Current Work
I am trained as a neuroscientist, but am currently focused on using qualitative and quantitative approaches to understand the field and neuroscience education more broadly. In doing so, I hope to develop accessible and promising practices for neuroscience training and education.
Student attitudes towards coding
As STEM research in life science fields such as biology, cognitive science, and neuroscience moves towards larger datasets and more complex analyses, our students need to be trained accordingly. Students in life sciences majors tend to be more diverse in terms of gender and race, and therefore may be even further discouraged from pursuing programming, which is commonly viewed as a white and male field. As coding skills open the door to high-income jobs, inviting life sciences students to learn computer science is a matter of equity. However, there is limited research on how the barriers facing non-CS majors as they are introduced to programming or the attitudes of these students towards computing. My work therefore seeks to: 1) Understand the attitudes of & challenges confronting biology students in learning programming 2) Identify promising practices to streamline effective discipline-based coding education.
Tracking neuroscience career paths
With neuroscience as a field changing so rapidly, careers are quickly changing as well. In 2019, we launched a huge survey of almost 500 neuroscientists to understand their demographics, career paths, and skillsets. You can read about some of these findings in Shah & Juavinett (2022) and in this Neuroview. We ran a follow-up survey in 2022 to better understand the forces that drive individuals into computational subpaths. Stay tuned!
Building paths for diverse future generations
STEM career paths, including those in neuroscience, have long been restricted to a subset of our population. Although the representation within undergraduate neuroscience programs is improving, many groups are underrepresented at doctoral levels and beyond (Ramos et al., 2017). Working with the students of STARTneuro, we are developing promising practices for understanding how we can invite and maintain a more diverse array of future neuroscientists.
In 2021, we invited our first cohort of STARTneuro students to campus. We are following them throughout our program and beyond to understand their experiences and to develop best practices for training diverse students in STEM (as we have done with the initial START program, see Zuckerman et al. 2022). In addition, we are working with the mentors of our program to better understand how to train mentors of diverse graduate students (e.g., Zuckerman, Lo, and Juavinett, 2024). More recently, we have been working to understand how these students negotiate their sense of belonging on campus (forthcoming).
Former Work
Postdoctoral Work
As a postdoctoral fellow with Anne Churchland (CSHL), I used electrophysiology and ethological behaviors to understand multisensory circuits. In collaboration with an undergraduate intern George Bekheet, we developed a system to use and recycle Neuropixels probes in freely moving mice. Some of this data was used to corroborate the dominance of movement in neural activity. We also thought critically about how to best design rodent behavioral paradigms and leverage cutting edge technology in studies of decision-making.
Graduate Work
My doctoral research with Ed Callaway (Salk Institute) investigated cell types and circuits in the visual cortex of mice. I employed in vivo intrinsic signal imaging, two-photon calcium imaging, optogenetics, extracellular electrophysiology, and various tracing methods. My dissertation research showed that mice have visual areas that can compute complex motion, and that genetically- and hodologically-defined cell types in layer 5 of visual cortex are functionally different. In addition, I helped develop protocols to use intrinsic signal imaging to automatically draw borders between mouse visual areas. Most recently, we demonstrated the topographical organization of thalamocortical circuits.
Prior to my PhD work, I helped to identify biomarkers of stimulant addition and developed frameworks for the use of neurofeedback as a treatment for autism.