Time is something that most fields don't get
to until they sort of, you know, gain enough
courage or craziness to tackle. But it's so,
so fundamental to the broad principles of organization
of the brain. The human brain is the most complex
structure in the known universe, and we are in
the middle of a scientific revolution to understand
its inner workings. Join us for a conversation
with world -renowned neuroscientists as they
visit Rochester. I am Dr. John Foxe, Director
of the Del Monte Institute for Neuroscience at
the University of Rochester, and you are listening
to Neuroscience Perspectives. I'm John Foxe, Director
of the Del Monte Institute for Neuroscience here
at the University of Rochester, and I'd like
to welcome you to another episode of Neuroscience
Perspectives. I'm absolutely thrilled today to
introduce my guest, Dr. Kia Nobre. Dr. Nobre
is the Director of the Centre for Neurocognition
and Behaviour at the Wu Tsai Institute at Yale
University. She recently returned to her alma
mater after spending the majority of her career
at Oxford University, where she held several
major leadership roles. including the director
of the Oxford Centre for Human Brain Activity.
She is an international member of the National
Academy of Sciences and a fellow of the British
Academy, and she has received numerous honours,
including Lifetime Mentor Award from the Association
for Psychological Science, the MRC Suffrage Science
Award, the Broadbent Prize from the European
Society for Cognitive Psychology, and the D.
Carvajal Heineken Prize for Cognitive Neuroscience.
Her discoveries have literally revolutionized
our understanding of human brain and behavior.
So thank you, Dr. Knope, for being here on Neuroscience
Perspectives with us. Let's dive in. Let's dive
straight in with your research. We've known each
other quite some time, and actually we do stuff
in the same kind of vein. So I have been a huge
fan, and I've followed your work for... I shouldn't
say decades, but it is decades. Decades, likewise,
yes. So, and, you know, I always think of you
as an attention researcher. But you've really
spanned the gamut, looking at sort of the role
of cognition in determining behavior. And one
specific area is this business of time. attention
or cognition in time and frameworks of time.
So why time and why is it so important? I'm like
voraciously curious about the brain, always have
been as long as I can remember. And, you know,
when I was a graduate student, I didn't know
what I was going to do. Am I going to do cellular,
molecular, systems level, human stuff? So I'm
really curious about the whole breadth of it.
And so I kind of found a trick, which is to study
some things that are relevant. to everything
so that I can kind of dabble in understanding,
you know, ultimately trying to pick up the broad
principles of organization of the brain. So in
my sort of way of thinking about attention, it's,
you know, really maybe not about our... colloquial
definition of it but it's really about how the
brain picks out the relevant information out
in the world and how it does that proactively
dynamically as we moving around the world and
you know meanwhile how it's putting all those
signals together how it's putting away other
things and all of this is also happening through
time and you know and I think that time is something
that most fields don't get to until they sort
of you know gain enough courage or craziness
to tackle. But it's so, so fundamental to the
broad principles of organization of the brain.
So for me, like studying attention and studying
attention in a dynamic, temporally structured,
proactive way is a way of kind of carving out
the core principles of brain organization. And
it goes back to this idea of a limited resource,
right? There's only so much you can take on at
any given time, which is kind of how I think
most of the field think about it. I'm going to
attend over here, not over there. I'm going to
attend to red and not blue and so on. And those
are in instantaneous time. And so you've said,
I need to understand this as it plays out across.
an episode or a period. You know, I think that
framing that you gave is like the textbook framing
of the field. You know, like we have limited
resources, there's bottlenecks, and it kind of
emphasizes sort of the limitations of our mental
capacity and our brain. I like to think about
it a different way. I think that actually the
brain is pretty clever of trying to pick out
the right things in order to plan for adaptive
behavior. So it's kind of always ahead of the
game and picking out things to do as far as it
can tell what's going to be the right thing next.
