A Word From: Katherine Hajjar & Jacob Rand

Last week, Cold Spring Harbor Laboratory hosted Annexins 2017. This international conference is held in a different location every other year, and CSHL was chosen for the 2017 meeting because of its accessibility, on-campus amenities, and proximity to New York City. We are proud to have hosted the Annexins community and checked in with two of its three organizers – Katherine Hajjar and Jacob Rand – to talk about the conference. 

Katherine- What I see happening in the field more generally is that we're transitioning from basic biology with purified proteins and lipids. The field is now moving more into human health and disease, which for me  (3).png
Katherine- What I see happening in the field more generally is that we're transitioning from basic biology with purified proteins and lipids. The field is now moving more into human health and disease, which for me  (2).png

As the annexin community grows, the organizers do their part to ensure the “newcomers” take part in the conference: 


Speaking of abstracts, Annexins 2017 did adopt the CSHL Meetings & Courses tradition of selecting a majority of talks from the submitted abstracts.


We ended the chat talking about the annexin community: 


Thank you to the organizers for choosing Cold Spring Harbor Laboratory as the venue for Annexins 2017!

For more conversations with other meeting organizers, check out our A Word From... series. 

A Word From: Mark Reimers & Pascal Wallisch

2017 Neural Data Science instructors Mark Reimers and Pascal Wallisch (L to R)

2017 Neural Data Science instructors Mark Reimers and Pascal Wallisch (L to R)

We recently sat down with co-lead instructors and co-founders, Mark Reimers and Pascal Wallisch, to talk about their biennial course on Neural Data Science. The course was first offered in 2015 to help neuroscientists develop conceptual and practical capabilities for analyzing large datasets such as those resulting from single- and multi-electrode extracellular recordings, local field potentials and electroencephalograms (EEGs), as well as two-photon and wide-field optical imaging. Cutting edge data analysis methods are still very much the focus of the Neural Data Science course. Here, Mark and Pascal go into detail about the course’s importance to neuroscience.

Pascal: We now have a lot of new ways of recording, storing, and processing neural data but we don’t yet have a good understanding of how to analyze the data. The richness of the newly-available data demonstrates how much we still don’t understand about the brain and that one would be well-advised to be more modest and humble about what we actually understand about brain function. A lot of other courses focus on existing theories and models; whereas our course de-emphasizes modeling and theory. We won’t tell you what to think about how the brain works, but rather how to analyze your data. 
Mark: I would agree that this course really is very distinct from other computational neuroscience courses. We’re not focused on trying to simulate the brain or impose models on data. We’re exploring the data in a hypothesis-free context rather than use it to buttress or falsify a particular theory. I think the real imperative for neuroscientists now is to look closely at their data and to let it inform them, rather than impose their ideas on their data. Because the new technologies enable us to see more richly than before, I would argue that it’s appropriate in this stage of neuroscience to be more exploratory. 
Pascal: I think the students are loving the exploration aspect of it. It’s a very hands-on course. Someone came up to me this year and said, “This course instills in me confidence.” He is trained as a medical doctor with no mathematical background and was always afraid of equations. But our hands-on approach showed him that he can absolutely do this. It’s actually not that hard once one gets the hang of it.
Mark: The students are asking questions about their data that we can show them how to address. Many of them feel that some of the longstanding theories and ideas are not really giving them insight or traction on their data. So I think they’re welcoming of this new perspective.
Pascal: Regardless of whether someone takes this course or not, those continuing in neuroscience will, in my opinion, need a solid understanding of statistics and at least one relevant programming language to be successful in the field. 
Mark: I second that. I think it’s a fundamental transformation in all of biology, though it’s been particularly rapid and, perhaps, hard for some people at this point in neuroscience. It used to be that it was important for you to have understanding of the animals, ability to do careful surgery, really good microscope skills, be able to identify neurons, and be familiar with your technical apparatus and its artifacts. All of these are still very important but, increasingly, you also have to think quantitatively and pose questions that can be addressed by data analytic methods.
Pascal: Which may be challenging for someone who has no training in that kind of skillset. Biology used to be a field where you could have a long, productive and respectable career while skirting math and statistics for the most part. But this is no longer the case – at least not in neuroscience. So a course like this is desperately needed. 

