University of California - San Diego
UCSD - Neurosciences Graduate Program

Computational Neurobiology Specialization

 

Overview

The Computational Neurobiology Specialization is a new facet of the broader Neuroscience Graduate Program at UCSD.  The goal of the specialization is to train the next generation of neuroscientists with the broad range of computational and analytical skills that are essential to understand the organization and function of complex neural systems.  The specialization is intended for students with backgrounds in neuroscience, physics, chemistry, biology, psychology, computer science, engineering, and mathematics.

The specialization allows Neuroscience students to concentrate on a focused program of rigorous course work in both the theoretical and experimental aspects of computational neuroscience.  Students are encouraged to pursue thesis research that includes both an experimental and a computational component, often arranged by the student as a collaboration between two research groups.  Upon achievement of degree requirements, students will receive a diploma indicating both their successful completion of the broader Neuroscience Program as well as their specialization in Computational Neurobiology.

Note: The Computational Neurobiology Specialization is nearly finalized as of September 2007, but it awaits formal endorsement by a university committee, expected by early 2008.

Themes

The program is focused on these major themes relevant for computational neuroscience research:

  • Neurobiology of Neural Systems - the anatomy, physiology, and behavior of systems of neurons, with emphasis on basic phenomenology.
  • Advanced Measurement Tools in Neuroscience - Advanced imaging and recording techniques reflecting the impact of experimental physics on neuroscience.
  • lgorithms for the Analysis of Neural Data - New algorithms and techniques for analyzing data obtained from physiological recording
  • Theoretical Basis for Collective Neural Dynamics - A synthesis of approaches from mathematics and physical sciences as well as biology will be used to explore the collective properties and nonlinear dynamics of neuronal systems.

Requirements

Accordingly, in addition to the broader Neuroscience program requirements (Theme 1), students are required to take the following course sequence:

  • PHYS 271.        Biophysics of neurons and networks (Kleinfeld/Levine)
  • BGGN 260.        Neurodynamics (Cauwenberghs/Abarbanel)
  • GGN 266.        Advanced imaging and electrophysiology lab (Kleinfeld)

At the end of each requried course, an oral exam is administered by the instructor and one other faculty member to test the student's mastery of the area.

The Computational Neurobiology journal club is also strongly recommended:

  • BGGN 246 Computational Neurobiology journal club (Sejnowski)

Finally, because of the mathematical rigor of the program, students are encouraged to take additional classes in engineering, mathematics and physics to supplement their backgrounds as needed. Sample classes students have taken include:

  • ECE 101 - Linear systems
  • ECE 161 - Digital signal processing
  • ECE 250 - Parameter estimation
  • ECE 255 - Information theory
  • Physics 210 - Nonequilibrium statistical mechanics
  • Math 180 - Introduction to probability
  • Math 250 - Differential geometry
  • Math 280 - Probability theory
  • Math 281 - Mathematical statistics
  • Math 285A - Introduction to stochastic processes

 

Page last updated: September 26, 2007


Contact Information

Graduate Program in Neurosciences
University of California, San Diego

9500 Gilman Drive 0662
La Jolla CA 92093-0662
Phone: (858) 534-3377
Fax: (858) 534-8242
E-mail: neurograd@ucsd.edu

© 2005 UCSD Graduate Program in Neurosciences.

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