So I kind of think of this idea of picking out
information as a positive, constructive, proactive
thing for guiding behavior rather than because
we have these limited resources. And I also think
that that kind of framing of the limited resource
doesn't really tell us anything about how it
works. So I think it's true that there are some
limitations in the brain, but we should think
about how do they come about? What kind of nature
are they and how does that? So I think a lot
of it is, you know, we pick up the world through,
you know, our different, you know, quite restricted
sensors. Then we split out that information into
lots and lots of different features. They're
all rumbling around the brain at different, you
know. and looping around. And somehow we have
to put that all together. So I think the constraints
are really about when there's overlap of information
hitting on the same cells, how do the cells know
who to connect to. And it's not about that there's
just too much. It's the problem of stitching
it all together again that I think is the tough
bit. Does it go hand in hand? Theories come and
go in our field and we're all about predictive
coding at the moment. This idea of having like
a model and projecting out into the future. Is
it related to that? Yeah, I mean, I think, you
know, attention research has been looking at
that stuff for a long time. And I think predictive
coding, so I don't want to bad mouth predictive
coding. I love predictive coding colleagues.
But, you know, predictive coding has come in
as almost like a new framework. But it's an old
idea. Yeah, and I think the two fields could
do better at finding the points of conciliation,
convergence, mutual information. So I think a
lot of the predictive coding literature has emphasized
the fact that if you already know something,
then you don't actually need to process it because
you kind of filter it out and you just process
the things you don't know. Whereas the attention
literature... tells you exactly the opposite.
It says if you know things, you can put them
to really good use and do that thing to the best
of your ability, like if you're in a tennis game
or, you know, marathon and having to figure out.
I think that both of those things are probably
correct, and they happen probably in different
circumstances, within different mechanisms, and
possibly within different circuits. But I think,
you know, sometimes the predictive coding has
kind of swept the attention. field under the
carpet and I think it would be much better if
we bring all those threads together and build
a better tapestry out of it. Tell me something
that you've learned about a mechanism that keeps
track or divvies out my resources in this temporal
way over time. Would you have a simple answer
to that or is that an impossible question? I'm
not sure what you mean, but I think we can read
out the fact that the brain is pre -playing and
pre -playing things in time. We can read these
things out. We can read out what you're focusing
in mind based on what you're going to have to
retrieve all the way to your eyeballs by measuring
your pupil. We can look at how the brain is selectively
focused on the information it's going to need
to retrieve at a given moment. We can measure
that from your eyes, for example, which is pretty
crazy. So seeing the signals in neuron circuits.
Using electrophysiology or imaging and saying,
yeah, this area. And even physiological signals
all the way to, you know. Right, and the periphery.
Yeah. Right, right. And is that, like, do oscillations,
for example, like, you know, as part of a temporal,
a way to hold on to time. Yeah. Is that a player
in this? There are a lot of potential players
in time processing at the moment. And I think
that, I don't think we have a. consensus, broad
understanding of which of the many potential
mechanisms that might be contributing to this.
For example, there are oscillations. Oscillations
have been proposed as keeping beats and keeping
tempos and possibly structuring a bit of our
active sensing of the world. There are also activity
in neurons that ramp up to anticipated moments.
There are dynamical systems that are very dynamical
and that At given moments of time, if something
happens that's important, you get a plasticity
event, which then consolidates that state, which
intrinsically carries time information in it.
So there are lots and lots of different types
of potential time -contributing mechanisms, and
I think a really big challenge for the field
is going to be to... try to understand, like,
do all of these happen? Are some of them incompatible
with each other? Do some serve certain purposes
or others? And I don't think that we'll, you
know, John, you and I, we're not going to be
able to do this only with the human methodology.
So I think this is going to take a concerted
effort of colleagues working across scales, you
know, all the way to some of the cellular mechanisms,
but also, you know, very importantly, like the
animal models, circuit models, to try to put
it all together. Very good. So I'm going to pull
back up a little bit. I recently saw you giving
the Fred Cavley Distinguished Contributors Award
lecture at the Cognitive Neuroscience meeting
in Toronto. I was out there in the adoring crowd.
And I was really struck by what you did there.
You pulled back and did one of those 30 ,000
-foot sort of career -wide things. And a number
of things you said there. struck me what one
was you talked about us as a young immature field
yeah and and another thing you said was you know
we've gone down many cul -de -sacs you've you've
you know having a sort of front row view from
really the very early days of cognitive neuroscience
so so two things two questions for you there
are we still young are we maturing um is there
a lesson to be learned about ways that going
forward we don't track ourselves down these cul
-de -sacs do you have an insight on that you
know now that you're in this really enormous
leadership role. Thank you for that question.
