|
By Shruti Vij To advance human brain mapping we need to develop and identify novel facets of brain function, and understand how they are affected in clinical disorders. Like any other field, we rely on young investigators to bring innovation and creativity. And when we find stellar individuals that contribute towards the advancement of the entire field, we reward them, with a Young Investigator Award! This year’s OHBM Young Investigator award winner is one such impressive researcher with a reputation for making significant contributions to cognitive neuroscience – Lucina Uddin. Katherine Karlsgodt from UCLA who nominated her for the award introduces her as “a researcher with remarkable focus and productivity”, highlighting that: A remarkable feature of Dr. Uddin’s work is her ability to bring together sophisticated neuroimaging analytic approaches with important and insightful theoretical questions. As one example, over the last several years she has developed and tested a novel model of network function focused on the role of the insula (and the salience network as a whole) in large scale brain network dynamics. She has supported this model empirically with a series of innovative papers in high impact journals, presenting the theoretical development of her model and its relevance to understanding autism. Consequently, she has become a sought-after speaker for many national and international courses on neural connectivity, an impressive accomplishment for someone relatively early in her career. I have no doubt that she will continue to apply her strong work ethic, acute intellect, and leadership abilities to this project and that the results will have considerable impact on our field. As a postdoctoral fellow in her lab, it is an immense personal pleasure to interview Lucina Uddin and to discover the makings of a talented Young Investigator. Shruti Gopal Vij (SV): Congratulations Lucina on winning the young investigator award at OHBM this year! Tell us a little about yourself --- where you come from and how you grew up. Lucina Uddin (LU): To make a long story short, I was born in Bangladesh and my parents immigrated to the United States when I was less than a year old. So, I spent most of my time growing up in southern California and then moving from coast to coast to get my postdoctoral training at NYU and Stanford till I finally ended up here in Miami! SV: Do you like it here? LU: I love it here. I live on the beach and I really enjoy it! SV: What was your first reaction when you were notified that you were the winner of this year’s OHBM Young Investigator Award? How did you feel? LU: I was really happy because it is always great to have your work recognized. I was also surprised mainly because if you look at the previous 21 years’ awardees for the Young Investigator award, I don’t fit the profile of being a white male researcher. So, I was really surprised to be honest! But I have to say that I think the OHBM leadership has done a wonderful job in recent years in addressing issues of gender and diversity in the organization both at the program committee level and at the leadership level. So, I am happy to see these issues really come to the forefront now. SV: When did you start thinking about cognitive neuroscience and developmental neuroimaging? LU: I went to UCLA, which is a really large school with over a hundred and thirty majors for undergrads to choose from. It was overwhelming, but at the same time I did what I guess any 18-year-old would do. I looked at the list and thought about which one seemed cool to me. Neuroscience jumped out at me, and so I picked that as my major and to this day I haven’t regretted that decision. And then as all my friends started preparing for med school, I realized that I didn’t necessarily want to become a doctor. The other career path that seemed viable was research, and I ended up having the good fortune of staying at UCLA for my PhD with a great group of mentors who basically let me do what I wanted. That was where I got to just explore cognitive neuroscience, learn from the experts and figure out what really interested me. And I am still doing it to this day. SV: Why do you feel so passionately about developmental neuroimaging and autism research? LU: Autism is a very interesting disorder. I was very excited when I got the opportunity to do my first neuroimaging study on autism as a graduate student, collaborating with Susan Bookheimer and Mirella Dapretto. It was just fascinating to me how different individuals with autism are from each other. There is such heterogeneity in the disorder, and there are also varying levels of abilities. There are severe impairments in some individuals with the disorder, and in other cases there are exceptional skills. I just thought it was a really unique condition and I really wanted to learn more about the brain basis of it. So I continued that research as a postdoc and still do it now as a PI. SV: What has been your scientific approach to excellence? LU: Oh, I don’t know about that! But I really value collaborations with friends and colleagues all over the world and I encourage students and trainees at the lab to look outside of the lab for growth and learning. The reason for that is that I have a background in neuroscience and cognitive psychology, and because I am trained in a particular way, there are some things that I am great at and other things that I really struggle with – statistics and programming are not my strong suit. So, I always try to surround myself with computer scientists and engineers and other people that I can learn from and hopefully we can have a symbiotic relationship. At least that’s the way I see it. But I think everyone stands to benefit from collaborations. And I try to push that in all of our projects. SV: How have your life experiences affected your mentoring methods? LU: I mean being a mentor is like being a parent (I imagine) except you have a lot more kids. So you say “I am not going to do it that way” or “I will try to emulate this mentor that I really enjoyed”. I think I have learned a lot from everyone I came in contact with. My graduate advisor Eran Zaidel always brought food to lab meetings and I thought “That’s a great idea! Why shouldn’t there be food at lab meetings?”. We always had great discussions and he always let us pursue exactly what we wanted to. So, I have taken that approach quite a bit, which is trying to figure what people want to study and making sure that there are no obstacles for them. Trying to put people in touch with the right collaborators for the right idea and just being open to new ideas. And that means people are going to fail, and I am open to that. I think everyone needs to fail and learn from failure. So, I think my own mentoring has been sort of hands off. Do what you want and I am going to try to point you towards the resources that will help. SV: Have you had a singular inspiration in your life? LU: Well I have to say that it was my father. He came to the US at age 34 to complete his PhD in comparative literature. He basically started his life all over again, learned a new language and experienced a whole new culture. And you know a lot of immigrants do that and succeed. It is definitely a lot harder to do than what I had to do which is live in the same country most of my life (with the exception of a six month teaching stint at the Asian University for Women in Bangladesh in 2010). So, I consider myself really lucky and try to make the most of it. SV: I guess this year has been really exciting for you! You got your tenure and now the Young Investigator Award! What is the next step for you?
