Some say life is about choices, and to be human is to make choices in a way that sometimes defies logic. Call it intuition or instinct, there is often more than meets the eye. Such choices are what make humans human, and Christian Ruff has committed his career to uncovering the inner workings of human decision making. This is human brain mapping near the “outer limits”.
Jean Chen (JC): It’s very exciting that your research embodies a tangible way in which neuroimaging could have social impact outside of medical and biological research. Can you outline for us what path led you into this field?
Christian Ruff (CR): Since my early undergraduate days, I have always been interested in why we behave the way we do, and why there are individual differences in this respect. The brain was the obvious place to look for the answer, and I started my research with clinical neuropsychology in psychiatric patients. While I found it fascinating to get to the bottom of each patient’s cognitive deficits and help patients cope with them, I came upon the impression that many of the deficits reflected idiosyncratic inabilities to cope with the test situation itself, rather than impairments in specific neuro-cognitive functions. I therefore switched to cognitive neuroimaging of executive control and reasoning in healthy, high-functioning participants, using experimental paradigms and models from cognitive psychology, cognitive science, and psychophysics. I continue to be excited about how this approach can identify brain activity that “physically“ corresponds to well-formed predictions from models of cognitive processes. Some nagging concerns as to whether the identified brain activity really controls the behaviour or simply reflects behaviour can be addressed by combining brain stimulation methods with the imaging. However, after some years of using this approach, I again felt that what I was studying did not reflect the neurobiological reasons for why participants behave the way they do. After all, in my experiments, I always told the participants what they should do, rather than letting them choose this for themselves as they would do in real life. This realization came at the time when decision neuroscience started to emerge, based on a cross-fertilization between behavioral economics, artificial intelligence, and cognitive neuroscience. The central idea of this approach immediately made sense to me - that we need to observe free choices with real-life consequences in order to understand and model the processes driving behaviour. I started to combine this conceptual approach with the neuroscience tools and concepts I had acquired in the time before, and have not regretted doing it ever since.
JC: The title of your OHBM 2017 keynote lecture is “Multiple brain systems for decision making”. Without imparting too much, can you comment on whether you think at this time human decision-making can be reasonably replicated using mathematical models?
CR: Within the limited scope of the tasks we use to study different aspects of decision-making, I think we are pretty good at capturing human choices with mathematical models. If we gave people choices between options that differ on a clearly defined dimension, we could for example replicate how a given individual chooses between options with different risky payoffs, how he/she chooses between options with smaller immediate or larger long-term payoffs, how much he/she chooses to maximise her own self-interest or to help others, and so forth. Where we are still limited is in our understanding of how these different facets of decision-making are triggered, weighted, and integrated in real life. For example, if you think of a typical choice situation from your recent past, it would be very hard or impossible for models to recognize by themselves whether your choice should be driven by concerns for risk, temporal aspects of the outcomes, or the consequences of your actions for other people (or combinations of these). We clearly need to make major advances on that front to start to truly understand and simulate human choices.
JC: Why do concepts from economics factor into your research on decision-making?
CR: If we want to understand something as complex as human decision-making, we cannot afford to ignore any sources of information on it. I therefore pay attention to all disciplines that have come up with ways to study decision-making. They all have strengths and weaknesses. For instance, Cognitive Psychology has developed well-controlled experiments that account for many different types of perceptual and cognitive limitations, but that may sometimes be too artificial to capture real-life behaviour. Behavioral economics is the opposite: It employs experiments that are close models of real-life decisions but that may sometimes not account properly for the participant’s perceptual and cognitive limitations. I try to combine these approaches, hopefully pooling their strengths. Apart from experimental approaches, economics provides interesting mathematical models that conceptualize choice behaviour as cost-benefit trade-offs. These models can be fruitfully linked with neuroscience models of how the brain processes and resolves conflict, helping us understand the neurobiological basis of behaviour in many different types of choice situations.
JC: Can you give some examples of how findings from your research could be applied in everyday life?
CR: Our research is basic science and is not designed to lead to direct applications. However, I hope it can provide inspiration or stepping stones for applied research. For instance, we have shown that brain stimulation of a specific area in the lateral prefrontal cortex makes people comply more with social norms, but only if they know that another human being may sanction them for violating the norm (by deducting money, similar to a fine). The stimulation had no effect when the same monetary sanction was issued by a computer. This shows that the type of norm compliance controlled by these processes may be much more sensitive to the projected social consequences of norm violations than to the purely material consequences. Thus, in situations whereby it is required to prevent violations of specific social norms, it may be more helpful to provide collective social feedback rather than to slap a monetary fine on offenders. However, concrete policy recommendations in this respect would of course require further applied studies.
JC: What do you think is the most exciting body of work coming out of your lab in the past 5 years?
CR: I am excited about all the research we do, but it appears that there are two major lines of work for which we get most feedback from the community and the public. One of these employs brain stimulation combined with imaging to understand our brains, which functions through processes dedicated to complex, uniquely human social behaviors. Until now, we have found evidence for such processes in the domains of norm compliance, honesty, and strategic social behaviour. The second line of work identifies generic neural computations that underlie both preference-based and perceptual decisions. These types of behaviours have traditionally been studied in isolation, but our work shows that there are shared neural-choice computations and shared principles of how both types of information are processed. This is important as it helps us understand how the brain can flexibly combine affective and perceptual information to control actions.
JC: How do you foresee the evolution of your research program for the next 5 years? 10 years?
CR: I hope to be able to merge the two lines of work mentioned above. Even though our brain appears to contain dedicated processes for social behaviour, we usually effortlessly combine social considerations with perceptual and preference-based information to take decisions. I therefore plan to model and study in much more detail to what degree abstract social information is processed during decision-making in ways that can be integrated with basic sensory and affective information. This will require unifying the separate computational models that have emerged in these different domains, understanding a lot more about their correspondence to both metabolic and electrophysiological measures of neural function, and establishing possible causal relationships. I also hope to tackle the question about individual differences more directly, by going back to my roots and investigating whether behavioural symptoms of psychiatric disorders may reflect disruptions in the neural choice processes identified in our research.
JC: Do you feel that the current neuroimaging methods are sufficient for achieving your goals? If not, how do you hope they can improve?
CR: I think no-one disputes that all of our current neuroimaging methods are limited. It is sometimes frustrating that we have to combine several techniques just to get a low-resolution glimpse of the location, timing, and causal role of neural processes. In the fantasy world, all these aspects would be covered by a single non-obtrusive method. Since this is probably not going to happen, I feel pretty comfortable addressing my questions with the present multi-modal neuroimaging and stimulation approach. The biggest limitation here is that the current brain stimulation and electrophysiological methods are largely limited to the cortical surface. This prevents us from fully integrating them with fMRI and from addressing many interesting questions. I have mild hope that this may change in the future, but do not want to be overly optimistic.
JC: Can you provide two pieces of advice to new/emerging/aspiring scientists?
CR: My first advice – at the danger of sounding cliché – is to follow your own instincts and passions when choosing the fields and questions you want to study. What matters is that you find a question fascinating - not whether it is en vogue, low-hanging fruit, certain to get you a grant, or the favour of a supervisor. Life is too short for studies targeting questions that you do not care about. Such studies are unlikely to keep you motivated and therefore will get neither you nor our knowledge anywhere.
My second advice is to value other people’s criticism of your work and use it to move forward. We have a tendency to become very defensive about our ideas and studies, which is understandable given the hard work necessary to develop them. However, this tendency can prevent us from truly listening and taking on board valuable information about whether and how other people understand our work. This is what ultimately matters for your science! Thus, a paper rejection with good comments can ultimately be more valuable than a clean acceptance, and a talk that triggers a heated and confrontational discussion can benefit you more than a muted applause without any questions.
BY NIKOLA STIKOV
Alan Evans is a natural storyteller. He has been with the OHBM since its very beginning, and he has the stories to show for it. We spent a pleasant afternoon in his office at the Montreal Neurological Institute (MNI), talking about the turbulent early days of the organization, peeling off the hidden layers of brain imaging, and wading through his memorabilia collection, which he affectionately calls ‘the little shop of horrors’. The central place in this collection is reserved for an old military helmet, which is only one of the many hats that Alan has worn for the society.
Nikola Stikov (NS): What is the story behind the helmet?
Alan Evans (AE): Well, throughout the 80s my contemporaries and I were going to five, six, seven different conferences in a given year, each covering different aspects of what interested us. Soon it became clear that we wanted our own community, so Bernard Mazoyer volunteered to organize the first OHBM meeting in Paris. Back then there was this big debate on whether we should call ourselves a society or an organization, because some people wanted to keep us paired with other existing societies, such as CBFM (Cerebral Blood Flow and Metabolism). This debate rumbled on from the very first meeting, and at the second meeting in Boston in 1996 I was asked to be a moderator of the town hall. So that afternoon I went to the local military surplus store, I bought a helmet and put it under the table. And then when the town hall started I said ‘I understand that today will be another chapter of what has become a contentious discussion, so I have come prepared.’ Then I put the helmet on and the whole auditorium erupted in laughter, diffusing the tension. Then I put the helmet back on the floor and forgot about it. But the story doesn’t end here.
NS: So what brought you to the MNI?
AE: I was one of two physicists working on the development of a PET scanner, a commercial version of the PET scanner that was built here at the MNI. The original PET scanners were designed by Chris Thompson at the Montreal Neurological Institute, and AECL took his prototype and redesigned it for commercial purposes. So I did a lot of “suitcase physics”, running between AECL in Ottawa, the Chalk River nuclear facility and the MNI, where I worked with Chris Thompson, the developer of the bismuth germanate crystal based PET scanner that replaced sodium iodide PET scanners. Bill Feindel was director of the MNI, so when the program folded in 1984 because AECL realized PET scanners were not commercially viable at that time, Feindel asked me to come to the newly established McConnell Brain Imaging Centre (BIC) at the MNI, which was the world’s first dedicated brain imaging research environment.
NS: Which you eventually got to lead as its director…
AE: Yes, when I took over as director in the 90s I became interested in brain mapping, first with PET activation studies, atlases, and subsequently throughout the 90s more and more with fMRI. I was lucky that I was able to find Keith Worsley, who was a dear friend and partner in crime for many years. The one thing I remember vividly about those days was the bunker, a little room deep in the bowels of the BIC. There were many weekly meetings with Keith, Sean Marrett and Peter Neelin, very smart people who were permanent staff and comprised what I like to call the hidden layers at the BIC. This pattern of hiring a cadre of permanent highly-qualified scientific staff in addition to transient PhD students and fellows was critical to the continued growth of the lab.
NS: Can you tell us a little about your lab today?
AE: Currently I have about 65 people in the lab. About half of them are the scientists who are asking the biological questions, and the other half are the geeks who build the computing and neuroinformatics infrastructure. The challenge is to make sure these people stay together and have a common mission. The lab operates at three levels. First is the IT infrastructure and things like CBRAIN and LORIS. Second is developing algorithms and analytical methods to explore connectivity, and the third is applications of those methods to specific patient cohorts. The two major domains are developmental disorders, autism in particular, and neurodegeneration, particularly Alzheimer’s disease. One of the high points of our recent activity has been the work of post-doc Yasser Iturria-Medina, who has been developing causal models of amyloid propagation in Alzheimer’s using a number of different imaging metrics. Now we are working on generalizing this machinery so as to apply it in development, using the same underlying modelling principles but applied to different imaging metrics. I believe It is important to preserve the general approach as far as possible before it is customized for different applications, but you need a methodological and IT critical mass to support this approach.
NS: What do you think are the most burning questions in neuroimaging today?
AE: Over the years my research has become more involved with connectivity, both structural and functional. Historically, imaging had spent over 20 years confirming what it was possible to do with more invasive methods by identifying focal areas of response to stimulus. There were people who were not convinced that imaging added anything new beyond, for instance, single unit recording. At the turn of the millennium, however, it became evident that imaging can do things other methods cannot, i.e. conduct a whole brain non-invasive survey of brain structure and function. So we could then start to explore the interaction between different parts of the brain, its underlying systems circuitry, over time. This opened up a whole new frontier to examine subtle aspects of brain connectivity in normal brain and in distributed disorders of neurodevelopment and aging.
Scientifically, I think that our field is getting very exciting, if overwhelming, with the consolidation of neuroimaging with other forms of brain data. We should be looking to integrate other forms of information, such as behavior and genetics into the multi-modal characterization of brain states. Some argue that we will lose focus if we do that, but I believe that the way we will understand the brain is by incorporating all this information, along with the computation and big data analytics machinery to combine all this information in predictive models. I think the next 10-20 years will be a golden era for the organization.
NS: Which brings us back to the OHBM and its role as a leader in the field of neuroimaging. What can we expect from the annual meeting in Vancouver?
AE: I feel that in Geneva we came of age, so we are more realistically functioning now as a society. We are broadening our pallet of activities, be it through international chapters or through special interest groups such as the hackathons. I feel like the geeks are the lifeblood of the society, so we can expect more organizational practices, white papers on best practices, as we have seen with the COBIDAS report.
NS: Is there one topic that you are proud to bring to the table as chair?
AE: Well, one of the questions that is going to come up in Vancouver is the question of diversity. I am both delighted and nervous about this, as we recently launched a diversity task force on my watch and this has revealed some schisms between people who want to prescribe solutions and those who want to see this process evolve organically. It is not my place to voice a personal opinion, but I look forward to the discussions at the upcoming town hall meeting.
NS: There are many aspects to diversity, gender and geography being two of the more obvious ones. How do you feel about the recent changes in US immigration policy that will prevent some scientists from attending the annual meeting?
AE: I am very much an internationalist, so I find it unacceptable that people would be prevented from attending meetings based on their nationalities. We as a scientific community have to be on record that we reject identity politics. My lab and OHBM on a bigger scale are excellent examples of how we are being enriched by the international exchange of ideas.
by NILS MUHLERT
At what point did you start preparing to read this article? When you arrived at the webpage, when you read the link, or even earlier? Increasingly, evidence demonstrates how we proactively anticipate events, affecting our perception and cognitive performance. Your mood’s influence on memory is obvious, just think about having to re-read whole paragraphs when you’re tired, distracted or sedated. But even when you’re alert, highly dynamic anticipatory biases operating over brief timescales can affect attention and memory, influencing performance on a trial-by-trial basis.
My interest in neuroscience crystallized during University, when I took a course on physiological psychology. The field of neuroscience was not well known or established then. It was magical to discover that I could turn all those questions in my head into a useful scientific career.
NM: Much of your work focuses on understanding selective attention. What triggered your interest in this field?
KN: I have a fundamental curiosity about the brain-mind interface. Narrowing down my interests was a struggle for me. Since the undergraduate years, I tried multi-unit recordings (eyeblink conditioning), recordings and imaging of hippocampal slices, event-related potentials, intracranial recordings, fMRI, TMS, MEG… I dabbled in conditioning, computation, language, visual categories… Finally my research settled in (or at least around) attention. I love working on attention because I see it as providing core infrastructural support for most if not all psychological functions. The prioritization and selection of information to guide adaptive performance (which is how I define attention) are essential in perception, as well as in working memory, long-term memory, language, etc. By studying attention I can work on cognition broadly, both keeping a coherent line of research and keeping alive my spectrum of interests.
NM: Your recent paper on flexible attention suggests that older adults may retain this capacity. Was this a surprise? And are there more resilient brain structures/ networks that support this preserved function?
