Program Directors: Brent Doiron, Jason MacLean and Stephanie Palmer
Administrator: Elena Rizzo
Openings: 6 Predoctoral, 0 Postdoctoral
To understand the function and dysfunction of the brain it is necessary to confront its complexity. Over the past two decades the field of neuroscience has leveraged the tremendous advances in electronics, genetics, and microscopy to collect a bewildering amount of neuronal data, especially when compared to the state of the field at the turn of the last century. More than ever these datasets require sophisticated analysis techniques to expose the salient aspects of brain dynamics and computation. Of equal importance is building a coherent theory of brain function. Theory can both organize these datasets under a conceptual umbrella, as well as suggest the next series of experiments to be performed. These realities require more neuroscience researchers to be trained in a variety of computational and mathematical techniques. This project outlines an ambitious graduate and undergraduate Training Program in Computational Neuroscience (TPCN) at the University of Chicago.
The University of Chicago TPCN has 30 training faculty distributed over 10 departments. The training faculty are composed of 6 faculty in computational neuroscience (dry-lab), 9 training faculty whose laboratories are primarily experimental, and 15 training faculty whose laboratories are both computational and experimental. At the graduate level the TPCN offers a PhD program in Computational Neuroscience and a complementary PhD program in Neurobiology. At the undergraduate level the University of Chicago has a highly popular Major in Neuroscience, and students can Minor in Computational Neuroscience. The TPCN is set within a highly collegial, cross-disciplinary environment of our Neuroscience Institute and the Grossman Center for Quantitative Biology and Human Behavior. The Neuroscience Institute was established in 2014 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 87 faculty having appointments in 16 departments. The Grossman Center was launched in 2020 and is a space within the Neuroscience Institute with an explicit focus on computational and theoretical neuroscience. Over the next five years the Grossman Center will grow to house 5 computational neuroscience faculty to complement our already existing community of theoretical neuroscientists. During this funding period the TPCN will (1) strengthen the course offerings in computational neuroscience at both the graduate and undergraduate level; (2) create a undergraduate research program in computational neuroscience; (3) enhance our minority recruitment by taking advantage of the undergraduate neuroscience research program.
TPCN trainees work in vertically integrated, cross-disciplinary research teams. Graduate students take a series of directed courses in computational neuroscience that span both statistical and modeling approaches. To ensure their competency in core neuroscience principles they also take courses in cellular, systems, and behavioral neuroscience. Their training will be supplemented with courses in a relevant quantitative discipline, such as computer science, engineering, mathematics, or statistics. All graduate students will have extended experience in at least one experimental laboratory, and they take part in journal clubs and seminars within the University of Chicago Neuroscience community. Supported undergraduates take courses in mathematics, computer programming, statistics, and neuroscience; they take an additional course in neuroscience or psychology and two courses in Computational Neuroscience; and they complete a research project. In addition, they complete the TPCN summer program. Undergraduate trainees in the summer program go through the boot camp on topics in computational neuroscience, including tutorials in Matlab, statistical methods, fundamentals of differential equations, and ideas of neural coding; they then complete a research project under careful guidance. All trainees receive training in responsible conduct of research.