Director: Ruth Wood, PhD
Application deadline: December 1
Breadth of interests and training are major features of the graduate program in neuroscience. Wide and varied skills in many research areas characterize the faculty of the program. Close contact between faculty and students is considered of major importance in this highly interdisciplinary field.
Training is given in several areas of specialization: behavioral and systems neuroscience, cellular and molecular neurobiology, cognitive neuroscience, computational neuroscience, neuroengineering and neuroscience of aging and development.
Applicants should normally have defined an interest in one or two specializations. A final choice of the specialization will be made during the first year.
A baccalaureate degree in a field relevant to the student’s graduate goals is required.
Appropriate fields would include neuroscience, biology, chemistry, computer science, linguistics, psychology and many areas of engineering. Undergraduate study should provide evidence of proficiency in mathematics, including statistics. Students planning to enter the specialization in computational and mathematical neuroscience should have taken course work in calculus and, where possible, linear algebra and computer programming. Applicants who are accepted with minor deficiencies are expected to correct these during the first year.
These degrees are awarded under the jurisdiction of the Graduate School. Refer to the Requirements for Graduation section and The Graduate School section of this catalogue for general regulations. All courses applied toward the degrees must be courses accepted by the Graduate School.
The student will be advised during the first year by the Graduate Advisement Committee. As soon as the student has selected a specialization, an Advisory Committee of appropriate faculty will be appointed. This committee will be chaired by the thesis adviser, when chosen. The purpose of the Advisory Committee is to help the student in the selection of courses and research; to monitor the student’s progress; to ensure preparation for the qualifying examination; and to administer that examination.
A minimum of 60 units is required, consisting of formal courses, seminars and research credits. At least 24 of the 60 units are to be formal graduate course work (lecture or seminar courses). During the first year the student is expected to complete the core courses in neuroscience (NSCI 524 and NSCI 525 ), one key course, INTD 500 Responsible Conduct of Research, and two semesters of NSCI 539 . Other courses in the area of specialization may also be taken in the first year and will be taken in subsequent years.
Core Courses: NSCI 524 and NSCI 525 Advanced Overview of Neuroscience (8 units), will be taken by all students in the fall and spring of their first year to provide an integrated multilevel view of neuroscience. To take the core course, students should have mastered the material currently taught in BISC 421 . (Students will be expected to review a detailed syllabus and reading list for BISC 421 to identify their level of knowledge prior to their arrival at USC and will receive advice at Orientation on whether to take BISC 421 or read recommended material to remedy their deficiencies.)
Key Courses: All students will be required to complement their thesis-directed studies with a “breadth with depth” requirement by taking two key courses, one each from two different tracks listed below. Each key course will be for 3 or 4 units. (At least one of these courses will serve to advance thesis-related study as well.)
- Cellular, Molecular and Developmental Neuroscience Track
- Cognitive Neuroscience Track
- Computational Neuroscience and Neuroengineering Track
- Systems and Behavioral Neuroscience Track
All students are required to take INTD 500 Responsible Conduct of Research (1 unit), as well as a 4-unit approved statistics course (PM 510 , PSYC 501 or equivalent).
Students may request permission to have non-NSCI advanced courses satisfy the track requirements.
It is required that all neuroscience PhD students demonstrate competence in statistics in fulfillment of their PhD requirements.
The qualifying examination concentrates on the student’s ability to demonstrate a grasp of the major area of interest chosen and its relation to other areas of training offered in the program. The examination is partly written and partly oral and is designed to test the student’s ability to meet the demands of the profession.
An acceptable dissertation based on completion of an original investigation is required. The candidate must defend an approved draft of the dissertation in an oral examination.