LU: Well, people always say once you get tenure, you can do whatever you want. But I have always done whatever I want. I haven’t particularly done things in pursuance of tenure or specific types of research because they were trendy. If anything, I was working in resting state fMRI in 2006 when really it wasn’t trendy, it was very fringe. People sort of looked at you funny if you said you are looking into intrinsic networks or resting state networks. They didn’t take it seriously until much later. So I did what I thought would be interesting and I am going to continue to do that. And one way to capitalize on recent trends in open science is to take “big-data” approaches. The Human Connectome Project and many other sources have become available for researchers to mine. It is great for discovery and good for students. I think we are going to continue to go more into neuroinformatics and computational neuroscience. I am hoping that in a few years, I will have time to take a sabbatical and visit a few big computational neuroscience labs and learn more about it. SV: Do you have any significant advice that you want to give to the OHBM mentees? LU: My advice to mentees is don’t take anybody’s advice! Because it is hard to glean truths from other people’s experiences. I think you have to be honest with yourself at every step of the career. People always ask advice about personal questions and nobody’s responses to these questions are going to be necessarily applicable to you. So I think you have to assess your own needs and wants in terms of both your career and personal life. And I have done things both professionally and personally that I am proud of and others that I regret. So, I am not in any position to give any advice other than to say make sure that you are honest with yourself when making big life decisions. SV: Last, University of Miami is now launching a Cognitive and Behavioral Neuroscience Program which you are spearheading. Can you tell us a little about it? LU: Yeah. I am excited that we are starting this cognitive and behavioral neuroscience program here. There is a real need for training in this area and we previously didn’t have the resources in place for that. But now we have the faculty and curricula in place. We have an excellent group and most of the necessary courses. We are excited to take graduate students and I am hoping to bring some of the great things I learned from UCLA’s neuroscience program to the University of Miami and continue to grow the program. SV: Thank you for all these wonderful insights into what makes this year’s OHBM Young Investigator an accomplished researcher. Congratulations! As the interview wrapped up and I headed out to my office next door, I was left with immense inspiration for the future of my own academic career as an immigrant woman in science!
1 Comment
Innovation doesn't come just from giving people incentives; it comes from creating environments where their ideas can connect. June 28th 2017, Vancouver, 4:30 am Looking out the window in that predawn hour, it was like peering into the black box of time itself, a place where the past, present, and future come together. But as I watched, the sky played with at least a thousand permutations of midnight blue, before it burst into all hues of gold and red. It was at that moment that I thought to myself … “it’s gonna be a great ride today”. Because, not only was I launching the OHBM Student and Postdoctoral Special Interest Group’s inaugural Mentorship Symposium that afternoon, an initiative that I ardently hoped would continue in future years, but also would I be interviewing Marsel Mesulam, a founding member of OHBM and a longstanding academic inspiration of mine. June 28th 2017 was the day I was going to board the OHBM time machine to record an oral history of neuroimaging from one of the pioneers of the field, and gain his perspective on its future.  Organization of Human Brain Mapping - An incredible journey thus far! AmanPreet Badhwar (AB): I would like to start by asking you about your background and why and how you became interested in neuroimaging. Marsel Mesulam (MM): I started Neurology residency way back, I believe in 1973 or 1974, and I was at that time trying to make a choice between psychiatry, psychology, and neurology, so it was very clear that the common theme in all three was brain function. The question was how I was going to approach it. I decided to go into neurology, and that was largely due to the influence of Geschwind, who was then at Boston City Hospital and teaching at the Harvard Medical School, where I was a student. Neuroanatomy became my main research area. So, with Deepak Pandya and Gary Van Hoesen, I carried out a number of neuroanatomical studies. I developed a method for tracing cortical projections in the primate brain. Neuroanatomy, and how it relates to animal models and complex behaviour, such as memory and attention, was my primary interest at that time. Since I was also a neurologist, I was trying to apply this information to my patients. When I was doing my training, there were no CT scans available. So at that time those of us doing very detailed neuroanatomy in monkeys, well when we tried to translate what we learnt into the human brain, there was really nothing. My first CT scan experience was like an epiphany, where I said “my goodness”!! At that time CT scans were very, very noisy. So then, one development followed another, and there were better CT scans. The first serious demonstration of fMRI was reported in Jack Belliveau’s paper in Science, and just before that he actually called me and said “come to my laboratory --- you’re gonna see something that you would not believe”. This was a Saturday, and we used to have a summer place we used to go to, so I had to make a special arrangement not to go away, and instead went to Jack Belliveau’s lab. That day the experiment did not work! Over the next few months or so everything started to