First of all, I really agonized about whether
I should give that kind of talk or whether I
should just talk about the trajectory of my own
science. I feel like some of those messages are
important enough to me that I thought maybe it
was important to say them out loud and not just
to my people in my own research group. I know
the audience appreciates that. Maybe that actually
goes to the immaturity pieces. We need the...
the foundational people in the field to step
up that and and really take that longer view
and say like what are we doing here and are we
are we really approaching these questions in
the right way i mean i think you know i think
we are in an amazingly exciting time i mean in
our you know, careers. We've seen all of the
human neuroimaging methodology emerge and it
keeps, you know, it keeps transforming and advancing
at, you know, a relentless pace. And we've learned
a lot really very, very fast. And I think the
thing which, you know, you know, naturally we're
swept away by how much we've learned and how
smart we are and how much smarter we are than
we were 10 years ago and stuff. But I would say
that, yeah, we are. crawling as a science you
know first of all a point that I made only I
just mentioned this and I didn't talk about it
in my talk is that our science had a really tough
genesis. People did not believe that you should
or could understand the subjective mind. You
can understand the brain, the organ, but actually
understanding cognition was not something that
people thought should happen necessarily in the
1800s and 1700s. So if you read some of the original
papers of some of those pioneers, like Wundt,
for example, or Helmholtz, those people were
fighting. deep prejudice to sort of you know
create you know psychophysics and psychophysiology
and all these different approaches that we have
today so we started late we started much later
than most other sciences and yeah the mind is
hard you know it's subjective it's crazy stuff
to try to get a hold of we have to triangulate
it you have to get it through behavior through
brain you know you can't you can't measure it
necessarily directly so you have to kind of approach
it so it's it's it's a hard science and I think
if you look at the state of our field we still
kind of you know really the the grounding start
point for most people are is just intuition how
do we think oh we make a decision we have this
choice or that choice we you know it's very much
folk psychology intuition still grounding us
we don't have like a formal language of the field
and and you know I think we're doing really well
I don't think we're immature I think we're young
yeah so would you mean things like you know right
we have these this sort of taxonomy of terms
that, you know, consciousness. We don't even
have a good taxonomy yet, you know. Yeah, attention.
Yeah. And I know you think we may need to really
re, even re -examine those concepts. I think
we're going to, I think. Constructs. I think
many of those things will probably, you know,
if we're successful, many of those things are
going to be radically transformed and we will
have a different understanding. You know, it
could be, you know, that it's more of an evolutionarily
rooted thing. It could be, you know, that we
focus more on the senses and sensory motor anchors
or. I don't know what it's going to look like,
but I think we're still carrying a lot of folk
psychological baggage with us. Right. So I think,
you know, I think we are in the stage like kind
of the... aristotelian slash newtonian phase
of like you know we kind of use common sense
observation intuition but yeah we have amazing
measuring tools and they keep getting better
and better we can quantify and measure and relate
but we haven't kind of gotten to that core theoretical
principles we're not like where some of the quantum
physics and some of the other more advanced and
would you say in some ways those are advanced
science because the questions themselves are
more tractable is it does it go back to that
business of complexity i think that's part of
it you know obviously the universe is also very
complex and the mind is only you know one part
of it but I think complexity matters and also
the fact that yeah the mind is still I would
say the biggest you know mystery in the universe
still so I'm looking forward to things getting
really crazy you know so and I think you said
that you know how do we avoid cul -de -sacs I
think the other thing is you know one thing are
psychology has been really good at is kind of
revealing to us what social animals we are. So,
you know, everything we do is social, political,
you know, and we work as kind of tribes, you
know, our labs and things. So I say, oh, look,
John Fox is doing this. Oh, I don't think he
used the right interval. I'm going to do it right.
So we end up kind of, you know, creating little
cottage industries of working on, we're working
on these, you know, there's a big territory.
It can get a little esoteric sometimes. Yeah,
it gets esoteric. We build like very, crowded
neighborhoods of research and then other vast
interesting landscapes are left open. So the
thing I try to do is just always like know your
stuff, you know, like bring some scholarship
along, but just look at it with really open eyes,
you know, curiosity, look at it for what's out
there, you know, is this question everything.