KN: Recently, we have started exploring various aspects of attention in the aging brain. Contrary to proposals emphasizing deficits in flexible control in the aging brain, we have found that older adults show equivalent benefits of temporal expectation to young adults; are able to prioritize items flexibly in working memory; and show robust memory-based orienting, despite significant deficits in explicit retrieval for those same memories. These studies are highly encouraging. They provide a basis for developing interventions to counteract some of the deleterious effects of cognitive impairments. Our studies also provide a foundation for understanding how various attention-related functions are compromised in different neurodegenerative and neuropsychiatric conditions. This is an active area of research in the lab.
NM: What do you consider to be your greatest scientific achievements?
KN: Science is a living process of discovery and refinement of ideas. The two fields that frame my own research – psychology and neuroscience – are still young and far from mature. Most of our ‘theories’ still have a naïve Aristotelian feel to them. I can only hope that future generations will leave us way behind and achieve much higher levels of understanding. I hope all of my specific contributions will eventually be superseded, and that my discoveries can serve as stepping stones for others.
My aims as a scientist are to explore, experiment, learn, and help transform the process of discovery. I value the process over the outcome. The most rewarding moments come when a finding changes my perspective or opens an unexpected door.
Milestones with personal meaning along my career path include: discovering brain areas relevant for orthographic and semantic processing in ventral occipital and temporal cortex, far away from the language network (early 90s); observing the strong relationship between brain networks for spatial attention and oculomotor control (late 90s); revealing the ability to orient attention in time (late 90s) and in working memory (early 00s); and appreciating the forward functions of LTM (mid 00s).
Other great moments came from the excitement of seeing something for the first time or being able to measure something in a new way. Cherished memories include: spending whole days with a big team to image one slice of prefrontal cortex in an experimental fMRI machine when nothing was automated (e.g., the physicists would calculate shimming gradients on the back of an envelope), recording reversals of large semantic potentials in the ventral temporal cortex (early 90s), seeing activations of the frontal eye fields in the raw signal of perfusion-based fMRI (mid 90s), building contraptions to record EEG simultaneously with TMS (mid 00s), deriving population tuning curves of stimulus orientations using M/EEG to study representations in working memory (recently).
NM: Through the OHBM mentoring program we are pairing up novice and experienced researchers to share successful career strategies and avoid common pitfalls. What is the best piece of scientific advice you have received, and from whom?
KN: I feel so fortunate for the people who have inspired and supported me in my scientific path. It’s not the specific words of wisdom that stick out, but the genuine enthusiasm, the examples set, the opportunities created, and the trust shared. I’ve tried to improve along the way, learning from the distinctive qualities of my mentors. Greg McCarthy, my doctoral supervisor, and Marsel Mesulam, my mentor as an early-career fellow, are strong influences. I share, or took from them, a deep appreciation for scholarship, asking big questions, grounding any cognitive study in the available understanding of the relevant physiology and anatomy, thinking of neural processing in terms of circuits and networks, obsessing over experimental design, and following rigorous methodological procedures and controls.
A pivotal inspirational context was scanning at the functional imaging lab or FIL (then still at the Hammersmith Hospital) when I moved to Oxford (1994). (Oxford did not have its own imaging centre then.) I remember my first meeting with Richard Frackowiak who expressed perplexity at why I should come so highly recommended given my measly record of publication, but then welcoming me anyway. The early days of the FIL were electrifying. If I have one sadness about neuroimaging today, is that it may never feel that exciting again.
NM: Last, at OHBM we have been actively pursuing ways to increase the diversity of our leadership, committees and speakers. During your career from junior scientist to senior PI, have you personally encountered bias, or noticed changes in attitudes towards women in neuroscience/ neuroimaging?
KN: I never felt held back. Whether this is because I personally encountered no bias or because I took little notice of it is hard to tell. However, as I have progressed in my career, and witnessed the treatment of colleagues by others, I have come to appreciate that prejudices are real and have deep harmful consequences. Biases, of course, are not restricted to gender, but include many under-represented groups.
I have certainly embraced promoting a culture change toward equal opportunity, treatment, representation, and promotion of individuals across genders, race, and other groups. I feel things are changing for the better. Slowly, maybe, but surely. For me, it is immensely gratifying to meet the new generations of ever more diverse, talented, and confident scientists. I have enjoyed becoming more aware of and engaged with these important issues. The political tides at the moment remind us that it is necessary to work to promote and preserve the values of a just, open, and inclusive civilization.
BY AMANPREET BADHWAR & ESTRID JAKOBSEN (members of the Central Executive Committee of The Neuro Bureau and co-organizers of the 2017 OHBM Art Exhibition)
Science and art both seek to observe, record, and explain the world around us. While both have their own theoretical frameworks, evolving techniques, and different schools of thought, what is common for scientists and artists is the need to be creative and insightful to make meaningful contributions to their respective fields.
The arts and sciences can collaborate symbiotically. In doing so, they have the potential to create new knowledge, ideas and processes beneficial to both fields. Combining science and art allows scientists to showcase the creative thinking required by the scientific process outside the confines of the standard publishing formats, and allows artists to draw inspiration from sources outside their usual environments. In addition, neuroscience-based art grants a powerful means of public outreach for the scientific community, providing a stimulating common ground on which scientists and non-scientists can begin a conversation on complex themes. Conversely, exposing artists to the latest neuroscience research facilitates the translation of scientific concepts and novel technologies into artwork, which again is a powerful tool for raising the general public’s awareness of science.
In recent years, The Neuro Bureau has brought together neuroscience and art through the annual Brain Art Exhibition and Competition at OHBM. In addition to the upcoming show at the annual meeting in Vancouver, several local exhibitions showcasing submissions by artists and neuroscientists have taken place in Germany, France, and Canada. These local exhibitions extend the reach of the brain art initiatives beyond the OHBM community and raise awareness of neuroscientific research among the general public.
The most recent exhibition entitled “Reaching Beyond the Obvious” is currently being hosted in Montreal. The exhibition aims to foster a dialogue between neuroscience and the arts by bringing together works by artists and members of the neuroscientific community. By doing so, it aims to capture the beauty of the human brain through both literal and metaphorical representations.
The study of brain microstructure (structures invisible to the naked eye) through histological methods results in images that have been appreciated for their raw aesthetic beauty since the late 19th century drawings of Ramon y Cajal. Such images are incredibly complex at the level of single cells, and require creative solutions to understand in relation to the brain as a whole. Contrary to this, In contrast, modern neuroimaging techniques result in data that describe the brain at the macrostructural level (visible to the naked eye), but are difficult to interpret due to their high dimensionality, often encompassing information about both time and space. With recent advances in the quality and resolution of such techniques, understanding the complexity of the resulting data is one of the biggest challenges in neuroscientific research. The development of unique and creative techniques for mapping and visualizing such data has therefore become a vital aspect of neuroimaging science. By making use of abstract representations that reduce the dimensionality of the underlying data to highlight features of interest, such techniques often result in visualizations that carry their own unique aesthetic value and challenge the already blurry boundaries between science and art.
Images from Reaching Beyond the Obvious
Memory Traces | AmanPreet Badhwar
Alluding to the historical neuro-anatomical illustrations of Santiago Ramón y Cajal, this painting depicts an abstract representation of the physical encoding of memory or memory traces in neural tissue. Based on our current understanding, memories are not statically represented in specific areas of our brains, but rather must be actively put together from a variable number of memory traces pulled from multiple locations in the brain.
Edge-bundled DSI | Joachim Böttger
The image shows the result of the application of a method from the field of information visualization, force-directed edge-bundling, to two connectivity datasets. Both graphs (DSI-based on the left and resting-state based on the right) contain nearly 4000 single connections between 1015 regions of interest, which makes their visualization in anatomical 3D brain space a challenge. Edge-bundling groups together similar connections through the simulation of electrostatic attraction forces, and thus helps to make underlying structure visible.
Cerebral Infiltration | Maxime Chamberland, David Fortin, Maxime Descoteaux
Effects of a high-grade brain tumor on the white matter fibers of the brain. Fibers are colored (red to blue) according to their distance from the tumor, which provides an efficient way to visualize the impact of the tumor or tumor resection on the brain’s white matter.
Dance of the Connections | Sara Ambrosino, Emmanuela Ambrosino
The complexity and synchrony of neural connectivity represented as the harmonic movement of dancing bodies. Both brain networks and dancers show a beautiful interplay of elements, with unlimited possibilities of interaction and exchange, performance and communication.
Caught in a Whirlwind | AmanPreet Badhwar
An allegory for negative rumination, or the tendency to remember and dwell on painful past failures. Abnormally increased connectivity in the brain’s “default mode” network, an anti-pattern in this case, has been linked to such ruminations.
Flattened Connectome | Roberto Toro, Katja Heuer
Unfolded whole brain human tractography with highlighted arcuate fasciculus.
Parisian Mask | AmanPreet Badhwar
From mapping a city to mapping the brain - much like on a map (in this case the map of Paris), grid patterns generated by specialized brain cells are crucial for the cognitive representation of Euclidean space (i.e. space that can be represented using a coordinate system), and facilitate the encoding of spatial memory.
The Multi-Resolution Effect | AmanPreet Badhwar, Pierre Bellec
From neurons, to stars, to galaxies, understanding the universe requires a multi-resolution approach. Technical note: An average functional connectivity matrix was generated across all individuals of the Kennedy Krieger Institute site in the ADHD200 sample, and further binarized by application of a threshold. An automated layout was generated using the Gephi software. The size and color of each node was set proportional to its degree, and further edited for aesthetics.
Swirls of Synchrony | Pierre Bellec
Each point measures the synchrony (correlation) of spontaneous brain activity with that of the cingulate cortex. Rows are brain regions (space), columns are time windows. Rows have been ordered to expose the spatial structure of synchrony. Non-linear deformation of the space/time grid have been applied to expand outlier synchrony values, and visually emphasize their importance. This may turn out to be a useful trick to explore space-time dynamics, or not.
The Resolution Effect | AmanPreet Badhwar, Pierre Bellec
This image represents the binarized average functional connectivity matrices generated using functional brain parcellations of differing sizes (the smaller the parcels,the higher the resolution). The size of each node is a function of its degree of connectedness. It alludes to the fact that the dense web of connections visualized result from the use of high-resolution functional parcellations.
Untitled | Crean Quaner
Conceptualization of the human brain as a fundamentally pattern-forming, self-organizing system governed by non-linear dynamics. In this view, cognition is the embodied, situated formation of expansive spatio-temporal patterns of activity that connect with and extend out to their surroundings as a result of widespread brain-body-environment interactions.
Above the Clouds | Josefina Maranzano
This piece is part of a special series created to mark the Autism Awareness Month. Inspired by differences and similarities in the way our brains work, I tried to illustrate the importance of our minds from the moment we are born. The title is a quote from a poem by Thérèse de Lisieux, « Au-dessus des nuages, le ciel est toujours bleu » (Above the clouds, the sky is always blue)… the interpretation is yours.
Cerebral Graffiti | AmanPreet Badhwar
Graffiti in public spaces are mnemonic battlegrounds. Layer upon caked layer of combinations and contrasts, vulnerable to fading. The problem is trying to figure out what will stay, and what will be lost. It's puzzling, because not unlike memory itself, the mnemonic initiatives that tend to stick around aren't always the ones that felt most memorable at the time.
Lace Brain | Michel Thiebaut de Schotten, Benedicte Batrancourt
The piece was created using diffusion images, photoshop color filters and a final filter called percolator. Lace brain is the official cover image of the OHBM blog team.
Inside-Out | Simon Drouin
Curved slice extracted from an anatomical MRI and tattooed on the subject’s skin.
Astrocytes | AmanPreet Badhwar
Astrocytes are not usually associated with memory. This view is slowly changing. A recent study demonstrated that astrocytes control gamma oscillations, brain waves associated with recognition memory. This painting is inspired by the beauty of fluorescence immunohistochemistry.
This year The Neuro Bureau is launching its seventh annual Brain-Art Competition in order to recognize the beauty and creativity of artistic renderings emerging from the neuroimaging community. Researchers are invited to submit their favorite unpublished works by June 14th, 2017.
BY THOMAS YEO
Professor Kalanit Grill-Spector is the principal investigator of the Vision and Perception Neuroscience Lab at the Department of Psychology and the Stanford Neuroscience Institute at Stanford University. She will give a much anticipated keynote lecture at the upcoming 2017 OHBM Annual Meeting at Vancouver. We caught up with Professor Grill-Spector to discuss her illustrious research career.
Thomas Yeo (TY): Imagine that you meet some random person off the street. How would you describe your research to the person?
Kalanit Grill-Spector (KGS): The core of my research is figuring out how the brain enables us – as humans – to understand what we see. Therefore, my research examines how the function, anatomy, and computations of the parts of the brain that are involved in visual processing relate to visual perception. Additionally, I am interested in uncovering how these parts of the brain develop from childhood to adulthood and what aspects of this development are shaped by experience.
TY: How did you end up on this research path?
KGS: I first studied electrical engineering and computer science (CS). However, when I started working as an engineer, I did not like it. Then, I discovered the fascinating world of vision science by reading a Scientific American article by Semir Zeki in 1992. I thought, “I want to study this too!” Someone told me that there is a group in the Weizmann Institute of Science that works on Computational Vision. I asked to audit a seminar jointly run by professors in CS and Neurobiology. One of the meetings was devoted to a Nature paper by Fujita and colleagues from Tanaka and Cheng’s group: Columns for visual features of objects in monkey inferotemporal cortex. The CS and Neurobiology researchers were so passionate in their heated discussions that I got hooked. I wanted to be part of something that was obviously important. So, I applied to the graduate school at the Weizmann Institute of Science. I started my scientific career in computational modeling of orientation columns in V1 with Shimon Edelman and Rafi Malach. During this process, Rafi returned from a sabbatical at MGH (Boston), and said “there is this new thing called functional magnetic resonance imaging (fMRI)”. No one at Weizmann believed him that it was going to be a worthwhile research direction, but Rafi had a vision and was both energetic and stubborn. So, armed with energy and determination, Rafi and I set out to develop the first fMRI system in Israel. I think we would all agree that it turned out to be successful after all…
TY: What is the most exciting thing your lab is working on now?
KGS: C’mon, if I’m spending time working on projects, obviously, they are all exciting to me! But, if you had to twist my arm, Thomas, there are two things that perhaps I’m the most excited about. One is integrating many types of anatomical and functional in-vivo neuroimaging measurements within individual brains to understand the interplay between structure, function, and behavior, especially in the context of development. The second is developing the next generation of computational encoding models of the visual system with the goal of predicting cortical responses resulting from both bottom-up and top-down inputs.
TY: Moving forward, what do you hope your research will accomplish in the next 10 years?
KGS: I am hopeful that we will make big strides in three domains: (1) Understanding the structural and functional development of the ventral visual stream and in particular which aspects of development are shaped by experience. (2) Elucidating the anatomy of the visual system. We are far behind in understanding the anatomical constraints underlying the function of the visual system. For example, we do not even have a wiring diagram of the white matter tracts in the visual system in the human brain. (3) Developing precise computational models of the visual system based on empirical functional and anatomical measurements in humans. The development of such models will hopefully help us understand how the brain perceives and recognizes the visual input.
TY: Can you give us a teaser or preview of your OHBM keynote lecture?
KGS: In the lecture, I will address a central neuroscience question: how do brain mechanisms develop from childhood to adulthood to enhance behavior? I will use the ventral visual stream as a model brain system to address this question, and present data addressing two main developmental hypotheses: pruning and growth. Since this is OHBM, I will underscore how recent advances in multiple non-invasive neuroimaging approaches give us – as a field – a powerful toolkit to study how the development of brain function and structure relates to behavioral development.