work, and there was this Science paper that was a revolution in the field. I mean the ability to see function in the living human brain, and with decent anatomy! Those developments made me shift my laboratory focus from primate connection neuroanatomy to imaging, so I could apply what I learnt in the monkey to the human brain in neurological patients with specific lesions. That’s how I got interested in the field. AB: What was it about the fMRI experience that moved you --- the protocol, the equipment, the potential knowledge to be gained or simply the esthetic beauty of the end product - the image? What inspired you to shift gears from traditional neuroanatomy to imaging? MM: For people who do the kind of work that I do, which makes up the majority of OHBM members, our algorithm is “where in the brain does such and such happen”, i.e. localization of function from the ‘very, very simple one area, one center’ to a ‘very, very complicated and parallel distributed processing’. The beauty of new modalities, like fMRI and PET, is suddenly the ability to see function in a real brain in anatomical terms. And that was an absolute revolution! I cannot think of any other event in the history of cognitive neuroscience that made such a difference. So the beauty is inherent in the anatomy of the human brain. What the imaging did is that it allowed us to see and experience this beautiful complexity in a living human brain. AB: You are a giant in the field of neurodegeneration. What do you feel are your most significant contributions? MM: That’s a good question, a humbling question. You know I don’t think I would be able to name any single contributions in the imaging area. But in contrast, there are things that I did in my neuroanatomy days that were new discoveries. The beauty about neuroanatomy is that it changes over millions of years. So once you discover something, it’s true for a few million years. And I have made some discoveries in neuroanatomy that were published maybe 30 to 35 years ago and are as true today as they were then.  Twitter feeds relating to Marsel's lecture at OHBM 2017 In the field of imaging we are dealing with a much more flexible, shifting atmosphere in that things that are discovered evolve over time. Truth is much more elusive in imaging. So I have published lots of articles, but I must say that I can’t point out to something and say that this discovery has withstood the test of time, that’s not the sort of thing that imaging lends itself to. My first involvement in functional imaging was in the network for spatial attention; I did the neuroanatomy in the monkey, and then applied it to the human. In fact I wrote a paper a long time ago called ‘Large scale neurocognitive networks and distributed processing for attention, language, and memory’, that was one of the first times the word ‘networks’ was used for human cognition. It was based on my adaptation of the macaque monkey cortical interconnections to the human spatial attention network and hemispatial neglect syndrome. In that way I was able to apply the physiology and anatomy of networks that was described in the monkey to the human condition and then take it to functional imaging to confirm the relationship between the two. So I came up with a system of serial connections embedded in parallel connections to come up with the principles of distributed processing in cognitive networks. I think that is a lasting contribution even though it has been much embellished and improved, but it’s not a single finding, it’s a conceptualization. And then my recent work in primary progressive aphasia and language, I think that it is adding something to the field. AB: Being involved with OHBM from the very beginning you see the big picture of human brain mapping as a field. How do you see neuroimaging moving forward? Do you still expect really big changes? MM: Yes. Yes. Its an issue of specificity, of resolution. Resolution in space. Resolution in time. But it’s important to have a sense of perspective. Sometimes when students and postdocs come, they tend to be very focused on methods. And they say, “we would like a 7 Tesla” , or we would like this and that, i.e. more precise measurements. I give them the following thought experiment: let’s assume I give you the following apparatus that will allow you to put the intracellular electrode in all 40 billion neurons with recordings. What will you do with the information? You really need no more precision than your conceptual framework requires. So every time there is a new development we have to take a deep breath and say, how do we integrate this precision with our concepts of brain function before going further. OHBM has done that beautifully. When we started initially, PET scanning was dominant, fMRI was just coming in. And now we have more precision, more powerful magnets, more analytical methods. So there is a tremendous set of advances, alongside conceptual advances --- the task is to integrate the two, and see where we go. But as a society, I think this is a tremendous success story from where things started back in Paris in 1995 to where things are now. One thing I have always liked about the OHBM -- there is a tremendous amount of young people who get interested in this, and that’s great! AB: I would be interested in knowing how OHBM come together as an organization? Also, how has it evolved over the years? MM: In 1994 I got an invitation to attend a meeting in Paris. I believe it was Bernard Mazoyer who convened the meeting. It was something about imaging at that time, PET scanning was the main modality. At that time there was no OHBM, and it was not entirely clear where this meeting would go. It was absolutely a fantastic meeting! It left the desire to do it again. The decision was made to go to Boston in 1996. Bruce Rosen took responsibility to organize this meeting, and the story is that he had to mortgage his house to guarantee the financial backing of this meeting.