So I think, you know, I don't, it doesn't always
work, but it kind of helps you getting, you know,
stuck in, in like, you know. fashion corners
of the field i think absolutely so and then projecting
out like if you were giving some advice to the
younger obviously you do this all the time with
your graduate students and trainees and that
you know what do you say to them about that like
getting on stock or or framing out the questions
in a way that that will make them meaningful
and important yeah i i sometimes uh feel for
people in my lab because uh you know i i really
push them hard to um to To make their own decisions
and really to think, like, is this really interesting
to you? Do you care about this? Do you, you know,
what do you think is going to, you know, how
is this going to change the way you think about
things? Is this going to change our understanding
of things? I really try to operate at that very
basic low level where I think things are really
important. So I really try, and I think, you
know, there are many ways to be a successful
mentor, but sort of my approach is really to,
try to help each individual find meaning and
joy and their own you know pathway of the balance
of productivity for themselves so i i try not
you know i'm not one of those things like everyone
has to do this every month and here we do you
know it's all very more organic it's kind of
intense and organic yeah uh working on personhood
as well as just Like, you know, this is a great
project. And not just the person as a scientist,
but the whole person, you know, like, I mean,
I think you're only going to do great science
if you're really happy and if it fits in your
life. So, yeah, that's very good. And of course,
you had some extraordinary mentors. I had the
great privilege of knowing two of your foundational
mentors, Greg McCarthy and Truett Allison. Can
we talk a bit about that, like the mentorship
in your life and maybe some people that lifted
you up and framed the way you approach things?
Absolutely. I mean, I think I've been so lucky.
I've had pretty much only support and championing
and enthusiasm from people I've worked with.
Of course, everybody's weird and quirky from
close up, and you have to embrace the quirks
of your mentor. Especially in our business. Yeah,
absolutely. I just always try to take the best
out of people. So Truett Allison, who, as you
know, has now passed, I mean, he was one of the...
very modest giants in the field. You know, I
remember him singing, you know, country music
and I can't actually sing some of the songs because
they're not repeatable in public. He was a super
funny guy and he was part of the beatnik generation,
you know, traveling around in his convertible
in the 50s. But yeah, you know, his mentor and
he were the people who turned squiggly lines
into ERPs, event -related potentials. And then,
you know, Greg. super methodical, brilliant.
He really cared about the big conceptual questions
and trying to get the best out of the methods
and really always pushing the methods. He was
at Yale at the time when there was the rumblings
of the big MR revolution. He was the one who
really... initiated the first cognitive study
with using non -invasive MRI. And he had made
all the connections with all the biophysics and
the biochemistry and the physics guys and brought
the monkey people together. And he had that kind
of entrepreneurship and methodological initiative,
which he still has. So actually, one of the best
things, so it's a bit of a tangent, but going
back to Yale after 30 years at Oxford is reuniting
with Greg, because Greg also had left and now
he's back there. The other thing that Truett,
was amazing about is is i mean he didn't do this
um explicitly it was just him he just created
such an amazing culture so we all had lunch together
all the time and he had funny championships that
he would put up and competitions you know all
about you know non -scientific things sometimes
um and then he had he had the the secret santa
party which he had we all gave each other silly
anonymous gifts and teased each other He created
diplomas for people who left the lab, which were
kind of based on people's features and traits,
which I still do. I still carry those traditions
till now. And so like, yeah, so actually when
I left Oxford, now my whole lab gave me my Oxford
diploma. And they're all just poking fun at each
other and not taking ourselves too seriously.
All about that sort of generating a culture in
the lab that makes people, I know there's a lot
of buzzwords these days, like safe and secure.
