Program in Neuroscience

Co-Director

Jonathan D. Cohen, Psychology

David W. Tank, Molecular Biology

Executive Committee

Michael J. Berry, Molecular Biology

William Bialek, Physics

Carlos Brody, Molecular Biology

Jonathan D. Cohen, Psychology

Ingrid C. Daubechies, Mathematics and Program in Applied and Computational Mathematics

Jonathan T. Eggenschwiler, Molecular Biology

Lynn W. Enquist, Molecular Biology

Susan T. Fiske, Psychology

Asif Ghazanfar, Psychology

Elizabeth Gould, Psychology

James L. Gould, Ecology and Evolutionary Biology

Michael Graziano, Psychology

Charles G. Gross, Psychology

Michaela Hau, Ecology and Evolutionary Biology

James V. L. Haxby, Psychology

Bartley G. Hoebel, Psychology

Philip J. Holmes, Mechanical and Aerospace Engineering

John J. Hopfield, Molecular Biology

Barry L. Jacobs, Psychology

Sabine Kastner, Psychology

Sean D. Kelly, Philosophy

Kenneth A. Norman, Psychology

Wolfgang Richter, Chemistry

Daniel I. Rubenstein, Ecology and Evolutionary Biology

Clarence E. Schutt, Chemistry

Robert Stengel, Mechanical and Aerospace Engineering

Jeffry B. Stock, Molecular Biology

David W. Tank, Molecular Biology

Alexander Todorov, Psychology

Anne M. Treisman, Psychology

Samuel S. H. Wang, Molecular Biology

 

Understanding how the brain works, and how it gives rise to mental function, is one of the most exciting challenges in science. This effort is inherently interdisciplinary, drawing upon developments in molecular and cell biology, genetic engineering, cognitive and social psychology, as well as chemistry, engineering, mathematics, and physics for new methods of measuring and understanding neural function.

To help prepare the next generation of neuroscientists for these challenges, Princeton offers an interdisciplinary program leading to the degree of doctor of philosophy (Ph.D.) in molecular biology and neuroscience or psychology and neuroscience. Joint degree possibilities in other relevant departments are possible. The program encourages the serious study of molecular, cellular, developmental, and systems neuroscience as it interfaces with cognitive and behavioral research. Current examples at Princeton include molecular, genetic, and pharmacologic analysis of learning and memory; the role of neural stem cells in the adult brain; viral infections of the nervous system; optical and electrical recordings of neuronal function; brain imaging studies of cognitive functions, such as attention and memory in humans; and mathematical and computational analysis of neural network function. A more extensive listing of research opportunities in neuroscience is available on-line at neuroscience.princeton.edu

Admission

Candidates for the program should apply to one of the cooperating home departments, which include the Departments of Chemistry, Ecology and Evolutionary Biology, Molecular Biology, Philosophy, Physics, and Psychology; departments in the School of Engineering and Applied Science; and the Program in Applied and Computational Mathematics. The candidate must fulfill the admission requirements of the chosen department.

Plan of Study

Upon entering the program, an adviser is selected who is normally a member of the student’s department as well as the program interdepartment committee (see list above). The student and the adviser prepare a plan of study following the student’s major interest and in keeping with the goals of the program. The plan of study should provide depth in one methodological area and breadth in some areas of practical concern. All students are expected to participate in the weekly neuroscience seminar (PSY 511). Additional course selections are made in consultation with the student’s faculty adviser based on the student’s background and interests, and in accordance with the requirements for the Ph.D. program in the student’s home department. Students must satisfy the normal pre-general examination requirements and pass the general examination of their respective departments.

Financial Assistance

Fellowship awards and assistantship appointments are made by the University after recommendation by the cooperating departments and with the concurrence of the program committee. Additional opportunities for support are available through participation in an NIMH-funded training grant in quantitative neuroscience (additional information available online at neuroscience.princeton.edu/neurotraininggrant.html).

Pertinent Graduate Courses

Chemistry

514 Molecular and Biomolecular Imaging

Computer Science

551 Introduction to Genomics and Computational Molecular Biology

Ecology and Evolutionary Biology

502 Fundamental Concepts in Ecology, Evolution, and Behavior I

Mechanical and Aerospace Engineering

511, 512 Experimental Methods I and II

541 Applied Dynamical Systems

546 Optimal Control and Estimation

Molecular Biology

504 Cellular Biochemistry

506 Molecular Biology of Eukaryotes

507 Developmental Biology

508 Advanced Topics in Neurobiology

514/EEB Biological Dynamics

515 Methods and Logic in Quantitative Biology

549 Laboratory in Neuroscience

Physics

557 Electronic Methods in Experimental Physics

561, 562 Biophysics

Psychology

500, 501, 502 Proseminars in Basic Problems in Psychology

503 Quantitative Analysis in Psychological Research

Undergraduate Courses of Interest

Applied and Computational Mathematics

350 Introduction to Differential Equations

Chemical Engineering

448 Introduction to Nonlinear Dynamics

Computer Science

402 Artificial Intelligence

487 Theory of Computation

494 Special Topics in Artificial Intelligence

Ecology and Evolutionary Biology

311 Animal Behavior

314 Comparative Physiology

Mechanical and Aerospace Engineering

345 Robotics and Intelligent Systems

Mathematics

201 Multivariable Calculus

202 Linear Algebra with Applications

203 Advanced Multivariable Calculus

204 Advanced Linear Algebra with Applications

305 Mathematical Programming

Molecular Biology

342 Genetics

345 Biochemistry

348 Cell and Developmental Biology

408 Cellular and Systems Neuroscience

431 Advanced Topics in Developmental Neurobiology

437 Computational Neurobiology and Computing Networks

Operations Research and Financial Engineering

201 Computer Methods for Problem Solving

245 Fundamentals of Engineering Statistics

307 Optimization

309 Probability and Stochastic Systems

411 Operations and Information Engineering

Philosophy

315 Philosophy of Mind

322 Philosophy of the Cognitive Sciences

Psychology

306 Memory and Cognition

330 Introduction to Connectionist Models: Bridging Between Brain and Mind

407 Developmental Neuroscience