TY: What do you think is the most exciting development that is happening in your area or the broader field of neuroscience.
KGS: In my field, computational and anatomical advancements have made a big impact. One hot area is combining neuroimaging measurements of brain function with computational (encoding) models that not only predict brain responses, but also explain the underlying computations. The second is significant advancement in anatomical methods including quantitative MRI and diffusion weighted imaging as well as improved analysis tools to define tracts and determine cortical networks. While fMRI has significantly advanced our ability to map human brain function, we still know very little about the underlying anatomy.
TY: Who are the people that have inspired you throughout your career?
KGS: The people who have inspired me and continue to inspire me are those that push me in new directions. For example, Rafi Malach (my PhD adviser) taught me how to ask – and answer – big questions with enthusiasm and attention to detail. Brian Wandell (at Stanford) is an excellent mentor who continuously makes it clear that the gold standard for good research is one that can be articulated in precise quantitative and reproducible terms. My students, who have taken me on new paths. In particular, Kevin Weiner, who took me on a successful trip down neuroanatomy lane (I’d never have thought that I’d drive there) and Jesse Gomez, who has introduced new and neuroimaging methods to the lab.
TY: What is the biggest challenge that you have experienced in your research career?
KGS: One of the biggest challenges I have experienced as a young researcher was coping with adversarial reviews of papers and grants. For example, one of my most cited papers is my 1999 Neuron paper about fMRI-adaptation. However, the first round of reviews was tough to handle. Some parts of the review were insulting, for example, a reviewer wrote that our findings were mundane. Other parts were so nasty that we don’t even know what the reviewers wrote as the editor blocked them out with a black marker. As a young researcher, I can tell you that this review really shattered my confidence. Critically, however, this early experience made me learn fast that to become a scientist, you not only have to be determined, but you also need to develop thick skin. So, while this and other challenges have affected me, it didn’t deter me from staying on this great path of scientific discovery.
TY: What advice would you give to aspiring researchers?
KGS: Neuroimaging today is an increasingly computational field, so I have two main pieces of advice. First, you should really learn how to code. You need to be able to understand, own, and develop your research tools. Importantly, being able to code will also help you do reproducible research. Second, inspect your data, not just the summary statistics – from individual participants’ data, to individual brain anatomies, even individual voxels in each participant. Computational tools and automation do not prohibit close contact with your data. On the contrary. This type of approach has helped me understand the consistent and variable aspects of the data across participants and also flag artifacts that otherwise would have been missed.
We thank Professor Grill-Spector for her time in answering these questions. We look forward to attending her exciting keynote on “Brain Growth and the Development of Face Recognition” on Monday 9.30am at Ballroom AB.
BY SHRUTI GOPAL VIJ
Human nature dictates that each and every one of us seeks guidance on life choices and trajectories. A key to this is mentorship. As scientists navigating the ever hardening world of academia it is vital today to find a mentor. A mentor that can show you the short-cuts, encourage you, applaud your achievements and support you in tough times. While some of us are lucky to find such mentors in some form or other, there are a large number of students, postdocs and other early career researchers who are left in the lurch. On the other hand, neuroimaging has quite a few established researchers and PIs who have themselves taken a long winding path picking up tips along the way that will make them great mentors. The OHBM Student and Post-doc SIG of 2017 aspires to provide a platform for both mentors and mentees to come together and establish an independent and effective mentoring relationship. This initiative, spearheaded by AmanPreet Badhwar (chair) and Michele Veldsman (chair-elect) with enormous support from SIG officials, covers two aspects, 1) a Mentorship and Career Development Symposium at OHBM 2017, and 2) an online Mentorship program.
The Mentorship and Career Development Symposium slated for Wednesday, June 28th 2017 (12:00 - 14:30 pm), is aimed at imparting meaningful information on how to navigate initial career transitions. Since an overwhelming number of our social media followers requested information on non-academic or industry transitions, the symposium is set to answer many of the hard questions facing junior researchers. The program promises to cover a variety of topics such as transitioning to PI, science writing/journal editorial positions, how to deal with micro-aggressions in work environments, managing work-life balance, starting a business post PhD and much more. Following short-talks from individual speakers, the panel will answer questions from the audience on what it is like to be a PI, run their own lab and what they look for when hiring junior researchers for academic and non-academic positions. The collection of 7 speakers and 5 panelists includes a variety of academic and industry experts who are not only approachable and personable but are also well-equipped to provide us significant advice. If you have questions that you want featured in the panel discussion at the Mentorship and Career Development symposium, please feel free to send them to us in advance.
While much has been talked about on the importance of mentorship in today’s world as well as the requisite nature of pro-active attitude on behalf of the trainees to find appropriate mentors, the trainees of OHBM have been largely isolated. In further bridging this gap, the OHBM Student and Postdoc SIG has announced an online mentorship program that promises to bring together mentors and mentees from the world over throughout the year. The idea behind this is primarily to provide another platform for mentees to seek support outside of their current environment and increase their knowledge of the ever-expanding unknown of academic and/or non-academic careers. The online forum was recently announced and sign-up for this year was closed on 1st May 2017. Even at the nascent stage of this being the first year for such trainee-focused initiatives, we have an impressive enrollment of 331, of which 89 PIs have signed up to be mentors. About 143 trainees have signed up to be mentored and will be pleasantly surprised by who they end-up with as a mentor. An additional 88 brain mappers have signed up to be both mentors and mentees, principally post-docs who are vital rungs in the academic ladder and can provide invaluable advice to students whilst also seeking support for their own career development. The SIG will match these mentors and mentees and introduce them via email. The mentors are required to meet their mentees online once every quarter and in person at the annual meeting and establish a mutually beneficial relationship resulting in the betterment of science all-around.
I have also signed up to be a mentor and a mentee. My reasons are simple. My career trajectory to a post-doc has been unique, with its own up’s and downs, and the kind of jobs best suited for me are also unique, even though they may be hard to come by. If I can help other scientists and especially women scientists break more boundaries, I personally consider that a win! There are many ways of getting to the end-goal of our own careers. I believe the only way to learn is to participate and talk. So here is me participating and discussing and learning. I welcome you to come participate, discuss, learn, find new mentors and become great brain mappers. Let’s make science self-supporting and self-sustaining in today’s age of uncertainty!
Suggestions, questions and comments are most welcome at @OHBM_trainees, Facebook and email@example.com.
BY DAVID MEHLER
In a recent blog post we learned about the activities of the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), whose members work on establishing recommendations and tools to increase transparency and reproducibility in human neuroimaging. Together with other early career researchers I was fortunate to recently attend a workshop dedicated to Advanced Methods for Reproducible Science. There, a number of pioneers in reproducible science discussed the challenges of the field, and introduced ways to improve current practices. As part of this, Dr. Russell Poldrack discussed creating reproducible research pipelines for neuroimaging.
Russ Poldrack is a professor of Psychology at Stanford University where he also heads the Stanford Centre for Reproducible Neuroscience. He presented a new exciting framework for reproducible neuroimaging called Brain Imaging Data Structure standard application (BIDS app). Russ agreed to an interview, providing an ideal opportunity to find out more about his views on the reproducibility crisis in science and get his recommendations for the field.
Whenever you find a seemingly good result – one that fits your prediction – assume that it occurred due to an error in your code. - Russ Poldrack
1) David Mehler (DM): How would you describe the reproducibility crisis in psychology and neuroimaging to a (tax paying) member of the public?
Russ Poldrack (RP): I would explain it like this: Some of the research practices that scientists have used in the last few decades have turned out to generate results that are less reliable than we thought they were. As we have come to recognize this, many researchers are trying to change how we do things so that our results are more reliable. This is the self-correcting nature of science; we are human and we make mistakes, but the hallmark of science is that we are constantly questioning ourselves and trying to figure out how to fix the problems and do better. An important part of the problem is that researchers are not currently incentivized by the system to do reproducible research; there is much more pressure to publish large numbers of papers in high-profile journals, which focus more on splashy findings, than there is to make sure that those findings are reproducible.
2) DM: The definition of direct and conceptual replications can be debatable and it is not always clear how close a replication must be to the original study to count as a direct replication attempt. In neuroimaging, best practice for each element of the processing pipeline might change over time and these changes can affect the final result. In your view, what constitutes a successful direct replication in neuroimaging?
RP: It’s a challenging question. On the one hand, you would hope that the minor details don’t matter very much; if they do, then the result has limited generalizability and thus is probably not that important even if it’s true under those specific circumstances. On the other hand, we know from the work of Stephen Strother and his colleagues, and from the work of Josh Carp that processing choices can make a substantial difference. In my opinion, what’s most important is that a replication attempts to be as close as possible to the original study in its details, recognizing that this will never be fully possible. If a well-powered replication attempt of an important study fails, then it’s the responsibility of the field to determine whether the replication attempt reflects true lack of effect, differences in methodological details, or random fluctuations. It’s worth remembering that some number of well-powered replication attempts will always fail due to chance even when there is a true effect, and thus a single replication failure should not necessarily cause us to abandon the initial finding.
3) DM: Do current open science/data practices favor senior researchers, who already have tenure and high impact publications, over junior researchers, who often must put in the extra work? If so what can be done about it?
RP: Yes, definitely. Doing reproducible science will almost certainly make it harder to succeed by today’s criteria of large numbers of publications in high-profile journals. Just as one example, I have become convinced that pre-registration of study design and analysis plans is critical to improving our science. However, doing a pre-registered study makes it more likely that one will come up with null effects, because there is no flexibility to tweak the analysis until a significant effect is found. I think there are a few ways to address the problem. First, established researchers need to lead by example; if we can’t engage in open and transparent research practices then there is no way that we can expect the younger generation to do so. Second, we need to pay more attention to open and transparent practices when we are judging job applicants, tenure cases, and grant proposals. This is much harder than simply counting up numbers of publications and impact factors, but it’s the only way that we can ensure that people doing solid research have a chance of making it on the job market, since they will always be outgunned by those who use shoddier practices to get papers in high-profile journals. One way to help with this was suggested by Lucina Uddin in a recent Tweet, where she described adding a section titled "Contributions to Open Science" to her CV; I could see this listing things like shared datasets, code, and pre-registrations. This would help signal that one is committed to open and reproducible science.
4) DM: This brings us back to the role of incentive structures. Together with other OHBM committee members you have recently initiated an OHBM Replication Award for the best neuroimaging replication study. What is your vision for a system that creates the “right” rewarding and incentive structures to promote data sharing and open science work?
RP: Foremost, people need to get credit for their efforts. The rise of “data papers” has helped with this, since now a person can get citation credit for a shared dataset when it’s used by others. Registered Reports are another good move in this direction, as they ensure that one will get a publication for a well-designed study regardless of the outcome. As I mentioned earlier, we also need to work to make these practices more central to our hiring and tenure decisions; changing these kinds of processes is challenging, and requires more senior researchers to take the lead, which many of us are trying to do but it’s an ongoing effort.
5) DM: Thanks Russ. Finally, what is your main message for early career neuroscientists? What would you advise them to look for when choosing a lab and planning their career path?
RP: First, focus on finding a scientific question that fascinates you. Science is full of long hours, intense criticism, and repeated disappointments, and only a burning scientific question will give you the continued motivation to persevere. Second, find a lab that shares your values. Talk to people in the lab and find out whether they have adopted the kinds of practices that would make you feel confident that your interest in openness and transparency will be supported and nurtured. Third, be open to change. It’s natural to make plans for the future, but often the world has different ideas for us, and it’s important to be able to take advantage of the best of whatever your situation has to offer you, even if it’s not what you initially planned for. Finally, realize that we are humans and we make mistakes, so that nothing you do will ever be perfect. One unfortunate consequence of the reproducibility crisis is that it seems to have led many trainees to worry that their work is never quite good enough, and that someone in the future will find a flaw or fail to replicate their work. This is a problem because if you don’t get the work written up, you will never get credit for having done it, regardless of how clever the experiment was.Science is a process for attaining knowledge, not an endpoint, and we need to keep that in mind. We should do the best we can to make our work transparent and reproducible, but also realize that at some point you just have to put the work out there for the world to see.
Figure 2: Attendees and speakers of the Advanced Methods for Reproducible Science workshop at Cumberland Lodge, Windsor. The workshop was organized by Dr. Dorothy Bishop (top row, 5th from the left), Dr. Chris Chambers (top row, 4th from the left) and Dr. Marcus Munafo, and funded by the Biotechnology and Biological Sciences Research Council (BBSRC) and the European College of Neuropsychopharmacology (ECNP).
Dynamic Functional Connectivity – A Brief Overview and Latest Thoughts from the Rotman Research Conference on Neural Dynamics
BY JEAN CHEN
For those who have not yet come across functional connectivity in their research, it won’t be long before you do. In the human brain mapping community, functional connectivity is often defined as the correlation between brain regions that share functional properties (activation patterns or fluctuations). Functional connectivity can be measured in an active or “resting” (task-less) brain state, using electrophysiological, optical and MRI methods. In recent years, the brain’s functional connectivity has begun to capture the public’s imagination in a tangible way. In 2009, the National Institutes of Health launched the Human Connectome Project to map all connections in the brain, including functional connections. This was followed by the European launch of the ambitious Human Brain Project in 2013. Today, beyond helping us to understand how the brain works, functional connectivity measurements are widely used in studying brain aging and brain diseases. Some examples include ADNI (USA), BIOCARD (USA), ONDRI (Canada), CCNA (Canada), SMART (Europe), Rotterdam Study (Europe) and the Sydney Memory and Aging Study (Australia).
With the extensive use of functional connectivity in various domains, many of us have come to expect functional connectivity, like the fibre structures physically connecting different brain areas, to be more or less stable. Most studies revolve around “static” functional connectivity, averaged into a single quantity over the course of many minutes. The dominant belief is that we would like this “static connectivity” to be reproducible across multiple time points. However, more recent work has shown that getting “stable” functional connectivity measurements within individuals has been rather difficult, especially in resting-state measurements. This, for me, was when two bodies of knowledge collided. On the one hand, image-analysis research has largely been focused on making functional connectivity within an individual more “static”, i.e. more stable across time. On the other hand, many years of electrophysiological research have shown that a healthy brain is a variable brain. It would be natural to reconcile these two streams of knowledge into a coherent and more complete view of functional connectivity. Through dynamic functional connectivity, we can observe moment-to-moment (seconds apart) changes in connectivity. Yet, it had seemed to me, that by allowing functional connectivity to vary with time, we would lose a degree of tractability in this “wanna-be” biomarker. “How should it be calculated?” “How should it be interpreted?” “Should it replace conventional static functional connectivity?”
The added challenges have not stopped researchers from increasingly embracing this new trend. At the recent Rotman Research Conference on Neural Dynamics, I caught up with some world authorities on dynamic functional connectivity, trying to get a sense of how dynamic connectivity should be measured and what the future holds for it.
Who’s mapping dynamic functional connectivity and why?
The Rotman Research Conference is an annual research conference series hosted by the Rotman Research Institute of Baycrest (University of Toronto). Since its inception in 1990, the Rotman Conference has varied its theme from year to year, but always revolving around important current concepts in cognitive neuroscience and brain aging. The objective for the 2017 conference was to showcase cutting-edge research in neuroimaging of brain dynamics and its clinical translation. Amongst the notable speakers at this year’s conference, Drs. Vince Calhoun, Viktor Jirsa, Randy McIntosh and Cheryl Grady presented their work on dynamic connectivity.