But a culture that doesn't make people feel like
they have to produce something positive, positive
results we talk about in that. But that you're
there to be part of an adventure to get to the
truth, right? Yeah, absolutely. I mean, that's
one thing that was the most scary thing for me
moving over after, you know, 30 years at Oxford
is whether I would be able to reestablish. the
kind of lab that i i still have you know some
people are still in oxford now the lab that i
have is like amazing and it's every you know
first of all it's flat it's everybody counts
everybody is you know as valuable as anybody
else in the lab obviously everyone will have
different contributions different levels of knowledge
different skills so we kind of respect each other's
qualities and also our defects we all have defects
as well but it is a lab where i try to create
a space where we can be honest scientists we
can kind of you know tell each other like when
something is amazing when something is not quite
there yet and just be open and when you know
we're I always celebrate like... unexpected results
and mistakes because that's where we learn from.
And we have a very safe lab, but safe in a very
different way, I think, than how people tend
to use it now. It's not like we're not challenged.
We challenge ourselves all the time, but we challenge
ourselves in a supportive, honest environment
where we're all just trying to be the best we
can. You're an electrophysiologist first, right?
And so you're squiggly lines and high temporal
precision. And then along came fMRI and you and
I both had the great good fortune of being right
there when this all happened so um i often wonder
actually about our youngsters you know are they
going to have the same opportunity you know there
is a big happenstance component to it yeah but
um when you see all this uh work now using functional
imaging where they're talking about temporal
correlations between areas and we're really still
looking at the brain plumbing do you think about
this you know uh you know the the tension between
what you know about timing, given that time is
so important to you, from electrophysiology and
the way this is talked about with the functional
imaging folks. Absolutely, and I think I touched
on that in that Kavli lecture, and that was one
of the things I was hesitant to mention. I tried
to couch it in a friendly way. But, yeah, I think,
you know, ultimately the brain is working at
a very... maybe not super fast way because it's
still biology, not compared to electricity and
stuff, but things are happening in the tens and
hundreds of milliseconds scales. The MR -based
and PET -based imaging are much, much slower.
They're kind of looking at the multiple downstream
consequences of that neural activity and not
even in a necessarily one -to -one way, right?
So we don't even know exactly what's all contributing
to the hemodynamic response. The thing that baffles
me is that people actually use imaging to say,
like, what is this area doing? You can't ask
that question. That's right. Because, you know,
what you're going to see in an MR image is all
the activity that's going through that area as
part of the network that this area is in. And
you don't know what the contribution of that
area is or what's the feedback to that area,
what's the reentrant stuff, what's the lateral
connection. Right. So that really... you know,
worries me. And I've actually, and that's, I
would say, now I think people are using MR also
for many other different types of questions,
which some of which I think are. great and fine.
But I think the bulk of the MR work is still
about, you know, what's this area doing? And
not only do we now do, you know, just look at
an activation, we also like throw in really complex,
you know, computational equations to understand
exactly what factor of this process is. And I
think that's even more crazy because, you know,
I think, so I actually worry that, you know,
we are creating a... sort of a hallucinogenic
kind of view of what the brain is doing based
on MR. Precisely the same way, because in the
end of the day, when you go back to first principles,
we're looking at fluid dynamics in a tissue system,
you know, compartmentalized tissue system. But
they, by definition, are slower than the actual
events of interest to us. And there is no amount
of speeding up of the capture of the data that's
going to change that fact. The signal is the
signal. Yeah. Yeah, so that does worry me. I
mean, I still... think there are lots of amazing
things that MR can do so I think you know if
you're just trying to understand in general are
areas correlated with each other that's good
because it doesn't really matter the fine grain
so you can kind of get the broad networks maybe
I think if you want to say you know if you want
to like say I can measure I can see that the
brain is coding this kind of information or some
area has that kind of information by using decoding
methods or compare this kind of representation
versus that representation or the transformations
of representation. I think that's okay as long
as you're not trying to pin it down to a specific.
So I think there are lots of good questions that
people can ask. But I think, as usual, you know,
having that respect for the limitations of the
methods often falls short. It also falls short
in our area. I mean, to be honest, I think, you
know, when I, I remember when I went to Oxford
initially, I was trying to set up the sort of
first, EEG and ERP lab there. And what everybody
wanted to do is like, oh, I want to know what
this area is doing at what point in time. I said,
well, you can't really ask that question with
EEG, you know, because we don't have that kind
of spatial resolution or pinpointing. So again,
like we can ask lots of interesting questions,
but there are some that are not as well answered.
