Faculty Interview: Dr. Kurt Haas

Transcription

1 Faculty Interview: Dr. Kurt Haas SS: So first of all, thank you for your time, I really appreciate it. I think we're trying to do something that's really valuable for students by offering a candid voice from faculty. Our format for these interviews has followed the theme of past, present and future, and some questions that relate to your particular approach to science. So, starting with the past, what was your background outside of science and how did you end up in science? And what sort of lead you towards science? KH: Growing up I was always interested in science, and I thought deeply about what I wanted to do while I was in high school. I realized that I had to eventually get a job and I gave it good effort and came to the conclusion that science was the most attractive, interesting option. And when I realized there was a career that you can have in science I was interested in pursing that. I was lucky enough to think that neuroscience, or brain science, was particularly interesting and that allowed me to focus my attention at a very early stage on that area. The more I found out about neuroscience and got into it, the more I realized it was the right place for me. I went from thinking that I wanted to be a brain scientist in high school to selecting neuroscience as my undergraduate major at Cornell University. Luckily, I very quickly was able to get positions in a number of research labs, so I got some really great hands-on experience in science at a very early stage. SS: So would you say that's important to really think about what you want to do early on so that you can focus on it? KH: Absolutely, I mean that you can imagine having seven or eight years to focus on one thing; you should be pretty good at it when you're done. So certainly, four years of college, of your formative years when you're probably at your intellectual peak, it's fantastic to be able to focus that on something you're actually interested in. I find people aren't challenged to find something they're interested in. Either they're interested in too many things or they're not interested in really anything. If you have one thing, that's great, go do that. If you are falling into these other categories, there are strategies to deal with that. And all of them involve picking something, getting into it, trying it out and deciding if you like it, stay on, if you don't, go to the next thing. If you're interested in five things, start hitting them, doing them, getting into them and moving between them as

2 quickly as you can. And once you find the place that's particularly good, stay there for as long as you can to really get a good deeper understanding of it. SS: That's great, solid advice. Moving on to the present: what are your current scientific interests? KH: I've always been interested in consciousness, and I think that's a very important endeavour to understand. I think to understand that, one has to understand how the brain processes information and to recognize that individual neurons are doing really amazing things for information processing. So I think my interest for now and the future is to understand neuron coding at the cellular level and then try to build up from there. But I think there's deep knowledge and understanding of consciousness that we can get from just understanding how individual neurons process information. I think we're at this fantastic age of science where we can follow information in a very beautiful way using non-invasive imaging technologies rather than just electrophysiology to track information processing. So I think that there's a lot of very interesting things that will come out of this age, and I'm excited to be a part of it. SS: So that's obviously an important aspect of it - is to do it as non-invasively and physiologically as possible? KH: Yeah, I understand why one does more in vitro work; it's a higher resolution perspective of anything, whether it's structure or molecular components. But to really understand what's happening in a neural circuit, because especially thinking about something like information flow, it's something that has to be done in an in vivo intact system. And now we have the tools to do it. Other big things I'm also interested in are brain circuit development, and how you build something like a brain circuit and make it functional. I think that's intrinsically interesting, and it relates directly to how neurons process information because neurons are constrained by their biology and their evolution and how they're built. So it's interesting to understand how development and evolution constrain these other, higher-level questions we're interested in. And, of course, I'm always interested in disease too. Understanding how fundamental processes work invariably gives us insights to how dysfunction of those same events can lead to different kinds of diseases. SS: Right, that's great. How do you believe that the state of neuroscience has changed over time? Or if it has?

