20:04,240 --> 00:20:05,800
But I have, Yeah, it's a great
way to put it.

369
00:20:05,800 --> 00:20:09,960
I have a student of mine that he
I teach high school and 9th this

370
00:20:09,960 --> 00:20:15,480
year is 9th, 10th and 12th,
which is really fun spectrum of

371
00:20:15,680 --> 00:20:19,280
teenagehood.
And one of my students was

372
00:20:19,280 --> 00:20:21,720
having a really hard time in the
classroom and I always had a

373
00:20:21,720 --> 00:20:23,920
hard time in the classroom too.
I was not a great student by any

374
00:20:23,920 --> 00:20:27,320
means and I put a lot of
pressure on myself and whenever

375
00:20:27,320 --> 00:20:30,080
I take tests, my mind would just
go blank no matter how much time

376
00:20:30,080 --> 00:20:33,800
I spent studying.
What do you what do you, what do

377
00:20:33,800 --> 00:20:34,960
you think about that
immediately?

378
00:20:35,200 --> 00:20:42,160
What was that thought I?
Can't diagnose so to go on, but

379
00:20:42,280 --> 00:20:46,920
you know, I see kids struggling
because of the area that I, I

380
00:20:46,920 --> 00:20:49,920
work in and because I work with
kids and I often talk with

381
00:20:49,920 --> 00:20:54,680
parents, you know, I, I have
these conversations with, with

382
00:20:54,680 --> 00:20:57,440
parents all the time.
And I have, you know, college

383
00:20:57,440 --> 00:20:59,840
kids who are struggling with
different difficulties.

384
00:20:59,840 --> 00:21:02,000
And it can, you know, it can be
a number of things.

385
00:21:02,200 --> 00:21:05,560
And I really encourage people
to, you know, go and seek help

386
00:21:05,560 --> 00:21:08,120
and find out, you know, what are
your challenges and what are

387
00:21:08,120 --> 00:21:12,400
your strengths and, you know,
build upon those strengths as

388
00:21:12,400 --> 00:21:16,920
you're trying to use
interventions to improve where

389
00:21:16,920 --> 00:21:20,280
you have challenges.
And a lot of times, I think

390
00:21:20,280 --> 00:21:23,400
people feel shame.
Parents feel shame if they feel

391
00:21:23,400 --> 00:21:26,920
that they're, you know, somehow
their child is at a disadvantage

392
00:21:26,920 --> 00:21:30,160
or a child feels shame because
they have a learning disability

393
00:21:30,160 --> 00:21:32,760
and, you know, they think that
says something about their

394
00:21:32,760 --> 00:21:38,640
intelligence, which it doesn't.
I used to argue with my mom and

395
00:21:38,640 --> 00:21:41,560
my mom would be like, you're
smart, like Emma, I love you.

396
00:21:41,960 --> 00:21:43,720
I'm your oldest son.
Of course you're going to say

397
00:21:43,720 --> 00:21:47,520
I'm smart.
There's no smart, but I don't

398
00:21:47,520 --> 00:21:49,720
think I'm that smart.
I'm studying for bio for five

399
00:21:49,720 --> 00:21:51,960
hours and taking notes and I'm
getting X and I don't know what

400
00:21:51,960 --> 00:21:53,800
to tell you.
Like maybe I'm not smart, you

401
00:21:53,800 --> 00:21:56,800
know, And I really, and I
really, really until I, until I

402
00:21:56,800 --> 00:21:58,520
got to college, I thought I was
dumb as a doorknob.

403
00:21:58,680 --> 00:22:00,880
And I was like, I guess I happen
to be nice and I guess I happen

404
00:22:00,880 --> 00:22:03,280
to like reading.
But like, if I can't do these

405
00:22:03,280 --> 00:22:05,320
tests, I'm obviously not a smart
dude, you know?

406
00:22:06,000 --> 00:22:08,240
Yeah.
But there's there we're become

407
00:22:08,240 --> 00:22:13,760
sort of very rigid in, in how we
assess a person, not even just

408
00:22:13,760 --> 00:22:17,640
yes, definitely intelligence,
but just how we assess content

409
00:22:17,640 --> 00:22:21,160
knowledge, right?
And you know, I've even done it

410
00:22:21,160 --> 00:22:25,400
myself where, you know, you
teach a certain amount of of the

411
00:22:25,400 --> 00:22:29,360
topic of the content and then
you give them a written test and

412
00:22:29,360 --> 00:22:31,400
you have so much time to
complete the test.

413
00:22:31,400 --> 00:22:34,720
And you know, that's a challenge
there.

414
00:22:34,880 --> 00:22:37,280
I mean, sometimes we absolutely
have to do that.

415
00:22:37,280 --> 00:22:42,200
But there are other ways to get
at that knowledge that a person

416
00:22:42,200 --> 00:22:47,120
might have, you know, and test
anxiety is a real thing, right?

417
00:22:47,120 --> 00:22:50,320
And if you're really anxious
about taking that test, you

418
00:22:50,320 --> 00:22:52,840
might not be able to focus on
what's in front of you.

419
00:22:52,920 --> 00:22:55,600
And in actuality, you're not
really taking anything in.

420
00:22:55,840 --> 00:22:59,640
So then it's hard to let
somebody know, you know, your

421
00:22:59,640 --> 00:23:02,000
level of knowledge on that
particular topic.

422
00:23:04,040 --> 00:23:08,720
So yeah, it, it is a challenge.
And that doesn't mean, you know,

423
00:23:08,720 --> 00:23:11,760
having anxiety and doesn't on a
test doesn't mean that you're

424
00:23:11,760 --> 00:23:13,800
anxious.
It could just be the situation.

425
00:23:13,800 --> 00:23:15,920
It doesn't mean you have a
learning disability.

426
00:23:16,240 --> 00:23:19,080
I mean, it could be anything.
So the only way to really know

427
00:23:19,080 --> 00:23:22,520
is to to go and seek support.
And yeah.

428
00:23:22,680 --> 00:23:24,880
Definitely.
The professionals help you sort

429
00:23:24,880 --> 00:23:28,200
it out.
Yeah, so when I so, so to that

430
00:23:28,200 --> 00:23:29,280
point.
Exactly.

431
00:23:29,440 --> 00:23:32,200
So this student that I had that
was having a hard time, I could

432
00:23:32,200 --> 00:23:34,560
see that he was brilliant.
I could see, you could see when

433
00:23:34,560 --> 00:23:36,320
you're talking to someone with
their eyes and how quickly

434
00:23:36,320 --> 00:23:38,360
they're processing what you're
saying, that they're thinking

435
00:23:38,360 --> 00:23:40,720
and responding.
And he just could not deal with

436
00:23:40,720 --> 00:23:42,240
school.
You could see he was not one of

437
00:23:42,240 --> 00:23:45,280
these kids that sits behind a
desk from from, you know, 8:00

438
00:23:45,280 --> 00:23:48,280
AM to 5:00 to 6:00 PM, which is
really what the hours are.

439
00:23:49,400 --> 00:23:52,640
And so he actually ended up
leaving the school and I ran

440
00:23:52,640 --> 00:23:56,720
into him at a local synagogue
and I said, you know, and I, and

441
00:23:56,720 --> 00:23:59,920
I said hi and I and I went, went
up to after, after, after the

442
00:23:59,920 --> 00:24:01,680
services.
And I said, I just want to tell

443
00:24:01,680 --> 00:24:06,320
you, I was like, not everyone is
meant to in the classroom.

444
00:24:06,320 --> 00:24:08,320
And that does not make you
stupid by any means.

445
00:24:08,320 --> 00:24:10,800
I was like, you are clearly
brilliant.

446
00:24:10,800 --> 00:24:13,360
I was like, and school is going
to be hard for you.

447
00:24:13,360 --> 00:24:15,400
And then you're going to get
past it and you're going to

448
00:24:15,400 --> 00:24:17,240
figure and you're going to
realize that you have an entire

449
00:24:17,240 --> 00:24:20,480
world of ways that you can do
things that are your method, You

450
00:24:20,480 --> 00:24:21,960
know, that you could figure out
your way.

451
00:24:22,720 --> 00:24:26,840
Like, unfortunately, this system
is old and unfortunately, it

452
00:24:26,840 --> 00:24:30,480
hasn't adapted at all to anyone
that's kind of outside the box

453
00:24:30,480 --> 00:24:33,120
even a little bit.
Because I don't think because

454
00:24:33,120 --> 00:24:36,040
you don't fit into a cookie cut
space that you're not brilliant

455
00:24:36,040 --> 00:24:38,160
and keep learning, keep trying
to figure out your way of

456
00:24:38,160 --> 00:24:40,800
learning.
And you know, and I don't know

457
00:24:40,800 --> 00:24:42,040
whether he'll ever think about
it again.

458
00:24:42,040 --> 00:24:44,120
And you know, I mean, maybe he
will, maybe he won't.

459
00:24:44,440 --> 00:24:49,200
But we need, I think that we
definitely need more

460
00:24:49,200 --> 00:24:52,640
encouragement in general.
And I've found from teaching and

461
00:24:52,640 --> 00:24:54,080
I've only been doing it for four
years now.

462
00:24:54,080 --> 00:24:57,720
But that when you said, when you
make it clear to the people that

463
00:24:57,720 --> 00:25:01,040
you're that you're talking to,
that you know they're capable

464
00:25:01,040 --> 00:25:03,720
and you expect good things from
them because you know they're

465
00:25:03,720 --> 00:25:06,520
capable, they will So rise to
the occasion.

466
00:25:06,560 --> 00:25:09,160
You know, the, the the undue
pressure is kind of where they

467
00:25:09,160 --> 00:25:11,520
say, hey, I don't want to deal
with this right now, but I'll

468
00:25:11,520 --> 00:25:12,920
say, hey, I know that you're
smart, dude.

469
00:25:12,920 --> 00:25:14,600
You know you're smart, right?
He's like, yeah, I'm like, you

470
00:25:14,600 --> 00:25:16,360
think this is the best you can
do is like, I don't think it's

471
00:25:16,360 --> 00:25:18,080
the best thing.
OK, give me, give me a little

472
00:25:18,200 --> 00:25:20,840
bit better, you know, like
that's, that's the, that's the

473
00:25:20,840 --> 00:25:22,160
way that we should be
encouraging people.

474
00:25:22,680 --> 00:25:26,280
Yeah, it, you know, it's really
true whether I'm working with a

475
00:25:26,320 --> 00:25:30,080
little kid for the my research
or working with 18 to 22 year

476
00:25:30,080 --> 00:25:32,400
old, You know, a lot of times
you do, you just need that

477
00:25:32,400 --> 00:25:34,240
reassurance that you can do
this.

478
00:25:34,240 --> 00:25:40,080
And one of the things, you know,
trying to get kids over, I mean,

479
00:25:40,080 --> 00:25:41,920
they're not kids.
If you're 18 to 22, you're an

480
00:25:41,920 --> 00:25:45,600
adult.
But you know, I'm 52, so my

481
00:25:45,600 --> 00:25:49,000
kids.
But to know it's OK to fail.

482
00:25:49,640 --> 00:25:54,080
So I've learned way more by my
failures than I have from my

483
00:25:54,080 --> 00:25:56,480
successes.
And it's necessary.

484
00:25:56,560 --> 00:25:59,800
And learning how to pick
yourself up when you've had a

485
00:25:59,800 --> 00:26:03,600
failure.
In high school, I didn't have to

486
00:26:03,600 --> 00:26:05,360
study.
I could, you know, take the

487
00:26:05,360 --> 00:26:07,520
test.
And I did really well and, and

488
00:26:07,520 --> 00:26:10,600
everything was fine.
But my first year of college, I

489
00:26:10,600 --> 00:26:12,200
figured, oh, it's just the same,
right?