Beyond the resolution of the technique. And those,
for some reason, because I guess ultimately humans
are phrenologists at heart, maybe phrenology
in space and time. Those are the things that
they want to ask, and the methods don't really
allow us to ask those things. Yeah, exactly,
yeah. So let's go back a bit then. Let's go way
back. You're not from these shores. You were
born in Brazil. There's a couple of things I
want to ask about that. So how does a girl from
Brazil end up in the U .S.? And how does a girl
growing up the way you did end up thinking, I
want to be? a neuroscientist? Yeah, so I think,
you know, life is full of coincidences and circumstances,
and I think those make a huge difference to people's
lives. I was a small kid in Rio, in Rio de Janeiro,
in Brazil, and my parents were very young, so
they were sort of in their early 20s when they
had me, and my mom convinced my dad that he should
go and do a course. Let's go and travel abroad.
And, you know, why don't you go and do a course
in the States? So, you know, so that was kind
of unheard of at that time in Rio and stuff.
And, you know, they didn't come from very, you
know, rich families or anything. So my dad was
a very good student and he got a fellowship and
we ended up, he spent a little bit of time at
Princeton, NYU doing some, he was doing law.
And that's when I was like in my real formative
years, I was four, four to six. So, you know,
that's kind of where all my... So you were put
into school then? Yeah, I went into an international
school, like the United Nations School, which
was amazing because I met, you know, friends
from all over the world. I had like my best friends
were from Kenya and Peru and Canada. So we all
had our little flags, you know, in our different
countries. That was... blast that was amazing
it was also during you know the hippie year so
you go outside everyone's like dropping LSD and
you know there was the Black Panther movement
it was a really interesting crazy time in New
York City so those were very vivid memories when
I when I went back when we went back to Brazil
my parents realized that I had this great gift
that I spoke English you know and they thought
that this would be a good thing for me. So they
kind of convinced the then American school there
to let me in on a scholarship to continue studying
and being able to speak English. And then that
school was a great school, again, with people
from all over the world landed in Rio. You can
imagine people from all kinds of corners, from
the Netherlands and Cape Town and everywhere.
And so I grew up in this very international community,
but the school was very good at sort of preparing
us, and their aim was to get us to the... American,
you know, Ivy Leagues kind of thing. And at that
point, I had a really big young life crisis,
you know, because I wanted to go to the States.
My dad was like, you can't do this. If you leave
Brazil now, you're never going to come back.
And we'd have these, like, you know, many hours
long, everyday discussions about this and stuff.
And in the end, I had decided that I wasn't going
to come to the States. And like, I, you know,
didn't actually, I threw out a lot of my... college
applications but i had applied to some places
still so i got into those places and then i ended
up in the most bizarre place for me which was
a wonderful place but i ended up in williams
college which is probably the other side of the
universe from rio de janeiro which is very you
know at the time very homogeneous very conservative
very small right so coming from you know the
the whole world on the Rio Beach to Williamstown,
and the snow was a bit like a mind bend. But
good education and a good experience. Yeah, the
education was amazing. Actually, I think because
I was a bit of a misfit there, you know, it was
good in that sense. I did a lot of soul searching,
and I studied. Like hell, you know, like I just,
like I know I'm supposed to take like four courses.
I was always taking six courses at a time just
to keep myself from trying to, you know, cope
with a bigger growing up issues or something.
Right, right, right. And then what happened?
After Williams, did you go straight into PhD
studies? No, I took a year back in Brazil after
that. I wanted to go back. There were just stuff
going on with family and things. I also wanted
to be there for some difficult times in the family.
