Neuroscience is inherently computational. As experiments and neural measurements become more complex and extensive, analyses require more computational expertise. In addition, theories spanning experiments from a variety of domains require computational integration. Many students are therefore seeking more training in computational techniques.
A growing number of University of Minnesota faculty combine sophisticated computational techniques with experimental data. This includes a diverse set of topics in neuroscience, spanning multiple spatial and temporal scales and brain systems. We have Medical Discovery Teams in addiction and optical imaging and brain science. We have centers for neuroengineering, cognitive science, magnetic resonance imaging, and are developing centers for computational psychiatry. There are cross-discipline training grants in computational analyses of complex experiments, addiction, comorbidity in psychiatry, computation in sensory science, vision, and many others.
Over the past five years, the state of Minnesota has created multiple initiatives that have catalyzed the creation of a robust community in computational neuroscience. These initiatives - in neuroimaging, addiction, neuroeconomics, neuromodulation, and psychiatry - have led to more than a dozen new hires at all levels and have contributed to making UMN a world leader in computational systems and behavioral neuroscience research.
Applying to graduate school to do computational neuroscience at the University of Minnesota.
We currently do not have a graduate program in computational neuroscience. For students interested in pursuing research in computational neuroscience, neuroeconomics, or decision making, there are many pathways to joining our group. Which one works best for you will depend on your background and your eventual goals. This website is designed to help you see all the options and help you choose the best one for you.
Importantly, at the University of Minnesota, advisors are generally members of multiple graduate programs. This means that you can join a laboratory from multiple graduate pathways. We recommend contacting a faculty member to ask what graduate programs can provide access to their laboratory and what graduate program is right for you.
These different graduate programs have different requirements, and thus different classes and different breadths of training. Many faculty collaborate with one another. You are encouraged to apply to whichever program(s) you feel will best match your individual path. You are encouraged to apply to multiple programs at the University of Minnesota, as the programs are highly competitive.
There are hundreds of faculty at the University of Minnesota whose work interacts with computational neuroscience questions. Here is a small list of potential faculty to contact, but we encourage you to contact any faculty at the University of Minnesota whose work interests you to see what graduate programs they are a member of.