“Is dynamic connectivity a natural next step in functional connectivity research?”
Vince: Yes, it seems like it. We were always looking at functional connectivity associated with tasks, and even during a task block, connectivity within a brain network fluctuates. The brain is constantly variable, even at rest. By averaging connectivity across a 10-minute fMRI scan, a lot of information will be averaged out. We and others first published on this topic in 2010 and since then the field has really exploded. Functional connectivity should be measured within a dynamic context, but there may well be a mixture of both dynamic and static aspects in the data that are useful.
Randy: By construction, the brain needs to be dynamic, or else it wouldn’t work very well. It is how the system is set up.
Viktor: Dynamic connectivity can be more useful than static connectivity, since brain function is dynamic in nature, no matter what. Measures should not be repeatable. The brain is a nonlinear complex system, and multi-stability of the brain is a necessary feature. This is something we try to capture. Non-stationarity in brain activity is not a bad thing; it can give us much more useful information. There have been studies in which dynamic connectivity provides better prediction.
“How can dynamic connectivity be measured and used?”
Cheryl: In our research, we have been calculating functional connectivity dynamics, that is, connectivity over moving time windows. We then take the variability of connectivity across the windows. We find older adults demonstrating lower variability, and this is a very robust finding. There might always be issues with the sliding-window approach, but I’m not sure what the best approach would be at this moment.
Randy: In the 1970’s, there was much enthusiasm for using quantitative EEG signal as a biomarker, but the signal and its mechanisms were hard to understand. The same is true for functional connectivity. Functional connectivity is a consequence of a cascade of bottom-up and top-down processes, involving molecules and genes. What’s more, functional connectivity in clinical and healthy groups may be similar on the surface but be based on different mechanisms. Dynamic connectivity provides a way to generate more features to characterize the uniqueness of each individual brain.
“What does the future hold for dynamic connectivity?”
Vince: Functional connectivity is progressing towards being an imaging biomarker, but is not quite there yet. I think static and dynamic connectivity remain both useful. Certain connectivity components may vary a lot and others may not vary much. In addition, integrating this information within the larger structural/functional context is important. I am a big proponent of integrating multiple modalities, and in our work, we have been jointly modeling static and dynamic connectivity, letting the data tell us what is useful.
Randy: Until we can get a good understanding of the mechanisms behind functional connectivity, we will not be ready to use it as a biomarker. A biomarker ideally needs to be individualized, and it is not enough for functional connectivity to only show sensitivity when measured in a large group of individuals. For now, to find some way of concentrating the dynamic features of the individual brain would more likely lead to a biomarker.
Viktor: Static functional connectivity is not a bad measure. We just need to be careful how to use it and interpret it. We may need to recognize that non-reproducibility is part of the functional process, and modeling this variability may be a solution towards individualizing functional connectivity. The mathematical modeling is likely to benefit functional connectivity in terms of personalization.
Cheryl: I don’t think dynamic connectivity will replace static connectivity measures. We can still learn quite a bit from static connectivity. It can still distinguish young adults from older adults. What I hope from those that develop new data-analysis methods is an easy and reliable way to account for vascular effects in functional connectivity (and other fMRI) measures.
There you have it. It is likely that the only thing about the brain that’s constant is change. To help characterize it, dynamic functional connectivity may be a scalable brain measure that is accessible to neuroscientists and informatics researchers alike.
BY NIKOLA STIKOV
At the OHBM 2015 Annual Meeting in Honolulu, HI, the OHBM Communications Committee (or ComCom as we like to call it) was created by the OHBM Council. They appointed Randy Gollub as its first Chair and Niko Kriegeskorte as Chair-Elect. Over the fall and winter Randy and Niko worked with OHBM staff to recruit volunteers and create a structure for this new and exciting initiative.
The first step after assembling a group of eager and extremely talented Committee members was to divide the large group into four different specialized teams and a quarter of the members were assigned to the ‘Member Communication’ team. Our task was daunting. How do you communicate year-round with a membership that spans so many disciplines, continents and backgrounds? Do you create separate newsletters, Facebook pages and YouTube channels? Do you hold monthly meetings in which you assign specific tasks targeting specific audiences? Or do you put all this under one umbrella, call it a blog, and let the OHBM members decide what to do with it?
If you are reading this, then the answer is obvious. We began with a blog because it was the most inclusive (and easiest!) platform we could think of, and then allowed everything else to evolve organically. The “Member Communication” Team became the “Blog Team” and over the past year we have published 51 blog posts, featuring over 40 contributors from 11 countries. The blog has received over 165,000 page visits from 63,000 unique visitors, we’ve created 12 videos for our YouTube channel and OHBM had over 345,000 impressions on Twitter. The OHBM Communication Committee’s work has also been featured in the Huffington Post and cited by the New York Times. Not bad for a one-year old...
None of this would have been possible without the vision and guidance of Randy and Niko, the support and resourcefulness of the ComCom team captains Jeanette Mumford and Lisa Nickerson (Website Team Captains 2016/2017), Cyril Pernet (Social Media Team Captain) and Kevin Weiner (Media Team Captain), and the organization and professionalism of our Communications Manager, Stephanie McGuire. Finally, there is our core blog team that spans five time zones that are 15 hours apart, yet somehow manages to stay awake during grueling monthly discussions about guest posts, calendars, spreadsheets, SOPs and Trello cards, only to go back to their computers to do more pro bono work than they ever volunteered for. The fact that they keep coming back, month after month, means that we have found a way to have more fun than this post makes it seem. Don’t believe us? We have a suggestion for you-- become a contributor!
As we are transitioning from baby to toddler, we are looking for friends and role models to look up to. And while one-year olds are known to stumble now and then, they are also endlessly curious and growing at a rapid rate. We hope to continue to grow, evolve, and become more steady on our feet as we figure things out-- and most of all to be receptive and responsive to our community in the years to come!
BY GUEST AUTHOR ERIKA RAVEN
This post originally appeared on the ISMRM blog and in the MRM Highlights magazine.
Republished (and slightly modified) with permission.
Karla Miller is a professor of biomedical engineering at the Oxford Center for Functional MRI of the Brain (FMRIB, pronounced “fim-rib” for short). She directs the FMRIB Neuroscience Physics group, which specializes in many projects, from pulse sequence development to biophysical tissue modeling. More recently, she’s been a key figure of the UK Biobank, a mega-sized data initiative charged with imaging 100,000 adults by 2022. Karla is also a plenary speaker at the upcoming OHBM meeting in Vancouver, education chair of this year’s ISMRM meeting in Honolulu, and is poised to chair the entire ISMRM program for the 2018 meeting in Paris. In our interview, Karla makes connections between the many themes in her life, which ultimately are resolved by finding the right balance.
Erika Raven (ER): You’re one of the few people that feel comfortable straddling the line between ISMRM and OHBM. Do you see a synergy between these two societies, or would you rather they keep running on parallel tracks?
Karla MIller (KM): I think it’s incredibly important that people who are developing MRI techniques don’t do so in a vacuum. I’ve benefited tremendously from being at the FMRIB center. Although I’m in a physics group, I rub elbows with people on the analysis and neuroscience side. I think it’s important for people who are developing these sequences to understand how neuroscientists will want to use them. Cross society outreach is something I am keen to do as part of becoming chair of the ISMRM’s annual meeting program committee (AMPC) in about 6 months.
ER: How did you first become involved with ISMRM and what led you to become this year’s education chair?
KM: I first attended the ISMRM in Philadelphia (1999) and I have attended every ISMRM since. One of the first official roles I held was to serve on the AMPC. The AMPC is the hardest working, but also the most exciting, committee to be a part of. Now for this year’s ISMRM, I am coordinating the education for Hawaii, and then at the Paris meeting in 2018 I’ll be chairing the entire program. I’m incredibly grateful to Dan Sodickson for appointing me - although as the huge task ahead really hits me, I might save my thanks until the meeting is a wrap!
ER: You’ve given many educational seminars. What is it about MRI education that you like?
KM: I absolutely love teaching. Beyond it being immensely satisfying to help people grasp difficult concepts, I think it's a good experience for the lecturer to think hard about the material. It’s an interesting challenge - can I do a better job of teaching this to other people than it was taught to me?
ER: Your work is multifaceted - can you explain your primary research themes and how those came to be?
KM: My training was very much in pulse sequences and image reconstruction. And so I still have a big chunk of my group working in that area. In the past few years, I’ve become interested in the idea that we can improve our acquisitions and reconstruction by taking a lead from how people analyze their data. We tend to think of this as a linear process – you try to get the best data you can and then you analyze it. But there are tricks that we can learn based on how people analyze the data that would enable us to improve the acquisition and reconstruction itself.
ER: I would imagine he would be useful! You also study biophysical modeling and ex vivo imaging of tissue microstructure. Can you tell us about that?
KM: We’re acquiring microscopy data so we can close the loop between what is the biophysical model, what is the MRI data, and what is the actual measurable microstructure. The key aspect of our experiments are that we have all three things –MRI and microscopy in the same tissue samples, and a proposed model linking them. By actually having a measurement of the underlying microstructure, it guarantees thatis if you’ve got your model wrong, you are the absolute first person who is going to know. Not just, “can I take a biophysical model and show that it kind of matches the data”, but “can I actually take something that I know reflects the underlying microstructure, make a prediction through some biophysical model, then say - YES - that is exactly the MRI signal that I measured”. And it’s a really hard thing to do.
ER: That was like a mission statement!
KM: Putting this process to work, we’ve been looking at diffusion based estimates of fiber dispersion. We use microscopy techniques to essentially ask what aspects of the microstructure you need to incorporate to accurately predict what the diffusion signal looks like. It’s a project that has a true palpable output, and interestingly it’s created a signature that we hadn’t expected to find. We’ve now demonstrated that this particular effect also exists in the Biobank data - so it’s a real effect, which is potentially a signature of something biologically interesting. More importantly, we’ve managed to have a first go at what it might look like to actually close the loop of biophysical modeling, microscopy, and MRI acquisition.
ER: I really like that turn of phrase, closing the loop. And since you mentioned the UK Biobank, I’ve given myself permission to bombard you with Biobank questions! To start, when did you first become involved?
KM: What I’m actually doing right now as you’re asking me this question is looking in my emails to see when I had my first Biobank email logged. 2008! Email from Paul Mathews, basically asking if we would be interested in getting involved in the Biobank. It’s quite a project – scanning 100,000 subjects. And although there is quite a long author list on the paper that we published this year, that doesn’t even begin to cover the number of academics involved, let alone the enormous staff that is entirely dedicated to the project. As one colleague said – its behemoth. In a good way.
ER: What do you think will change from having 10,000 scans to 100,000 scans?
KM: One of the most exciting aspects of Biobank is that it’s an entirely prospective study: it has no particular disease focus, but is playing the numbers. Most of the participants in this huge cohort have yet to show symptoms of major disease, but we’ll be able to follow their health records as that changes. So, for example, we expect 2000 new diagnoses of Alzheimer’s and 50 new diagnoses of ALS over the next five years from participants who were pre-symptomatic at the time of imaging. The value in Alzheimer’s is obvious, but for rare diseases like ALS, that is a needle in a haystack. You just can’t find those subjects otherwise. It certainly might provide you with markers for tracking response to therapy or disease progression.
ER: It sounds like the translational aspect of this research might become even more important now, such as borrowing techniques from other fields that have already been established and validated for big data sets.
KM: It’s partly techniques and it’s partly culture. The same thing with open science – I know it’s the right thing to do, but there is part of me that thinks, “Ahh!, it’s going to be yet another thing I have to adhere to”. But once we have a culture of doing it, everybody looks back and says, “What were we thinking?”
ER: A more general question, what brought you to the academic life? Did you have any major influences that led you down this path?
KM: I got very interested in the brain when I was a kid. My mother had to have pretty drastic brain surgery when I was about 12 or 13. It really struck me - the idea that it might fundamentally change who she was. When I went to university, I started out as a psychology major. I was taking a cognitive psychology class in maybe 1995 when I saw functional MRI in a textbook - totally state-of-the-art . I was so impressed with what it had to offer compared to current methods for studying cognition. I also thought maybe the way I could have an impact was to develop the technology and move towards the engineering side. And so it’s kind of nice for me now that I’ve done the engineering side in anger for about 10 years, and I’m able to shift towards getting back to neuroscience. And for me that’s incredibly rewarding.
ER: It’s like you’re closing your own personal loop.
KM: There’s a theme there, isn’t there?
ER: Now for some words of wisdom. What things did you learn along the way that you feel would be important for people who are just starting out?
KM: I have to be profound on short notice! Well… Going into science with a great deal of passion, and a great love of what you’re doing is absolutely critical. Particularly if you want to stay in academia, because let’s face it - academia is a tough world to get by in. One of the things I did sort of instinctively early on was to look towards people who were a year or two ahead of me, doing the kind of science I wanted to do. If I have to name names – Brian Hargreaves and Bill Overall. They were my role models. I tried to see what it was that they were doing at my stage to get where they were. That sounds simplistic, but honestly, that was what I did. And it’s good advice.
ER: It has come up repeatedly that you frequently go outside your comfort zone. That’s sometimes a scary thing to do – what drives you to change?
KM: You know how I would sum this up… For me - and I know this is not true for everyone - being an expert is boring. To some degree, the fact that I’m the one “blah blah’ing” in this interview the whole time, from my perspective, it’s flattering but not stimulating. It would be far more fascinating for me to be asking you about what you’re doing and learning about what you’re doing. Being an expert is, for me, it’s the way you earn the opportunity to be an inexpert - that is the fun bit. That said, I wouldn’t encourage people to just jump from one thing to the next willy nilly, because you’ll never become an expert in anything, and that’s also not good. You have nothing then to leverage. So you have some safe stuff, and some risky stuff, and you’re hopefully pushing your personal envelope the whole time. It’s kind of about finding the right balance.
SHRUTI GOPAL VIJ
COBIDAS: OHBM Committee on Best Practice in Data Analysis and Sharing
Neuroimaging researchers study both the structural and functional organization of the brain in health as well as a variety of neuropsychological conditions. Extensive exploration has been conducted over the past few decades using novel experimental and analysis techniques. However, recent evaluations of these techniques have highlighted concerns that published scientific results are less reliable or reproducible primarily due to the lack of transparency in research practices. To address the need for outlining principles of scientific research that will increase transparency and reproducibility in human neuroimaging, the Organization for Human Brain Mapping created the Committee on Best Practices in Data Analysis and Sharing (COBIDAS).
COBIDAS has initiated efforts in distilling best practices for open science in human neuroimaging and has compiled suggestions for specific research practices to support open data and open methodology. These suggestions were composed in a report that was drafted and ratified using community collaboration. While the report itself provides a detailed description of best practices as well as approaches to avoid, a commentary that reviewed the impact of COBIDAS and the challenges ahead was published in February 2017.
The commentary underlines the importance of reproducibility and highlights the different aspects of replicating a study including generalizability over methods, materials and results as shown in Figure 1. One practice that was universally recommended is the transparent and complete reporting of all facets of a study, allowing the critical reader to evaluate the work and fully understand its strengths and limitations. Additionally, thorough reporting will equip the reader/other researchers with a detailed knowledge of how to fully replicate the study.
COBIDAS MRI report presents reporting checklists in Appendix D that researchers can follow while preparing manuscripts. These checklists are highly comprehensive and run the gamut of stages a human neuroimaging study passes through. The report also pinpoints specific bad practices, especially in statistical modeling and inference (Pages 11 & 12), and provides concrete recommendations for avoiding them. COBIDAS also suggest that researchers at all levels be mindful of these considerations while conducting individual studies and compiling manuscripts.