For the second iteration of the course this summer, Mark and Pascal made revisions to the curriculum and schedule that maximized what the trainees learned. 

Pascal: We made four big changes to this year’s course that made things run much more smoothly. The first is that the course now runs a full two weeks instead of just ten days, with one week dedicated to data recorded with electrical methods and the other to data recorded with optical methods. The second change is that we cut topics that were not directly related to electrical and optical methods, like information theory and fMRI, as there are other courses that focus more directly on those topics. The third change we made is that we streamlined the way we teach, in the sense that we now work with much fewer data sets. In 2015, each invited lecturer brought his/her own data, and we spent hours and hours learning the structures of all the different data sets. Finally, we increased the number of teaching assistants in the course. 
Mark: Most of our theories are built on a kind of information processing model that increasingly seems unlikely to be true except for a few specific areas, such as the visual system, so we no longer emphasize information theory in the curriculum. In addition, we’ve oriented the course towards the new revolutionary technologies like optical imaging. Our plan for the future is to try and pivot toward emerging transformational technologies as they become important. They all pose dramatically different (and difficult) data analysis issues.

We then switched gears and talked about what a typical day for their trainees look like.

Mark: We typically have intense conversations about neuroscience over breakfast, occasionally about politics as well. Then starting at 9 o’clock, we have three hours of seminars, followed by a lunch break. We bring in one invited lecturer to give two talks each morning. The lab sessions then run from 1 to 4:30 and when we say lab, we don’t mean pipetting and test tubes.
Pascal: We mean MATLAB. A key feature of the afternoon lab sessions is that the students work in pairs, and the partners are assigned by us based on their experience with MATLAB. We purposely assign two students per computer so they have someone to talk to while they’re doing analyses and grappling with the data. It prevents the students from feeling isolated and it’s been working really well.
Mark: In the late afternoon, the students have free time when they can go to the tennis court or beach, or take a walk or run around the estate. Dinner is at 6 and, of course, we have even more intense conversations about neuroscience, politics, teaching, and universities. We resume again at 7:30 with evening sessions that are more of a diversion. For example, we’ll have a presentation on how to write a good scientific paper, a discussion about contentious issues in data analysis, or a presentation by someone from Mathworks on new capabilities in their program. The students typically stay up late to do more coding or work on what they didn’t finish during the day. 

Acceptance into the Neural Data Analysis course is competitive. We asked Mark and Pascal what they look for in potential course trainees and their application materials. 

Mark: We’re looking for someone who’s wrestling with fundamental questions about the brain, who’s exploring and using some of the cutting-edge technologies, and who is quantitatively-minded but doesn’t have the tools to analyze the data they’re getting in any detail. We would like to help our students formulate rigorous statistical and mathematical approaches for answering questions that may be lying underneath their experiments, that they want to address but don’t know how to formulate. 
Pascal: We look for three things: 1. Scientists who will benefit from the course. We’ve rejected some applicants because we felt they already knew too much about the material. 2. People who are working on data from electrical or optical methods. Some people who applied for the course were qualified, but were interested in clinical neurology, neurosurgery, or neuro-imaging, and there are other courses for developing those skills. 3. And, of course, we look for overall curiosity and a demonstrated record of achievement. 
Mark: For those whose applications were not accepted this year, I would encourage them to try again. The competition this year was stiff and there were many talented students we couldn’t accept. 
Pascal: We only have 20 spots and we’re already at maximum capacity, so we had to make some really tough choices, heartbreaking in some cases. 

We ended by asking what their favorite moments have been throughout the two iterations of the course.