490
00:26:12,240 --> 00:26:13,280
You know, you're already
laughing.

491
00:26:13,280 --> 00:26:14,880
I could tell you already know
where I'm going then.

492
00:26:15,320 --> 00:26:19,240
So, you know, I played soccer
and I was in choir and, you

493
00:26:19,240 --> 00:26:23,080
know, I took my classes and I
figured I didn't need to study.

494
00:26:24,240 --> 00:26:27,840
And I learned the hard way that
that is not how I'm going to.

495
00:26:27,880 --> 00:26:30,120
And I did really terrible my
first semester.

496
00:26:30,120 --> 00:26:33,000
And my father was even starting
to question whether or not I was

497
00:26:33,000 --> 00:26:38,160
as smart as he thought I was,
which is like a huge, you know.

498
00:26:39,680 --> 00:26:44,720
The pain there.
And, you know, so I had to pick

499
00:26:44,720 --> 00:26:46,920
myself up and I had to figure
out how to study.

500
00:26:46,920 --> 00:26:49,600
And, you know, and I did.
And, you know, I had to fight

501
00:26:49,600 --> 00:26:52,840
hard to dig myself out of the
hole I got myself into.

502
00:26:52,840 --> 00:26:55,400
But, you know, I learned a
valuable lesson from that.

503
00:26:56,440 --> 00:26:59,520
And that's one of the things
I'm, I'm always telling my kids.

504
00:26:59,520 --> 00:27:02,640
I said, you know, I know it was
way more challenging for you

505
00:27:02,640 --> 00:27:07,240
than it was for some of your
friends, you know, trying to get

506
00:27:07,240 --> 00:27:09,520
through school because, you
know, at a certain point, you

507
00:27:09,520 --> 00:27:12,000
know, you go from learning to
read to reading to learn.

508
00:27:12,000 --> 00:27:14,960
So if you're already behind on
the reading, it gets really even

509
00:27:14,960 --> 00:27:17,240
that much more challenging to
learn what everybody else is

510
00:27:17,240 --> 00:27:18,240
learning.
You always feel like you're

511
00:27:18,240 --> 00:27:21,240
behind.
But they learned how to work

512
00:27:21,240 --> 00:27:23,320
really hard and how to not give
up.

513
00:27:23,320 --> 00:27:27,120
And that perseverance that's
going to take them so much

514
00:27:27,120 --> 00:27:28,040
farther.
Yeah.

515
00:27:28,760 --> 00:27:32,720
Definitely, definitely learning
to learn is the most valuable

516
00:27:32,760 --> 00:27:34,240
skill that you could teach
someone.

517
00:27:34,240 --> 00:27:35,960
I, you know, my students
whenever they complain to me

518
00:27:35,960 --> 00:27:38,320
about what does history have to
do with anything?

519
00:27:38,520 --> 00:27:39,800
What does bio have to do with
anything?

520
00:27:39,960 --> 00:27:43,000
Like, you know what, I'm not
even going to have this stupid

521
00:27:43,000 --> 00:27:44,760
argument with you guys.
I was like, you're right.

522
00:27:44,760 --> 00:27:45,800
And what I'm going to do with
you.

523
00:27:45,800 --> 00:27:49,160
I was like, accepted the fact
that your brain is actually

524
00:27:49,160 --> 00:27:53,400
learning a new learning process
and how to you know, retain and

525
00:27:53,400 --> 00:27:56,040
understand and breakdown
different forms of information

526
00:27:56,040 --> 00:27:57,880
in different ways.
And I was like, even if you

527
00:27:57,880 --> 00:28:01,720
remember nothing, you will walk
away a smarter, better person

528
00:28:01,720 --> 00:28:04,960
because your brain has learned
how to deal with different sets,

529
00:28:04,960 --> 00:28:09,320
different ways of thinking.
So hot is it?

530
00:28:10,280 --> 00:28:12,920
I actually, I'm telling my
students that all the time.

531
00:28:12,920 --> 00:28:15,720
It's I, it's that it's about,
you know, taking something

532
00:28:15,720 --> 00:28:18,760
complex, learning how to break
it down, understanding the

533
00:28:18,760 --> 00:28:21,440
pieces and then putting, being
able to put them back together

534
00:28:21,440 --> 00:28:24,160
to make sense of it and.
Then they all end up making and

535
00:28:24,160 --> 00:28:26,000
then all end up popping back up
into your life again at

536
00:28:26,000 --> 00:28:28,840
different points, you know,
which is also really, really fun

537
00:28:28,840 --> 00:28:30,720
and really interesting.
You know, I always thought I was

538
00:28:30,800 --> 00:28:34,880
bad at science until I wasn't
until I was an adult and I heard

539
00:28:34,880 --> 00:28:39,200
a podcast with a good professor.
You know, I, I, I was exposed to

540
00:28:39,200 --> 00:28:42,520
Angie Huberman and I listened to
his episode on alcohol, which

541
00:28:42,880 --> 00:28:45,960
scared the life out of me.
And then you know it.

542
00:28:45,960 --> 00:28:50,680
But, but, but the, what I, what
I realized was like when I was

543
00:28:50,680 --> 00:28:52,840
in high school, I don't know if
I was, if my brain was ready to

544
00:28:53,280 --> 00:28:54,800
process that type of
information.

545
00:28:54,840 --> 00:28:58,480
And like I am on, I'm, I'm
prepared now and I'm more and

546
00:28:58,480 --> 00:29:00,320
I'm more ready.
And I, and I, and I wrote it off

547
00:29:00,320 --> 00:29:03,840
for when I was 14 for the rest
of my life or 15 because of the

548
00:29:03,840 --> 00:29:05,160
rejection for the rest of my
life.

549
00:29:05,520 --> 00:29:08,080
And it's so stupid as a 30 year
old father that, you know, I

550
00:29:08,080 --> 00:29:11,000
shouldn't be able to look at,
by, I look at, you know, basic

551
00:29:11,000 --> 00:29:13,680
biology and be like, you know,
how's the food that I'm eating

552
00:29:13,680 --> 00:29:16,600
impacting my body?
What's the value of exercising,

553
00:29:17,440 --> 00:29:19,920
even if I, if I don't use it for
anything other than be alive for

554
00:29:19,920 --> 00:29:22,720
longer, somebody I could see my
kids grow up or my grandkids or

555
00:29:22,720 --> 00:29:24,960
anything like that.
So everything ends up coming

556
00:29:24,960 --> 00:29:26,640
around full circle.
You want to understand current

557
00:29:26,640 --> 00:29:29,160
events, learn some history, you
know, like anything ends up

558
00:29:29,160 --> 00:29:31,040
happening.
And if you're, if you're too

559
00:29:31,160 --> 00:29:33,160
immature in high school to see
that, that's fine.

560
00:29:33,800 --> 00:29:35,640
But you're learning and you're
building those blocks.

561
00:29:36,280 --> 00:29:41,480
Yeah, absolutely.
I teach statistics and you know,

562
00:29:41,480 --> 00:29:43,880
nobody wants to take an 8:00 AM
stats class, right?

563
00:29:43,880 --> 00:29:46,000
It's it's usually a required
course.

564
00:29:46,000 --> 00:29:47,200
It's not something you're
choosing.

565
00:29:47,360 --> 00:29:49,360
Yes, how's giving the 8:00 AM is
stat class?

566
00:29:49,360 --> 00:29:50,480
What's that?
Your end?

567
00:29:51,080 --> 00:29:52,800
What?
What's that like from your end

568
00:29:52,800 --> 00:29:54,440
giving the 8:00 AM stat class?
Do you I?

569
00:29:54,960 --> 00:29:58,240
Love it.
You know, can only go up, right?

570
00:29:58,240 --> 00:30:01,200
Nobody wants to be there.
Everybody's exhausted.

571
00:30:01,440 --> 00:30:04,440
So if I can get them, you know,
by the end of the class, if

572
00:30:04,440 --> 00:30:07,200
they're awake and they're taking
in what I'm saying, then I have

573
00:30:07,200 --> 00:30:09,200
done my job.
I love it.

574
00:30:12,240 --> 00:30:13,760
But I'm always just pointing out
to them.

575
00:30:13,760 --> 00:30:16,400
So if you take anything away
from this, I want you to be

576
00:30:16,400 --> 00:30:20,720
better evaluators of what you're
consuming, whether you know what

577
00:30:20,720 --> 00:30:23,560
you're consuming in the media,
what you're, you know you're

578
00:30:23,560 --> 00:30:27,160
purchasing, what you know
statistical significance

579
00:30:27,160 --> 00:30:29,920
actually means.
So yeah, I absolutely agree.

580
00:30:29,920 --> 00:30:33,000
Even if they never use it again
in the particular context in

581
00:30:33,000 --> 00:30:36,120
which they're learning, they
will use aspects of it again

582
00:30:36,120 --> 00:30:38,520
later in their life.
Yeah, definitely.

583
00:30:38,840 --> 00:30:43,200
Can you tell me?
I'm curious about this the new

584
00:30:43,200 --> 00:30:46,080
the lab you mentioned in passing
earlier that you started from

585
00:30:46,080 --> 00:30:49,000
the ground up about and I and I
wrote down notes that I don't

586
00:30:49,000 --> 00:30:52,400
know if makes any sense, but the
EEG and chips interface devices.

587
00:30:54,680 --> 00:30:59,640
A professor in engineering, Yi
Chen Yu, and I started years ago

588
00:30:59,640 --> 00:31:01,800
now, Brain Computer Interface
lab.

589
00:31:02,320 --> 00:31:06,960
OK.
There was a call for what they

590
00:31:06,960 --> 00:31:10,520
had called a think tank grant
and trying to connect

591
00:31:10,560 --> 00:31:14,040
engineering with other areas of
the college.

592
00:31:14,400 --> 00:31:19,840
And I had been teaching a class
on brain computer interface just

593
00:31:19,840 --> 00:31:22,280
as part of a values in science
and technology class, like a

594
00:31:22,280 --> 00:31:27,120
sophomore level class.
And I was just thinking, you

595
00:31:27,120 --> 00:31:28,880
know, I think we could do this
here.

596
00:31:29,000 --> 00:31:30,440
And I think it would be
valuable.

597
00:31:30,600 --> 00:31:33,160
And I didn't know Yi Chiang at
that point.

598
00:31:33,160 --> 00:31:37,480
And he got connected with me.
And we're like, you know what?

599
00:31:37,680 --> 00:31:39,400
Let's just, let's just go for
it.

600
00:31:39,400 --> 00:31:43,600
And then we reached out to
Jonathan Walpole, who was at the

601
00:31:43,600 --> 00:31:47,480
Wadsworth Center at the time.
And now he's at NCAN in Albany.

602
00:31:47,680 --> 00:31:49,880
And we said, you know, we're
interested in doing this.

603
00:31:49,880 --> 00:31:53,760
Can you teach us?
And it is so shocking.

604
00:31:53,760 --> 00:31:57,120
I'm always telling people, you
know, just just call somebody,

605
00:31:57,120 --> 00:32:00,080
just ask, send an e-mail.
I mean, the worst they can do is

606
00:32:00,080 --> 00:32:02,880
say no or ignore you.
But you have, you know, you're

607
00:32:02,880 --> 00:32:05,520
no worse off now than you were
before.

608
00:32:05,800 --> 00:32:10,000
And he was the greatest guy he
had, he had us up there.

609
00:32:10,000 --> 00:32:13,440
We brought some students with
us, taught us the basics.

610
00:32:13,680 --> 00:32:16,000
We went down and we built our
own system.

