The goal of the Computational Neuroscience Specialization (CNS) is to train the next generation of scientists with the broad range of analytical and computational skills that are essential to understand the organization and function of complex neuronal systems. The specialization allows students to concentrate on a focused program of rigorous course work in both the experimental and theoretical aspects of computational neuroscience. Students are encouraged to pursue thesis research that includes both an experimental and a computational component, often arranged as a collaboration between two research groups.
All students admitted to the Neurosciences Graduate Program (NGP) are eligible to pursue the CNS. Effective fall 2016, PhD candidates in Physics and Bioengineering matriculated fall 2015 and thereafter, are also eligible to apply to the CNS.
Upon completion of the CNS required coursework, a Neuroscience, Physics or Bioengineering student can apply for the specialization by submitting a copy of their C.V., undergraduate and graduate transcripts, and a short description of their research interests to the CNS Oversite Committee. Application materials should be sent to the CNS Committee Chair, Dr. David Kleinfeld at email@example.com. The CNS committee can either admit or reject an application, or provisionally approve an applicant contingent on completion of additional coursework.
Upon achievement of degree requirements, students will receive a diploma indicating both their successful completion of their PhD program as well as their specialization in Computational Neuroscience.
All CNS students are expected to complete a PhD dissertation connected with an issue in contemporary computationalneuroscience. Either the student's primary advisor or a close co advisor (approved by the Computational Neuroscience Committee) must be a member of the NGP faculty.
Their thesis committee must continue to meet all the requirements of their home department.
Neuroscience, Physics and Bioengineering students who intend to pursue the CNS are required to complete their home department course requirements as well as three CNS courses designated by the Oversight Committee, and will be required to pass oral and written examinations for each course to demonstrate their preparation for research in computational neuroscience:
Fall quarter: BGGN 260/PHYS 279 ("Neurodynamics", Dr. Gert Cauwenberghs); this course deals with fundamental aspects of excitable membranes and analytically tractable models of single cells and synapses.
Winter quarter: PHYS 278 ("Biophysical Basis of Neuronal Computation", Dr. David Kleinfeld); this is a core course on network models of neuronal computations.
Spring quarter: COGS 281 ("Neural Signal Processing", Dr. Eran Mukamel); this course deals with the use of modern statistical tools to analyze point processes and continuous data streams.
In addition to the CNS course series described above, Physics and Bioengineering graduate students will be required to take BENG 234: "Introduction to Neurophysiology: Molecules to Systems". This course was specifically designed by Prof. Gabriel Silva for students with physical sciences or engineering background. The course is offered in the spring quarter and may be taken by a Physics or Bioengineering student at the end of their first (or second) year. A Physics or Bioengineering student can waive the BENG 234 requirement by petition to the CNS Oversight Committee giving evidence of sufficient background neuroscience knowledge. Final determination of this sufficiency is at the discretion of the Oversight Committee.