Mark: During the 2015 course, I fondly remember singing math songs. 
Pascal: I remember that! That was definitely a community building moment. 
Mark: Several of our perhaps best-remembered moments were those where students see that someone is taking seriously a fundamental confusion or uncertainty of theirs, something they had but never articulated very clearly, or had never seen articulated explicitly. Before the course, they’d just had to cope, sort of make do, make stuff up, or do something to produce what’s expected. And now they see that yes, something is really problematic: that it’s not clear how to go from, let’s say, an electrical trace to a discrete set of times where a particular set of neurons has fired. We really need to make processes of the brain visible to researchers so they can come up with better ideas of how the brain works.

Make sure to read the rest of our A Word From... series.

A Word From: Maria Jasin


Last weekend, we hosted the third CSHL meeting on Genome Engineering: The CRISPR/Cas Revolution. We met with Maria Jasin, one of the three original organizers and a CSHL meeting veteran, to talk about the CRISPR meeting. Here is a quick overview of her research:

We study double strand break repair and genomic instability, with a particular interest in the breast cancer suppressors BRCA1 and BRCA2. We’ve also had a major interest in understanding meiotic recombination and how double strand breaks are repaired there, and maybe aberrantly repaired in other syndromes. 

Maria provided a great overview of the meeting, how it has evolved with the field, and the developments she’s most excited about. 

One major change is the expansion in the number of enzymes and nucleases that are being used. The first meeting focused primarily on Cas9 itself. Now, many different enzymes are used that have better applications than Cas9 in some contexts, which is an exciting development in the field that is much more represented in the meeting than it was in the past. It’s a recognition of how large the CRISPR repertoire is in bacteria, the almost limitless number of proteins that can be cloned and characterized, that have somewhat different specificities or other reasons that make them preferable in different situations. 
This year’s meeting started with a lot of CRISPR biology which I found really exciting, because it lets us non-CRISPR biologists understand this beautiful genetic system of adaptive immunity in bacteria. Also, there’s been an emergence of anti-CRISPRs - peptides that can halt CRISPR activity. These peptides are numerous and act differently by blocking different steps, which is a really fascinating system. It’s perhaps not surprising that there are some practical uses to them as well. 
One of the really exciting things for me was Kathy Niakan’s talk about using human zygotes to address important questions about embryonic development in humans. Obviously, it’s a very difficult system that needs to be heavily regulated. But as much as we know about mouse development and the very earliest stages of mouse embryos, one thing that’s clear is how different things are in human embryos. We have known for a long time that human oocytes are very prone to aneuploidy, and that results in miscarriages or birth defects. Trying to understand the genome instability that arises in the early stages of embryos is something that’s also important for human health and infertility. 
Another talk I was excited about was given by Danwei Huangfu, who uses human pluripotent stem cells to understand pancreatic development. For a long time, we’ve only been able to use cell lines in humans that are transformed and highly aberrant. The ability to use cells that can be differentiated into human lineages is really exciting and highlights the ability to understand, again, human embryonic development at a much later stage. It’s related to human genetics that in the past we wouldn’t have been able to do.  
Also, my student, Weiran Feng gave a talk about his work on homologous recombination – one of the pathways people like to use to modify the genome. It was very touching for me to see one of my students develop a beautiful story and present it in a beautiful way. 

These days, there’s no shortage of scientific meetings focused on CRISPR. We asked Maria what sets the CSHL meeting apart from others, and also who benefits most from attending it.

There certainly has been a large explosion of CRISPR and genome engineering meetings, but the one thing that’s particularly exciting about this meeting is its emphasis on biology. We, of course, have talks that are more technical, about improving the CRISPR systems or adapting new systems or doing screens. But we’ve balanced it by having a lot of biologists present who are trying to understand human development. We even had a talk this year on using killifish  as a new model for aging, so the meeting brings together a lot of biologists.   
Commercial interest companies love this meeting because they are able to showcase their work here. Most of the talks are from academic scientists though, who love this meeting for the basic biology and technology developments that are coming from and presented by academic labs. 
And Cold Spring Harbor is always a great place for graduate students and postdocs. We do have invited speakers, but the number of talks given by postdocs or grad students outnumber the invited talks. My first talk as a scientist was at CSH when I was a graduate student! Attending a Cold Spring Harbor meeting is an ideal way to start your career because you are able to not only interact with a number of scientists but also have the opportunity to speak or present a poster. 