Another strong recommendation from COBIDAS is data sharing as highlighted in section 7 (Pages 19-24). While sharing of results was strongly agreed upon by the imaging community and COBIDAS, some concerns were articulated by the community. The main concerns of the neuroimaging community outside of COBIDAS included data ownership, maintaining autonomy over results, concern of uncovering errors in analysis, cost of data sharing, and protection of subject privacy. COBIDAS posits that there are ways to overcome each of these concerns by not only being personally open to the fallible nature of individual research and welcoming collaborations initiated by data sharing, but also by emphasizing the role of the organization and the lab in making these practices widespread. COBIDAS also suggests that a culture of constructive criticism needs to be imbued in the community to allow researchers to work on reproducibility studies. They credit some studies such as Waskom et al, Whitaker et al and Pernet et al as well as the Montreal Neurological Institute that have become the flag bearers of open science by sharing their research data and analysis scripts.
Such recommendations and practices are leading to the development of new data sharing methods and open science tools for neuroimaging. Some of the identified tools for data sharing at various experimental stages include the Brain Imaging Data Structure (BIDS); the CBRAIN web-based analysis service; the COINS service; the LONI pipeline; the Neurovault repository; and the FCP/INDI and ADNI data sharing repositories. The COBIDAS recommends using the many resources available to share data, analysis scripts, and well-written code, along with unthresholded result maps to allow precise meta-analysis and follow up studies.
Finally, the COBIDAS acknowledges that while many of the practices suggested and recommended require individuals to change the way they approach implementation and reporting of a research study, advancement of these open science initiatives will only bear fruit by institutional support and direction. They posit that universities and research centers, as well as the journals themselves, should require data and code sharing. Foundations and grant agencies should also recognize and fund the explicit costs of data sharing. However, none of these will be able to single-handedly bring about the radical change that open science warrants. COBIDAS seeks a coordinated effort from individual researchers, research centers,universities,grant agencies, and it also invites professional organizations to accelerate the drive towards open science via extensive education and outreach.
What does this mean for you and me as human brain mappers? We need to be more transparent in what we do. Not just because of the implications this has on clinical applications, but to make human brain mapping a more reliable field. Small changes in our approach to science such as documenting all the analytical methods applied while working through the projects and sharing this document on our personal sites or as supplementary material to manuscripts is a small initiative we can all take. Another simple task would be to share code written for projects on code sharing platforms such as github. At the level of the PI’s, making it a lab requirement to share this information with all the lab members including de-identified participant information and maintaining documentation for all projects: ongoing and completed would be speed up the process. This also makes it easy to follow up on projects once postdocs and graduate students have moved on.
As they say- “Little drops of water make the mighty ocean”, if we all commit to do our part, we can make open science a reality and very soon.
BY NILS MUHLERT
Every year OHBM receives thousands of abstracts, each a snapshot of the intensive work of individuals or teams of scientists. Contained within this bumper crop of science are telling replication studies, novel experimental designs, methodological advances and fresh insight into the workings of the human brain. This harvest, whilst welcome, necessitates difficult decisions about which prize specimens to highlight as talks, and which to promote through posters.
For those of us yet to work on program committees this process of selection can seem opaque - we can perhaps predict the established trends and exciting developments from year to year, but how do committees decide which emerging fields will pique the interests of the majority of OHBM attendees? Here we find out the decisions that were made in deciding on the OHBM 2017 program, through discussion with the Program Chair and Stanford Neurologist, Mike Greicius.
Nils Muhlert (NM): First, can you tell us about your career path into Neurology and Neuroimaging?
Mike Greicius (MG): I was a French major as an undergraduate but was able to get my pre-med classes done at the same time. I went to Columbia for medical school but was allowed to defer my matriculation for 1 year so that I could "teach English" in Prague and Paris, which, in fact, I sort of did.
Taking a year off allowed me to hit medical school refreshed. It was as a second-year medical student at Columbia that I had my epiphany about neuroscience. I was in a lecture on aphasia and the professor, Richard Mayeux (now the chair of Neurology at Columbia), had a videotape showing a conversation with one of his Wernicke's aphasia patients. I was thunderstruck and knew, from that point, that I wanted to be a behavioral neurologist. In my head I summed it up as something like "why study the kidney or the liver when you can study the one organ that talks back to you?".
I did my one-year of internal medicine at Columbia and then residency training in Neurology at Harvard, which is a fondly remembered blur. Fondly, mainly because it is blurry. At the time I was rather zombie-like, overworked, underpaid, etc. Those were three tough but formative years. In 2000, on finishing my residency I came to Stanford for an fMRI fellowship (with Allan Reiss and Vinod Menon) which I combined with a behavioral neurology fellowship (done at UCSF with Bruce Miller). The sun came out and everything changed. I was delighted to learn that my wife still loved me and that I could now spend time awake with my then 2-year old son.
My big resting-state epiphany actually happened at my very first conference, which happened to be OHBM 2001 in Brighton. That was my first taste of resting-state fMRI. The Biswal paper had been published in 1995 but I had had no exposure to imaging research in residency. I recall sitting in my hotel's pub sponging insights from Dietmar Cordes, whose group at Madison was doing a lot of the early fundamental methods work in resting-state fMRI. I was really blown away by the power of this approach and collared Vinod so that we could visit some of the posters together. When we got back to Stanford that summer we started thinking about how to adapt this approach to cognitive and clinical neuroscience questions.
NM: And more recently you started combining resting state fMRI with direct stimulation of the anterior cingulate cortex. Can you tell us a bit about how this work came about and the effects that this stimulation produced?
MG: The study stimulating the anterior cingulate cortex was one of my all-time favorites. Josef Parvizi is a friend and colleague of mine here at Stanford and he essentially created and now runs our research electrocorticography program. As a quick background, some patients with intractable epilepsy that does not respond to 2 or 3 anti-seizure medications may be candidates for surgical resection of small brain lesions that are the cause of their epilepsy. Often, such resections are essentially curative.
As part of the assessment, patients come into the hospital for surgery to have electrodes placed on the surface of the brain and/or in deeper parts of the brain (like the hippocampus) using depth electrodes. Patients typically spend many days in the hospital as their seizure events are carefully recorded in the hopes of localizing a single focus from which all seizures begin.
At Stanford, and many other centers, part of the clinical protocol is to stimulate each electrode in turn to see if stimulation triggers any aura-like symptoms in the patient or causes any suspicious activity on the recordings. For Dr. Parvizi’s cases, we started obtaining pre-operative resting-state fMRI scans so we could determine which electrodes were in which brain networks. Electrode placement is done strictly based on the clinical history and prior data (like EEGs and MRI scans) in an effort to cover suspicious candidate regions.
In these two cases we happened to have electrodes in the dorsal anterior cingulate cortex in the heart of the "salience" network. I'd done some prior work on this network (led by Bill Seeley, the salience network guru [read the OHBM interview with Bill here - NM]) and had settled on the idea that the salience network is involved by any stimulus (internal or external) that alters the sympathetic nervous system. So high-demand cognitive tasks, emotional tasks, painful stimuli will all activate this network (which is why previous micro-literatures have tended to call it their own: the pain network, the cognitive control network, etc.). This was the first time we'd been able to get first-person reports from subjects whose salience network was stimulated. Both subjects describe a feeling of approaching a challenging situation and, in so many words, having to marshal the resources to prevail. I think this is what the salience network does. It both recognizes the challenge and also allocates resources (increased cognitive focus, increased heart-rate and blood pressure, dilated pupils to maximize visual input, etc) to overcome the challenge.
I love the line in the video of patient 1 where he is describing this strange set of feelings and notes that his heart feels like it's beating faster and he asks Dr. Parvizi if we are recording his heart rate. We were and it did increase some. I just loved how invested he was in the whole procedure. I felt like we should have made him a co-author. In any case, it really points to the invaluable role of human subjects in neuroscience research.
NM: Turning to your work in Alzheimer’s disease - you recently used PET imaging to demonstrate that amyloid deposition in early Alzheimer’s rarely occurs in the same regions as hypometabolism. Was this lack of co-occurrence predicted by prior theories of Alzheimer’s - if not, what implications might it have?
MG: The Alzheimer's field is slavishly devoted to amyloid plaques. Our paper in Brain showing the general lack of correlation between regions with high amyloid plaque deposition and those with low glucose metabolism was an effort to free people of their reflexive tendency to associate amyloid plaques with local neural dysfunction. Good old-fashioned clinicopathologic studies have repeatedly made the case that the location of amyloid plaques at autopsy does not correlate well with brain regions that were affected in life (based on functional anatomy). These same studies have made a strong case that tau pathology (neurofibrillary tangles) is the better regional correlate of neuronal dysfunction. Humans are visual beings, however, and the amyloid PET imaging revolution eclipsed some of these old studies.
To be clear, amyloid PET imaging is an unbelievable research and clinical tool and constitutes one of the major advances in Alzheimer's disease research in the last 30 years. In addition, there is no getting around the critical, probably primary, role of amyloid in Alzheimer's pathogenesis. However, the specific species of amyloid (plaques versus smaller oligomeric aggregates of the peptide) that drives the pathology remains in question. Our study (like the numerous clinicopathologic studies that preceded it) makes the case that the relevant neurotoxic species of amyloid is probably not the plaques.
NM: Which figures in your career have inspired you?
MG: Human figures? Manuscript figures? Probably not financial figures.
Human figures include Richard Mayeux and Bruce Miller (as mentioned above). Allan Reiss was a great mentor and in particular helped me learn how, as a PI, to let a trainee run with something that they are passionate about even if it is a good ways off the topic they have been assigned. Vinod Menon was also a great mentor and really helped me dive into resting-state fMRI. I also get inspired by peers. Bill Seeley as mentioned, Mike Fox, Catie Chang, Steve Smith, Heidi Johansen-Berg, Vesa Kiviniemi, and Christian Beckmann among many others have all helped my thoughts on brain connectivity and plasticity evolve.
Then, and this is not false modesty, I have benefitted considerably from several trainees. Andre Altmann and Jonas Richiardi really helped me shift gears from an imaging lab to an imaging genetics lab and lately, at times, to a straight genetics lab (with additional trickle-up education coming from Valerio Napolioni, a genetics postdoc in my lab currently).
Manuscript figures: Figure 2 (below) is my favorite, mainly because it features my wife's cingulum and descending cingulum bundles which I find incredibly beautiful.
NM: What led to you getting involved in the OHBM Council?
MG: I've been to OHBM every year since 2001. I love the community, I love the science, and I love the cities we get to visit. The other conferences I go to (and which I will not name) tend to be a bit stuffier; people wear ties and occasionally (and unironically) bow-ties. At some point I was encouraged to put my name on the slate as a candidate for Council. I was roundly pummeled in my first attempt but with some salience-stimulation and pride-swallowing was encouraged to run a second time where my perseverance was rewarded with another sound beating. In my third round I was narrowly elected to this august assembly.
NM: What challenges are there in putting together the program for OHBM?
MG: Serving on the Program Committee is a serious undertaking. We end up doing a lot of work in a short period of time. We have a few weeks to review all abstract evaluations (about 2500), educational course proposals (20 or so), and symposia proposals (more than 40). The main program building takes place each February over 2 days in a fun but somewhat chaotic in-person meeting where people make the case for (or against) the selection of education courses, symposia, and specific abstracts for oral presentations. We are also responsible for getting the Talairach speaker and keynote speakers selected and lined up (but this is usually wrapped up by September). The ideal program is challenging to build because numerous variables need to be considered including novelty, rigor, speaker diversity, and topic diversity among others. The make-up of the program committee needs to reflect these challenges and that can be challenging as well (but I assure you we are working on it and making some measurable progress).
NM: Last, what do you see as the emerging research trends in your field? (and can you give our readers a hint as to what this year's main themes for OHBM might be?)
MG: In my field, Alzheimer's disease, the biggest trend is molecular imaging (amyloid but also tau PET with some increasing enthusiasm for PET that can measure activated microglia as well). This work tends to be quite clinical and so is not well-represented at OHBM currently (something I'd like to change in my remaining year on the program committee but it's a tall order). In terms of brain networks, I am excited about ongoing efforts to bridge the gap between cell-level molecular pathways and systems-level distributed networks. Network plasticity (following behavioral or pharmacologic interventions) is also an area I find compelling. I'm happy to report that these themes will both be well-represented at OHBM 2017 in Vancouver.
NM: Many thanks for your insight!
BY THE OHBM STUDENT AND POSTDOC SPECIAL INTEREST GROUP
OHBM is open to brain mappers of all ages and career stages, and the students and postdocs are a vital part of the society. Despite strong representation by PIs, there remains a need for trainees to have their own platform where they could discuss and disseminate information specifically relevant to them, such as job opportunities, funding, scholarships, and awards. The OHBM Student and Postdoc Special Interest Group (SIG) was set up to achieve these aims, while also creating the opportunity to interact in-person during the famous Monday Night Social at the annual OHBM meeting.
In 2017, however, there is more to the SIG’s efforts than the above mentioned activities. The SIG has a new initiative on mentorship to help prepare trainees to transition to early-career researchers; that includes a symposium and the launch of an online international mentoring forum. The symposium is slated to include a panel discussion, in addition to talks by academics that will help provide career direction to human brain mapping postdocs and students. The new online mentoring forum will pair students, postdocs, and researchers in online mentoring relationships that cross the globe; these mentoring pairs will have the opportunity to meet in person during the annual meeting. Together, these initiatives offer information about possible career paths, and organize information seekers and givers into a cohesive unit. Such information will breed confidence in early-career researchers and help them become the leaders of future research initiatives. To do all this and more, we have put together a team of excellent students and postdocs to lead the SIG. These committee members come from varied backgrounds in their research, and are representative of the diversity of our community at-large.
The chair of the committee, AmanPreet Badhwar, is committed to scientific diversity, open science, and public outreach; she has also organized many events promoting career development and fostering dialogue between neuroscience and art. The chair-elect, Michele Veldsman, has been a passionate advocate of mentorship for early career researchers through her many initiatives in postdoctoral associations and college committees. Kirstie Whitaker, the SIG's secretary, ardently believes in fair representation of early career researchers, and has championed these causes at many role model events designed to inspire young talent. The secretary-elect, Alex Barnett, brings experiences in university social affairs, as well as his own career transitions to help others in the field. Julio Yanes draws from his experiences serving on community service-based student organizations to bring enthusiasm to his new role as social chair, while social coordinator-elect Christian La works to bridge the gap between established and aspiring scientists. Our communication liaisons Shruti Vij and Shabnam Hakimi share a commitment to help publicize the SIG’s events and activities.
Each of these members brings to the table distinct profiles and abilities, but they are all committed to helping their peers and juniors. Together, all of us as members of the OHBM Communications Committee, will work to reach all corners of the diverse human brain mapping community, especially by fostering student and postdoc engagement. More information regarding the committee members and upcoming events can be found at the OHBM Student and Postdoc SIG page, their facebook group and on Twitter @OHBM_Trainees. We welcome this year’s new leadership to the OHBM’s Student and Postdoc SIG!
The SIG is also excited to welcome all students and postdocs to our group! We are currently looking for volunteers to help organize the many exciting events planned for OHBM 2017 in Vancouver and beyond. If you are interested in working with us to build these initiatives and support your career development, please contact us via email, facebook or twitter.