 In 1996 there was a huge debate of what to name this group. There were people who said it had to be a Society, but there was a tremendous pushback because people said that a Society means that you have to pay dues, and we don’t want to pay dues. All we want to do is organize a yearly meeting. So it was called the ‘Organization’. Of course now we pay dues! With dues we started to have enough money that we could back the financial risk of the meeting without having to mortgage our houses. Then I joined the council. There, we wrote the bylaws that you now follow, to have a committee of current president, the president-elect, and the past president, so three in each of the various levels. I actually wrote the rules for that. Of course it went through council discussions and modifications. Those were the formative years.
There were also some watershed meetings. For example, I was interested in writing a review or commentary from my point of view as a neurologist, and what made it possible for me to write this paper which was titled “From sensation to cognition”, was what I saw in the Copenhagen meeting. Because the Copenhagen meeting was the first time that fMRI really showed what it could do. That was the first time that we saw functional imaging of the face area, of memory circuits, it was a fantastic meeting. Every year has its own personality. These days there are a lot more topics, a lot more multidisciplinary interactions, and a lot of energy. AB: Do you find there is a greater proportion of students now, or have the demographics remained similar? MM: It’s pretty similar. There is always this tremendous energy coming from young people. Students, postdocs, and that’s the driving force behind the society. It’s always been that way. It was never top heavy! There was always the encouragement of young people to participate as much as possible. In fact, I have now been invited to be on the scientific advisory committee board, they took the ancients and put them together in a committee (MM smiles), and one thing I suggested is that the council should have a representative from postdocs and students so that your voice could be heard at the decision making level which may be helpful. AB: That’s really wonderful to hear!!! AB: It was wonderful talking to you, revisiting OHBM’s initial days, and discussing its role in the future of neuroimaging. Thank you for taking the time out of your busy schedule and making this interview possible. Thanks also to Sarabeth Fox for filming.  Bernard Mazoyer By Nils Muhlert Bernard Mazoyer, Professor of Radiology & Medical Imaging at Bordeaux University Hospital, has been at the forefront of the human brain mapping community for thirty years. In 1989, Bernard, Nathalie Tzourio-Mazoyer and Marc Joliot founded the functional imaging group (GIN-IRM), the first neuroimaging group in France. As a founder member of OHBM --- indeed, organising what was to become its first meeting in Paris --- Bernard has seen the organisation grow from hundreds of members to many thousands. Here we find out about his background, and his views on why OHBM may now be ready to become a society: Nils Muhlert (NM): Can you tell us about your route to neuroimaging? Bernard Mazoyer (BM): My initial background was in mathematics, which I completed with a PhD in biostatistics. I taught maths for a few years but I was more attracted by maths applied to biology and medicine. So I decided to go to medical school and started doing research in a medical nuclear imaging department. My first project in 1979 evaluated the paths through which blood moves from outside to within the brain by measuring the transit time of a radionuclide injected in the carotid artery using brain images provided by a gamma camera. Soon after my MD, I spent 2 years as a postdoc at the Lawrence Berkeley Laboratory where I worked on PET and MR advanced instrumentation and image processing. When I returned to France in 1986, Marcus Raichle and his colleagues from Saint-Louis had invented the PET O15 water brain activation mapping method and I was hired by the Atomic Energy Commission to implement and develop applications of this method. With my colleagues from CEA, namely my wife Nathalie Tzourio and Marc Joliot, we founded the GIN, the first research unit in France devoted to human brain mapping (HBM). Thirty years later we are still working together in the HBM domain. NM: What do you feel have been the real breakthrough findings within GIN-IRM? BM: Hard to answer that question! The GIN has been in the field since 1989 and has contributed over 200 articles. Besides, as with several other pioneer research groups in the HBM field, over its lifetime the GIN has gathered researchers from a variety of fields, from neuroimaging methods to cognitive (language, attention, mental imagery) and clinical (schizophrenia, Parkinson disease, Alzheimer disease) neuroscience. If I were to select the one study that I believe has had the highest impact on the field, I would certainly put forward the AAL: the atlas of anatomical ROIs. In the mid-1990’s the brain mapping community had largely adopted the stereotactic averaging approach, but there was no standard for labeling activation. On our side, we were interested in individual variability and thus very eager to match structural MR with PET. The AAL was conceived by Nathalie to solve these issues. Building upon a longstanding collaboration with the French neuroanatomist Georges Salamon, Nathalie designed an atlas of ROI’s having sulcal limits, literally spending days tracing the sulci and gyri on Louis Collins’ brain MRI slices. This quite tedious work provided the community with the reference anatomical labeling method it needed. Amazingly, in 15 years, AAL has reached over 5,000 citations and has been adopted not only by the HBM community but also by many clinicians.  Bernard and the GIN team in Paris, 1995: OHBM's first local organising committee. NM: You’ve been involved in OHBM since the very beginning. Initially, what were you looking to achieve, or what particular interests did you want to highlight, through OHBM?