We ended the conversation on how this year’s meeting turned out. 

I had thought that, with time, the meeting would get less exciting but this year’s meeting was just as exciting as the first one. It’s a testament to the growth of the field, the creative approaches people are taking, and the expansion of the number of nucleases involved. We brought in people with different expertise – stem cells, modifying human embryonic cells, etc. – which brought together people who don’t know or often see other. The meeting hits a lot of different areas in biology even if there’s a CRISPR coherence to it, and that promotes great scientific interactions.

The Genome Engineering: The CRISPR/Cas Revolution meeting will return to campus on August 22-25, 2018. Follow us on Facebook or Twitter for meeting updates. 

To read more conversations with CSHL meeting organizers and course instructors, browse through our A Word From... series

A Word From: Karla Kaun, Alex Keene, Chi-Hon Lee & Stefan Pulver

2017 Drosphila Neurobiology co-lead course instructors Karla Kaun, Stefan Pulver, Alex Keene, and Chi-Hon Lee (L to R)

2017 Drosphila Neurobiology co-lead course instructors Karla Kaun, Stefan Pulver, Alex Keene, and Chi-Hon Lee (L to R)

A few days ago, another batch of alumni from the course on Drosophila Neurobiology: Genes, Circuits & Behavior were welcomed into the ever-expanding network. We met up with Karla Kaun, Alex Keene, Chi-Hon Lee, and Stefan Pulver to talk about the annual course and exchange fly-centric one-liners. Drosophila Neurobiology, aka “the fly course,” is among our longest running courses and has therefore evolved significantly over the last 34 years. Here is an overview of the course format today and the major updates Alex, Chi-Hon, Karla and Stefan have made to keep it current and engaging. 

Stefan: One of the things we try to do in the course is continually reinvent and change it in response to student needs and feedback. The content of the course is usually structured by us ahead of students applying. But we build in flexibility so we have avenues where students can explore – maybe improvise different modules and extend some of the modules we teach, all while having a solid framework of learning objectives. The course isn’t a static thing that moves from one year to the next. It’s a growing, living thing that can actually change – sometimes even within the three weeks of the course. We make adjustments “on the fly!” 
Chi-Hon: One of the most significant changes we made is the addition of the capstone project. The course was originally designed to teach students how to use Drosophila to study neuroscience. The capstone project allows the students to link what they learn at the course with their own research interests.  
Karla: At the end of the course, the students give chalk talks on their capstone projects and what they want to do in the future in their own labs using what they learned in the course. We really like chalk talks because they create a lot of back-and-forth discussions between the students and faculty. 
Stefan: Another new thing we’ve introduced over the last few years is a do-it-yourself (DIY) component. We have a few sessions where we teach students how to build apparatus and create their own equipment. These are systems students can create by using 3D printed materials or purchasing separate components. The systems we DIY – generally behavioral apparatus and opti-genetic LED controls – are expensive if you buy them outright. 
Alex: With the advent of 3D printing, DIY-ing is becoming more and more common across science and we wanted to make sure we integrated it into the course. 
Karla: And the students love it. One of the scientific advantages to DIY is it permits a lot more creativity. We try to reveal to our students that it’s not that expensive to do it yourself, so anybody can do it. You don’t have to buy a pre-built thing. The only limitations are your imagination and ability to order materials.
Alex: Another thing that’s been ramping up is the integration of computational biology into the course’s physiology and behavioral sections. Computational biology is something that’s growing within the neurobiology field, and we make sure our students get a healthy background in it. 
Chi-Hon: We aim to empower our students. In Drosophila neuroscience, there is a norm to use creativity to overcome hurdles. Most of what you want to do, you cannot buy the right tool: you have to invent it, or write your own program to achieve a goal. Our sessions are designed to help students get to the stage where they can build a tool or program and realize it’s not that hard. 