611
00:32:16,000 --> 00:32:19,000
We got some data and we got an
NSF grant to purchase more

612
00:32:19,000 --> 00:32:21,160
equipment and been, we've been
doing this ever since.

613
00:32:22,080 --> 00:32:27,880
So with that, we use EEG
electrons, cyclography to detect

614
00:32:28,880 --> 00:32:33,000
neural activity, electrical
activity from the the neurons

615
00:32:33,000 --> 00:32:35,040
that are inactivated in the
brain.

616
00:32:36,040 --> 00:32:38,880
And we use it actually as a
trigger rather than detecting

617
00:32:38,880 --> 00:32:41,240
the signals to tell us something
about brain function.

618
00:32:41,480 --> 00:32:45,720
We use the brain function to
trigger an external device to

619
00:32:45,720 --> 00:32:50,040
sort of bypass your motor
system.

620
00:32:50,040 --> 00:32:51,840
So.
I'm sorry to just to clarify

621
00:32:51,840 --> 00:32:54,600
before you continue, just to in
case it's confusing at all.

622
00:32:56,760 --> 00:33:01,640
Of course, just in case of why
what you're saying is the

623
00:33:01,640 --> 00:33:03,200
opposite, how does it typically
work?

624
00:33:03,200 --> 00:33:07,800
For example that it would be
going vice versa, from your

625
00:33:07,800 --> 00:33:10,080
brain to the neuro to the neuro
to the EEG.

626
00:33:10,720 --> 00:33:13,800
So do you remember how we were
talking before about, you know,

627
00:33:13,800 --> 00:33:16,520
what something is versus how
something works, right.

628
00:33:16,800 --> 00:33:21,200
So if I wanted to look at sort
of neural function, I might use

629
00:33:22,160 --> 00:33:26,280
EEG to see the way the brain
behaves, right?

630
00:33:26,280 --> 00:33:30,600
To see, you know, you might give
a problem to two people, they

631
00:33:30,600 --> 00:33:34,080
might both get to the answer,
but perhaps one has to work

632
00:33:34,080 --> 00:33:35,520
harder at it than the other,
right?

633
00:33:36,600 --> 00:33:39,840
The differences and the neural
activation patterns in different

634
00:33:39,840 --> 00:33:44,560
areas of the brain.
Another way to use it is knowing

635
00:33:44,560 --> 00:33:48,600
what types of neural activity
occurs in response to specific

636
00:33:48,600 --> 00:33:50,920
behaviors or thoughts or
processes.

637
00:33:51,160 --> 00:33:54,800
We can then detect those signals
and every time a signal occurs,

638
00:33:54,800 --> 00:33:56,360
it's kind of like turning the
light switch on and off.

639
00:33:56,440 --> 00:33:59,520
Every time a signal occurs or
goes up to a certain level, it

640
00:33:59,520 --> 00:34:04,320
triggers a device.
So we ultimately we've used the

641
00:34:04,320 --> 00:34:09,600
EEG signals to fly a drone or
yeah, it's really cool.

642
00:34:09,600 --> 00:34:11,719
We have it on.
We have like a little YouTube

643
00:34:12,239 --> 00:34:13,719
video.
Someone's brain.

644
00:34:14,239 --> 00:34:19,120
Yeah.
So it's just an EEG electrode

645
00:34:19,120 --> 00:34:24,760
cap and they're basically using,
we're using the neural signals

646
00:34:24,760 --> 00:34:28,280
to operate the drone and they're
basically flying it around the

647
00:34:28,280 --> 00:34:30,400
gym.
Get out of here.

648
00:34:30,800 --> 00:34:32,280
Yeah, that's pretty.
What?

649
00:34:32,719 --> 00:34:34,159
How long you been doing this
for?

650
00:34:35,239 --> 00:34:37,239
Like quite some time, I think
2010.

651
00:34:37,920 --> 00:34:42,320
So our big thing is trying to
develop an EG system that's easy

652
00:34:42,320 --> 00:34:45,360
to use and affordable so it can
be used outside of the lab,

653
00:34:45,360 --> 00:34:46,960
which is actually really
challenging.

654
00:34:47,360 --> 00:34:48,920
Like if you have all the money
in the world and all the

655
00:34:48,920 --> 00:34:51,040
equipment in the world, you can
make some really cool things,

656
00:34:51,040 --> 00:34:58,600
but don't use it.
So wow, you've been, you've been

657
00:34:58,600 --> 00:35:06,440
since 2010, you guys have been
using neural networks to fly

658
00:35:06,440 --> 00:35:09,640
drones, to direct drones.
Yeah, it's actually one of the

659
00:35:09,640 --> 00:35:12,560
things we really want to do is
operate a wheelchair, yeah,

660
00:35:13,080 --> 00:35:16,440
which is harder than the drone
because the drone, you know, is

661
00:35:16,440 --> 00:35:18,600
flying through the air, so
there's not really a lot of

662
00:35:18,600 --> 00:35:21,520
obstacles to.
Whereas when you're trying to

663
00:35:21,520 --> 00:35:24,840
navigate a hallway and into
rooms and out of rooms, that's a

664
00:35:24,840 --> 00:35:29,920
little bit more challenging.
So what we are aiming for is to

665
00:35:29,920 --> 00:35:34,200
create a device to operate a
wheelchair for somebody who has

666
00:35:34,200 --> 00:35:37,800
a severe motor impairment,
particular vigils with locked in

667
00:35:37,800 --> 00:35:40,880
syndrome, so that they can gain
more independence.

668
00:35:41,080 --> 00:35:42,920
Definitely.
Well, definitely.

669
00:35:43,200 --> 00:35:46,920
And I mean, I was thinking, so I
guess that it's something, I

670
00:35:46,960 --> 00:35:49,360
mean, I hate to say it like
this, but Neuralink kind of

671
00:35:49,360 --> 00:35:51,880
sounds trivial relative to to
that, right?

672
00:35:52,000 --> 00:35:54,520
Oh, no, no, I mean, not at all.
I mean, he's doing some really

673
00:35:54,520 --> 00:35:57,440
cool things with that, that, you
know, the brain is really, it's

674
00:35:57,440 --> 00:35:58,800
fascinating.
I'm sorry, you're right.

675
00:35:58,800 --> 00:36:02,280
So the context that I meant to
say it in is the people that the

676
00:36:02,400 --> 00:36:05,440
the guys that I've seen that you
guys went on different podcasts

677
00:36:05,680 --> 00:36:09,200
that use that use their eyes to
play a video game like.

678
00:36:09,600 --> 00:36:12,560
It's.
Like this operating a drone to

679
00:36:12,560 --> 00:36:17,800
me sounds far more real world
useful and applicable and

680
00:36:17,800 --> 00:36:20,360
helpful.
I would almost imagine then

681
00:36:20,480 --> 00:36:22,200
playing.
I mean, not to say that one's

682
00:36:22,280 --> 00:36:24,440
not useful, the other by getting
one manifests itself

683
00:36:24,440 --> 00:36:26,400
differently.
And I never even I never even

684
00:36:26,400 --> 00:36:27,720
heard people talking about it
before.

685
00:36:27,720 --> 00:36:30,960
I mean, how come there aren't
things being commercialized in

686
00:36:30,960 --> 00:36:34,000
this sense?
Oh, I'm sure they are.

687
00:36:36,120 --> 00:36:41,960
So if you're using, you know,
these types of systems to play a

688
00:36:41,960 --> 00:36:45,160
video game, it's not that
actually hard to actually take

689
00:36:45,160 --> 00:36:46,680
it from video game to an actual
thing.

690
00:36:46,920 --> 00:36:51,040
So when we were training the
student to operate the device to

691
00:36:51,320 --> 00:36:56,000
then end up flying the drone in
the gym, we created essentially

692
00:36:56,000 --> 00:36:59,520
a video game to train how to do
it in a virtual setting.

693
00:36:59,520 --> 00:37:01,360
And then, you know, we let them
loose.

694
00:37:01,680 --> 00:37:05,840
I will say though, we tried
first to fly the drone out on

695
00:37:05,840 --> 00:37:09,600
the the field, the football
field, but we lost the

696
00:37:09,600 --> 00:37:13,280
connectivity, the Bluetooth
right.

697
00:37:13,280 --> 00:37:16,920
So in the gym it was a more
controlled environment, so it

698
00:37:16,920 --> 00:37:19,640
was easier to do.
So I'm making it sound like it's

699
00:37:19,880 --> 00:37:23,480
it's easier than it probably.
But that almost sounds like a

700
00:37:23,600 --> 00:37:26,120
relatively trivial problem to
resolve.

701
00:37:26,120 --> 00:37:28,360
Like we're working on that could
be something with Bluetooth,

702
00:37:28,360 --> 00:37:30,200
that could be something, you
know, I mean, like we, we that

703
00:37:30,200 --> 00:37:33,120
that those are issues that are
advancing because that's how

704
00:37:33,120 --> 00:37:36,160
society advances regardless that
you can kind of just take that

705
00:37:36,160 --> 00:37:38,240
technology and reapply it to
this issue, right?

706
00:37:38,600 --> 00:37:41,080
Yeah, absolutely.
How much would you dedicate to

707
00:37:41,080 --> 00:37:46,840
this to this project?
Well, so all my different

708
00:37:46,840 --> 00:37:49,520
research projects are sort of
going on all the time.

709
00:37:50,200 --> 00:37:53,400
We always have a team of
neuroscience and engineering

710
00:37:53,400 --> 00:37:56,120
students working together on
this project.

711
00:37:56,280 --> 00:37:59,720
That's one of the reasons I like
it so much, because it does

712
00:37:59,720 --> 00:38:02,400
bring students from different
areas together to solve a

713
00:38:02,400 --> 00:38:05,280
problem.
So one of the the cool, the

714
00:38:05,280 --> 00:38:07,160
coolest things, I mean, other
than technology.

715
00:38:07,160 --> 00:38:10,680
Technology is awesome, but it
requires the students to learn

716
00:38:10,680 --> 00:38:14,480
how to speak to each other in a
way that they wouldn't normally.

717
00:38:14,480 --> 00:38:19,040
So you tend to create your own
type of dialogue within your

718
00:38:19,040 --> 00:38:22,160
area of specialty, right?
So you have to learn how to

719
00:38:22,160 --> 00:38:27,040
communicate with each other and
explain things to somebody who

720
00:38:27,040 --> 00:38:30,440
might be a novice in one area
whereas you're a novice in their

721
00:38:30,440 --> 00:38:33,600
area.
So that's a huge learning

722
00:38:33,600 --> 00:38:36,200
opportunity.
It actually took Yi Chung and IA

723
00:38:36,200 --> 00:38:40,480
while before we, you know, we're
able to easily explain things to

724
00:38:40,480 --> 00:38:44,120
each other.
Yeah, yeah, I, I picked up jiu

725
00:38:44,120 --> 00:38:47,400
jitsu about a year ago and have
that exact issue and they're

726
00:38:47,400 --> 00:38:51,760
like do that I'm like, I don't
know what I mean and I'm like, I

727
00:38:51,760 --> 00:38:54,440
understand and they're like, do
that and I understand the words

728
00:38:54,440 --> 00:38:57,680
that are coming out of your
mouth individually and put them

729
00:38:57,680 --> 00:38:59,760
together and how to translate
that into doing something with

730
00:38:59,760 --> 00:39:01,400
my body.
I'm like, you're going to have

731
00:39:02,240 --> 00:39:06,640
it's that it's that same issue.
Yeah, that's why one thing I, I

732
00:39:06,640 --> 00:39:09,800
hope to, I, I've been, I've been
working on this for a long time

733
00:39:09,800 --> 00:39:14,840
because I've been, you know, I,
I, my, my, my family has very

734
00:39:14,840 --> 00:39:16,680
strong opinions.
All of us are pretty different

735
00:39:16,680 --> 00:39:19,280
and all of us have pretty strong
opinions just in general.

