Dr. Lucas Tian is an F32 award recipient who used the funding opportunity to study the neural mechanisms of behavior. The F32 funding opportunity supports the research training of promising postdoctorates early in their postdoctoral training period.
The NIH BRAIN Initiative funding portfolio enables the collaborative and multidisciplinary research necessary to help us understand the complexities of the brain. Dr. Lucas Tian is the recipient of a BRAIN Initiative F32 Individual Postdoctoral Fellowship award to support his research on behavioral sequences—specifically, what causes macaque monkeys to put together new thoughts or behaviors. The F32 program rewards promising postdoctorates early in their careers by enhancing their research training in project areas that advance the goals of the NIH BRAIN Initiative. This article is part of a series that highlights the careers of NIH BRAIN F32 grantees. The next deadline to apply for an F32 award is April 9, 2024.
Check out the interview below to learn more about Dr. Tian’s post-doc research, the path he took to his current project, the challenges faced when transitioning to a new animal model, and what advice he would give prospective F32 applicants.
Would you please briefly introduce yourself?
My name is Lucas Tian, and I'm a postdoc at Rockefeller University in Dr. Winrich Freiwald’s lab. My general background is in systems neuroscience with a highly cognitive slant. I am most interested in understanding the neural substrates of thought, or what goes on in your head when you're thinking complex thoughts, for example: imagining what you might do later in the day, or in simpler scenarios like solving puzzles, reasoning about how to cook something, or things that require multi-step, deeper processes in the brain.
What led you to research? What continues to drive your ambitions as a scientist?
When I was young, I was fascinated by the concept of consciousness and the idea that our mind is governed by biological tissues in our heads. As I grew older, I realized that I have a keen interest in research and focused on molecular biology and genetics initially. However, I soon realized my reductionist approach was not ideal to tackle the fundamental science questions that I wanted to answer. I switched my focus to systems neuroscience in graduate school. I studied the mechanisms of vocal imitation and learning in songbirds. Eventually, I realized that I wanted to study something a little closer to human cognition and the questions of thought.
That led me to my current postdoctoral research in macaque monkeys, studying compositionality—the capacity to create new thoughts or new behaviors by putting together multiple simple components in some rule-based or syntactic (syntax-based) manner. One example in humans is language; we can create new sentences to form thoughts without having prior knowledge or use of that specific sentence. My research is essentially about how we create new behaviors, as in speech, but in my case studying simpler tasks that monkeys can perform.
I designed a drawing paradigm in which monkeys learn simple drawing components like shapes and abstract syntactic structures: different ways to order the shapes in a space, transitions between shapes, or how to group shapes. They’re capable of creating new drawings based on generalizing and recombining these simpler elements and rules. Studying the cognitive and neural substrates of this behavior should lead to a better understanding of what's going on in the brain when you create complex things from simpler elements.
What are some major implications of your research?
My work is not going to completely explain how you think, but rather, it builds toward that goal by contributing to research that is trying to understand the basic mechanisms of cognition. It is very interesting to learn about how new ideas or behaviors pop into your mind. From a clinical standpoint, I believe this work might also contribute to understanding a variety of cognitive disorders that manifest in disorganized thought—disorders that create difficulty planning multi-step tasks or planning the day ahead of you.
As a field, we know very little about how the brain organizes complex, multi-component thoughts. I’d like to approach this problem from a more basic angle, and hopefully, these mechanisms of understanding will lead to better therapeutics in the future.
What are some of the challenges you have encountered in your research and/or career? How have you, or how are you, working to overcome them?
The main challenge was a transition to a new developmental model organism – from songbirds to macaque monkeys – and struggling to grapple with the complexity of the intelligence that these animals possess. I realized that they’re remarkably smart, and they find new ways to solve the tasks that I developed on touch screens. Kind of like little apps and games—you design a task, and the monkey must use some sort of cognitive strategy to solve it. Sometimes, they find an entirely different way to solve the task and you end up not studying what you initially set out to study.
At the career level, I’d say that many people struggle with negotiating or gaining the right amount of interaction with their mentors while also balancing the desire to have independence. I've had mentors that are a little more hands off, which has forced me at times to be more independent. It’s tricky to navigate the best mentorship style that is suitable for you. People are very busy, and I feel like I had to learn be more assertive.
What would be the next step in your research (or professional development)?
My long-term goals are to stay in academia and run a research lab to build on the questions I’m working on right now. The macaque research, computational modeling, cognitive modeling, cognitive behaviors, and cognitive psychology work was new to me when I started as a postdoc. I have a lot to learn and practice before starting my own lab. In addition to the technical aspects of macaque neuroscience, I’d like to learn more of the non-technical aspects of running a lab like writing grants, mentorship, and lab management. These are all things I’m starting to get more experience with.
What would be your advice to others who may want to apply to the BRAIN F32 program?
I was surprised at how much work the application entailed, but it was a very useful exercise because it forced me to organize my thoughts on career development, training, and research plans. It takes a lot of time and feedback—don’t be scared to ask a lot of people to read your aims page and proposal, and to be a little more assertive with mentors.
Are there any specific relevant training and professional development opportunities that you find useful during the fellowship?
The Annual BRAIN Initiative Conference is a great opportunity to organize what you’ve done so far and present a poster to get feedback from the neuroscience community. It’s a useful aspect of being funded by the F32 award. By covering your salary, the F32 also potentially gives you a bit more independence in spending lab funds on other resources or for hiring a technician.
Fill in the blank: When I’m not working on a research project, I am…
Seeing my friends and catching up with them—my project takes a lot of time and energy, and I don’t want that to jeopardize my relationships and friendships. I want to be able to connect with the people I care about.
Stay tuned for more highlights on BRAIN Initiative award recipients in some exciting, upcoming series on the BRAIN Blog. If you are a BRAIN Initiative F32 fellow and would like to be featured on our blog, let us know by sending an email to BRAINfeedback@nih.gov!