3 KH: Oh, it changes dramatically. And it always changes through technology. And neuroscience is an amazing field in that it's a driver of all biology. I think that arguably, there's more technology development in neuroscience than in other fields of biology, and then those technologies once developed are often used for other fields. So I think that neuroscience has been a driver because of its particular needs. Because neurons do such different things, like communicating information, and their individual cell structures inherently intertwine to their function, we need high-resolution measures. First there was electrophysiology, then EM, but now imaging. And of course, there's been great use of genetic tools in neuroscience. It's a great combination of imaging, molecular biology, genetic engineering and electrophysiology techniques that's culminating in really powerful things. So technology is what drives everything, and every year there's a new imaging technology that advances our vision of this field, we get new genetic tools, optogenetics is really spectacular; our ability to not just listen to neurons communicate, but actually directly control them in real time, and in actually intact animals, is totally powerful. So the combination of genetics and optogenetics with imaging is great. I think functional connectomics is an incredible field; this idea that you would use in vivo imaging, things like calcium imaging or voltage imaging, to understand what neurons are doing in a living, behaving brain circuit and then to see an EM of the same tissue to understand the complete wiring diagram of those cells, what type of cells they are, is spectacular. I think layering on top of that, a more complete molecular, protein repertoire, is something that's going to happen in the future, a sort of array tomography version of that. So what we're doing right now is spectacular. You can just imagine if we keep advancing with this pace of technology what we're going to be able to do in 10 years. It's really exciting. SS: Right, that's really amazing. We'll have to share these images with the audience but I really think your work has a certain aesthetic component to it. When you're looking at these neurons they're really sort of artistic and beautiful. Do you ever find that that motivates you? KH: Absolutely. I think that one of the first things that really drew me to neuroscience were drawings by Santiago Ramón y Cajal. He's considered the father of neuroscience, back in the late 1800s he would make drawings of neurons that were projected from a microscope, so they were actually real neurons using staining by the Golgi method. It was actually the first time that people were able to see what neurons looked like, and that really gave birth to

4 the field. And since neurons are so strange, with their long dendritic and axonal branches, it was very clear to even these early visionaries like Cajal, that the structure of neurons really patterned a circuit, and implied that these cells were communicating and enacting information processing. This understanding just leapt off from seeing the intricate neuronal structures. I think it's hard to look at one of Cajal's drawings of these very elaborate, complex neuronal structures and not just be taken away by their very beauty, but also to see within that beauty the intrinsic complexity of function that's there too. That interests me very much, and what I love at my lab, which I've developed, is taking that approach of watching single neurons, but not in the static way of taking from dead tissue, which Cajal did, but to watch in a living animal, and watch these neurons change over time, especially during brain development where there's a dramatic amount of extension and retraction. Being able to watch that happen in real time in an awake little animal is spectacular. It's beautiful and the beauty of it definitely drives me. I originally started as an electrophysiologist, and I love electrophysiology because you have this tiny ear to a cell and you can hear things, and you can actually put in audio and hear the sounds of it, and you can hear synapses firing and action potentials firing and even the most beautiful thing is you can hear single channels opening and closing. That's the most powerful means to look at any protein conformational changes, with single channel electrophysiology, and that itself is beautiful because it's amazing to watch and listen and see that level of biology. I think that bringing it together and seeing a living cell grow is awesome. SS: That's amazing. So it obviously sounds like passion is an important thing to have in a successful academic career. KH: Yeah, science is really fun, but it's hard. It takes long hours and the monetary reward isn't fantastic. I think it's definitely a passion-driven, should be a passion-driven, endeavour. If you're not passionate about science, I hope that those people would not go into this field because the reward definitely is in the passion for the science and things like mentorship, which are really fantastic. The science is great, and I'm definitely drawn to neuroscience from my passion for the questions that are involved. For me, it's not just being a scientist; I can't imagine being a kidney scientist or a liver scientist. I'm glad that other people do that, but I have no passion for those fields. The questions and the beauty of neuroscience really drive me, and that's never waned since I was a high school student, an undergrad, a grad student, and in a post doc

