NIH Blueprint for Neuroscience Research

Boston University
In this campus-wide training program, young scientists, mathematicians, and engineers interested in computational neuroscience will be trained in both theoretical and experimental neuroscience. The undergraduate program provides students majoring in the biological sciences with a strong background in the application of mathematical and engineering concepts to neuroscience. Conversely, the Ph.D. program is designed to provide strong training in experimental neuroscience to students with engineering and mathematics degrees. The overall goal of the program is to integrate fundamental knowledge, interdisciplinary thinking, and translational skills to solve challenges in the neurosciences and promote a strong community of faculty and students with similar interests. A particular focus of this program is to train a new generation of neuroscientists who will combine experimental and theoretical techniques to increase our understanding of the brain, to transition their discoveries from the lab bench to the clinic, and to invent new technologies to restore lost brain function. The program also will expose undergraduate students to the diversity of research careers in computational neuroscience and provide career guidance and grant writing training for pre-doctoral students.
Project Director: David C. Mountain, Ph.D.

Brandeis University
The goal of the program in Computational Neuroscience at Brandeis University is to identify early career students and provide them with the formal and informal education and training they will need to develop into the next generation of computational/quantitative neuroscientists. The program consists of a full-year research and education program for undergraduates and a Ph.D. training program. The training faculty has research expertise from human cognition to cellular and molecular neuroscience and was chosen because of their demonstrated commitment to the use of theoretical and computational methods to understand the nervous system in health and disease. Students take courses in computational neuroscience, obtain skills in building models of neurons, synapses, and networks, and employ these in a variety of independent research projects. Two cohorts of prospective trainees are to be targeted: 1) Individuals in degree programs in Physics, Math, and Computer Science who wish to receive training and work in neuroscience; and 2) Individuals in degree programs in Biology, Biochemistry, Neuroscience, or Psychology who wish to learn to employ quantitative and computational methods as part of their ability to tackle important problems in neuroscience. In addition to course work and laboratory research, students and trainees are engaged in a large number of other activities designed to enhance their speaking skills, writing skills, and ability to collaborate with other scientists.
Project Director: Eve Marder, Ph.D.

Carnegie Mellon University and University of Pittsburgh 
Interdisciplinary Training in Computational Neuroscience is a broadly-based computational neuroscience training program that provides students with opportunities for cross-disciplinary research in laboratories at Carnegie Mellon University and the University of Pittsburgh. This training program was launched in 2006.  It includes a full-year research and education program, a summer program for undergraduates and a Ph.D. training program. Training faculty come from a wide range of disciplines across both universities and have research interests ranging from dynamical systems to machine learning to biophysics in the quantitative domain, and ranging from neurophysiology to fMRI imaging to molecular biology in the area of neuroscience. The training program is administered by the Center for the Neural Basis of Cognition, an existing center that involves faculty and students at the two universities. Students in the program will gain expertise both in quantitative and biological approaches to the study of the central nervous system.
Project Directors: Robert E. Kass, Ph.D. (CMU) and Bard Ermentrout, Ph.D. (University of Pittsburgh)

Emory University and Georgia Institute of Technology
The program "From Cells to Systems and Applications: Computational Neuroscience Training at Emory & Georgia Tech" provides an integrated approach to class work and research on both the undergraduate and graduate levels that capitalizes on ongoing collaborations between the two institutions. Program faculty have funded research programs that range from detailed cellular computer simulations of neural dynamics to engineering approaches and the quantitative study of disease mechanisms underlying important disorders such as epilepsy and Parkinson's disease using computational methods. Undergraduate trainees will be recruited primarily from Neuroscience and Behavioral Biology majors at Emory and Biomedical Engineering majors at Georgia Tech, who will bring a biological and quantitative strength to the program, respectively. Pre-doctoral trainees will be recruited from the applicant pools for the Neuroscience and Biomedical Engineering programs. The program aims to make a significant contribution to fulfilling the need for highly trained scientists capable of integrating experimental results using computational and theoretical approaches to understand the complexity of brain processes underlying neurological and psychiatric disorders.
Program Directors: Dieter Jaeger, Ph.D. (Emory University) and Garrett Stanley, Ph.D. (Georgia Institute of Technology)

University of Washington
This undergraduate and graduate training program in computational neuroscience draws from faculty mentors distributed through many departments and schools, including Physiology and Biophysics, Biological Structure, Computer Science and Engineering, Applied Math, Biology, Psychology and Bioengineering. Support for undergraduate and graduate education and research will foster the ongoing growth of this area, enhance interaction between theorists and experimentalists, expand and integrate coursework in quantitative approaches in neuroscience, enhance interactions between undergraduate and graduate students, enhance opportunities for undergraduate research and draw together the community across campus to strengthen existing interdisciplinary exchange and collaboration. The undergraduate training program will establish a two-year sequence in computational neuroscience for students from neurobiology or from a computational major who will take a common core curriculum including both laboratory neurobiology courses and quantitative courses, where the laboratory section is enhanced with a parallel computational course. The graduate training program will draw from students in the Neurobiology and Behavior interdepartmental program or from departmental graduate programs. The program will train young neuroscientists to use mathematical and computational tools to understand the highly complex, dynamical processing capabilities of the brain and neural circuitry. It will also give students in physics, mathematics and computer science deeper insight into the biology of the brain in order to devise more appropriate theoretical models. Advancing this collaborative approach to neuroscience will help us to intervene in brain pathologies and ultimately to create assistive technologies that integrate with nervous system function.
Program Director:  Adrienne L. Fairhall, Ph.D.