BM: The main goal of the first OHBM meeting in Paris in 1995 was to gather together the different communities involved in human cognitive neuroimaging. In the early 1990’s, PET was in its golden age thanks to the O15-water blood flow mapping, functional MRI was just born, MEG was being developed and EEG-cartography was just starting. Cognitive process mapping was the common denominator for all, but was not clearly identified as a field of research of its own. As a matter of fact, there were no meetings or professional societies where these different communities could meet. In particular, methodological issues were very important but there was rarely an open forum for discussions. So Paris was really designed as a place for exchange between neuroimaging communities with the long-term prospect of gathering all communities within a common scientific society. NM: How do you feel the organization has changed over the years? Do you feel Alan Evan’s famous OHBM helmet can stay safely locked away in his office, or have there been times when the debates may have required it? BM: The main change that has happened over the past 20 years is certainly the sustained development of OHBM, in terms of membership, meeting attendees, and spectrum of activities. Membership has reached 2,000, and while 900 people showed up in Paris 1995, an average of 2,500 have attended the recent OHBM meetings. More importantly, we started as an organization, i.e. a structure focused on setting up an annual meeting. Today, my personal view is that we are now a society, i.e. a group of individuals, with a large spectrum of shared activities besides the annual meeting. To name a few, we have regional chapters, special interest groups, committees on gender and diversity, multimodality, education, career, and we are developing relationships with societies’ sharing some of our goals. This development has been progressing over the past 20 years and came about as the result of demands from the OHBM community. I am not saying that some strategic options and their implementation did not raise concerns and debates. But, apart from that very hot first business session in 1996 in Boston, this development has been discussed and conducted in a constructive and peaceful atmosphere. So yes, I consider it very unlikely that Alan’s helmet will ever be used again. NM: We’ve recently found out that OHBM 2018 will now be held in Singapore. How did this decision come about – and what can we look forward to in the Lion City? BM: Due to the continuous degradation of the relationships between North Korea and other countries and repeated demonstration of military threats, both OHBM office and council members have received since June numerous messages of concern from OHBM members and sponsors about holding the 2018 meeting in Seoul. According to our bylaws, only the council can decide on the annual meeting location, and discussions between council members have been under way for several weeks. In September, the decision to move the meeting away from Seoul was approved by a very large majority of Council members. But it has been a difficult decision to take for every one of us because we were all well aware of, and very grateful for, the extraordinary job done by our Korean colleagues within the Seoul local organizing committee. However, we were also conscious that the meeting had to be moved away from Korea in order to give everyone a chance to attend next year’s meeting. This was the basis for our decision. The choice of Singapore was less difficult, first because we wanted the meeting to stay in Asia, and second because Singapore was previously shortlisted as a potential host for OHBM2018. So, with the help of our Singapore colleagues, who were very responsive in forming a local committee, we all expect to have a great meeting in Singapore despite the overlap with the ISMRM meeting. As always, it will be attendees who make the OHBM 2018 meeting a big success. NM: As OHBM Chair, what do you hope to achieve during your tenure? BM: My first hope is to successfully lead the building of the new OHBM strategic plan for the next 3 years. It is Karen Berman who pushed the idea of having a strategic plan and it is under her leadership that the first OHBM strategic plan (2015-2017) was conceived. This plan has been instrumental in implementing fundamental elements of OHBM functioning and development. To name a few, gender and diversity, the increased role of students and interactions with other societies have been essential and successful components of the first strategic plan. In the new plan, I hope we will include among others very important topics such as developing HBM science in countries with limited resources, promoting the role of brain mapping in education and healthcare, and open science. My second hope is that OHBM becomes a Society. My view is that an Organization is a structure set up with a defined goal whereas a Society is a gathering of individuals sharing common interests and values. I believe that the past history of OHBM and its current large spectrum of activities both advocate for becoming a Society. My third specific hope is to have multimodality increase its place and visibility within OHBM. We need to be more open to methods other than MR and to be at the forefront of combining brain signals. But we need also to promote multimodality in a broader sense, namely combining neuroimaging signals with signals obtained at other scales, from genes to behavior, as well as in species other than humans. This, I think, is one of the main aims of OHBM future development. NM: Last, what do you see as the main challenges facing OHBM over the next 5-10 years? BM: OHBM is still a young “Society” and its steady development over the past 20 years has