We next asked them to describe the day-to-day life of their trainees.

Chi-Hon: The day starts at 9 o’clock with a lecture. Students then spend the latter half of the morning, which sometimes runs into the afternoon, to explore and work on achieving a specific  goal in the laboratory. We come back to the lecture room in the afternoon for the students to present their observations and discuss how to process their data. In the evenings, students continue to work on and practice very difficult techniques, and also hear invited lectures from world-renowned scientists. 
Karla: The faculty we invite as lecturers are experts in many different things and can tailor what they’re teaching to the students’ interests. So it’s rather dynamic in that way.
Stefan: We bring in a range of faculty members. And oftentimes, they bring along course aides or assistants – like postdocs and graduate students – who contribute to the course too. So you don’t only have faculty but also members of their laboratories coming in to help teach course practicals.
Alex: Oftentimes, the invited  lecturers come in to give a two-hour talk but stay for 3 or 4 days. They want to spend as much time with the students as possible. That generates opportunities for students to informally interact with them, talk to them about their projects and get feedback, which I think is one of the more valuable things the students get out of this course. 

The course runs close to three weeks and during that time, the trainees also have access to the equipment and technology acquired for the course. 

Stefan: Although we study Drosophila, this really is an integrative neuroscience course. We use Drosophila in part because we can teach a whole bunch of different concepts in neuroscience, from genetics to cellular physiology to behavior, that are very tricky to do with other model organisms. Cold Spring Harbor Laboratory is exceptionally good at bringing in cutting-edge technologies and giving students access to it 24 hours a day, 7 days a week. It’s important to not underestimate the access to resources and equipment here; we have equipment that is not easy to access in a lot of institutions. So students can see the full array of possibilities for addressing a question, from two-photon microscopy to live imaging to electrophysiology to inexpensive ways of doing behavior experiments.
Karla: And some of the most complex software for analyzing behavior, too. Altogether, it’s $2-3 million dollars worth of equipment.
Stefan: We have chunks of time in the course where there is no scheduled learning. So students can do their own experiments and access this fantastic equipment any time of day or night. 

When it comes to the value of the course, here is what the instructors had to say: 

Alex: We had an analysis done and it showed that 64% of the graduates of this course go on to faculty positions. Part of that is accepting some of the best people as students but we like to believe that the course itself contributes to this. I really think it’s priceless.
Karla:  On a recent long-term survey to people who had previously taken the course, we got amazing feedback from a lot of them. For me, I’m an assistant professor fairly new to professor-ing and it’s pretty amazing when these really big names email you and say, “This course was amazing! Thank you so much for continuing it!” I think this course is something that sticks with you your whole life. 
Alex: Go online and look through the roll of honor. The people who’ve taken the course over the last 34 years include huge names and people who have started new areas in the field, like Karla. To come in and see this year’s students, I can’t help but think that at least half of them will go on to make their own big contributions. 
Chi-Hon: This course offers more than just skills, knowledge, and technology – we provide an environment to network.
Karla: The lifelong friendships that start in the course are priceless and make the biggest impacts. 
Stefan: Having a network of colleagues you can trust and go to with questions or problems is really helpful. Each year of students formulates that network.      
Chi-Hon: We have a mixer with the Advanced Techniques in Molecular Neuroscience course where we invite a world-renowned scientist to give a research talk to students of the two very different but overlapping fields. The students in both courses intermingle and discuss their field’s perspective on the same topic. It’s followed by a cheese and wine reception so the discussions continue for hours afterwards.
Alex: This year, we had Amita Sehgal of the National Academy give this talk. Amita’s in my field and I’ve seen her talk probably a dozen times, but it was neat to see her teaching to a small group.
Karla: We also do a mixer with the Frontiers and Techniques in Plant Science course. 
Alex: We “cross-pollinate!”

Acceptance to the Drosophila Neurobiology course is competitive. We asked the course instructors for tips on what they look for in applications and how they make their selections. 

