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.