been fueled thanks to the advent and development of in vivo HBM tools and related neuroscience research at the systems level. This field of research is very rapidly expanding. In my opinion, the major challenge facing OHBM in the future will be to maintain the coherence of the HBM community while attracting scientists from other domains that are now essential for understanding brain systems. Maintaining the coherence of the HBM community is a challenge by itself, as the risk of split from groups of people with insufficiently represented special interests is very high, given the size of OHBM. Meanwhile, attracting scientists from other domains is a challenge as well, as it will require giving them the space they need within OHBM. NM: Many thanks Bernard - we look forward to OHBM 2018 in Singapore! by Agâh Karakuzu The 5th OHBM Hackathon was an official component of the 23rd Annual Meeting of the OHBM held in Vancouver, June 25-30th 2017, with support from two leading open science institutions: the McGill Centre for Integrative Neuroscience, and the Stanford Center for Reproducible Neuroscience. Imagine entering a room full of people with flashy stickers on the back of their laptops. Gathering around tables, they stare at screens full of code, colorful text on a black background reminiscent of the code rain from the Matrix trilogy. Welcome to the control room of computational neuroscience! There is a reason why we call these neuroscientists ‘hackers’: they are hacking to provide their colleagues with accessible and powerful computational methods, or whatever means necessary, to crack the brain code.  OHBM 2017 Hackathon While trying to wrap my head around a way to explain the hackathon concept, I received an email by the Free Software Foundation. It was an article by Richard Matthew Stallman (‘rms’, considered by many to be the founding father of free software), explaining why hackathons should insist on developing free software. Such a lucky coincidence! Its opening lines were an eloquent description of the core mandate of hackathons: “Hackathons are an accepted method of giving community support to digital development projects. The community invites developers to join an event which offers an encouraging atmosphere, some useful resources, and the opportunity to work on useful projects.” OHBM Hackathons are organized by the OHBM Open Science Special Interest Group (SIG), to achieve open sharing of ideas, data and tools between members of the OHBM community. In line with this mission, most projects in the hackathon aimed to improve analyses using free software libraries, releasing computational tools from the grip of proprietary software. For example, the AFNI Love project team built some of the most complex tools for Analysis of Functional Neuroimaging (AFNI) into nipype, an open-source Python project that aims to piece together algorithms from different packages into a single processing workflow. Managing to complete the project in only three days, this team demonstrated how the hackathon could bring people together to create useful new software, while also creating networking opportunities to connect novice and more experienced hackers, and planting the seeds of long-term, more ambitious projects. This is well summarized in the following tweet by Pierre Bellec, the chair of the OHBM Open Science SIG:  Dylan Nielson introduces the AFNI love project team: Katie Bottenhorn, Taylor Salo, Elizabeth DuPre, Matteo Visconti di Oleggio Castello, and Ross Markello. Pierre Bellec has put his heart and soul into the hackathon for years, and this dedication has clearly paid off. In discussing this year’s hackathon he told me: “Vancouver, that was beyond anything I’ve seen so far. Because, there, the hackathon had matured and taken on a life of its own. I feel like the previous hackathons were more like experiments, a recipe in the making. This time around the community jumped right in, everybody knew their part and seamlessly integrated the new members. By the end of the event, there was no telling the newcomers from the veterans.” Indeed, the level of productivity and communication in Vancouver was off the charts. After talking to Pierre, I spotted my friend Gregory Kiar, whom I first met at the hackathon. The most exciting thing to him was that so many new people were coming into the hackathon and, in a short period of time, achieving something remarkable. He mentioned how five projects were merged into one, as captured by another member of the hackathon organizing committee, Kirstie Whitaker:  Gregory Kiar presents a brief outlook on the project Clowdcontrol with his teammates: Anisha Keshavan, Lee Tirell, Amanda Easson and Chris Gorgolewski. The OHBM hackathon is designed to encourage collaboration and sharing of knowledge, rather than competition. This drives productivity and enables people to learn and develop quickly. During three days of hacking, the teams worked hard to develop software that could make computational neuroscientists’ lives easier. Most importantly, several small and somewhat redundant individual projects will merge into an open source collaborative effort, with much higher chance of long term success and reaching high code quality. For instance, Mindcontrol, Abide, Deep-qc, Clowder and Freesurfer teams united their considerable hacking prowess under one banner: Clowdcontrol. This new user friendly web platform can run demanding “deep learning” analyses in large and distributed networks of computers - the metaphorical cloud. The PyNets project team developed a Python toolbox that automates functional and diffusion-weighted MRI network analysis. By leveraging existing open source tools, they were able to assemble an impressive array of methods, that has kept growing since.