736
00:39:19,680 --> 00:39:24,000
So one thing that we risk is
fighting a lot, but one thing

737
00:39:24,000 --> 00:39:27,600
that we benefit or gain from is
that we really do have, we have

738
00:39:27,600 --> 00:39:29,560
learned to see things from a lot
of different perspectives over

739
00:39:29,560 --> 00:39:32,280
the years because all of us
growing up under the same roof

740
00:39:32,280 --> 00:39:36,400
all saw things very differently.
And one thing that I did realize

741
00:39:36,400 --> 00:39:40,600
is that 90 to 95% of fights or
arguments that I've ever gone in

742
00:39:40,760 --> 00:39:42,960
was really just that we're
speaking two different languages

743
00:39:42,960 --> 00:39:44,640
to each other and not
understanding what the other

744
00:39:44,640 --> 00:39:48,000
person was saying instead of
like actually disagreeing on an

745
00:39:48,000 --> 00:39:50,400
idea like.
Well said.

746
00:39:50,680 --> 00:39:54,200
Absolutely.
And in the beginning, you, Chung

747
00:39:54,200 --> 00:39:57,640
and IA lot of our confusion, we
were both saying the exact same

748
00:39:57,640 --> 00:39:58,720
thing.
We just didn't know it.

749
00:39:58,880 --> 00:40:01,680
Yeah.
So, you know, it's a process.

750
00:40:01,680 --> 00:40:05,680
My oldest loves to push my
buttons and loves to argue with

751
00:40:05,680 --> 00:40:10,240
me and, and, but in all honesty,
as frustrating as it is in the

752
00:40:10,240 --> 00:40:13,600
moment, we really understand
where each other is coming from.

753
00:40:13,600 --> 00:40:16,200
And oftentimes we are arguing
the exact same thing.

754
00:40:16,200 --> 00:40:17,640
We're just coming at it from
different ways.

755
00:40:18,080 --> 00:40:20,400
Yeah, yeah, definitely.
That's really cool.

756
00:40:20,400 --> 00:40:21,560
That's awesome.
I love that.

757
00:40:22,480 --> 00:40:28,280
So going a little bit down the
sci-fi rabbit hole, does this

758
00:40:28,640 --> 00:40:32,680
open up the world of like
cyborgs and like, I mean, this

759
00:40:32,760 --> 00:40:37,000
almost sounds and you know, I
was kind of freaking out about a

760
00:40:37,000 --> 00:40:39,720
year ago.
It's probably has to do with

761
00:40:40,320 --> 00:40:43,200
some marijuana ingestion, but I
was freaking out about the

762
00:40:43,200 --> 00:40:45,320
drone.
Now we're in New Jersey that

763
00:40:45,320 --> 00:40:50,200
everyone was seeing and and then
and one thing that was freaking

764
00:40:50,200 --> 00:40:52,600
me out again was, you know, the
size and it didn't look like

765
00:40:52,600 --> 00:40:53,840
anyone was like, you know,
they're small.

766
00:40:53,840 --> 00:40:55,880
It didn't look like anyone is
was moving them around.

767
00:40:55,880 --> 00:40:57,240
And I'm like, we don't even know
what that means.

768
00:40:57,480 --> 00:41:01,360
But I mean, if what you're
saying is true and the science

769
00:41:01,440 --> 00:41:03,800
of this kind of stuff has been
going on that we've been trying

770
00:41:03,800 --> 00:41:07,920
to work on this neural to neural
to physical object connection

771
00:41:08,120 --> 00:41:12,400
for since the 2010, since the
early 2 thousand 2010.

772
00:41:12,960 --> 00:41:15,720
I would imagine that the
government and military could be

773
00:41:15,720 --> 00:41:19,040
developing some serious stuff
with this, with this capacity,

774
00:41:19,040 --> 00:41:22,120
right?
Yeah, as as scientists, we

775
00:41:22,360 --> 00:41:26,120
always have to consider, you
know, what the next steps are,

776
00:41:26,360 --> 00:41:30,840
not just can we do it, should we
do it, what the guard where

777
00:41:30,880 --> 00:41:34,000
rails should be.
And you know, and oftentimes we

778
00:41:34,000 --> 00:41:37,000
don't always have control of all
the aspects of that.

779
00:41:37,320 --> 00:41:42,520
So, yeah, I mean, it's it's
always a potential problem of,

780
00:41:42,800 --> 00:41:46,680
you know, how something is going
to be used and why it's used and

781
00:41:46,680 --> 00:41:52,480
being responsible and ethical
use of not only the research

782
00:41:52,480 --> 00:41:54,920
you're conducting, but the tools
that you're making.

783
00:41:54,920 --> 00:41:58,320
And I completely hear you.
Right, right, right.

784
00:41:58,320 --> 00:41:59,640
Yeah.
And I, you know, because I was

785
00:41:59,640 --> 00:42:02,720
thinking a lot about this with,
with, I don't know if you were

786
00:42:02,800 --> 00:42:08,360
aware of this Anthropic and
Department of War feud, but

787
00:42:08,360 --> 00:42:10,920
anthropic was looking, you know,
they basically wanted to keep

788
00:42:10,920 --> 00:42:13,480
the AI safeguards on.
And, and the government was

789
00:42:13,480 --> 00:42:15,720
like, Hey, like we got to do
this, to do what we got to do

790
00:42:15,720 --> 00:42:18,840
with this and, and topics like
we're really not comfortable

791
00:42:18,840 --> 00:42:20,720
with that.
And then ChatGPT is like, you

792
00:42:20,720 --> 00:42:26,920
can do it.
And are you, listen, I, I'm sure

793
00:42:26,920 --> 00:42:30,200
you can make a case, you know
what you know for both ways, But

794
00:42:30,800 --> 00:42:33,640
you know, these are, these are
rabbit holes that are a little

795
00:42:33,640 --> 00:42:38,120
concerning and we can't put the
genie back in the bottle, as

796
00:42:38,120 --> 00:42:39,600
we've learned so many times in
history.

797
00:42:40,200 --> 00:42:43,520
Yeah, that that's the big thing.
You, you can't, you can't put it

798
00:42:43,520 --> 00:42:45,640
back in the bottle once you've
let it out.

799
00:42:46,720 --> 00:42:50,360
And watching that whole
discussion on unfold between

800
00:42:50,360 --> 00:42:53,920
anthropic and the government
and, you know, and ChatGPT was

801
00:42:53,920 --> 00:42:59,680
kind of surreal because we
don't, we don't often do our due

802
00:42:59,680 --> 00:43:02,600
diligence of figuring out where
those safeguards need to be in

803
00:43:02,600 --> 00:43:06,640
place and holding to them when
we're developing something.

804
00:43:06,640 --> 00:43:09,880
It's usually, oh, geez, we, you
know, we didn't think about

805
00:43:09,880 --> 00:43:11,680
this.
And it's not because, you know,

806
00:43:12,160 --> 00:43:16,800
people are inherently, you know,
they're not doing their due

807
00:43:16,800 --> 00:43:21,200
diligence, but, you know, new
thinking about every possible

808
00:43:21,200 --> 00:43:23,400
aspect is, you know, is a bit of
a challenge.

809
00:43:23,760 --> 00:43:26,920
But once we are faced with the
information and the

810
00:43:26,920 --> 00:43:30,280
possibilities, it's our
responsibility to take action.

811
00:43:32,200 --> 00:43:36,440
And the regulators, and almost
by definition, regulation has to

812
00:43:36,440 --> 00:43:39,160
be a step behind because you
need something to regulate.

813
00:43:39,160 --> 00:43:41,560
Like, you know, there's like
without Avengers used to say,

814
00:43:41,560 --> 00:43:43,480
like if there's no, like if we
didn't lose to begin with,

815
00:43:43,480 --> 00:43:45,440
there'd be nothing to avenge.
You know, like there's like, if

816
00:43:45,440 --> 00:43:47,720
we don't have a problem, then
there's nothing, then we

817
00:43:47,720 --> 00:43:49,160
wouldn't need the government to
regulate it.

818
00:43:50,000 --> 00:43:54,960
Yeah, I absolutely agree.
But I think we can also

819
00:43:54,960 --> 00:43:59,360
preemptively say, you know, if
we keep going in this direction,

820
00:43:59,360 --> 00:44:04,040
this is what's going to happen.
And you can see a few steps

821
00:44:04,040 --> 00:44:06,840
down, you may not have realized
it was going to be used for X,

822
00:44:07,200 --> 00:44:13,560
but, you know, we need to be a
little bit more anticipatory and

823
00:44:13,560 --> 00:44:17,280
in terms of how we regulate
ourselves and, and what are the

824
00:44:17,280 --> 00:44:20,400
potential misuses of what we're
developing.

825
00:44:20,600 --> 00:44:23,200
But again, that's all that's
easier said than done.

826
00:44:23,200 --> 00:44:25,680
It's easier to look back and
say, oh, yeah, we should have

827
00:44:25,680 --> 00:44:28,680
noticed that it was going, you
know, to go in this particular

828
00:44:28,680 --> 00:44:30,680
direction.
But, you know, hindsight.

829
00:44:31,080 --> 00:44:33,120
Yeah.
And the other problem is that

830
00:44:33,200 --> 00:44:35,640
people are so limited.
We only look at things to the

831
00:44:35,640 --> 00:44:37,480
scope that we're used to looking
at things at.

832
00:44:37,640 --> 00:44:39,640
Yes, absolutely.
Absolutely.

833
00:44:40,320 --> 00:44:43,560
And we, you know, so I might
look at it, I might look at the

834
00:44:43,560 --> 00:44:46,640
issue from a teaching
perspective and as a dad and as

835
00:44:46,640 --> 00:44:48,920
a salesman and be like, oh, this
is going to have a problem for

836
00:44:48,920 --> 00:44:50,800
me.
But you're looking at it from a

837
00:44:50,960 --> 00:44:54,080
neuroscience perspective and
being like, hey, like this is a

838
00:44:54,080 --> 00:44:56,600
whole nother world that we're
looking at things from.

839
00:44:56,600 --> 00:44:59,040
And like, you didn't even
realize what's even look out

840
00:44:59,040 --> 00:45:00,320
for.
You even know what the potential

841
00:45:00,320 --> 00:45:02,160
consequences could be.
Exactly.

842
00:45:02,520 --> 00:45:05,560
I, I, I hear, and that's it's
always got to be a dance.

843
00:45:05,560 --> 00:45:07,760
I mean, we've seen it's a dance
and it's a given play.

844
00:45:07,760 --> 00:45:12,360
It's a give and take.
And it just, and I mean, I think

845
00:45:12,360 --> 00:45:15,640
that as long as we just keep,
encourage good minds to that

846
00:45:15,640 --> 00:45:20,200
want to solve problems, to keep
at it, we'll be, you know, I, I

847
00:45:20,200 --> 00:45:23,400
hope I'm optimistic, I'm hopeful
and I have to be because I have

848
00:45:23,640 --> 00:45:26,240
kids.
But you know, I mean, we got to

849
00:45:26,240 --> 00:45:27,480
do, we got to do the best we
can.

850
00:45:28,520 --> 00:45:31,440
Yeah, I mean, absolutely.
This is why we need to work

851
00:45:31,440 --> 00:45:34,840
together across, you know,
divisional boundaries.

852
00:45:34,840 --> 00:45:37,400
We have to talk to people about
what we're doing.