BY THE OHBM DIVERSITY AND GENDER TASK FORCE
It’s often been said that the best predictor of future history is past history. Thus, after comments at the OHBM town hall meeting in Geneva regarding the current gender imbalance of Council members (1 female, 14 males), the Council made a decision that something needed to be done to enhance gender equity and geographic diversity. Thus, the OHBM Diversity and Gender Task Force was formed.
If it is true that the best predictor of future history is the past, then it was important for the committee to obtain a historical perspective of how OHBM has been doing with respect to women in leadership roles. Perhaps the current 14:1 relationship between males and females is merely a dip in what was otherwise a balance in gender. Thus, we took a close look at the distribution of gender within leadership roles and education at the OHBM annual meetings. Like all good scientists, we will let the data speak for itself (See figures below).
Of course, like all good scientists, we also like to say ‘in brief…’ the ratio between males to females in leadership positions, awards, and keynote presentations is about 5 to 1 over the history of the organization. The one area in which there appears to be a transition to greater gender equality is in the Keynote lectures. However, such a transition has not been present in Council positions, which was highlighted at the Geneva Town Hall Meeting. The gender distribution of the general membership is not known because this information has not been requested in the past. Similarly, race and ethnicity of the membership is also not known. However, the gender distribution of poster submissions is approximately 50:50.
The goal of the Diversity and Gender Task Force is to help work with Council and the program committee over the next year to recommend changes to promote greater diversity, not only regarding gender, but also regarding ethnicity and geographic distribution. The Diversity and Gender Task Force will be using this blog site as one of our forums to communicate our work. We welcome input from the community to achieve this goal. You can share your ideas and suggestions using the comments field on this blog and/or by sending email directly to the Chair of the Task Force, Tonya White at firstname.lastname@example.org. We hope that as a consequence of our work those in the future will look back and see an encouraging historical trend, not only in gender, but also in race, ethnic, and geographic backgrounds of the OHBM leadership. And, most importantly, that diversity will translate into even more impactful and positive advances in our field.
As the time is upon us to vote for the new incoming members of Council, it is our desire that you vote for the best candidates, considering each individual, irrespective of gender, race, and geographic location. Please vote, your vote counts!
Panthea Heydari (PH): You seem to have a lot of different interests: You’re working with individuals with Alzheimer’s Disease, children on the Autism Spectrum…what would you say is the focus of your lab?
Susan Bookheimer (SB): I’ve focused on developing brain imaging techniques to be used on clinical populations. I work with a lot of different clinical populations (Alzheimer’s, Autism, ADHD, dyslexia, brain tumor patients, epilepsy). The idea is not to focus on a particular disorder, but, instead, to focus on making techniques appropriate for clinical evaluation, both for basic research and to help patients.
PH: Have you always been interested in neuroimaging or is this something you transitioned into from another field?
SB: It was one of those things that I accidentally happened upon. I was an epilepsy specialist and conducting neuropsychology of epilepsy research at the National Institute of Health (NIH). I happened to be there when they had a PET scanner (before fMRI existed). The NIH was one of the few places that had the capability to do water PET (activation PET) studies. Since I was working with epilepsy, we used PET for presurgical planning and language mapping. Soon, we had a MRI scanner where we could do very primitive, but effective, fMRI evaluations and that was it- I was hooked after that!
PH: That sounds like it was an amazing time to be at the NIH!
SB: Oh, it was incredible! There were amazing people there: the great Denis Le Bihan, who did the first diffusion scans, Bob Turner, who was instrumental in understanding the BOLD effect, and Peter Jezzard, among others. Since the techniques were just coming out, everything was being developed in real time, so it was very exciting!
PH: Can you please tell us a bit about your career path before and after the NIH?
SB: I spent one year at Smith College and two years at Cornell, where I studied psychology. I went to graduate school at Wayne State University in Detroit, which, at the time, was one of only three universities in the country that had a Clinical Psychology PhD Program with a specialty in Neuropsychology. I completed my internship at Yale with a focus on the Neuropsychology of Epilepsy and then was a post-doc for four years at the Epilepsy Center at the NIH. I came to UCLA afterward and have been here ever since.
PH: What are some questions that you think neuroimaging allows us to answer about the brain that we are unable to answer otherwise? What do you think is the most interesting advance you’ve learned through neuroimaging?
SB: I’d say it must be the complexity of systems that we had previously thought to be simple, i.e. systems that we understood based on watching patients experience a stroke. Prior to functional imaging, we had to wait for someone to get a stroke in a specific location, determine that location, determine what that person could no longer do, and then deduce what that brain area should do based on what the patient could no longer do. It’s a very roundabout way of trying to understand the brain and it led to very oversimplified maps- even maps is too generous a word—a very oversimplified understanding of the brain systems. I was particularly interested in language and memory at the time; where, initially, we thought we could use functional imaging to find the two common language areas: Broca’s area and Wernicke’s area. We quickly realized the language system was way more complicated than we had ever imagined.
PH: So maybe it’s like a starting point that we can continue to learn from…
SB: Yes, and it turns out that we have an awful lot to learn!
PH: Do you find that you still have the same level of passion now for science and imaging techniques that you did when you were first starting out? How has it changed over the years?
SB: I certainly have as much interest and passion for it now as I ever did. Back then, I spent a lot more time in the scanner. When we were conducting PET research, we took turns delivering the ligand to the patient (to share the radioactivity), and in the MRI, I was always either in or near the scanner. Back then, it was much more hands on and analysis software was just starting out too. There’s a tremendous amount of excitement in being right there when it’s happening! Unfortunately, that’s something I don’t really have the luxury to do anymore--I definitely miss it. Now, I spend more time trying to fund the lab, make sure the grants get written, and I do a lot of administrative work--but that’s not nearly as fun. I’d say my excitement for the science is completely undiminished but I spend lesser time doing the science than I used to then.
PH: What is your greatest scientific achievement?
SB: I would say my greatest scientific achievement was the first project that we completed which ultimately developed into the field of imaging genetics. We investigated a common polymorphism, APOE-4, a risk gene for Alzheimer’s Disease, in normal population and showed that normal volunteers who differ in their possession of the risk polymorphism had different brain activation patterns. This was my initial foray into a different way of examining the brain. Integrating the imaging and genetics together was my biggest accomplishment, even though it was a long time ago.
PH: What is your greatest non-scientific achievement?
SB: My children. I have two wonderful kids. They are my greatest achievements.
PH: Do they also share your passion for science?
SB: In their own way. My daughter ended up working with children with autism; autism research is one of my focuses. My son is interested in computers and information technology. Both my kids ended up having a scientific mind.
PH: Did you integrate the sciences into their day-to-day life?
SB: Science has been a big part of their day-to-day life since they were born. Their father and I both work here at UCLA and are both imaging scientists, so our lives were always surrounded by science. Science was very much part of my children’s upbringing.
PH: You were at OHBM 2016 in Geneva. How did you like it?
SB: It was awesome! I was initially nervous because I gave one of the keynotes, so I spent the first couple of days obsessing over my slides. I think the meetings are getting better, the science is getting better, the technology is getting better. I love OHBM.
PH: Is there anything you’ve heard or seen at the conference that has changed or influenced your work?
SB: I think the main things that I try to do, particularly at OHBM, is to be apprised of the newest techniques in acquisition and analysis. I don’t even know if I can point to one thing because there are just so many! If I could say one thing, it would be graph theory. We’ve been using graph theory for some time but to find new ways to conceptualize connectivity in the brain was a major change in the direction of imaging, evidenced by Bill Seeley’s keynote. Watching those techniques develop and seeing them at OHBM has been exciting. Most of our work now has a component of connectivity and use of graph theory.
PH: What do you think is the best piece of scientific advice that someone has given you?
SB: This is more like personal advice, but very early in my career, I was writing my first papers and feeling terribly anxious. This concept is particularly a problem for women who are not raised with natural self confidence. At this time, I contacted a friend of mine who had been publishing and asked her, “how do you get over the barrier of being so self-conscious about your work that you can write freely?” She said “I send my papers out to the scariest people I know before I send them out for publication. I figure that if I can take the criticism of the big name people in the field who scare me, then I will be okay”. So, I took her advice and that’s what I did. I sent one of my first papers to Peter Fox. He responded, read it, made comments, and he was fabulous! How to become a productive scientist is an important question, and that advice helped me tremendously.
PH: One of the things that came up at the OHBM 2016 town hall meeting was about diversity and the representation of women in science. You’ve been in the scientific world your entire career…can you comment if that representation has changed, or how you feel the role of women in science has changed over the course of your graduate degree, your post-doc, and your time here?
SB: Certainly, the laws have changed. When I was at Yale during my internship, I was the only female in the neurosurgery department and I was pregnant. Back then, it was legal for people to fire you for being pregnant. My internship advisor told me how wrong he thought it was for women to have careers and raise children. Of course, now it would be illegal to do so. I think in the old days, the sexism was much more overt and women had no legal protections. Proportionally, there exist more women in science today than there used to be, but I am disappointed with how many barriers still exist. These barriers are mostly in the unconscious biases of both men and women, but particularly men, in reviewing papers, in reviewing grants, and in setting salaries.
There are still a lot of people, particularly older men, in our scientific community who clearly exhibit covert sexism or implicit biases, and sometimes it is overt: they won’t listen to what women say, won’t listen to their opinions, make assumptions about what women can and cannot do. My female friends who are interested in mathematical aspects of what we do get a particularly hard time because it seems to be assumed that women cannot be good at math. Women who submit these complex statistical proposals get shot down. It’s just a huge problem!
PH: What do you think we can do to help that change along more quickly?
SB: I think that women need to work collectively more. We need to make the implicit biases explicit. If you see something, point it out. A lot of women don’t want to say anything because they are worried about rocking the boat; I feel we have to rock the boat, and rock it, and rock it! Let's not allow anyone to get away with this. Let’s be vigilant! For example, at grant review sessions, I’m very vigilant about the initial scores that males and females receive. I consciously look at my own review biases.
I tell my female mentees to have babies whenever they want to. You worry about it so much but, in the end, it doesn’t make that much of a difference in your career trajectory if you take a year off here or there. I feel that for most everybody, family is the most important thing no matter how hardcore a scientist you are. The more that we assert the importance of our families and normalize it, the easier it will be for the next generation of women as well.
PH: Great words! What do you do outside of the science world? What do you like to do for fun?
SB: I like to travel. I’m trying to tackle my bucket list. The first item on the bucket list was to go horseback riding across Mongolia, which I did. I’m a big fan of horseback riding and do it often. I used to have my own horse, which I loved. I hope to go back to Mongolia in a few years. I’ll be going to Thailand in April. I just returned from a week in Paris, just for fun.
PH: Wow! Sounds so fun! Well, thank you so much for chatting with me. It was a pleasure!
Interested in having your favorite neuroimager interviewed for the OHBM Blog? Let us know at email@example.com.
BY SHRUTI GOPAL VIJ
The human brain is a complex organ that continues to fascinate many researchers the world over. Brain researchers (including those involved in bench work using microscopy to those analysing brain images with supercomputers and complex algorithms) demonstrate a range of expertise, from neuroanatomy to diverse cognitive processes. The Organization for Human Brain Mapping (OHBM) is aimed at bringing together brain researchers and providing them with a platform to discuss new science, foster collaborations and improve our understanding of the brain.
In the past twenty-two years, OHBM has achieved this goal by presenting new facets of human brain mapping at each conference. The growing presence and influence of social media compelled OHBM to foray into the blogosphere, where we present greater insight into the workings of OHBM to researchers at all levels. Our offerings also highlight recent scientific discoveries and increase your acquaintance with contributions of researchers world over. Since its inception in April 2016, we asked you (our blog visitors) to indicate your area of expertise, in order to get a sense of who we are ultimately writing for. We found a diverse, wide-ranging span of responses representative of the many, many areas of specialization that represent human brain mapping. Most of our blog visitors were academics working on modelling and analysis, imaging methods, and higher cognitive functions (See figure).
These trends are generally consistent with the nature of posts featured on the blog. However, we have not yet had time to cover some areas such as brain stimulation and applications in psychology. Moreover, human brain mapping is a multi-disciplinary field that includes scientists in basic biology attempting to understand the microstructure of the brain as well as psychologists and clinicians exploring brain functioning and changes in neurological and neuropsychiatric conditions.
As we begin our second year, we will continue bringing you the type of articles that have made our blog so successful such as our interview with Karl Friston, response to Eklund’s paper on cluster failure (which was covered in the New York Times), and recent post on MEG, yet also find ways to reach readers seeking information on basic biologic and physiologic aspects of the brain. We would also like to hear from you - which bloggers would you like featured on the OHBM blog? So, go to the right sidebar to complete the new survey on neuroscience and brain imaging bloggers you follow. Comments and suggestions can also be sent to firstname.lastname@example.org.
The diversity of interests and expertise within the OHBM membership is one of the many things that makes our Annual Meeting one of the most anticipated and regarded events in the brain mapping community. We look forward to seeing you in Vancouver June 25-29!
BY KEVIN WEINER
New OHBM Communications Committee article on HuffPost Science:
When I was little, I used to catch leaves with my dad in autumn as I waited for the school bus in the Pine Barrens (a part of southern New Jersey that takes credit for the origin of the Jersey Devil). I was thinking about those moments as I read a recent interview with Karl Friston (KF).
Among his numerous honors, Friston is a Fellow of the Royal Society (joining the likes of Isaac Newton and Francis Bacon) and is an inventor of many tools that allow thousands of brain mappers to statistically test hypotheses about functional brain imaging data. For his contributions, he recently received the Glass Brain Award, which is the lifetime achievement award for the Organization for Human Brain Mapping. Read more
BY KEVIN WEINER
New OHBM Communications Committee article on HuffPost Science:
It’s often hard to find easy-to-read articles about cool scientific findings that are written in a clear way - let alone articles that are understandable enough to use as bedtime reading with your child. But, here’s a little secret: there are articles out there that are actually written by scientists and approved by children before they are published. Read more
BY LEONARDO FERNANDINO
For over two decades functional magnetic resonance imaging (fMRI) has been the indisputable workhorse in human brain mapping. Its ability to localize brain activity with high spatial resolution (millimeters), coupled with its non-invasiveness, make it an excellent tool for mapping behavioral and cognitive phenomena onto detailed brain anatomy. However, since fMRI relies on changes in blood flow, volume and oxygen concentration as indicators of neural activity, millisecond-scale fluctuations in neuronal activity are not reflected in the signal. The temporal resolution of fMRI (typically > 500 ms) is therefore too coarse to track neural activity in real time and discriminate rapidly succeeding neural events.
For example, some fMRI studies indicate that auditory cortical activations in response to signed language are stronger in deaf participants than in hearing individuals, raising the possibility that the auditory cortex is rewired to process visual information in deaf individuals. An alternative interpretation, however, is that visual processing of sign language occurs entirely in the visual cortex for both groups, and that activations in the auditory cortex reflect only a later, conceptual processing stage. The speed with which these processes occur makes it challenging to determine the precise sequence in which different brain regions become active using fMRI (or any other method that relies on metabolic responses, such as fNIRS or PET).
Fortunately, other non-invasive techniques can provide such precise temporal information. Electroencephalography (EEG) and magnetoencephalography (MEG) directly track the electrical activity of brain cells by measuring its effects on the electrical and magnetic fields just outside the head. They allow researchers to record brain activity at a very high temporal resolution (milliseconds), close to the actual timescale of neural computations.
