Professor Aina Puce is the Eleanor Cox Riggs Professor in the department of Psychological and Brain Sciences at Indiana University, Bloomington, and a senior editor at Neuroimage. She has followed a career path that is now becoming more common in human brain mapping, starting firmly rooted in the methods end but, over time, gradually shifting focus towards understanding complex patterns of behaviour. To do this, she has made use of a number of imaging techniques, exploring ways to extract converging lines of evidence.
Here, we find out how her interests changed throughout her research, the promises and pitfalls of multi-modal imaging, and why you should not be discouraged by rejections but instead focus on and be motivated by the paper acceptances and other highlights in your career.
Nils Muhlert (NM): You initially graduated with degrees in Physics/ Biophysics. Now, one of your lab’s key interests is specific applications - such as understanding social cognition - though clearly facilitated through your expertise in imaging methods. Can you tell us about how your research focus has changed throughout your career?
Aina Puce (AP): My undergraduate degree was in Biophysics and my Masters degree was in Physics. For my Masters I was already recording EEG/ERPs in the operating room under anaesthesia – generating a frequency response of the visual system using sinusoidal visual stimulation through closed eyelids. During my PhD, I recorded intracranial EEG/ERPs from the hippocampus and temporal lobe for the purposes of identifying the epileptogenic temporal lobe in presurgical patient assessments.
My interest has always been tied to the relationship between brain and behavior. Over the years it has evolved from consciousness under anesthesia, to hippocampal integrity, to recognition memory of objects, to face perception, to recognition of face, hand and body actions, to multisensory perception, and now to the implicit recognition of emotions and other non-verbal signals. Seems like a lot of topics perhaps, but the evolving theme is how we make sense of our world. I owe a lot to my colleagues from the humanities: over the years they have patiently taught me so much about psychology.
NM: Much of your work involves imaging across modalities. Alongside the higher temporal and spatial precision, multi-modal imaging often involves the challenge of combining very large datasets. How have you got round these issues?
AP: Important question. When you study brain function using only one imaging method you will look at the world with a set of (rose-colored) glasses that give you only part of the story. We tend to forget that. Using multiple methods (either across or within subjects) keeps you honest, as you might get different answers to a scientific question. Then the onus is on you to get to the bottom of those differences, which means taking more time to study a problem. This can be frustrating, because at times you feel you are not getting anywhere relative to others in the field. At the same time, I would rather generate work that is reproducible and replicable by others! The field needs a solid foundation, and this can only be achieved by paying attention to data quality and also fully understanding the methods we work with.
With respect to large multimodal datasets, the biggest challenge right now as I see is data quality control. Data will likely be analyzed by individuals who may not have expertise in data acquisition and artifact recognition/rejection. When multiple assessment modalities are involved, this problem becomes compounded.
Another challenge that I see relates to cloud computing and subject privacy. Increasingly, subjects in these big datasets will be patients. As more investigators around the world interact with these datasets there is an increased potential for hacking and accessing sensitive information. Having easy to use, but secure, user interfaces and procedures for interacting with big datasets is key.
Another critical component is user training on computer hygiene. I am continually horrified by what I see those who are not computer-savvy doing with data-archiving and sharing. We cannot blame these people as they have not been formally trained in this area, but these are the potential weak links in the chain. That said, user-training needs to be made meaningful and interesting and something that users view as important – and that is also a big challenge in my opinion.
NM: Where do you see multi-modal imaging going over the next 5 years?
AP: With respect to methods and scientific practice: these have been re-examined and will continue to do so. With respect to neuroscience in general: I think that meso-scale neural interactions will be a major focus, as this work is critical to building bridges between systems neuroscience and molecular/cellular neuroscience.
Finally, for social neuroscience, measuring/monitoring brain and bodily function will also become more important as science moves more and more from a lab-based focus to a real-life one. Smart clothing used with dry electrode portable EEG systems and smartphone applications to gather data will become more common. Exciting developments in MEG sensor technology will continue, with attempts to develop higher temperature MEG devices and also flexible sensor helmets to better fit any head shape or size. This is a really exciting time to be involved in neuroscience!
NM: In your work on social attention you have proposed a ‘socially aware’ brain mode of social information processing. Can you tell us a bit more about this. How, if at all, does this brain mode map onto specific resting-state networks?
AP: I have recently been interested in how we use social information that we access implicitly to make social judgments or decisions about the behavior of others. Most lab-based studies in social neuroscience use tasks where subjects make explicit social decisions about others. Yet, this is so unlike what we do in real-life. In our lab we use both implicit task (involving a ‘default’ mode, where there is an internal focus on achieving goals) and explicit tasks (requiring a ‘socially aware’ mode, where we make explicit social judgements), using the same stimuli in the same subjects. We found very different neurophysiology across tasks – explaining in large part the existing variability seen in the literature.