So I spent a year there. At that point, I had
applied to graduate school and I just deferred
for a year. And then I went to Yale. The jump
from here to Oxford, 1994, just a couple of years
back, that was a big jump as well, right? And
what was your experience with England and Britain
before that? I mean, I had visited Europe, but
I mean, I really was, you know, I'm very much
a New World girl from Rio. And so, you know,
it wasn't really part of my DNA in any way. I
ended up in England again for, you know, vagaries
of happenstance in life. You know, I had a boyfriend
at the time who was English and from London and
wanted to go back. And so I thought, like, oh,
it'd be fun to do a, you know. a fellowship there
for a while and i'll see how it goes so i i ended
up in oxford broke up with a boyfriend within
the month you know and uh and yeah and then life
is peculiar like that and uh divergences and
yeah and it was it was you know i think the thing
that i one of the things that i most love in
life is just learning new things, obviously in
science, but also in terms of meaning of life
and why are we here and perspectives. And so
England was so different in many ways. And also
the tone of the science was different. I think
people were, at that time, more interested in
some of the theoretical questions rather than
the data, productivity. And that resonated with
me. So it was like it's been forever a trajectory
of learning and change. And I've really enjoyed
it there. And I can't really say I lived in England
because I lived in Oxford. Oxford is another
small crucible of the universe. And I love that
place. So going back home to Yale, a kind of
a home, it's been a good experience. And navigating
the re -entry into the U .S. system. Yeah, I
was very much like Oxford establishment. as you
were kind of implying, and I have all my great
friends there, and I kind of gave my blood and
soul to that institution, and I still love it
dearly. So I think when we decided to move, my
husband and I, it was kind of a shock to everyone.
It was like, what? But it was really interesting
because I'd been there for 30 years, and... I
loved it. But I knew what was ahead, you know.
And as I said, I'm like a voracious learner and
stuff. And when this opportunity came, I mean,
other opportunities had come back and forth.
But it was either something that maybe was interesting
for me, maybe was interesting for my husband.
But, you know, we always kind of said, no, we're
happy where we are. But when Yale called, I was
like, you know, this was a special place for
me. These are, I'm the scientist I am because
they really invested me at those graduate. student
years you know those such important years and
I had that loyalty to the institution and then
Luciano my husband who's a digital ethicist you
know he was like I don't know Yale not really
in the on the planet in my area but it turns
out that this was a huge priority area for them
so he was able to build all the stuff you know
and lead so it was a really interesting opportunity
for both of us and we kind of thought about it
well you know we're a little bit past our prime
year are we really gonna do this and we're like
let's do it let's just do something new and adventurous
and then getting there has been amazing you know
but it's i try to say to people because everybody
who knows i've been there it's like oh you've
been here before and i was like it's not like
that yeah it's like i was walking around in oxford
and i opened the portal and i ended up in some
other you know, parallel future in a slightly
weird New Haven that wasn't the same as the one
I left. Right. You had quite some amount of time
in the past. Yeah, I think it's been 30 years.
And you were young. Yeah, I was a different person.
New Haven, you know, has been much gentrified.
Luckily, it still has some rough edges, but it
was like, you know, it's a very different place
than it used to be. So it feels, in a way, familiar,
in another way, really eerie and different, you
know. But the colleagues have been amazing. People
have been, like, so... welcoming and generous
and collaborative. It's been really fun. I mean,
maybe again, this might be a little unfair. Do
you see a difference now, 30 years later, between
the system in Europe or in Britain particularly
and what you've come back to or emerged back
in, re -entered here in the US? Are the systems
set up different? Are the motivations different?
Are there good and bad components to that? Yeah,
I think they're, you know, they're in a way academia
is the same everywhere. You know, we're a bit
conservative, a bit entrenched. You know, we
we kind of have creative and whatever souls,
but we kind of get stuck in the academic machinery.
And that's kind of the same everywhere. Yeah.
But of course, there are like a lot of really
interesting differences as well. Yeah, I think
one of the things that's very similar between
Oxford and Yale, which I like, is that there
is kind of a collaborative spirit. So people
across, they're very loyal to the institution,
and there's this idea of doing things together
and doing it as a team. It's a little bit...
I think Yale has that reputation among the Ivies,
or at least Yale thinks it has that reputation,
I don't know, from the outside, compared to some
other institutions of really doing things for
each other together as a team and collaboratively.
And I think Oxford... also has that. People don't
see it because everything is so distributed in
all the colleges, the institutes, the centers,
the things. But ultimately, if you ask anyone,
hey, do you want to work on this project? They're
like, yes. If you manage to get the connections
going, things really synergize. And I think that's
true in both places. But then I think the institutions
are conservative in really different ways. The
thing that has struck me in the U .S. is the
Yeah, the agony that people put into the recruitment,
promotion of faculty. It's just so cutthroat,
so involved to an extent that it's probably beyond
what's necessary or even optimal. And I think
it causes a lot of angst and work for everybody.