EEG measures changes in electrical potential generated by the brain, which reflect the bulk electrical activity of many pyramidal neurons depolarizing in synchrony, through electrode leads placed on the scalp and connected to an amplifier. Researchers can then estimate the locations of the neural sources of these signals. The accuracy of these estimates depends, among other things, on the number of electrodes used, with higher numbers resulting in more precise estimates. Typically, between 64 and 256 electrodes are used.
Nevertheless, MRI-assisted EEG source localization is becoming more common. In both cases, the inverse solution is typically computed through an iterative algorithm that searches for the combination of cortical sources whose forward-modeled signal best matches the observed signal.
The main advantage of MEG over EEG comes from the fact that, while electrical signals are blurred and distorted by the skull, magnetic fields can traverse it virtually unobstructed. Thus, the MEG signal has higher spatial resolution, which allows better estimation of its neural sources.
MEG’s main disadvantage is the cost: the scanner and magnetically shielded room run in the millions of dollars, while a high-density EEG system costs under US$150,000 (although recent advances in quantum sensing might herald the coming of low cost, room temperature MEG). Even leaving these financial considerations aside, MEG still cannot completely replace EEG (nor vice versa), since the two techniques have complementary strengths. Because a magnetic field is oriented perpendicularly to its generating current, MEG is virtually blind to activations outside the sulcal walls, while EEG is maximally sensitive to activations in the gyral crests (and somewhat sensitive to activations in the sulci). Thus, simultaneous recording of EEG and MEG can add valuable information to the source estimation procedure.
Both EEG and MEG have been used clinically in the detection and localization of seizure activity in epileptic patients, which can be crucial for diagnosis and surgical planning. In research, they have been used to study a wide variety of problems, from spatial attention and synesthesia to sentence comprehension. Researchers at the University of California San Diego, for example, used them to answer the question posed earlier, of whether the auditory cortex in deaf individuals is indeed rewired for visual processing. By recording the MEG responses to signed language in deaf and hearing participants, they showed that, in both groups, activity was confined to the visual cortex in the early perceptual stage (~100 ms), and only later, during the lexico-semantic stage (~300 ms), the auditory cortex became active. This result provides compelling evidence against the auditory rewiring hypothesis.
Like any technique, MEG and EEG have unique strengths and limitations. The advantage afforded by high temporal resolution is partly offset by the relatively low spatial resolution of the estimated source locations. Nevertheless, researchers who manage to incorporate these approaches into their toolkit should expect a rewarding boost in their ability to probe the living human brain.
BY GUEST AUTHOR R. ALLEN WAGGONER
I had the honor of knowing Dr. Kang Cheng not only as a scientific colleague, but also as one of my closest friends for more than 20 years. He was the picture of health, so I was as stunned as everyone else when I learned that he has passed away suddenly at the age of 54. He left behind his wife, Professor Mariko Miyata, and their young son Kai.
Kang was born in Ningbo, China, in the province of Zhejiang, in 1962. He did not start out as a neuroscientist but graduated from Zhejiang University in 1983, with a B.A. in Geology. After graduating, Kang worked at the Chinese Academy of Sciences, Chengdu Institute of Geography for six years, doing image processing of satellite images. His work in image processing led to several opportunities to come to RIKEN (The Institute for Physical and Chemical Research, in Wako-shi Japan) for short visits. One of those visits was in a neuroscience lab, the Information Science Laboratory, headed by Dr. Keiji Tanaka. Dr. Tanaka offered Kang the opportunity to join the lab on a more permanent basis, if he was interested in becoming a neuroscientist. Kang accepted this offer and moved to Japan in 1989.
Kang's neuroscience career ranged from histology and electrophysiology studies, to PET and, eventually, fMRI. In essence he left behind a career of making maps from satellite images for a career that would eventually lead to making brain maps from MRI images. The very first neuroscience study that he coauthored was published in Nature, not a bad start to a scientific career. That paper was on columnar organization in the inferotemporal cortex and columnar organization in the brain proved to be one of the primary themes in his scientific career. In 1995, Kang received his Ph.D. from Osaka University Department of Biophysical Engineering. His dissertation was entitled "Studies of Extrastriate Visual Cortex of Primates" and included both electrophysiological studies in monkeys and PET studies in humans. These studies were carried out in Dr. Tanaka's lab.
Kang stayed on in Dr. Tanaka's lab as a postdoc and when Dr. Tanaka received funding for a 4 Tesla MRI system in 1996, Kang became one of the primary members of the fMRI team within the lab. He spearheaded the effort to image cortical columns, which was and remains, a primary interest in the lab. His initial efforts lead to our 2001 Neuron paper on observing ocular dominance columns in humans, with fMRI. Ours was not the first paper reporting the observation of ocular dominance columns with fMRI, but many neuroscientists were skeptical of the earlier reports. In our paper, Kang described in detail many key methodological issues, such as the necessary shape of the Calcarine sulcus, the required slice orientation, and included illustrations of what the expected functional maps should look like if columns were successfully observed as well as when, for example, the slice orientation was not quite right. Kang's attention to detail won over the skeptics and this became the work for which Kang is best known.
Neuroimaging studies lie at the intersection of a variety of scientific disciplines. Kang (a neuroscientist) and I (an MRI physicist) working together was an example of this. But Kang recognized the importance of each member in the team having a basic understanding of all the methods being brought together. He felt that no aspect of the experiment or the analysis should be viewed as a black box, and that without at least a basic understanding of the contributions each discipline brings to neuroscience, communication with scientists from the various disciplines is very difficult. Thus our collaboration over the years included many long conversations about recent advances in MRI technology, the details of the neuroscience questions we were trying to answer, and whether the methods we, or others, were employing were even capable of yielding answers these questions. This also meant that we would often require new postdocs arriving in the lab to attend lectures aimed at lifting the cover off the black boxes in their background.
In 1997, RIKEN established the Brain Science Institute (BSI) and Dr. Tanaka's lab became one of the founding labs. In 2001, Kang was named Deputy Laboratory Head of the Laboratory for Cognitive Brain Mapping (the current name of Dr. Tanaka's lab). In 2006 Kang was named Head of the newly formed Support Unit for functional Magnetic Resonance Imaging. Kang continued to hold both appointments until the time of his passing. He was also an Adjunct Associate Professor in the Graduate School of Science and Engineering of Saitama University.
Kang's life was not limited to science; during his years at RIKEN he helped organize intramural clubs for badminton, basketball, and soccer. He also enjoyed singing karaoke. In fact, in his early days at RIKEN, one of the main ways that he learned to both read and speak Japanese was by going to karaoke with his coworkers and learning to sing Japanese songs. At Kang's wedding reception, after prompting by several friends, he even gave an impromptu rendition of one of his favorite karaoke songs. He was also an avid photographer, and enjoyed filling the inboxes of his friends with pictures of conference dinners, his family having fun, or cherry blossoms in the spring.
I first met Kang and Dr. Tanaka at the University of Western Ontario. They were visiting Ravi Menon's lab and invited me there to interview for an MRI physicist position in Dr. Tanaka's lab. Kang picked me up from the airport and since then (for the next 20 years) he always enjoyed telling people how nervous I was when we first met in the airport. From that beginning we became life-long friends and he was even a groomsman at my wedding.
Kang was a good friend not only to those of us who worked closely with him, but to many in the neuroscience community as well. He will be sorely missed by all who knew him.
Two memorial websites have been set up in Kang's honor:
- One by his friends and colleagues at RIKEN: http://www.brain.riken.jp/labs/cbms/kchengmemorial.html
- The other by his friends in the Overseas Chinese Society for Magnetic Resonance in Medicine: https://ocsmrm.wordpress.com/2016/11/13/memorial_to_prof_kang_cheng/
BY GUEST AUTHOR PETER BANDETTINI
This post originally appeared on The Brain Blog by Peter Bandettini and Eric Wong. Republished with permission.
I’ve been working to advance Functional MRI (fMRI) since its inception. On Sept 14, 1991, two years into graduate school, and a month after seeing preliminary Massachusetts General Hospital results at the SMR meeting in San Francisco, Eric Wong and I performed our first successful fMRI experiment (Bandettini 2012).
Functional MRI, to this day, over a quarter century later, remains as exciting to me as on Day 1 as developments and applications continue at a rapid rate. While human brain imaging methodologies have arisen and grown over the years, and all of them, I’m certain, have interesting stories behind them, I wanted to share why I feel fMRI is unique:
1. fMRI was a surprising, rapid discovery.
Elements leading up to the discovery of fMRI were the discovery of BOLD by Ogawa et al (Ogawa 2012), the discovery of the dependence of blood T2 on oxygenation by Thulborn et al (Thulborn 2012), the advent of arterial spin labelling techniques by Williams et al. (Williams, Detre et al. 1992), the technical capability to perform EPI (Cohen and Schmitt 2012), and for the Minnesota group, higher field strengths (Uğurbil 2012).
The first fMRI results came from Ken Kwong’s penchant for trying interesting experiments. With Ken’s experiment, the method was discovered rather than incrementally developed. In fact, the pulse sequence and basic parameters used by Ken for BOLD were not anything overly complex or new – simple T2* weighted gradient-echo EPI at 1.5 Tesla. There was minimal time series processing involved then – in stark contrast to processing methods today. Interestingly, aside from the explosion in the sophistication of time series processing, the details of Ken’s first experiment have not qualitatively changed in terms of general practice over the years. He was just the first to realize that such a straightforward thing could be done!
This discovery surprised and excited the MRI community. To provide an analogy, it was as if we realized that if one sets the exposure settings of a standard camera just right, rather than just getting a photograph, you can get a picture of, say, subatomic particles. While the MRI scanner vendors adopted a wait-and-see approach before putting any resources into developing fMRI, the clinical and basic neuroscientists were highly motivated to start scanning.
2. fMRI was a revolutionary advance in functional imaging capability.
Functional MRI was, and still is, the only non-invasive, whole-brain method that has enough sensitivity to see human brain activity with about 2mm detail as it is happening in real time. This made for good science fiction before 1991. No one imagined it would become reality so quickly.
3. fMRI is deeply multidisciplinary.
Functional MRI brought disparate disciplines together in a way that was unprecedented. Suddenly, cognitive neuroscientists were having intense conversations with MR physicists. Computer programmers were talking with clinicians. The best fMRI research today has a signature of advancing methodology and insight into brain function – requiring close collaborations between physicists, statisticians, programmers, and neuroscientists.
4. fMRI is riding on the back of the clinical MR industry.
A huge factor that many people overlook is that fMRI was able to launch and propagate so rapidly because it leveraged the massive clinical MRI industry. In the early 90’s there were at least 20,000 clinical MRI scanners worldwide. By 1998, most MRI scanners were equipped with EPI – for other more clinically relevant purposes such as following a bolus of gadolinium for perfusion imaging or visualizing the heart beating.
Even though fMRI had minimal clinical impact, almost every MRI scanner in every hospital in the world was a potential brain function imaging machine. There was no need for a manufacturer to make fMRI machines. They already existed! These scanners were priced at over $1M each and were paid for and supported by hospital revenue – not neuroscience research grants. Today, that’s changing somewhat as the fMRI market grows and research grant revenue towards fMRI increases, but the reality is that fMRI depends on the clinical MRI market to survive.
fMRI has tremendously benefited from essentially riding on the back of the clinical MRI industry. This relationship has clear drawbacks too. Many interesting pulse sequences and custom fMRI setups are not being disseminated worldwide because the scanner vendors do not yet see a large enough market of fMRI to necessitate adding more development resources. Until fMRI becomes a thriving clinical technique (hopefully soon), it will be at the mercy of the clinical focus of the MRI scanner vendors – namely Siemens, General Electric, and Philips.
5. The degrees of freedom in fMRI acquisition is vast and unexplored.
We can do so much more than collect a simple time series of T2* weighted echo planar images. The ability to derive physiologic and neuronal information from MRI is still being explored as there are so many “knobs” you can adjust on the acquisition side to highlight gray matter, white matter, CSF, flowing blood, perfusion, iron deposits, vascular territories, trauma, leaks in the blood brain barrier, hemorrhage, deoxygenated blood, metabolism, pulsation, macromolecules, temperature, water diffusion, diffusion anisotropy, and much more. Additionally, the information that may be useful to fMRI is also still relatively untapped. Along with mapping the magnitude of the hemodynamic response as is most commonly done, we can derive information about latency, fluctuations, oxidative metabolic rate changes, blood vessel sizes, oxygenation, and more.
6. Processing methods are exploding in variety and sophistication.
Functional MRI processing methods continue to surprise – as it seems that the field continues to find new and better ways to extract, compare, and display new hemodynamic and neuronal information in groups and individuals. With the emergence of massive shared data sets, ever more subtle information about individual differences and similarities is being plumbed with the help of modern machine learning approaches.
7. Functional MRI just works.
Functional MRI just works – almost every time! It’s a stunningly robust technique. The functional effect size to noise ratio (from 6/1 to 1/1) is still perhaps too small and subject-wise variability a bit to large (with current post processing techniques) for robust clinical use (at least 10/1 is considered essential) but is large enough to see a significant effect within a few minutes of averaging. If it took 6 hours of averaging to see something, ambitious people would still do it but it would be much more difficult and the field would be much more anemic at this point.
8. fMRI requires two highly serendipitous properties.
Another key to fMRI that is commonly taken for granted: It requires two very subtle yet all-important properties to be possible at all. The first is that hemoglobin has to change its magnetic susceptibility in a non-trivial manner between being oxygenated and deoxygenated. This is an extremely rare property of a biologic tissue. If our blood were copper based – as with mollusks – rather than iron based, this would not happen. We would not have BOLD contrast as copper based blood does not change susceptibility with oxygenation. The second all-important property is that, with activation, a localized flow increase in the active region creates a highly focal overabundance of oxygenation. Why didn’t nature just require that the oxygenation stay the same in the active regions? We are still trying to figure that out, but the fact that it does – every single time with every person – similarly across species – in the same precise way in a stunningly consistent manner is highly fortunate. Perhaps our brains could have evolved a system where localized activation-induced changes in flow increased to simply match the increased metabolic needs rather than apparently overshoot them. If this happened, there would be no BOLD changes. We are lucky!
9. fMRI fills a unique temporal and spatial niche.
The information that fMRI provides fills a large and interesting temporal and spatial niche in understanding brain organization. Our brains are highly modular, and fortunately, the larger modules (motor cortex, visual cortex, etc..) are easily large enough to be discerned with fMRI. If our largest brain modules happened to be no larger than ocular dominance columns, fMRI would have never taken off, and if it did, interpretation of the results would have been a challenge at best. We’ll likely gain enough sensitivity and resolution soon to routinely probe the columnar and layer level organization of the brain soon – which brings us to the next unique property…
10. The highest fMRI spatial resolution matches the intrinsic precision of hemodynamic control.
It appears that the highest resolution achievable to fMRI (limited by scanning technology) – that of cortical columns or layers – matches the intrinsic precision of hemodynamic control. In other words, the smallest homogeneously activated region that causes a focal change in blood flow is on the order of columns or layers (<1mm). This perhaps suggests that this is the smallest scale in which groups of neurons are activated together. This last point is potentially controversial as it may suggest that looking any finer than this scale at neuronal activity may not necessarily lend insight into modular brain organization. Either way, again it’s fortuitous that fMRI resolution limits match the hemodynamic control limits – at least in humans.
The OHBM Blog Team thanks Peter Bandettini for this guest post.
Interested in submitting a guest post for consideration? Email your post to the OHBM blog team at email@example.com.