853
00:45:37,400 --> 00:45:43,160
We have to present our research.
We have to engage people in

854
00:45:43,160 --> 00:45:46,800
conversation because others are
going to see things that we

855
00:45:46,800 --> 00:45:49,640
missed.
Yeah, When did you say that?

856
00:45:49,640 --> 00:45:53,880
And I noticed this too, but that
people have become a little bit

857
00:45:53,880 --> 00:45:56,120
more interdisciplinary.
And I've been hearing the

858
00:45:56,120 --> 00:45:59,480
sentiment these days, especially
because this is really

859
00:45:59,480 --> 00:46:01,640
interesting with AI and a really
interesting consequence.

860
00:46:02,920 --> 00:46:07,720
Anyone that used to be an expert
on something, it's much better

861
00:46:07,720 --> 00:46:10,880
to be a generalized, you know,
it's better to be a master.

862
00:46:10,880 --> 00:46:13,520
What was it?
Jack of all trades, master of

863
00:46:13,520 --> 00:46:16,560
none.
And I is the master of whatever

864
00:46:16,560 --> 00:46:19,040
thing that you want to dive into
as deeply as you want to.

865
00:46:19,040 --> 00:46:21,880
If you want to be a very
particular type of doctor, you

866
00:46:21,880 --> 00:46:24,920
want to study a very particular
type of research.

867
00:46:25,880 --> 00:46:30,040
AI can help you gather and
understand and understand

868
00:46:30,040 --> 00:46:34,120
information on a level that
we've never had access to

869
00:46:34,120 --> 00:46:35,600
before.
The example I'd like to give

870
00:46:35,600 --> 00:46:38,920
actually with recent government
use was with Venezuela.

871
00:46:38,920 --> 00:46:41,840
When they, when we, when we
kidnapped or took Maduro,

872
00:46:41,840 --> 00:46:43,920
whatever, whatever, whatever.
What do you want to use for it?

873
00:46:44,760 --> 00:46:46,880
One thing that did that they
that the government said they

874
00:46:46,880 --> 00:46:50,760
used AI for was hey, we have
didn't have access to classified

875
00:46:50,760 --> 00:46:53,200
information.
We gave it a stack of, you know,

876
00:46:53,200 --> 00:46:55,000
someone said, hey, give me
everything we have on Venezuela

877
00:46:55,000 --> 00:46:57,960
and someone gives you and
someone drops 30 billion files

878
00:46:57,960 --> 00:47:00,440
into a room and says, good luck
sorting through this.

879
00:47:00,680 --> 00:47:03,200
You know that it used to be that
you get a bunch of staffers, you

880
00:47:03,200 --> 00:47:05,360
get a bunch of aids, you get a
bunch of people to or grad

881
00:47:05,360 --> 00:47:08,160
students or whatever it is to
sit through, get them a bunch of

882
00:47:08,160 --> 00:47:10,320
pizza and have them work for a
week and try to figure out the

883
00:47:10,320 --> 00:47:12,480
best plan.
Now you sift through that

884
00:47:12,480 --> 00:47:16,760
information in just a matter of
seconds and gather the best, the

885
00:47:16,760 --> 00:47:19,080
best Intel.
And So what we're going to have,

886
00:47:19,080 --> 00:47:21,080
I think what people are going to
have to learn how to do is be

887
00:47:21,080 --> 00:47:28,080
really good adept at being
general thinkers, is able to hop

888
00:47:28,080 --> 00:47:30,560
around from one area to the next
to the next to the next, and

889
00:47:30,560 --> 00:47:36,320
kind of be conversational across
industries and across fields in

890
00:47:36,320 --> 00:47:37,480
order to really be able to keep
up.

891
00:47:37,480 --> 00:47:41,440
Because AI has kind of taken all
the specific oriented jobs and

892
00:47:41,440 --> 00:47:45,800
research I feel like or will be.
Yeah, I mean, it's really good.

893
00:47:45,840 --> 00:47:49,440
So that wasn't a really good
example where, you know, you

894
00:47:49,440 --> 00:47:51,880
have all this information and
you have to coalesce this

895
00:47:51,880 --> 00:47:55,960
information and connect it.
And it's a lot faster definitely

896
00:47:55,960 --> 00:48:00,000
to upload all that information
into an AI engine and say here,

897
00:48:00,000 --> 00:48:05,800
I need you to sort this for X,
summarize this for me or edit

898
00:48:05,800 --> 00:48:10,680
this for me.
But we we definitely don't want

899
00:48:10,800 --> 00:48:16,240
to dismiss the ability of an
individual and processing that

900
00:48:16,240 --> 00:48:18,520
information and finding certain
keys.

901
00:48:20,720 --> 00:48:24,120
Overlook it you're.
Saying yes, that, you know, AI

902
00:48:24,120 --> 00:48:28,960
might not be able to do.
And I have found that it's what

903
00:48:28,960 --> 00:48:31,600
you ask and how you ask it.
And, you know, you have to

904
00:48:31,600 --> 00:48:33,640
challenge the information you're
getting.

905
00:48:33,880 --> 00:48:37,200
And it works really well in an
area that you are already an

906
00:48:37,200 --> 00:48:40,360
expert in so that you can
evaluate the information that's

907
00:48:40,480 --> 00:48:43,480
coming back.
But that would be a lot harder

908
00:48:43,480 --> 00:48:47,360
to do if you were a novice in in
a particular area.

909
00:48:47,360 --> 00:48:49,880
You would get that information
back and you would assume it's

910
00:48:49,880 --> 00:48:53,400
right because it knows more than
you do at this point, so.

911
00:48:53,440 --> 00:48:55,120
You know, that's, that's a
really cool point.

912
00:48:55,120 --> 00:48:58,960
That's a really cool point.
Yeah, you're right.

913
00:48:58,960 --> 00:49:02,280
I, so I use, I use Grok to help
me find podcast guests, right?

914
00:49:02,280 --> 00:49:05,640
And I, I have it, I say, hey,
check out my show.

915
00:49:05,640 --> 00:49:09,600
I have 100 and whatever amount
of episodes and tell me I want

916
00:49:09,600 --> 00:49:12,960
to find 5 people that study
history of New Mexico, right.

917
00:49:13,240 --> 00:49:16,440
And please only include people
online who have their e-mail

918
00:49:16,440 --> 00:49:18,960
addresses available and it'll
spit out five names for me.

919
00:49:18,960 --> 00:49:21,640
And here's some guests based on
what you, what your, what your

920
00:49:21,640 --> 00:49:25,440
tone is like.
And went, and then I've gone to

921
00:49:25,440 --> 00:49:27,760
and I've, and I always make a
point now to Google the guests

922
00:49:27,760 --> 00:49:31,280
because sometimes they're dead,
sometimes they're, sometimes

923
00:49:31,280 --> 00:49:33,280
they're convicted.
Sometimes, you know, yeah, he's

924
00:49:33,440 --> 00:49:35,520
going to give me all this, all
this context.

925
00:49:35,520 --> 00:49:37,800
And I'm like, I find out that
this guy that it's recommending

926
00:49:37,800 --> 00:49:41,840
for me to, to interview is in
jail for, you know, XY and Z.

927
00:49:41,840 --> 00:49:45,480
And I'm like, OK, well, you
know, I've and, and I would have

928
00:49:46,000 --> 00:49:47,880
just given up.
I would have just said, oh,

929
00:49:47,920 --> 00:49:49,600
well, you know more than I do.
And I wanted five

930
00:49:49,600 --> 00:49:51,280
recommendations, so I'll take
your word for it.

931
00:49:51,280 --> 00:49:53,480
So that's a good, that's a good
point.

932
00:49:53,480 --> 00:49:54,440
That's a good way of thinking of
it.

933
00:49:54,440 --> 00:49:57,000
I didn't think about it like.
That yeah, I mean, there are

934
00:49:57,000 --> 00:50:00,000
definite advantages to using it,
but knowing what the limitations

935
00:50:00,000 --> 00:50:03,200
are are key.
And humans have a level of

936
00:50:03,200 --> 00:50:06,080
creativity that I think is
unmatched at this point.

937
00:50:06,520 --> 00:50:08,400
Yeah, well, for now.
Forever.

938
00:50:10,200 --> 00:50:14,800
I would I would love to and and
it's and and I'm curious and you

939
00:50:14,800 --> 00:50:17,520
know, I mean going down the
sci-fi world, brave new world

940
00:50:17,520 --> 00:50:24,760
and you know, whatever it is.
I mean, if we end up, I don't

941
00:50:24,760 --> 00:50:27,040
know what, I don't know what
world our kids are going to grow

942
00:50:27,040 --> 00:50:28,320
up in.
I don't know what's going to be

943
00:50:28,320 --> 00:50:30,280
normal.
I don't know what right now we

944
00:50:30,280 --> 00:50:32,160
have our phone that I'm at that
I'm addicted to.

945
00:50:32,160 --> 00:50:34,800
I don't know what I don't know
what happens if I never get my

946
00:50:35,000 --> 00:50:36,960
to turn my phone off.
And it's just in my head.

947
00:50:37,240 --> 00:50:40,360
And I don't know how to, you
know, and I and I can't separate

948
00:50:40,360 --> 00:50:43,960
the two.
And I mean, we know that not

949
00:50:43,960 --> 00:50:46,320
that this isn't that the phone
isn't necessarily healthy and

950
00:50:46,320 --> 00:50:49,960
the best for, for development
and for retaining information

951
00:50:49,960 --> 00:50:56,000
and for general use.
So by mixing our technology with

952
00:50:56,000 --> 00:50:58,440
our brains, I'm afraid that we
won't be able to ever kind of

953
00:50:58,440 --> 00:51:00,480
turn it off and we just turn
into something else completely.

954
00:51:01,120 --> 00:51:04,840
Yeah, I mean, that's one of the
things that should we, I mean,

955
00:51:04,840 --> 00:51:06,880
can weigh and should weigh,
right.

956
00:51:06,880 --> 00:51:11,440
So I worry about that too,
because it's, you know, I have 3

957
00:51:11,440 --> 00:51:15,080
kids and they, they all have
phones because, you know,

958
00:51:15,080 --> 00:51:18,400
sometimes they have after school
activities and I need, and in

959
00:51:18,400 --> 00:51:21,200
this world, I kind of want to be
able to get in touch with them.

960
00:51:23,560 --> 00:51:28,320
You know, processing information
is very different for them now

961
00:51:28,320 --> 00:51:31,240
than it was for me growing up
because, you know, we didn't

962
00:51:31,240 --> 00:51:33,280
have cell phones.
I didn't, that wasn't a thing

963
00:51:33,280 --> 00:51:35,560
until I was really crushed with
student.

964
00:51:37,960 --> 00:51:44,080
So that needing constant
information and very short, it's

965
00:51:44,080 --> 00:51:46,280
seemingly very short attention
spans.

966
00:51:46,280 --> 00:51:50,880
It's, you know, doom scrolling
is not something that I had to

967
00:51:50,880 --> 00:51:55,280
contend with when I was younger.
And a lot of people in my

968
00:51:55,280 --> 00:51:58,640
profession have talked about how
they, you know, sort of banned

969
00:51:58,640 --> 00:52:02,000
phones from their classroom and
they just, and put the computers

970
00:52:02,000 --> 00:52:05,600
away even just so that they can
have a conversation and how

971
00:52:05,600 --> 00:52:09,400
great those conversations are.
And it was really different

972
00:52:09,400 --> 00:52:14,160
after COVID.
People sort of forgot how to

973
00:52:14,160 --> 00:52:17,320
actually have a conversation
face to face with each other.