Relationship to resting-state networks? Excellent question! We have been looking at the EEG dynamics during these implicit and explicit tasks, but have not yet looked at resting state EEG in these same subjects. So this is something that I would like to look at in future work.
NM: What advice would you give an early career researcher to help them stand out in the hunt for competitive fellowships, grants and faculty positions?
AP: I usually tell everyone to find what their passion is. What topic of study really motivates you scientifically? Doing science is a perpetual set of ups and downs – often more down than up. If you follow that passion, you are more likely to be successful, because it will help you get through the bad times.
As for specific advice for early career researchers. First and foremost, find a mentor – a senior scientist who you trust, have a personal rapport with, and who can help you work on your desired career goals. They should be a good sounding board, but also be able to network you with other scientists and point out career opportunities you may not know about. OHBM has an excellent mentor-mentee matching service. I have been recently assigned to mentor two young scientists, and I am looking forward to interacting with them on-line and face-to-face at the OHBM meeting itself!
Second, network network network! Don’t be afraid to speak with senior scientists at scientific meetings – not just at your poster, but do it at the various social events. Getting to know someone can allow you to visit their lab (perhaps even on a short stay to analyze some data), and who knows what other opportunities that might lead to? Applying to competitive Summer schools can also give you this opportunity.
Third, seek feedback from peers and colleagues on your fellowship and grant applications. People do not do this enough. That said, it requires being organized – you need to allow time for people to read and give you feedback, so that you can make the edits before the submission deadline. Same thing applies for job talks or conference talks – in our lab no-one does a talk anywhere without doing a dry run first! This rule also applies to me, and I value the detailed and caring feedback I get from my trainees.
Fourth, you can stand out by being yourself – scientifically and personally. Scientists are by nature prone to eccentricities. I like to celebrate those. Your (hopefully positive) eccentricities make you who you are, and importantly make you distinctive and memorable to others. (I'll never forget a job candidate who told us that he had a pet tarantula. He got the job!)
NM: Next month, you’ll be a keynote speaker at the Brain Twitter Conference. Can you give us some insight into what you’ll be presenting - and what you think can be achieved through this online mini-conference?
AP: I will keynote tweet on the different modes of social information processing that I mentioned before.
What can be achieved with an online Twitter conference? A couple of things quickly come to mind. First, the conference builds a greater sense of community, allowing new connections between scientists around the world to be made through interactions generated in response to speakers’ tweets. (It is interesting to finally meet people at scientific meetings that you have been tweeting with.) Second, communicating one's ideas with a series of 10 Tweets makes one distill the absolute essence of the ideas to be presented. It allows the presenter, at least, to work out what is really important in the practice of their science.
NM: When did you become involved in Neuroimage - and how have you seen it develop over the years?
AP: I became a member of the Editorial Board in 2005, a Handling Editor in 2009, a Section Editor in 2011 and finally a Senior Editor in 2013. It has been wonderful to watch our field grow exponentially over the years and to work with so many dedicated and committed people in our NeuroImage family. Back in the early 1990s we had no outlet where (f)MRI-related work was welcomed, whereas work related to MEG and EEG was being published in well established neurophysiology journals. Today we have NeuroImage as well as Human Brain Mapping (which also began very early to meet the need to publish MRI-related work). It is terrific to see neuroimaging work so mainstream and regularly appearing in high-profile neuroscience journals. Indeed it is hard to keep up with it all right now!
NM: ...and finally, you’re currently serving on the program committee for OHBM. What does this role involve - and how can others contribute?
AP: OHBM is my tribe. As a post-doc I presented a poster at the very first OHBM meeting in Paris organized by Bernard Mazoyer in 1995. I have only missed a couple of OHBMs since then, due to issues related to visas... I have presented in Educational Courses, Symposia and given a Keynote, as well as chairing scientific sessions over the years. I was a member of Council from 1999-2002, where I was the Meetings-Liaison. Back then we did not have the wonderful Secretariat we have now, so the meeting organization was a bit different. Currently, together with Cyril Pernet I am Co-chairing a COBIDAS for MEEG committee for OHBM. I am also a member of the OHBM Scientific Program Committee – and right now this is busy time for the committee. I want to give a huge shout out to Michael Chee and his very capable team in Singapore. World-events forced the change of the meeting city at the last minute, and Mike and his team are making sure that OHBM 2018 will be just as successful as all of our other meetings. I am really looking forward to it!
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