To conclude, the hackathon served to pull together researchers from different institutions as a team while being open to add new members and committing themselves to push the limits of productivity during the event. While the previous sentence was sprinkled with GitHub jargon, the good news is that even if none of these commands ring a bell with you, you are always more than welcome to participate in the Hackathon. As long as you don’t let the jargon intimidate you, the Hackathon will help you gain useful skills on the fly, make new connections and broaden your academic horizon. As one of the participants noted during the wrap-up, the OHBM hackathon is helping to put back the collaboration and the fun at the heart of science, right where it belongs. Hope to see you at the OHBM Hackathon 2018 in Singapore!
 BY RUSSELL POLDRACK, 2018 OHBM EDUCATION CHAIR
The Educational Courses at OHBM are an essential part of the meeting for many attendees, and we are always looking for ways to make them more effective and engaging for a diverse group of participants. Educational courses are selected based on submitted proposals from the community, with submissions due on Dec 15. We desire a diverse set of presenters, and women and individuals from underrepresented groups are strongly encouraged to apply. Historically, educational courses have been composed of lectures along with some time for discussion. This year we would like to encourage proposers of educational courses to consider the adoption of active learning approaches in their proposals. Active learning means many different things to different people, but in general it refers to approaches in which the student takes an active role in the learning experience beyond simply absorbing information from the lecturer. A substantial body of research has shown that active learning approaches improve educational outcomes and student engagement (see for example this commentary by Carl Weiman). Additional information about these approaches can be found at the CSWEI and the University of Michigan. The spectrum of active learning is broad, and we encourage proposals that span the range of possible activities. This document from the University of Michigan outlines a number of ways to incorporate active learning into the classroom, several of which could possibly be used in the context of an OHBM Educational workshop. At one end of the spectrum would be a fully active course in which a set of brief lectures is followed by hands-on group activities, with brief presentations by the groups at the end of the course. At the other end of the spectrum could be a standard lecture-based format in which the lectures include specific activities meant to engage the students more actively. These could include:
One important resource that could be used in service of active learning is the library of videos of educational courses from previous years that are hosted by OHBM OnDemand. These could be used as resources for students needing additional background knowledge prior to the Educational Course day. We hope that members of the OHBM Educational community will embrace the use of active learning in their proposed courses. We realize that it will require additional work beyond the standard lecture, but the science of learning strongly suggests that the adoption of active learning techniques will significantly improve learning outcomes for the community. Q&A with Wouter BoekelBy Neuroskeptic & Chris Gorgolewski At the 2016 OHBM Annual Meeting, a new ‘Replication Award’ was announced that aimed to promote and reward reproducibility in neuroimaging research, and to open science more generally. Here, we hear from Neuroskeptic, a prominent blogger and advocate of open science, as to why replication studies are pivotal in improving the quality of our science. We then learn from this year’s recipient of the OHBM Replication Award, Wouter Boekel, about his winning study.  Neuroskeptic: I’m very pleased to have been invited to write a few words on why replication studies are important in science. Congratulations to Wouter Boekel for winning the Award (for a study which I blogged about at the time it was published). In my view, replicability is the essence of scientific truth. To say that a certain scientific result is true or valid, is nothing other than to say that someone, who correctly carries out the same methods, would be able to confirm it for themselves. Without the assumption of replicability, scientific papers would become merely historical documents – ‘we did so and so, and we observed so and so, but your mileage may vary.’ While most (although, I should acknowledge, not all) researchers accept the importance of replicability in principle, it is still common to hear it said that actually doing a replication study is unworthy of a good scientist. Sure, replications are all very well, but they’re not very exciting. Even some journal editors have been known to express this view, refusing to consider any replication studies for publication in their journals (although I think this is becoming less common). The problem is that replications lack novelty, which is, at least for many people, the hallmark of science at the highest level (or at least, the highest impact factor). I think that this cult of novelty is unfortunate. While novelty can be a virtue in a scientific work, this is only true if the result is valid. A novel, but false, claim is unlikely to advance science, while a failure to replicate such a claim does. Successful replications, too, are a contribution to science. It could be said that they ‘merely confirm what we already knew’, but in fact we can’t assume that a given claim will be confirmed, until it is. To build a road through the wilderness, we do need pioneers to map out a new path, but we also need people to check the path is sound.