974
00:52:17,320 --> 00:52:20,480
They were still I had students
sitting right next to each other

975
00:52:20,480 --> 00:52:22,520
in the lecture hall, texting
each other.

976
00:52:24,640 --> 00:52:28,640
So we have to learn how to
balance how to use the

977
00:52:28,640 --> 00:52:32,560
technology to our advantage
without letting it take over our

978
00:52:32,560 --> 00:52:33,280
lives.
Yeah.

979
00:52:33,280 --> 00:52:35,000
And losing all humanity.
Yeah, for sure.

980
00:52:35,000 --> 00:52:37,600
And that was in, I mean, when I
was in minutes and I was

981
00:52:37,600 --> 00:52:41,760
actually, so I was born in 95
and I was growing up just as

982
00:52:41,760 --> 00:52:44,600
cell phones were becoming pretty
much ubiquitous.

983
00:52:44,880 --> 00:52:51,040
And, and I went to, I went to an
all boys school for middle

984
00:52:51,040 --> 00:52:54,680
school and, but there were girls
on campus just in different

985
00:52:54,680 --> 00:52:57,760
classrooms.
And I found out I could text a

986
00:52:57,760 --> 00:53:00,200
girl instead of talking to her.
And instead of being 10, I was

987
00:53:00,200 --> 00:53:02,040
terrified.
I was terrified to look at a

988
00:53:02,040 --> 00:53:04,640
girl and talk to her.
And I remember, you know, in the

989
00:53:04,640 --> 00:53:08,200
feeling of 6th, 7th, 8th grade,
you know, praying and wishing to

990
00:53:08,200 --> 00:53:10,400
talk to a girl.
And then I have a cell phone and

991
00:53:10,400 --> 00:53:13,240
all of a sudden it's so easy to
strike up a conversation and I

992
00:53:13,240 --> 00:53:15,560
don't have to deal with any of
the potential rejection and

993
00:53:15,560 --> 00:53:19,200
getting shut down.
And I'm not, I would be, you

994
00:53:19,200 --> 00:53:22,440
know, socially a little bit
nervous and would I would get my

995
00:53:22,440 --> 00:53:24,560
name wrong.
Like I'd hesitate with my name.

996
00:53:24,560 --> 00:53:27,000
I'd stop there and you know, and
I'd be like, oh, crap, I'm just

997
00:53:27,040 --> 00:53:29,840
going to give up and go home and
like, I'll try again tomorrow.

998
00:53:30,160 --> 00:53:32,120
But I found out that I didn't
have to deal with any of that

999
00:53:32,120 --> 00:53:34,440
discomfort.
And why would why would I if I

1000
00:53:34,440 --> 00:53:36,800
don't have to?
And until I realized that I was

1001
00:53:36,800 --> 00:53:39,600
losing out on a muscle that I
really was really important to

1002
00:53:39,600 --> 00:53:41,440
exercise.
But I had to come to that

1003
00:53:41,440 --> 00:53:44,400
conclusion myself.
I had to say, I can't spend my

1004
00:53:44,400 --> 00:53:46,360
whole life just texting girls
what I'm going to do.

1005
00:53:46,360 --> 00:53:47,880
I, you know, what am I ever
going to do when it comes to

1006
00:53:47,880 --> 00:53:51,400
having a real conversation or
having a real confrontation or

1007
00:53:51,400 --> 00:53:55,800
anything like that?
Yeah, it's definitely a skill

1008
00:53:55,800 --> 00:53:59,320
that, you know, people are
starting to lose.

1009
00:53:59,320 --> 00:54:03,600
And I also think, you know, the
the anonymity of being behind

1010
00:54:03,600 --> 00:54:04,600
the phone.
And.

1011
00:54:05,600 --> 00:54:09,320
People feel free to say things
that they would never say to

1012
00:54:09,320 --> 00:54:14,680
you, you know, and that's,
that's problematic.

1013
00:54:14,920 --> 00:54:18,640
You know, we, we don't talk to
each other anymore and we

1014
00:54:18,640 --> 00:54:23,280
sometimes lose the positive
aspects of, of human connection.

1015
00:54:24,120 --> 00:54:26,760
And I would love to see that
come back a little bit more.

1016
00:54:26,840 --> 00:54:28,480
I think it will.
I think it will.

1017
00:54:28,480 --> 00:54:31,280
I think that I think that there
are certain indications that

1018
00:54:31,920 --> 00:54:34,800
that it's going to and I think
that this was, I think that

1019
00:54:34,800 --> 00:54:37,880
whatever mass experiment social
media was for the amount of time

1020
00:54:37,880 --> 00:54:41,320
that it that it was this kind of
experiment, people are realizing

1021
00:54:41,320 --> 00:54:42,800
on the map.
Like people are seeing how

1022
00:54:42,880 --> 00:54:46,160
unhappy a lot of people have
been in the last 10-15 years and

1023
00:54:46,160 --> 00:54:49,680
they do want to change.
Like one thing is like, that's

1024
00:54:49,680 --> 00:54:53,120
amazing how humanity is that
generations come and go fast.

1025
00:54:53,120 --> 00:54:56,440
And I think we realize and we
learn from each other.

1026
00:54:56,440 --> 00:55:00,000
You know, like I learned from my
parents things to and not things

1027
00:55:00,000 --> 00:55:02,080
to do and not to do.
And my kids will certainly learn

1028
00:55:02,080 --> 00:55:04,800
from me things to do and not to
do and we'll correct.

1029
00:55:04,800 --> 00:55:07,440
And well, you know, and I think,
and I really think that people

1030
00:55:07,440 --> 00:55:09,600
see that relationships are at
all time low.

1031
00:55:09,600 --> 00:55:12,760
Loneliness is at all time high
for everyone.

1032
00:55:12,760 --> 00:55:15,880
You know, women don't, guys are
afraid to ask girls out on dates

1033
00:55:15,880 --> 00:55:18,760
and go, you know, and, and, and,
and just, I mean, no one knows

1034
00:55:18,760 --> 00:55:20,000
how to have relationships
anymore.

1035
00:55:20,000 --> 00:55:23,000
And, and then kids are saying,
Hey, screw that.

1036
00:55:23,160 --> 00:55:24,680
I don't want to be a part of
that.

1037
00:55:24,680 --> 00:55:27,000
And you know, if, if, if
everyone says that this is

1038
00:55:27,000 --> 00:55:30,440
social media doing it, then, you
know, then I'll put it away for

1039
00:55:30,440 --> 00:55:33,120
a day a week, you know, a couple
of times a week, or I'll leave

1040
00:55:33,120 --> 00:55:36,040
it at home instead of taking it
to school or whatever it is.

1041
00:55:36,040 --> 00:55:40,120
But I think I, I, I, I am
hopeful in that in that sense, I

1042
00:55:40,120 --> 00:55:42,280
do want to actually talk to you
also.

1043
00:55:42,280 --> 00:55:45,600
And hopefully you know, this
will be the last fun part of the

1044
00:55:45,600 --> 00:55:47,480
whole thing's been fun, but the
last fun part of our

1045
00:55:47,480 --> 00:55:50,120
conversation is music in the
brain.

1046
00:55:51,800 --> 00:55:56,560
I love music.
Music means everything to me in

1047
00:55:56,560 --> 00:55:59,640
so many different capacities.
I love music for the music,

1048
00:55:59,680 --> 00:56:02,280
which I've only learned to
recently appreciate because I

1049
00:56:02,280 --> 00:56:05,280
started playing guitar.
I used to listen to music for

1050
00:56:05,280 --> 00:56:08,760
the lyrics as opposed to, you
know, as opposed to just for the

1051
00:56:08,760 --> 00:56:10,400
music.
So I'd focus more on the

1052
00:56:10,480 --> 00:56:14,600
singer-songwriter and simple,
simply simply musically

1053
00:56:14,600 --> 00:56:18,880
structured music.
And I found that they've

1054
00:56:19,240 --> 00:56:23,240
actually served very different,
as very different tools in my

1055
00:56:23,240 --> 00:56:27,320
life depending on what I'm going
through for different things to,

1056
00:56:27,400 --> 00:56:29,880
you know, for me, you know,
sometimes I need more lyric

1057
00:56:29,880 --> 00:56:34,280
based, story oriented narrative
to get me through whatever I'm

1058
00:56:34,280 --> 00:56:36,600
experiencing.
And sometimes I do need music,

1059
00:56:36,600 --> 00:56:39,840
like just the music and just the
sounds and just the melody and

1060
00:56:39,840 --> 00:56:43,120
just the interplay between the,
between the band members.

1061
00:56:44,280 --> 00:56:47,480
What how'd you get started on
this and what you know and and

1062
00:56:47,600 --> 00:56:50,440
how do you go about studying and
what do you study as far as

1063
00:56:50,440 --> 00:56:53,680
music in the brain?
Yeah, it's a really interesting

1064
00:56:53,680 --> 00:56:56,320
question because again, it's
it's really broad.

1065
00:56:56,360 --> 00:57:01,880
And I started teaching a class
called Music in the Brain with a

1066
00:57:01,880 --> 00:57:04,640
music professor.
Her name's Jennifer Kelly, and

1067
00:57:04,640 --> 00:57:06,680
she and I really want to teach a
class together.

1068
00:57:06,920 --> 00:57:11,760
And so we decided that we would
bring, you know, neuroscience

1069
00:57:11,760 --> 00:57:14,080
and and music together.
And there's so many different

1070
00:57:14,080 --> 00:57:17,200
ways you'd come at it.
And it's really interesting that

1071
00:57:17,200 --> 00:57:20,240
you were talking about lyrics
versus the melody and the tempo

1072
00:57:20,240 --> 00:57:22,600
and what's more important to you
at a particular time.

1073
00:57:23,320 --> 00:57:25,560
And when we would talk about
music, and again, we're both

1074
00:57:25,560 --> 00:57:27,920
coming at it from really
different directions, she was

1075
00:57:27,920 --> 00:57:30,920
really adamant that when we were
focusing on music, we were just

1076
00:57:30,920 --> 00:57:34,600
focusing on the more
instrumental component and not

1077
00:57:34,600 --> 00:57:37,880
the lyrics and how the lyrics
could interfere with your

1078
00:57:38,680 --> 00:57:44,160
appreciation of of the music.
And I didn't, I didn't see it

1079
00:57:44,160 --> 00:57:46,120
that way because that's not how
I was.

1080
00:57:46,400 --> 00:57:51,240
I was coming at it and our class
was very different.

1081
00:57:51,240 --> 00:57:54,560
So she would teach, you know,
about music and music

1082
00:57:54,560 --> 00:57:57,080
appreciation, and I would teach
about the brain.

1083
00:57:57,080 --> 00:57:59,840
And then we would have to bring
these two converging ideas

1084
00:57:59,840 --> 00:58:03,120
together to meet the needs of
both of our students, both the

1085
00:58:03,120 --> 00:58:05,480
neuro students and the music
majors.

1086
00:58:05,880 --> 00:58:11,520
And one of the things that I was
really fascinated about was this

1087
00:58:11,520 --> 00:58:16,360
neuroscientist and musician.
His name is Charles Lim and he

1088
00:58:17,200 --> 00:58:20,560
found a way to study creativity.
So studying creativity in the

1089
00:58:20,560 --> 00:58:23,840
brain is a really hard thing to
do because how do you define

1090
00:58:23,840 --> 00:58:26,640
creativity?
How to find it?

1091
00:58:26,640 --> 00:58:28,440
How do you define it?
Define it.

1092
00:58:28,640 --> 00:58:32,080
I would say, I would say free
flowing personalized

1093
00:58:32,080 --> 00:58:34,040
associations.
OK, great.