BY NILS MUHLERT
Many neuroimaging projects are multi-disciplinary. They often involve collaborations between physicists, engineers, computer scientists, biologists, cognitive scientists, and clinicians amongst others. Inevitably, this leads some to go well beyond their core discipline, learning and making notable advances in complementary fields. Michel Thiebaut de Schotten’s career falls firmly within this camp. With a background in Psychology, Michel went on to make substantial advances in neurobiology and neuropsychiatry, co-authoring a fundamental book on white matter anatomy (Atlas of Human Brain Connections), and papers on the anatomy of spatial neglect, attention and word reading ability, before reinterpreting and re-analysing data from historical case studies in neurology. This breadth of experience lends itself well to OHBM, a society that provides a bridge between disciplines.
Following 8 years as postdoc and research fellow in King’s College London, Michel recently crossed the channel back to France, starting the ‘Brain Connectivity and Behaviour’ group in Paris’s famous Hôpital de la Salpêtrière at the Sorbonne. Michel has also recently taken over the role of OHBM treasurer, from the previous incumbent Kevin Murphy. Here, we find out more about Michel’s scientific journey and what he hopes to achieve in this new role.
Nils Muhlert (NM): Looking back over your studies, which would you say you are most proud of, and why?
Michel Thiebaut de Schotten (MTdS): Our most recent work on the subdivision of the brain based on structural connectivity is a real source of pride. My team and I have been working hard on this method. I feel that we are making a big theoretical step forward in the way that we look at structural connectivity. We now, finally, can unify white matter organisation with the functional specialisation of the grey matter. I am really excited about the future discoveries that this new method will bring.
NM: Sounds exciting! How does this new approach approach work?
MTdS: We identified units of cortex with a specific signature of connectivity with the rest of the brain and decoded their function using the tool ‘decode’ on neurosynth. Interestingly, areas defined by their connectivity exhibit variations in extent and localisation between brains but retain a robust pattern of connectivity. Hence, these methods offer an ideal new way to study the relationship between structural and functional variability by providing more individually tailored brain models (for more info, see our recent editorial).
NM: Your published work could easily be described as ‘multi-disciplinary’ - do you see yourself as more of a cognitive scientist, neurology-researcher, historian, or something else?
MTdS: I am a neuropsychologist and I am passionate about my work. This sometimes leads me to explore and use new methods or spend long hours reading antiquated manuscripts. My motto is to “strive for a better understanding of the research of the past in order to appropriately contribute to the research of the future”.
NM: Why did you want to become involved with the OHBM executive committee?
MTdS: Mostly out of curiosity. I am a great admirer of OHBM`s work, having attended every annual meeting since 2006. As each year passes, the work of OHBM has become more and more impressive with regard to both the content of the programme as well as to the overall organisation of the meeting. Having served as a dedicated Program/Treasurer Committee Member in the International School of Clinical Neuroanatomy in the past, I wished to expand on my experience as OHBM treasurer.
NM: Tell us a bit about the logistics of being treasurer for OHBM - what are the main roles and challenges?
MTdS: As Treasurer, the core attribute of my role is to verify, monitor and validate expenses, and prepare the budget for next year’s conference.
The main challenge of the role is mobilising committee members in order to reach a consensus on each proposition. Committee members are very intelligent expert scientists, professionally trained to question everything. That in itself makes the OHBM Committee a particularly challenging crowd to convince.
NM: What would you like to achieve as OHBM treasurer?
MTdS: In my term as OHBM Treasurer, I would like to accomplish three specific goals. I would like to (1)Set up a policy for the OHBM’s reserve funds, (2) Reduce the price of the educational courses’ registration to its bare minimum, (3) Reduce the price of the conference registration for students.
Many thanks Michel!
BY TZIPI HOROWITZ-KRAUS
Read Part 1 of this interview here.
Tzipi Horowitz-Kraus (THK): What do you consider to be the greatest scientific discovery that was made possible by neuroimaging?
Karl Friston (KF): That's a difficult question. I think we all have to acknowledge that there is no field in systems neuroscience that hasn't been profoundly touched by neuroimaging. However, I think the impact and import of neuroimaging is not about discovery, it is seismic in a slower and subtler way; basically, neuroimaging makes a lot of sense of stuff that we already knew. In other words, I would not point to what has been discovered as the validation of brain mapping but point to how it makes sense of the vast amount of knowledge that has been accrued through the centuries of anatomy, physiology and psychology. We knew a lot of things in the past but now we know how to put them together. Neuroimaging can contextualize mesoscopic – and indeed synaptic or molecular – findings and say why that is important and how it relates to this, and how those findings could drive the next wave of imaging neuroscience.
THK: What do you think are the most pressing issues in neuroimaging for your area of interest?
KF: More detailed and mechanistic modeling of distributed neuronal responses. For instance, getting the right kind of connectivity and determining how to best integrate structural and functional connectivity. Other issues include connecting behavior to physiology and connecting functional connectivity to the underlying synaptic processing, and connecting synaptic processing to microcircuits – and microcircuits to whole brain connectomes.
When people ask me “What is the most important issue for you?” I respond "the issues that I work on"; namely, biophysical modeling (at least in my day job). In short, getting better and better modeling tools that enable people to ask evidence-based questions about the mechanisms that underlie the functional integration they are interested in.
THK: What do you think is the future of neuroimaging for basic research, for translation and maybe for applications as well?
KF: There are many avenues for neuroimaging in the future and I guess it depends where you place yourself in the spectrum of basic to clinical neuroscience. I think neuroimaging is not a field, it's a tool: it provides data or evidence for ideas and hypotheses. In this sense, the integration of neuroimaging with other modalities of enquiry probably holds the greatest promise. For example, one can see this in the use of whole brain imaging to contextualize invasive electrophysiology – which takes us into the realm of basic neuroscience and, if we put pharmacology and genetics on top of that, molecular neuroscience. A nice example of this is the molecular basis of neuromodulation and its effect on effective connectivity at the synaptic and molecular level. To get to this future, we need mechanistic, biophysically grounded, models in place – that can generate and make predictions about the molecular biology of synaptic plasticity; for example, models based on the short-term changes in synaptic efficacy that also explain a BOLD response in the fusiform gyrus. When we get that far, I think the future will no longer be brain mapping – it will be brain metrology.
I started in schizophrenia research. The future for people like me is ultimately translational in nature. Clearly, it will be nice to predict outcome trajectories of neuropsychiatric syndromes based on a psychopathology and pathophysiology. I suspect that this ambition has led to the emergence of computational psychiatry in recent years. Interestingly, most people working in computational psychiatry come from neuroimaging. There is a clear reason why that might be the case: if you're a doctor and you're worried about your patients, a non-invasive neuroscience is very appealing. Neuroimaging is par excellence, the non-invasive tool that can harness computational and basic science advances; hopefully, in the service of refining our understanding and treatment of neuropsychiatric conditions.
THK: Fifty years from now where do you think the neuroscience field will be?
KF: I think the interesting challenges I see around at the moment are in artificial intelligence. I think there are going to be big advances in artificial intelligence – and they will inform us at many different levels in neuroscience, clinical management and possibly well-being. From a personal perspective, this is largely the focus of my Sunday job.
I love the idea of having sentient curious machines living in your computer and working with you. One can imagine interactions with e-creatures that live in an electronic world and that have a purpose beyond minimizing some cost function. They have a purpose that is epistemic – and they want to learn what they can do and learn about you – like a proactive personalized Wikipedia. They will know that you are information hungry and might create novel situations for you that you have to explore.
THK: So it will be an extension of yourself without limits. ..
KF: I was thinking more of an extension of your parents. :)
Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include variational Laplacian procedures and generalized filtering for hierarchical Bayesian model inversion. Friston currently works on models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a free-energy principle for action and perception (active inference). Friston received the first Young Investigators Award in Human Brain Mapping (1996) and was elected a Fellow of the Academy of Medical Sciences (1999). In 2000 he was President of the international Organization of Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006. In 2008 he received a Medal, College de France and an Honorary Doctorate from the University of York in 2011. He became of Fellow of the Royal Society of Biology in 2012, received the Weldon Memorial prize and Medal in 2013 for contributions to mathematical biology and was elected as a member of EMBO (excellence in the life sciences) in 2014 and the Academia Europaea in (2015). He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award, a lifetime achievement award by OHBM (the Organization for Human Brain Mapping) in the field of human brain mapping. He holds Honorary Doctorates from the University of Zurich and Radboud University.
Special thanks to Jeanette Mumford for her assistance in transcribing and editing this interview.
This interview took place December 8, 2016 at the Educational Neuroimaging Center, Faculty of Education in Science and Technology, Technion, Israel.
BY TZIPI HOROWITZ-KRAUS
If there is one name in the field of neuroscience that is known and appreciated by many young researchers, it is likely Prof. Karl Friston. He is one of the founders of brain mapping, the father of multiple theoretical models, and the creator of tools that brain mappers use to better understand that most unique organ, the brain. Brain mappers from around the world recognize and acknowledge the contributions of Prof. Friston and their impact on our understanding of brain function and organization.
I recently had the honor and pleasure to meet Prof. Friston during his visit to the Technion in Israel. Following his fascinating talk entitled “I am, therefore I think”, we met for a cup of tea in the Educational Neuroimaging Center, to discuss some of the most pressing questions in the field of neuroimaging—questions that only Prof. Friston, with his vast experience and vision, can answer.
Tzipi Horowitz-Kraus (THK): If you are riding in an elevator, how would you describe your research and what you do for a living to person you are rising with?
Karl Friston (KF): My working week can be divided into two - my day job and my theoretical work on the weekends. My day job is to model and analyze brain imaging data and provide tools that allow for Discovery Science with neuroimaging. On Sundays, I indulge myself with theoretical neurobiology, computational neuroscience and more abstract theorizing about how the brain works and what it does. I do this in the fond hope [that is sometimes realized and sometimes not] that having a global, theoretical perspective on what the brain does will inform and constrain its empirical study. This theorizing helps with many practical aspects of developing schemes and models that enable people to pose questions to their data – and ensures this process is explicit transparent and rigorous. In short, I am largely an enabler during the week and a theorist at the weekend.
THK: What motivated you to go into that area of Neuroscience?
KF: From the age of 15, I wanted to be a neuroscientist but neuroscience as we know it today didn't exist at that time. For me, it was some form of mathematical psychology. I therefore went to my careers advisor and told him I wanted to be a psychologist, but I also wanted to do physics. He told me that “if you want to be a psychologist, you have to be a Doctor first”. He clearly thought I wanted to be a psychiatrist – and neither of us knew the difference! I followed his advice and diligently went to university (studying physics and medicine). I spent six years of my life becoming a doctor, before realizing my mistake.
Having committed to being a doctor, I then had to get back to brain research as quickly as possible: there were two routes in those days – Neurology or Psychiatry. At that time, psychiatry was – and still is – very exciting (in terms of things like neuropharmacology and addiction research). So I became a psychiatrist and, as soon as I qualified, took the first opportunity to enter research. All this meant that I was 28 before I began my research career, starting with psychopharmacology and then Schizophrenia research – inspired by my mentors in biological psychiatry. Luckily, brain imaging came along at precisely that time. It was lucky because it meant I could use my undergraduate training in physics and math.
THK: In the last meeting of the Organization of Human Brain Mapping you were awarded with the “Glass Brain Award” for your great contribution to the field of Brain Mapping. You gave an inspiring speech and acknowledged the role of friendship and colleagues in your scientific career. In the competitive world of science, it is sometimes challenging to remember these important values. Will you be able to share one personal story with me where it was friendship and collaborative work that resulted in a significant scientific accomplishment?
He was looking at the geometry of the tips of the maple leafs. Within a few months, Alan managed to supplant his maple leaves with neuroimaging data. A couple of years later, I met Keith (and one of his heroes – Prof. Robert Adler; now here in Electrical Engineering at the Technion and the reason that I'm here) and I learned about the utility of Random Field Theory, which is the basis of SPM (http://www.fil.ion.ucl.ac.uk/spm/). What came out of our collaboration illustrates a practical thing about international friendships: you can only make them work – when you're both very busy – through young people. It's very much like parents who are terribly distracted by other commitments but who share a common investment in their children. There were several young people that Keith and I engaged by inventing a question; for example, how do you estimate ‘smoothness’, when the smoothness of your data is not uniform. These problems were essentially an excuse to ‘adopt a child’ who would inevitably ‘grow up’ very quickly. A nice example of this was Jonathan Taylor, who was Keith’s PhD student who came to spend a year in the Technion with Prof. Adler. Someone who made Keith and I ‘proud parents’ is Jean-Baptiste Poline. Jean-Baptiste went on to be the first winner of the OHBM Education in Neuroscience Award. This joint supervision became a good model for all my collaborative innovations. There are many similar stories. The most recent arose from a friendship with Pascal Fries: we ‘adopted’ another young person (Andre Bastos) who is now doing a wonderful job dealing with hard core issues in electrophysiology and predictive coding. I should note one's ‘children’ generally become more expert than their parents, which is a hallmark of good parenting.
THK: What advice do you have for a young graduate student who is interested in pursuing a career in neuroscience?
KF: Develop a breadth of skills, interests, and perspectives. Then build a little pyramid on this broad base as the years roll on. You will naturally hone in on the things you find attractive and engaging. Usually, these are the sorts of things you knew you wanted to do at the beginning, but they only reveal themselves clearly with time. Breadth is the key thing; in terms of the people you can work with and in terms of conceptual tools you bring to the table.
For me, math is an important part of a broad base. I often meet people who say “I wish I learned more mathematics when I was younger”. I remember doing trigonometry and thinking "This is rubbish, when on earth am I going to use all these sines and cosines?" However, I guarantee within a year you will find yourself in a situation where you need a seemingly useless skill set (even trigonometry) – and you will be cross with yourself if you ignored the earlier opportunity. In short, keep your options open. That would be my advice.
I find that lots of young scientists are often worried about their next step. I've never worried about my next job. My advice is to make a sensible decision at every little point in your career path. All you have to do is to make the right small choices and everything will be fine (if you keep your options open).
Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include variational Laplacian procedures and generalized filtering for hierarchical Bayesian model inversion. Friston currently works on models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a free-energy principle for action and perception (active inference). Friston received the first Young Investigators Award in Human Brain Mapping (1996) and was elected a Fellow of the Academy of Medical Sciences (1999). In 2000 he was President of the international Organization of Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006. In 2008 he received a Medal, College de France and an Honorary Doctorate from the University of York in 2011. He became of Fellow of the Royal Society of Biology in 2012, received the Weldon Memorial prize and Medal in 2013 for contributions to mathematical biology and was elected as a member of EMBO (excellence in the life sciences) in 2014 and the Academia Europaea in (2015). He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award, a lifetime achievement award by OHBM (the Organization for Human Brain Mapping)in the field of human brain mapping. He holds Honorary Doctorates from the University of Zurich and Radboud University
Special thanks to Jeanette Mumford for her assistance in transcribing.
BY EKATERINA DOBRYAKOVA
New OHBM Communications Committee article on HuffPost Science:
There’s been an increasing amount of media attention to the topic of Traumatic Brain Injury (TBI) -bolstered in part by conversations surrounding the 2015 Hollywood blockbuster Concussion. The movie Concussion describes a particular phenomenon, Chronic Traumatic Encephalopathy or CTE, which occurs in the brain after repeated high impact blows to the head. The diagnosis of CTE requires examining brain tissue under a microscope after death, so it can’t be diagnosed in living individuals. But in fact, there are many types of TBI, with concussion being the mildest (but most common) form. Today, brain mapping techniques are making it possible to identify TBI and track recovery.