The Training Program in Theory and Computation for Next Generation Neuroscientists (TPCN) provides students with an introduction to research in Computational Neuroscience.

To understand the function and dysfunction of the brain, it is necessary to confront its complexity. This reality requires more neuroscience researchers to be trained in a variety of computational and mathematical techniques.

The TPCN aims to train the next generation of neuroscientists to apply quantitative methods from mathematics, statistics, and physics to the study of neural systems.

The goal is to create literacy in mathematical techniques and modeling applied to experimental data for undergraduate and graduate trainees who wish to become empirical neuroscientists as well as to foster the growth of trainees whose main focus is theoretical neuroscience.

The research covers a wide breadth of areas, from neuronal biophysics to microcircuit dynamics, neural coding, decision-making, learning, and behavior.

The training is set within a highly collegial, cross-disciplinary environment of our Neuroscience Institute and the Grossman Center for Quantitative Biology and Human Behavior.

During the funding period, it will (1) strengthen the course offerings in computational neuroscience at both the graduate and undergraduate levels; (2) create an undergraduate research program in computational neuroscience; (3) enhance our minority recruitment by taking advantage of the undergraduate neuroscience research program.

Across five years of funding, the Training Program in Theory and Computation will support 20 domestic PhD students, 10 international PhD students, and 30 year-long undergraduate students.

Undergraduate Training

In this program, undergraduate students in their first, second, or third years will engage in a funded computational neuroscience research project over a full calendar year. They will work under the guidance of a selected faculty member from the Neuroscience department, concluding their project with an oral presentation. Throughout the program, students will attend faculty seminars and lab visits covering a diverse range of neuroscience research topics.

Nominees do not need to be Neuroscience majors or Computational Neuroscience minors, but they must be actively involved in computational neuroscience research. To be eligible, students need to commit to multiple quarters of research, which can include any combination of Autumn, Winter, Spring, or Summer.

This NIH-funded training program offers a stipend for part-time research during Autumn, Winter, and Spring, and a stipend for full-time research in the Summer. In their final program quarter, students are required to deliver a 30-minute research talk.

Faculty members are responsible for submitting student applications, and undergraduate students interested in joining the program should contact one of the TPCN Training faculty members directly.

GRADUATE TRAINING

Ph.D. candidates supported by the TPCN will engage in a structured one-year training plan (with the potential to renew for one additional year).

In this program, graduate students will take a series of directed courses in computational neuroscience that span both statistical and modeling approaches. Their training will be supplemented with courses in a relevant quantitative discipline, such as computer science, engineering, mathematics, or statistics.

The trainees will have extended experience in at least one experimental laboratory, under the supervision of a select mentor. They are also required to attend a series of journal clubs, seminars, and events within the University of Chicago Neuroscience community.

TRAINING FACULTY

faculty graphic
The Training Program in Computational Neuroscience has 31 training faculty distributed over 10 departments. The team is composed of 8 faculty in computational neuroscience (dry-lab), 9 faculty whose laboratories are primarily experimental, and 14 training faculty whose laboratories are both computational and experimental.

The members of this group are tackling many of the most fundamental questions about how the nervous system works and how it can break down using state-of-the-art methodologies at all levels of analysis, from the biophysics of neurons to the dynamics of neuronal circuits to perception, cognition, and behavior.

Some of our trainers investigate how genes and proteins shape the response properties of neurons, while others investigate how neuronal properties emerge from the collective activity of circuits of neurons. Others work on how information is encoded in the responses of individual neurons and/or populations of neurons. This group includes trainers who study the neuronal mechanisms underlying cognitive functions such as attention, learning, memory, and decision-making. Many trainers also study diseases of the nervous system and seek potential cures.

see THE FULL LIST OF TRAINING FACULTY