Alex: I would advise applicants to clearly state what they hope to get out of the course. In addition to them being very talented, that’s one of the important things we look for in an application. 
Karla: Our goal is to create a really dynamic group of students that is diverse scientifically, by gender, and by nationality. It’s helpful for applicants to include a few sentences about their expertise so we know what they can contribute to the course and what they can take away from it. 
Stefan: We look for excellence in science and for people who, in a general sense, are going to be leaders in the field. Also, our makeup is international and we welcome people from Drosophila labs all over the world. Karla’s point about the students’ expertise is important in that the course can be considered a two-way street: Students teach other students about their own work, so those who can come in and contribute something new are actually really nice to have in the course.
Chi-Hon: We look for people who not only want to do their own thing, but are also willing to share. People who not only learn from lecturers and instructors, but those who can work with and learn from other students. 
Karla: It isn’t only graduate students and postdocs that apply to our course. We also receive applications from faculty at undergraduate institutions. And we welcome them because flies are particularly useful tools for doing undergraduate laboratories, so these faculty can have a really big impact on future generations of Drosophila scientists. 
Stefan: I would also say, if you apply to the course and don’t get in, don’t be afraid to try again. Don’t take an initial no as a permanent no. We have had students who, in our opinion, weren’t quite ready to come to the course one year, but then apply again and gain acceptance in another year. 

Here are a few more pieces of advice from the instructors:

Karla: Bring insect repellent!
Alex: And sunscreen!
Karla: And sleep a lot before you come!
Chi-Hon: I’ve been to many, many courses in different institutions and I always come back to Cold Spring Harbor. This is the best place.

If you'd like to learn of the Drosophila Neurobiology course from a trainee's perspective, read our Q&A with 2017 fly alum Tayfun Tumkaya. Also, for more on how to prepare for your time at CSHL, check out our course trainee informational guide series.

Make sure to read the rest of our A Word From... series. 

A Word From: Farran Briggs & Andrew Huberman

2017 Vision: A Platform for Linking Circuits, Behavior & Perception instructors Farran Briggs and Andrew Huberman (L to R)

2017 Vision: A Platform for Linking Circuits, Behavior & Perception instructors Farran Briggs and Andrew Huberman (L to R)

We recently sat down with Farran Briggs and Andrew Huberman, the co-lead instructors of our biennial course on Vision: A Platform for Linking Circuits, Behavior & Perception. This is their third time leading the course together but their ties to the course started almost twenty years ago when they both took it as graduate students (in 1999 and 2001, respectively).

Farran: One theme that has carried through since Andy and I were students in this course, is that it really is transformative. It’s transformative because of the exposure students have to the faculty via both formal and informal interactions with them. Students not only gain this tremendous knowledge that they will never get in a graduate program course, but they put faces to names on the papers. And beyond that, they actually talk to these faculty about their own projects, and dig into the technical details of “How did you do this analysis?” That is invaluable because it might shape the future of a student’s entire career. They might decide at this course – and I’m speaking from personal experience – to go after a question they never thought of before, that will then shape their entire research trajectory.

Andrew: This course is not like standard seminars. The faculty we pick are people who are here to educate, as opposed to just share what they do. There’s nothing really like it.

Farran: Just following up on that. CSHL’s bread and butter is the technical courses where a student comes here and learns a technique, which is fantastic and can be transformative in its own way. But as our field becomes increasingly obsessed with techniques and the students start to absorb that, it’s even more important to have a course like this where they hone their focus on a question.

Andrew: The concepts.

Farran: What am I going after? Why am I studying this? You get some of that in the technical courses as well, but we’ve already seen a transformation in a lot of our students. Our students, oftentimes, come from very famous and well-established labs and have a very general idea of what they should be working on but they haven’t actually honed their project. Coming here, talking to the faculty and their fellow students, they begin thinking about their project in a new way.

The Vision course, which consists predominantly of lectures and informal discussions, is one of our offerings held at the Banbury Conference Center. Banbury course schedules are works of art that instructors design meticulously by considering the latest developments in the field and, most importantly, what’s best for students.