From today’s perspective, it is relatively simple to acquire questionnaire data or a computerized task in combination with a T1- or diffusion-weighted structural scan. So most of the early data on brain-behavior relationships came from these kind of studies. At the time there were also increasing concerns coming from experimental psychology about problems with replicability and reliability of research findings. An increasing number of publications started to warn of file-drawer effects, questionable research practices, and sample size. There were also some notable cases of large-scale misuse of statistics and research methodology at the time, which further attracted attention to these concerns. We found ourselves in the middle of a fast increase in the rate of published cognitive neuroscience articles on one side, and increasing concerns about reliability and the absence of replications on the other. This seemed the perfect environment in which to set up a replication study of some of the many structural brain behavior correlations which had been discovered. CG: …and what did you find? WB: We tried to replicate a total of 17 structural brain-behavior correlation effects. Our Bayesian statistical results suggested there was reliable evidence for the absence of 8 of the effects, and none of the effects were reliably present when viewed through a Bayesian lens. We used some other statistics as well, including the p-value, which showed 16 non-replications. CG: Was the definition of replication problematic? WB: Yeah it was – this came back in the review process, and later in the commentaries and online discussions. We defined a ‘failure of replication’ as the inability to find a significant effect or a convincing effect in Bayesian terms. But that also means that we considered an absence of evidence to be a ‘failure of replication’. Maybe some other people would say “That’s a bit more ambiguous, you should reserve the ‘failure of replication’ only if you find convincing evidence that the effect is absent.” So, yeah, there were difficulties with that. CG: So if you rephrased the categories into: definitely replicated, definitely not replicated, no effect, and somewhere in between, what are the numbers then? WB: We found 8 effects where the Bayes factor was higher than 3. That means that the data were more than 3 times as likely to have occurred under the null hypothesis. For us, that number 3 was pretty convincing; in those cases we were satisfied that the effect was definitely not replicated. The other half – 8 effects – were more ambiguous. The Bayes factor for those tests was around 1, and mostly in favour of the absence of the effect, but not so much that we could make the claim that it was definitely absent. So, it was about 50/50. CB: Many of these comments came up after the paper was published. I know that there was a commentary and a rebuttal – bringing up concerns. How did you address them? WB: Indeed, two commentaries (here and here) came out of these discussions and we subsequently wrote a rejoinder as well. There were also discussions online in Neuroskeptic’s blogpost. The issues were mostly about our sample size. We had just 34 subjects, 35 for some effects. That was a bit low compared to some of the original findings - some of the original studies had over 100 subjects. That was raised as an issue in the commentaries. They definitely had a good point and we just tried to reason that this was new at the time, carrying out this sort of replication, so any replication is better than no replication, even if the sample size was modest. Another concern was about the differences in the pipeline that we used. We used FSL for the analysis of our structural data. Some of the original studies used SPM or other software. At the time we were familiar with FSL so we decided to use that. We assumed that volumes of grey matter would be similar using different software. It was demonstrated in the commentaries, that the algorithms used by different imaging software does impact on volume measurements. In future other investigators can look at the differences you get when using different analysis methods. CG: Critically, you preregistered the methods for the study and notified the authors of the original studies beforehand. Were there any complications or challenges in doing this? WB: Preregistration was pretty new back then. I think Cortex was just starting to set up their preregistered reports format and there were some other journals becoming interested in such a format as well. We decided to publish our preregistered methods on a blog. The main difficulty there was in deciding what to preregister, and what not to. There were no standardised guidelines yet so we had to think of our own. Indeed we also notified the authors of the original studies, who were very supportive and some even provided files that made our analyses easier and more comparable to the original study. CG: And to wrap up, what advice would you give to people who are planning or wanting to publish a replication?
WB: I think it’s really nice to involve the authors of the original work – send them your plan for replication and find out whether you should use a different method or just make sure that you’re doing the study correctly. That’s a good tip because it makes it a lot easier if you then find an effect that’s not there – you find a null effect – then it becomes more difficult for the original authors to try to find something by which they can discredit your finding. They agreed to the way you did it – so if you adhere to the preregistration then you should be fine. In addition, if everyone would replicate all of their published experiments at least once, that would already provide the field with a large increase in reliability. With that idea in mind I would advise any researcher who is interested in replication to start by replicating one of their own published studies. This should be easier than replicating someone else's study, simply due to the familiarity with one's own methods. I would also say – try to do it on a larger scale. This was one of our first replications so we only had a small sample size. In future it would be beneficial to have a larger sample, that would be an advantage. CG: Thank you so much and congratulations once again. The call for nominations for the OHBM Replication Award is now open. Deadline is January 12, 2018. For more information about the OHBM Replication Award, review the nomination criteria here and read our Q&A with Chris Gorgolewski. Neuroskeptic is a neuroscientist and a blogger for Discover Magazine. |
BLOG HOME
Archives
February 2021
|
RSS Feed