1094
00:58:34,320 --> 00:58:37,880
So, you know, as a scientist,
you really have to define all

1095
00:58:37,880 --> 00:58:40,480
your parameters.
You have to study, you know,

1096
00:58:40,480 --> 00:58:44,720
something very specifically.
So sometimes by defining the

1097
00:58:44,720 --> 00:58:46,760
parameters, you can sort of take
the creativity out of

1098
00:58:46,760 --> 00:58:53,400
creativity.
But he studied the changes in

1099
00:58:53,400 --> 00:58:56,720
neural activation patterns using
functional magnetic resonance

1100
00:58:56,720 --> 00:59:01,920
imaging and jazz so had.
Improv music for the most.

1101
00:59:02,520 --> 00:59:05,080
Yeah.
So we had them play a structured

1102
00:59:05,080 --> 00:59:09,040
component and then a more free
flowing component and looked at

1103
00:59:09,040 --> 00:59:11,280
the the activation patterns in
the brain.

1104
00:59:11,680 --> 00:59:16,480
And I just thought that this was
just that in itself was super

1105
00:59:16,480 --> 00:59:21,160
creative and fascinating.
And I was also really interested

1106
00:59:21,160 --> 00:59:24,360
in the use of music at in
therapy.

1107
00:59:25,200 --> 00:59:30,200
Yeah, so using music and the
tone and the pacing of music to

1108
00:59:30,200 --> 00:59:34,200
help people with motor
impairments or help people who

1109
00:59:34,200 --> 00:59:38,520
had lost their ability to speak
for whatever reason, to actually

1110
00:59:38,520 --> 00:59:41,360
sing the lyrics even though they
couldn't sing the words, as

1111
00:59:41,360 --> 00:59:45,680
opposed to speaking the words
and how that can be used to sort

1112
00:59:45,680 --> 00:59:51,400
of bypassed areas of damage.
So when we taught this class, we

1113
00:59:51,400 --> 00:59:57,240
used music to express emotion.
One of the things I find

1114
00:59:57,240 --> 01:00:01,360
fascinating is I used an example
of, you know, the Halloween

1115
01:00:01,360 --> 01:00:04,480
movie where the pumpkins sort of
getting closer and closer to

1116
01:00:04,480 --> 01:00:07,080
you.
Yeah, you turn the music off.

1117
01:00:07,360 --> 01:00:09,360
Yeah.
Totally not scary.

1118
01:00:09,480 --> 01:00:14,000
Sit all the time.
You have the music on, you know,

1119
01:00:14,000 --> 01:00:17,160
your heart rate starts and your
galvanic skin response and you

1120
01:00:17,160 --> 01:00:21,440
know, your hands start sweating.
The music is such a powerful

1121
01:00:21,440 --> 01:00:26,280
influence over our emotions and
our movement and you know.

1122
01:00:26,320 --> 01:00:28,040
Breathing even and our
breathing.

1123
01:00:28,040 --> 01:00:31,120
I've noticed that with, with
tense movies, I, I, I, my

1124
01:00:31,120 --> 01:00:34,080
breathing slows down right
before something really scary

1125
01:00:34,080 --> 01:00:36,200
happens.
And if I'm scared, I force

1126
01:00:36,200 --> 01:00:39,440
myself to take deep breaths
while while I watch the horror

1127
01:00:39,440 --> 01:00:41,920
movie that I that I'm being
forced to watch.

1128
01:00:43,520 --> 01:00:46,960
But and then the music in that
is like a whole nother character

1129
01:00:47,080 --> 01:00:49,400
to the movie outside of the
actors, right?

1130
01:00:49,840 --> 01:00:52,200
It helps to elicit those
emotions.

1131
01:00:52,400 --> 01:00:54,600
And I find all of that really
fascinating.

1132
01:00:54,600 --> 01:00:57,680
So This is why we want to teach
that class.

1133
01:00:57,680 --> 01:01:00,640
Actually, I had some students I
haven't been teaching the last

1134
01:01:00,640 --> 01:01:03,440
couple years because I was Dean
for a few years and I'm on

1135
01:01:03,440 --> 01:01:06,920
sabbatical right now.
And a student said that they

1136
01:01:06,920 --> 01:01:09,240
were graduating next year and I
really needed to teach that

1137
01:01:09,240 --> 01:01:13,800
class.
So I'm, I'm hoping to, but

1138
01:01:13,800 --> 01:01:16,480
again, it's one of those classes
that I think is better taught

1139
01:01:16,680 --> 01:01:19,520
when you have people who are
experts in two different fields

1140
01:01:19,520 --> 01:01:22,680
and you're bringing those
together rather me trying to

1141
01:01:22,680 --> 01:01:24,920
just teach it all by myself.
Totally.

1142
01:01:24,960 --> 01:01:27,160
That's really, really cool.
That's I never even heard of

1143
01:01:27,160 --> 01:01:29,600
collaborative classes like that.
I've never taken any in college

1144
01:01:29,600 --> 01:01:31,080
at least It's really.
Cool.

1145
01:01:31,080 --> 01:01:34,480
They're the most challenging to
teach from the side of a

1146
01:01:34,480 --> 01:01:37,400
professor, but they're the most
interesting.

1147
01:01:37,400 --> 01:01:40,120
It's actually twice the amount
of work as opposed to half the

1148
01:01:40,120 --> 01:01:42,320
amount of work, but I think
they're the most most

1149
01:01:42,320 --> 01:01:45,840
interesting for students.
I bet, I bet that's really, it's

1150
01:01:45,840 --> 01:01:49,720
really awesome.
I I'm also curious and there's

1151
01:01:49,720 --> 01:01:52,880
so much to go into, at least
from what we, the brief, the

1152
01:01:52,880 --> 01:01:57,280
brief, the brief overview.
But first of all, I'm also

1153
01:01:57,280 --> 01:01:59,720
curious about the relationship
between lights and music because

1154
01:01:59,720 --> 01:02:04,400
I know that, for example, when
and I've gone to some concerts

1155
01:02:04,760 --> 01:02:07,760
where, you know, I've listened.
So I'm actually much more

1156
01:02:07,760 --> 01:02:14,160
nowadays into the improvisation
improv provisional, thank you

1157
01:02:15,280 --> 01:02:19,280
Grateful Dead and and strings
and like that whole that whole

1158
01:02:19,280 --> 01:02:22,080
genre of music.
And one thing I didn't notice

1159
01:02:22,080 --> 01:02:25,040
I've noticed is that when I've
gone to see shows, cover shows

1160
01:02:25,040 --> 01:02:28,080
or real shows, an enormous
component Fish, which is a

1161
01:02:28,080 --> 01:02:31,040
famous jam band from your neck
of the woods to play around

1162
01:02:31,040 --> 01:02:35,080
there.
They they're they're light sky

1163
01:02:35,080 --> 01:02:37,680
is known as a six member of the
band because or the 5th member

1164
01:02:37,680 --> 01:02:40,800
of the band because it the
lights are so integral to the

1165
01:02:40,800 --> 01:02:42,680
audience experience during the
concert.

1166
01:02:42,680 --> 01:02:45,480
And there's something about when
music is playing that activates

1167
01:02:45,720 --> 01:02:49,640
another part of your brain that
and it's so interesting because

1168
01:02:49,640 --> 01:02:52,960
songs almost feel like they take
like they have color tones to

1169
01:02:52,960 --> 01:02:54,600
them.
So if like if you're playing a

1170
01:02:54,600 --> 01:02:57,520
song and then the and then the
and then the whole place flashes

1171
01:02:57,520 --> 01:02:59,520
red.
There's something about like the

1172
01:02:59,520 --> 01:03:02,600
relationship between the tone of
the music and the color that's

1173
01:03:02,600 --> 01:03:07,280
being flashed, you know it
across the room and it enhances

1174
01:03:07,280 --> 01:03:10,000
the experience to a tremendous
degree.

1175
01:03:10,000 --> 01:03:12,720
I mean, I, I can't even compare
listening to that kind of thing

1176
01:03:13,000 --> 01:03:15,840
even on great speakers at home
and then being there with the

1177
01:03:15,840 --> 01:03:17,440
crowd with the lights flashing
like that.

1178
01:03:17,440 --> 01:03:20,200
I'm curious if there's if you if
you've noticed any overlay

1179
01:03:20,400 --> 01:03:22,680
between the two.
You know, that's really

1180
01:03:22,680 --> 01:03:24,480
interesting.
And I've never studied the

1181
01:03:24,480 --> 01:03:28,640
interplay between.
So in this case, like your

1182
01:03:28,640 --> 01:03:33,240
emotional connection to the
music with, you know, what's

1183
01:03:33,240 --> 01:03:37,080
being presented visually and
what's going on in the brain.

1184
01:03:37,080 --> 01:03:39,040
So I haven't actually studied
that.

1185
01:03:39,040 --> 01:03:41,320
And, you know, when we're
studying something, the more

1186
01:03:41,320 --> 01:03:46,640
variables we put into the mix,
sometimes the more limit them.

1187
01:03:47,080 --> 01:03:51,120
But now that you said that, now
I'm actually curious and I I

1188
01:03:51,120 --> 01:03:54,080
want to go look and you know.
Get some, get some, get some

1189
01:03:54,080 --> 01:03:55,680
funding and go to the sphere in
Vegas.

1190
01:03:56,040 --> 01:03:58,880
You can check out over there I
mean.

1191
01:03:59,320 --> 01:04:01,280
Experimental Lab.
Real Life.

1192
01:04:01,640 --> 01:04:05,120
Experimental Lab and you and
there is no, there's no venue

1193
01:04:05,120 --> 01:04:07,920
like this fear and it's, and
it's so immersive.

1194
01:04:07,920 --> 01:04:09,880
And I mean, I don't know if
you've ever seen any videos of

1195
01:04:09,880 --> 01:04:13,720
it, but oh, man.
I mean, and I mean, I don't know

1196
01:04:13,720 --> 01:04:18,280
what kind of music you listen
to, but just about most great

1197
01:04:18,280 --> 01:04:21,080
bands have, you know, like a
band that you will certainly

1198
01:04:21,080 --> 01:04:23,360
appreciate has played there
where you can kind of see the

1199
01:04:23,360 --> 01:04:25,640
way they make use of, of, of
everything.

1200
01:04:25,640 --> 01:04:29,360
And you know, we know that music
also turns on the, the visual

1201
01:04:29,360 --> 01:04:32,160
aspect of our brain too.
I I do a creative writing

1202
01:04:32,160 --> 01:04:36,680
assignment with my students who
I'll play a well play a score,

1203
01:04:36,680 --> 01:04:39,640
I'll play an instrumental piece
and have them write the image

1204
01:04:39,640 --> 01:04:41,560
that pops up in their head from
the music.

1205
01:04:42,080 --> 01:04:44,560
Yeah.
And there's sometimes where it's

1206
01:04:44,560 --> 01:04:48,880
remarkable how 10 students or 15
students can all come up with

1207
01:04:49,200 --> 01:04:51,560
extremely similar themes from
music.

1208
01:04:51,560 --> 01:04:55,360
And you wonder, you know, is it
is that just association wiring?

1209
01:04:55,360 --> 01:04:57,960
Like, you know, the pirates type
of fat pirates in the Caribbean

1210
01:04:57,960 --> 01:05:00,080
theme?
Like everyone recognizes that

1211
01:05:00,080 --> 01:05:01,440
that's going to be pirate music,
right?

1212
01:05:01,440 --> 01:05:04,160
But what if there's music that's
a little bit less well known?

1213
01:05:04,400 --> 01:05:06,960
And then one person thinks it
reminds them of a field, another

1214
01:05:06,960 --> 01:05:09,400
person thinks reminds them of an
old French villa.