5 where I used to sleep in my lab for many, many nights through the years. I really enjoyed it. SS: So that's obviously one aspect to a successful career in neuroscience. Do you have any particular advice for students hoping to achieve a successful career? KH: There are many aspects to it. I think undergraduates should absolutely get into a lab and get real research experience to really get an understanding of what it means to be a scientist and decide if that's something they'd like to do. They should realize that it's a huge time commitment, and science takes many hours in the day, in the week, and it takes years to develop a scientific understanding of one's field, to be able to ask really good questions and be a good experimentalist. If you're interested, go get experience in it, but realize that you're going to have to dedicate a number of years to really understand what a career in science is and decide if it's right for you. It's definitely challenging, it's very competitive, it's hard to get positions, but if somebody is passionate and they understand the path and how to achieve the goals, it's definitely an achievable goal. So I think that if somebody really wants to do it, they should. SS: Okay, so moving on to a unique aspect of your particular approach, it definitely sounds like you take on a multidisciplinary approach to neuroscience, talking about genetics and imaging and statistics and everything. So do you think there's a particular way for students to prepare for this kind of approach to neuroscience? There's the classic way of students really getting deeply entrenched into a particular field and then joining a team and contributing their knowledge to the team, or should students get some knowledge in multiple fields from earlier on? KH: There are many different approaches that one can do, and as I said, my background was originally in neuroscience, which I trained in as an undergrad, as an electrophysiologist in my PhD, and for my post doc I learned molecular biology, imaging, and how to build microscopes. In my own lab I was able to combine electrophysiology, molecular biology and in vivo imaging in a very powerful way. So any time you are able to combine skill sets is very useful, and I think that is becoming more and more important in the field. One should always try to eventually have multiple skill sets. As far as at this stage, I think it's an interesting question to say what's the best undergraduate education that someone could have to become, say, a

6 neuroscientist, and I think there's many different paths. You certainly would like to have a good molecular biology background, but I think that everyone should also learn programming because that's becoming so important to all aspects of the field. But when I look at who I would take into my lab as a graduate student, I look for a range of people. I certainly would love to have physicists and engineers and computer scientists as well as biologists and geneticists. So I think you can come from many different backgrounds into neuroscience, I think you are bestserved if you can learn as many different things as you can, so I would definitely recommend people being comfortable with molecular biology, but also programming, and you're definitely served well by having strong math and stats skills. SS: It sounds like the necessary requirement is passion, which will allow you to go out and learn all of these skills. But it also sounds like one needs a combined set of skills, in which not all undergrads will get deeply trained in. So they really need that drive to go out and learn as much as they can. KH: Yes, I mean you can take a long term view of this, if you want to become a scientist, like an academic scientist, that means you go through the four or five years of undergrad, go through about five to seven years or so of Masters and PhD, and then you do a five year post doc. So if you add all that up together, say conservatively, if you're lucky, its 15 years, and 15 years is a long time for you to learn a number of different skill sets. So you can spread this out, but you should have these things as a goal of trying to achieve different things. You don't have to do it all right now, but the earlier you get into something like programming, the better. Also, I enjoy running an innovative lab, and I think small innovations go very far in science. But learning to be innovative is a skill, and one needs the basic tools from which to innovate, such as molecular biology and programming. For example, if you develop even a small innovation in new software to fix up the analysis of your work or your instrumentation, this can be a huge advance for the field. But I find that being comfortable thinking of new methods and tools takes experience.. SS: So don't close your mind to learning new things that are outside your boundaries.

7 KH: No, of course not. And that's what I do everyday, that's what it means to be a scientist, you learn everyday, and I'm always in new fields. A very small part of my lab is in regions where I feel very comfortable. I feel very uncomfortable most of the time, and its fun. I don't have a problem saying when I don't know something, and I get to learn all the time, that's great. SS: Do you feel like students should ever be sort of afraid of how far their ability can go? Like certain students might say "I don't think I'm able to learn that, it's just too hard." KH: I think that you should always be able to self-evaluate things; you're usually surprised by what you can learn. Just get into it and see how it goes. Take it stepwise, don't jump into the most complex math and be confused why you don t understand it, start off small and you build and you grow. Just work at it, form communities that help you learn things. I think you can take classes all you want, that's a fine way for learning, but I think everyone has to develop their own strategies for learning on their own, outside of the classroom structure. Classes are a very strange, artificial way of learning, and you have to be able to be self-motivated on your own too. I'm a biologist, but I have a lab that does engineering, software development and other things. So, a lot of this is beyond me, but what I've done is created a community where people with expertise I lack can come together, and since I know what I want to achieve, so I can direct their efforts. You don't always have to be doing all this stuff yourself; you can be part of a community or help direct where that goes. SS: That's great, that's all the questions that I had. Thank you! KH: Cool, well thanks for doing this, I think it's really important.