Andrew: This course has been going on for a long time. We inherited it from our advisors, so to speak.

Farran: We’ve learned a lot from those who came before us. When I took the course and probably when Andy took it, the course had a very hierarchal structure.

Andrew: The course ran in an anatomical hierarchy – moving from retina to the brain. A few years ago, Farran and I realized that it made more sense to make it more conceptual, so those who work in different parts of the visual system and brain could communicate throughout the course. We also changed the overall schedule. We have four hours of lecture in the morning, take an afternoon break, and then 2-3 hours of lecture and discussion in the evening.

Farran: Two faculty lecturers are scheduled per day, who both speak in the morning session until one o’clock. We start back again around 7:30 and go on until the students stop asking questions. The evening sessions start with at least two or three short student talks; this gives a forum for everyone to get direct input and feedback on their projects. The talks are followed by an open Q&A session with the faculty lecturers from the morning session.

Andrew: In previous iterations of the course, we had a format where we had morning and after-lunch lectures. In my opinion, our current format works far better because people get time to synthesize and think about their work. I’m a big believer that students and faculty cannot reasonably sit all day long in a room. Your brain goes to mush. And nothing in our schedule is haphazard. If you look at the schedule, everything is there for a reason – including the breaks.

Farran: The mid-day break allows the students to catch the faculty lecturers. Oftentimes, they’ll go for a walk or sit by the beach together, giving the students a much more informal chance to ask about their projects.

Andrew: The value of a pure lecture course like this one is hard to justify and explain unless you’ve been to one. It’s not so much about the lectures but the opportunity to dive really deep into a topic. You have to leave time for spontaneous interactions, and that’s what we did when we re-designed the course’s schedule.

It’s not only the course schedule Farran and Andrew have revised. They’ve also invited younger lecturers to demonstrate emerging techniques and contribute to career discussions.

Andrew: Junior faculty lecturers bring in a great energy and they have a different kind of approach. They are also able to talk about career stuff that’s relevant for the students, who are understandably interested in their career trajectories. This year, we’ve dedicated a lot more time to career development. The students get to really think about the entire arch of the field and decide where they want their specific contribution to be. I think that’s what’s missing from most career training in the sciences. People get really focused on what they do without really knowing how it fits in the big picture.

Farran: We also wanted to bring in faculty who would be able to showcase – and instruct – on the details of the many new emerging techniques in vision research, because that’s what the students are using. In previous iterations of the course, we had people doing traditional techniques but not necessarily branching out into the new, so we made a push to include faculty who are using a bit more cutting-edge techniques.

Andrew: The field now readily embraces everything from mouse to primate models to humans. It used to be rare that a lab would do more than just one or two techniques. Now, it’s not uncommon for people to lecture about everything from virology – not in-depth virology but the use of virus – to systems neuroscience and computational methods. We also include stuff on atypical model species: we brought in someone who works on marmosets and had discussions about comparative approaches.

Farran: And imaging. A lot of imaging.

Andrew: We’re focusing less on development now, mostly to reflect the fact that a lot more people are interested in visual system disease. We brought in two clinician lecturers this year and have a few students who are clinician scientists.

For those interested in applying for the course on Vision: A Platform for Linking Circuits, Perception & Behavior, here is additional insight and advice regarding the application process:  

Andrew: If someone is interested in attending the course, they should have an interest in vision, be highly motivated to learn, and have something they want to share, questions, or something they’re wondering about - and that can be anything related to the course topic. We respond well to someone who is both excited to learn and excited to contribute. The students are as much a part of the course tutorial as the faculty because they ask really, really good questions.

Farran: We aim for a class of participants who are both graduate students and postdocs. One of the things we look for are postdocs transitioning into vision from another field, because this is a sort of crash course for them and opens up a new professional family they’re going to belong to. And in all of the applications, we look for a passion and excitement for vision research.

Thank you to both Farran and Andrew for taking the time to chat with us. For more conversations with our other meeting organizers and course instructors, go here