1215
01:05:09,400 --> 01:05:12,240
You know, I mean you, you, you
know, So I've had a lot, a lot

1216
01:05:12,240 --> 01:05:14,920
of fun tinkering around students
perception of music too, and

1217
01:05:14,920 --> 01:05:17,960
it's really cool.
Yeah, usually, you know, so when

1218
01:05:17,960 --> 01:05:21,880
I teach introduction to
neuroscience class, I'll take a

1219
01:05:21,880 --> 01:05:25,280
song that was, you know, very
popular over the summer,

1220
01:05:25,280 --> 01:05:28,160
whatever song that may be, and
I'll play a clip from it.

1221
01:05:28,160 --> 01:05:30,680
And I just tell the students,
just just free, right, right,

1222
01:05:30,680 --> 01:05:33,000
whatever comes to your mind.
And then we talk about all those

1223
01:05:33,000 --> 01:05:36,200
different aspects, and it helps
me to introduce the idea that

1224
01:05:36,880 --> 01:05:39,760
although there are parts of your
brain that are responsible for

1225
01:05:39,840 --> 01:05:43,200
vision and auditory, your brain
is all interconnected, right?

1226
01:05:43,200 --> 01:05:48,720
So it's the circuitry that
ultimately gives us this sense

1227
01:05:48,720 --> 01:05:52,520
of connectedness between visual
and auditory and, and movement

1228
01:05:52,520 --> 01:05:55,840
and so on and so forth.
And it's that part of the brain

1229
01:05:55,840 --> 01:06:00,440
that really fascinates me.
Yeah, I have a friend and maybe

1230
01:06:00,440 --> 01:06:02,880
you could speak to this.
I have a good friend of mine who

1231
01:06:02,880 --> 01:06:05,280
has, I mean, he's very good
about it, but he has a little

1232
01:06:05,280 --> 01:06:07,920
bit of a stutter.
And one of the ways that he

1233
01:06:07,920 --> 01:06:11,600
deals with it is if he catches
himself stuttering, he'll kind

1234
01:06:11,600 --> 01:06:14,840
of slow down on that word.
So if he was going to stutter on

1235
01:06:14,840 --> 01:06:19,760
the West of the word, it's a,
it's this herd that I'm having a

1236
01:06:19,760 --> 01:06:23,600
hard time with.
He does rap and he is an

1237
01:06:23,920 --> 01:06:27,560
excellent rapper and he is
incredibly creative and he has

1238
01:06:27,560 --> 01:06:30,920
no problems just freestyling and
coming up with that.

1239
01:06:32,080 --> 01:06:36,160
Can you speak to the, you know,
is it the beat that's doing it?

1240
01:06:36,160 --> 01:06:39,000
What's happening with the
stutter that is that that or I

1241
01:06:39,000 --> 01:06:41,200
guess I don't know if you could
speak about his particular case,

1242
01:06:41,200 --> 01:06:45,200
but in general what happens?
Yeah, you'll even hear about.

1243
01:06:45,200 --> 01:06:51,640
So something about the beat and
the music has been very helpful

1244
01:06:51,640 --> 01:06:55,040
in a lot of different aspects.
So somebody with movement

1245
01:06:55,040 --> 01:06:58,880
disorder might use music and
might dance fluidly, but then

1246
01:06:58,880 --> 01:07:02,040
when the music stops, when they
have, you know, when they lose

1247
01:07:02,040 --> 01:07:09,640
that thing to attach to, to help
preempt the next motion, now

1248
01:07:09,640 --> 01:07:12,480
they might lose their ability to
move as fluidly.

1249
01:07:12,640 --> 01:07:16,840
Or somebody with Tourette's
syndrome might use excuse.

1250
01:07:17,040 --> 01:07:19,040
Me Billie Eilish has Tourette's
syndrome, apparently.

1251
01:07:19,040 --> 01:07:22,360
I didn't know about that.
Yeah, and she and she's talked

1252
01:07:22,360 --> 01:07:24,600
about how music has helped her,
has helped her navigate her way

1253
01:07:24,600 --> 01:07:28,320
through it.
Yes, yes, there is an excellent

1254
01:07:28,320 --> 01:07:29,840
movie.
I think it's called The Tick

1255
01:07:29,840 --> 01:07:34,320
Code with and it's about a
little boy who has Tourette's

1256
01:07:34,320 --> 01:07:38,480
and how he's a musician and he
connects with another musician

1257
01:07:38,480 --> 01:07:40,520
who also has Tourettes that he
didn't know about.

1258
01:07:40,520 --> 01:07:46,680
And and how music helps with
their, you know, to control

1259
01:07:47,440 --> 01:07:50,800
their motor ticks and help them,
you know, connect with

1260
01:07:50,800 --> 01:07:54,080
something.
It's music is really powerful

1261
01:07:54,480 --> 01:07:57,600
and we haven't even scratched
the surface, I don't think.

1262
01:07:57,600 --> 01:08:00,520
And all you know and the power
it actually holds.

1263
01:08:01,520 --> 01:08:04,320
I think we've written an oath as
an art instead of looking at it

1264
01:08:04,320 --> 01:08:07,360
at the science.
Yes, I would absolutely agree

1265
01:08:07,360 --> 01:08:10,920
with that.
And yeah, it feels a little bit

1266
01:08:10,920 --> 01:08:18,000
like a shame that we that we do
that because we, I mean, we even

1267
01:08:18,000 --> 01:08:21,800
know the impact of there have
been so many times in my life

1268
01:08:22,359 --> 01:08:25,640
where I felt the weight of the
world, you know, when I was in

1269
01:08:25,640 --> 01:08:27,760
my early 20s and I had no idea
what I was going to do with

1270
01:08:27,760 --> 01:08:29,600
myself.
And I and everyone around me

1271
01:08:29,600 --> 01:08:31,439
felt like they had everything
worked out and were moving on

1272
01:08:31,439 --> 01:08:32,640
with their lives.
And I didn't.

1273
01:08:32,960 --> 01:08:35,479
And then they were.
And I would just RIP down the

1274
01:08:35,479 --> 01:08:38,520
highway and listen to music and
like, that was the only thing

1275
01:08:38,520 --> 01:08:41,040
that was going to, you know,
help me at that moment or set me

1276
01:08:41,040 --> 01:08:43,920
free at that moment.
Bruce Springsteen has saved my

1277
01:08:43,920 --> 01:08:47,960
life, saved me many times
throughout the years, you know,

1278
01:08:47,960 --> 01:08:52,200
but but there's something about
like, like there's something

1279
01:08:52,200 --> 01:08:55,520
interesting about the fact that,
hey, if I'm down, listening to

1280
01:08:55,520 --> 01:08:57,680
happy music doesn't necessarily
work to pick me up.

1281
01:08:57,760 --> 01:08:59,920
Sometimes I have to listen to
sad music when I'm down.

1282
01:09:00,000 --> 01:09:03,240
And then I'm like, Oh, now I'm
better, you know, and, and what

1283
01:09:03,240 --> 01:09:05,080
is that and why and why do we
feel that way?

1284
01:09:05,080 --> 01:09:07,760
And that's a science too, you
know, that that should be

1285
01:09:07,760 --> 01:09:09,760
something that we should be
employing and using.

1286
01:09:09,760 --> 01:09:12,859
My first podcast, one of my
first real guests, the quote UN

1287
01:09:12,859 --> 01:09:17,439
quote that you could say was
actually some, I believe she's a

1288
01:09:17,439 --> 01:09:21,600
nurse or a therapist down here
in South in University of Miami.

1289
01:09:21,960 --> 01:09:26,120
And she's a music therapist and
she uses the ukulele and the

1290
01:09:26,120 --> 01:09:28,399
piano and she uses it to help
student.

1291
01:09:28,399 --> 01:09:32,640
She uses it to help in all sorts
of fact faculties and with all

1292
01:09:32,640 --> 01:09:34,720
sorts of patients.
I think primarily with the youth

1293
01:09:35,240 --> 01:09:38,040
with kids, but they've been
expanding the program and she's

1294
01:09:38,040 --> 01:09:41,160
like, we can't even hire enough
music therapists is how popular

1295
01:09:41,160 --> 01:09:44,080
and how useful it's been.
So I hope that there's an

1296
01:09:44,080 --> 01:09:45,319
industry that keeps on taking
off.

1297
01:09:45,760 --> 01:09:47,760
Me too.
OK.

1298
01:09:47,760 --> 01:09:50,080
What are so to wrap up, what are
a couple of things that you're

1299
01:09:50,080 --> 01:09:53,319
looking forward to that you're
that you're I guess hopeful for,

1300
01:09:53,399 --> 01:09:56,000
I guess or excited about and
when some of the things that you

1301
01:09:56,000 --> 01:09:59,360
were a little nervous about that
you would like to at least

1302
01:09:59,520 --> 01:10:03,640
people to bear in mind?
In terms of science or just life

1303
01:10:03,640 --> 01:10:06,200
or.
Yeah, whatever you think is

1304
01:10:06,560 --> 01:10:10,520
important.
You know, so I always, I always

1305
01:10:10,520 --> 01:10:14,080
go to my kids first.
I'm, you know, curious what life

1306
01:10:14,080 --> 01:10:17,040
is going to be like for them and
whether I've prepared them

1307
01:10:17,040 --> 01:10:19,320
enough to meet all of those
challenges.

1308
01:10:19,320 --> 01:10:22,640
And, you know, they're
incredible people.

1309
01:10:22,640 --> 01:10:25,120
And although they're all my
kids, they're all, you know,

1310
01:10:25,120 --> 01:10:29,640
very different.
So, you know, I'm interested in

1311
01:10:29,720 --> 01:10:33,280
in what the world is going to be
like for them and how they are

1312
01:10:33,280 --> 01:10:37,360
going to contribute to it.
In my field.

1313
01:10:38,160 --> 01:10:42,920
I would love if, you know, the
tool that we developed through,

1314
01:10:42,960 --> 01:10:47,840
you know, decades of science
actually helps somebody what

1315
01:10:47,840 --> 01:10:52,440
that be the BCI or whether we're
able to detect reading

1316
01:10:52,440 --> 01:10:55,600
impairment so that kids can get
help as soon as possible.

1317
01:10:56,720 --> 01:11:01,000
I would love to be able to, you
know, give it forward to have a

1318
01:11:01,200 --> 01:11:04,320
positive impact on others lives.
Definitely, definitely.

1319
01:11:04,640 --> 01:11:08,400
Well, Doctor Lisa Gable, thank
you so, so much for coming.

1320
01:11:08,400 --> 01:11:10,000
This is so much fun.
I hope you had fun with the

1321
01:11:10,000 --> 01:11:13,640
second podcast experience.
You were excellent.

1322
01:11:13,840 --> 01:11:16,920
And and I hope to do this again
because this is so much fun.

1323
01:11:16,920 --> 01:11:20,880
And when you have some exciting
new things, you can let me know.

1324
01:11:20,880 --> 01:11:23,160
I'll check back in.
But I'm really, I think this is

1325
01:11:23,160 --> 01:11:24,320
a lot of fun.
I'm really excited.

1326
01:11:24,320 --> 01:11:25,680
I hope to.
I hope to stay in touch.

1327
01:11:26,160 --> 01:11:27,800
Thank you for having me, I
really appreciate it.

1328
01:11:27,960 --> 01:11:28,880
It's a blast.
Take care.

1329
01:11:28,880 --> 01:11:30,880
Bye bye.
OK.

1330
01:11:30,880 --> 01:11:33,680
What do you think?
That was fun.

1331
01:11:33,680 --> 01:11:35,320
I just realized that I had like.