It sets up an incentive structure that's a little
anti -science maybe or a little anti -intellectual.
Well, yeah, I think that's one of the things
that... was exciting to me about coming to this
particular institute at Yale. It's an institute
that sits, you know, outside of any of the schools
or any of the departments. So it's kind of a
free -floating institute right under the provost's
office. So it has a lot of freedom there. And
I think one of the things that I would love to
do is kind of, you know, obviously push gently
and nudge, see if we can change some of these
academic incentives and help link our science.
to the world better. We do a lot of cool science
in our labs, but if we think about the science
of human behavior and science of the human mind,
a lot of it is happening in industry and companies
and tech companies and car companies collecting
all these data and stuff. We need to find ways
to partner and work together across academia
and non -academic sectors. So that's one of the
things that I think is... kind of pushing against
that conservatism is going to be hard, but it's
something I'm really determined to try to do.
So that's the next challenge. Yeah, I'll just
be annoying people that way. Well, I'm going
to ask you one more question. I really appreciate
all the time you've taken with us. I mean, you
brought up Luciano, your husband, and I wouldn't
normally ask about somebody's significant other,
but it's very meaningful in this case because
he's also an academic and he's a philosopher
working in this... digital ethics um and i mean
certainly i have a sort of fascination about
like you know what what's the conversation at
the dinner table like you know have you found
that you know being married to a philosopher
or has he found being married to a neuroscientist
that this there's been cross infection of the
way you guys think about things totally yeah
i think that's been so mutually enriching both
ways you know I mean first we kind of like we
were a bit at loggerheads that coming you know
at things from really different perspectives
but yeah I think Luciano has I mean first of
all he has kind of a really deep knowledge of
like you know history of science but also history
of thought and philosophy and stuff and that's
this it's a great great to have like a a gold
mine like that where you can bounce ideas off.
I usually have a great idea and he says, oh,
you know, Epiteto said that. And I'm like, oh,
okay, of course. There's always someone who's...
But that's just really fun and useful. But I
think we have... we've converged and changed
a lot together. That sounds wonderful. The usual,
the morning conversation, I'm not a morning person,
so the morning conversation usually goes that
Luciano brings me coffee, he brings me coffee
in bed, and he knows that for about 30 minutes
he can just, you know, say all these like heavy
philosophical things because I'm not ready yet
to fight back. So he would wake up and says,
Kia, you know, I think... I think I finally figured
out a way to separate meaning from truth. And
I'll go, oh, okay. Where's the coffee? Where's
the coffee? But yeah, so the conversations are,
they go all over the place and it's been, but
you know, I know that this is not like the most
important contribution, but as scientists, we're
sometimes quite sloppy at how we use concepts
and words and things. And I think having, someone
who thinks about high degree of precision yeah
he used words as like very very sharp tools and
things really helps the thinking as well so it's
been yeah and we actually just published our
first paper together Very good, right? I don't
know. I think it's just out two weeks ago or
something. Excellent. On everybody's reading
this. Now, I said I had one more question, but
I do have one more burning question, which I
happen to know is the question that the cognitive
neuroscience community wants to know the answer
to. Oh, dear. You are Anna -Christina Nobre.
Where the hell does Kia come from? Oh, okay.
Yeah, that's easy. So in Brazil, you know, maybe
like in Ireland, everybody is Anna something
or Mary something. Yes, indeed. Including the
boys. Yeah, exactly. So the Anna didn't really
count. So it was like Christina. And then Christina
in... in Portuguese is Cristina. It's quite hard
to pronounce. And so it's like, it's not a word
like... So it has a hard K on the front. Well,
Cristina, you know, it's like, so I think it
was like the first child who was born after me
couldn't, like, would just call me Kia, Kia,
Kia. And so there was just like a family name.
So that's where it came from. Okay, so now we
know. Now we know the origin of it. But yeah,
my name causes endless problems with Anna, Cristina.
Do you think I should change my name to Kia Nobre?
No, I think you've got the mystique of the Anna
Christina and Kia. It's very important. Thank
you so much for being here. We really appreciate
it. Thanks for all the hard questions.